YARN-5109. timestamps are stored unencoded causing parse errors (Varun Saxena via sjlee)

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice-hbase-tests/src/test/java/org/apache/hadoop/yarn/server/timelineservice/storage/TestHBaseTimelineStorage.java

@@ -20,6 +20,7 @@ package org.apache.hadoop.yarn.server.timelineservice.storage;
 
 import static org.junit.Assert.assertEquals;
 import static org.junit.Assert.assertNotNull;
+import static org.junit.Assert.assertNull;
 import static org.junit.Assert.assertTrue;
 
 import java.io.IOException;
@@ -42,7 +43,6 @@ import org.apache.hadoop.hbase.client.ResultScanner;
 import org.apache.hadoop.hbase.client.Scan;
 import org.apache.hadoop.hbase.util.Bytes;
 import org.apache.hadoop.yarn.api.records.ApplicationId;
-import org.apache.hadoop.yarn.api.records.timelineservice.TimelineMetricOperation;
 import org.apache.hadoop.yarn.api.records.timelineservice.ApplicationEntity;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEntities;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEntity;
@@ -50,25 +50,28 @@ import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEntityType;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEvent;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineMetric;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineMetric.Type;
+import org.apache.hadoop.yarn.api.records.timelineservice.TimelineMetricOperation;
 import org.apache.hadoop.yarn.server.metrics.ApplicationMetricsConstants;
 import org.apache.hadoop.yarn.server.timelineservice.reader.TimelineDataToRetrieve;
 import org.apache.hadoop.yarn.server.timelineservice.reader.TimelineEntityFilters;
 import org.apache.hadoop.yarn.server.timelineservice.reader.TimelineReaderContext;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineCompareFilter;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineCompareOp;
-import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineKeyValueFilter;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineExistsFilter;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineFilterList;
-import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelinePrefixFilter;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineFilterList.Operator;
+import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineKeyValueFilter;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineKeyValuesFilter;
+import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelinePrefixFilter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.TimelineReader.Field;
 import org.apache.hadoop.yarn.server.timelineservice.storage.application.ApplicationColumn;
 import org.apache.hadoop.yarn.server.timelineservice.storage.application.ApplicationColumnPrefix;
 import org.apache.hadoop.yarn.server.timelineservice.storage.application.ApplicationRowKey;
 import org.apache.hadoop.yarn.server.timelineservice.storage.application.ApplicationTable;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.EventColumnName;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.EventColumnNameConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.StringKeyConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.entity.EntityColumn;
 import org.apache.hadoop.yarn.server.timelineservice.storage.entity.EntityColumnFamily;
 import org.apache.hadoop.yarn.server.timelineservice.storage.entity.EntityColumnPrefix;
@@ -482,7 +485,6 @@ public class TestHBaseTimelineStorage {
     }
   }
 
-
   @Test
   public void testWriteNullApplicationToHBase() throws Exception {
     TimelineEntities te = new TimelineEntities();
@@ -494,7 +496,7 @@ public class TestHBaseTimelineStorage {
 
     // add the info map in Timeline Entity
     Map<String, Object> infoMap = new HashMap<String, Object>();
-    infoMap.put("infoMapKey1", "infoMapValue1");
+    infoMap.put("in fo M apK  ey1", "infoMapValue1");
     infoMap.put("infoMapKey2", 10);
     entity.addInfo(infoMap);
 
@@ -517,6 +519,7 @@ public class TestHBaseTimelineStorage {
       // retrieve the row
       Scan scan = new Scan();
       scan.setStartRow(Bytes.toBytes(cluster));
+      scan.setStopRow(Bytes.toBytes(cluster + "1"));
       Connection conn = ConnectionFactory.createConnection(c1);
       ResultScanner resultScanner = new ApplicationTable()
           .getResultScanner(c1, conn, scan);
@@ -626,7 +629,7 @@ public class TestHBaseTimelineStorage {
       hbi.start();
       String cluster = "cluster_test_write_app";
       String user = "user1";
-      String flow = "some_flow_name";
+      String flow = "s!ome_f\tlow  _n am!e";
       String flowVersion = "AB7822C10F1111";
       long runid = 1002345678919L;
       hbi.write(cluster, user, flow, flowVersion, runid, appId, te);
@@ -670,7 +673,8 @@ public class TestHBaseTimelineStorage {
       assertEquals(cTime, cTime1);
 
       Map<String, Object> infoColumns =
-          ApplicationColumnPrefix.INFO.readResults(result);
+          ApplicationColumnPrefix.INFO.readResults(result,
+              StringKeyConverter.getInstance());
       assertEquals(infoMap, infoColumns);
 
       // Remember isRelatedTo is of type Map<String, Set<String>>
@@ -706,11 +710,13 @@ public class TestHBaseTimelineStorage {
 
       // Configuration
       Map<String, Object> configColumns =
-          ApplicationColumnPrefix.CONFIG.readResults(result);
+          ApplicationColumnPrefix.CONFIG.readResults(result,
+              StringKeyConverter.getInstance());
       assertEquals(conf, configColumns);
 
       NavigableMap<String, NavigableMap<Long, Number>> metricsResult =
-          ApplicationColumnPrefix.METRIC.readResultsWithTimestamps(result);
+          ApplicationColumnPrefix.METRIC.readResultsWithTimestamps(
+              result, StringKeyConverter.getInstance());
 
       NavigableMap<Long, Number> metricMap = metricsResult.get(m1.getId());
       matchMetrics(metricValues, metricMap);
@@ -868,7 +874,8 @@ public class TestHBaseTimelineStorage {
           assertEquals(cTime1, cTime);
 
           Map<String, Object> infoColumns =
-              EntityColumnPrefix.INFO.readResults(result);
+              EntityColumnPrefix.INFO.readResults(result,
+                  StringKeyConverter.getInstance());
           assertEquals(infoMap, infoColumns);
 
           // Remember isRelatedTo is of type Map<String, Set<String>>
@@ -906,11 +913,12 @@ public class TestHBaseTimelineStorage {
 
           // Configuration
           Map<String, Object> configColumns =
-              EntityColumnPrefix.CONFIG.readResults(result);
+              EntityColumnPrefix.CONFIG.readResults(result, StringKeyConverter.getInstance());
           assertEquals(conf, configColumns);
 
           NavigableMap<String, NavigableMap<Long, Number>> metricsResult =
-              EntityColumnPrefix.METRIC.readResultsWithTimestamps(result);
+              EntityColumnPrefix.METRIC.readResultsWithTimestamps(
+                  result, StringKeyConverter.getInstance());
 
           NavigableMap<Long, Number> metricMap = metricsResult.get(m1.getId());
           matchMetrics(metricValues, metricMap);
@@ -963,7 +971,7 @@ public class TestHBaseTimelineStorage {
   }
 
   private boolean isRowKeyCorrect(byte[] rowKey, String cluster, String user,
-      String flow, long runid, String appName, TimelineEntity te) {
+      String flow, Long runid, String appName, TimelineEntity te) {
 
     EntityRowKey key = EntityRowKey.parseRowKey(rowKey);
 
@@ -978,7 +986,7 @@ public class TestHBaseTimelineStorage {
   }
 
   private boolean isApplicationRowKeyCorrect(byte[] rowKey, String cluster,
-      String user, String flow, long runid, String appName) {
+      String user, String flow, Long runid, String appName) {
 
     ApplicationRowKey key = ApplicationRowKey.parseRowKey(rowKey);
 
@@ -995,7 +1003,7 @@ public class TestHBaseTimelineStorage {
     TimelineEvent event = new TimelineEvent();
     String eventId = ApplicationMetricsConstants.CREATED_EVENT_TYPE;
     event.setId(eventId);
-    long expTs = 1436512802000L;
+    Long expTs = 1436512802000L;
     event.setTimestamp(expTs);
     String expKey = "foo_event";
     Object expVal = "test";
@@ -1038,20 +1046,18 @@ public class TestHBaseTimelineStorage {
       assertTrue(isApplicationRowKeyCorrect(row1, cluster, user, flow, runid,
           appName));
 
-      Map<?, Object> eventsResult =
-          ApplicationColumnPrefix.EVENT.
-              readResultsHavingCompoundColumnQualifiers(result);
+      Map<EventColumnName, Object> eventsResult =
+          ApplicationColumnPrefix.EVENT.readResults(result,
+              EventColumnNameConverter.getInstance());
       // there should be only one event
       assertEquals(1, eventsResult.size());
-      for (Map.Entry<?, Object> e : eventsResult.entrySet()) {
+      for (Map.Entry<EventColumnName, Object> e : eventsResult.entrySet()) {
+        EventColumnName eventColumnName = e.getKey();
         // the qualifier is a compound key
         // hence match individual values
-        byte[][] karr = (byte[][])e.getKey();
-        assertEquals(3, karr.length);
-        assertEquals(eventId, Bytes.toString(karr[0]));
-        assertEquals(
-            TimelineStorageUtils.invertLong(expTs), Bytes.toLong(karr[1]));
-        assertEquals(expKey, Bytes.toString(karr[2]));
+        assertEquals(eventId, eventColumnName.getId());
+        assertEquals(expTs, eventColumnName.getTimestamp());
+        assertEquals(expKey, eventColumnName.getInfoKey());
         Object value = e.getValue();
         // there should be only one timestamp and value
         assertEquals(expVal, value.toString());
@@ -1076,7 +1082,7 @@ public class TestHBaseTimelineStorage {
       assertEquals(1, events.size());
       for (TimelineEvent e : events) {
         assertEquals(eventId, e.getId());
-        assertEquals(expTs, e.getTimestamp());
+        assertEquals(expTs, Long.valueOf(e.getTimestamp()));
         Map<String,Object> info = e.getInfo();
         assertEquals(1, info.size());
         for (Map.Entry<String, Object> infoEntry : info.entrySet()) {
@@ -1095,9 +1101,9 @@ public class TestHBaseTimelineStorage {
   @Test
   public void testEventsWithEmptyInfo() throws IOException {
     TimelineEvent event = new TimelineEvent();
-    String eventId = "foo_event_id";
+    String eventId = "foo_ev e  nt_id";
     event.setId(eventId);
-    long expTs = 1436512802000L;
+    Long expTs = 1436512802000L;
     event.setTimestamp(expTs);
 
     final TimelineEntity entity = new TimelineEntity();
@@ -1142,21 +1148,19 @@ public class TestHBaseTimelineStorage {
           assertTrue(isRowKeyCorrect(row1, cluster, user, flow, runid, appName,
               entity));
 
-          Map<?, Object> eventsResult =
-              EntityColumnPrefix.EVENT.
-                  readResultsHavingCompoundColumnQualifiers(result);
+          Map<EventColumnName, Object> eventsResult =
+              EntityColumnPrefix.EVENT.readResults(result,
+                  EventColumnNameConverter.getInstance());
           // there should be only one event
           assertEquals(1, eventsResult.size());
-          for (Map.Entry<?, Object> e : eventsResult.entrySet()) {
+          for (Map.Entry<EventColumnName, Object> e : eventsResult.entrySet()) {
+            EventColumnName eventColumnName = e.getKey();
             // the qualifier is a compound key
             // hence match individual values
-            byte[][] karr = (byte[][])e.getKey();
-            assertEquals(3, karr.length);
-            assertEquals(eventId, Bytes.toString(karr[0]));
-            assertEquals(TimelineStorageUtils.invertLong(expTs),
-                Bytes.toLong(karr[1]));
+            assertEquals(eventId, eventColumnName.getId());
+            assertEquals(expTs,eventColumnName.getTimestamp());
             // key must be empty
-            assertEquals(0, karr[2].length);
+            assertNull(eventColumnName.getInfoKey());
             Object value = e.getValue();
             // value should be empty
             assertEquals("", value.toString());
@@ -1184,7 +1188,7 @@ public class TestHBaseTimelineStorage {
       assertEquals(1, events.size());
       for (TimelineEvent e : events) {
         assertEquals(eventId, e.getId());
-        assertEquals(expTs, e.getTimestamp());
+        assertEquals(expTs, Long.valueOf(e.getTimestamp()));
         Map<String,Object> info = e.getInfo();
         assertTrue(info == null || info.isEmpty());
       }
@@ -1194,6 +1198,67 @@ public class TestHBaseTimelineStorage {
     }
   }
 
+  @Test
+  public void testEventsEscapeTs() throws IOException {
+    TimelineEvent event = new TimelineEvent();
+    String eventId = ApplicationMetricsConstants.CREATED_EVENT_TYPE;
+    event.setId(eventId);
+    long expTs = 1463567041056L;
+    event.setTimestamp(expTs);
+    String expKey = "f==o o_e ve\tnt";
+    Object expVal = "test";
+    event.addInfo(expKey, expVal);
+
+    final TimelineEntity entity = new ApplicationEntity();
+    entity.setId(ApplicationId.newInstance(0, 1).toString());
+    entity.addEvent(event);
+
+    TimelineEntities entities = new TimelineEntities();
+    entities.addEntity(entity);
+
+    HBaseTimelineWriterImpl hbi = null;
+    try {
+      Configuration c1 = util.getConfiguration();
+      hbi = new HBaseTimelineWriterImpl(c1);
+      hbi.init(c1);
+      hbi.start();
+      String cluster = "clus!ter_\ttest_ev  ents";
+      String user = "user2";
+      String flow = "other_flow_name";
+      String flowVersion = "1111F01C2287BA";
+      long runid = 1009876543218L;
+      String appName = "application_123465899910_2001";
+      hbi.write(cluster, user, flow, flowVersion, runid, appName, entities);
+      hbi.stop();
+
+      // read the timeline entity using the reader this time
+      TimelineEntity e1 = reader.getEntity(
+          new TimelineReaderContext(cluster, user, flow, runid, appName,
+          entity.getType(), entity.getId()),
+          new TimelineDataToRetrieve(null, null, EnumSet.of(Field.ALL)));
+      assertNotNull(e1);
+      // check the events
+      NavigableSet<TimelineEvent> events = e1.getEvents();
+      // there should be only one event
+      assertEquals(1, events.size());
+      for (TimelineEvent e : events) {
+        assertEquals(eventId, e.getId());
+        assertEquals(expTs, e.getTimestamp());
+        Map<String,Object> info = e.getInfo();
+        assertEquals(1, info.size());
+        for (Map.Entry<String, Object> infoEntry : info.entrySet()) {
+          assertEquals(expKey, infoEntry.getKey());
+          assertEquals(expVal, infoEntry.getValue());
+        }
+      }
+    } finally {
+      if (hbi != null) {
+        hbi.stop();
+        hbi.close();
+      }
+    }
+  }
+
   @Test
   public void testNonIntegralMetricValues() throws IOException {
     TimelineEntities teApp = new TimelineEntities();

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice-hbase-tests/src/test/java/org/apache/hadoop/yarn/server/timelineservice/storage/flow/TestHBaseStorageFlowActivity.java

@@ -170,7 +170,7 @@ public class TestHBaseStorageFlowActivity {
     assertEquals(cluster, flowActivityRowKey.getClusterId());
     assertEquals(user, flowActivityRowKey.getUserId());
     assertEquals(flow, flowActivityRowKey.getFlowName());
-    long dayTs = TimelineStorageUtils.getTopOfTheDayTimestamp(minStartTs);
+    Long dayTs = TimelineStorageUtils.getTopOfTheDayTimestamp(minStartTs);
     assertEquals(dayTs, flowActivityRowKey.getDayTimestamp());
     assertEquals(1, values.size());
     checkFlowActivityRunId(runid, flowVersion, values);
@@ -194,7 +194,7 @@ public class TestHBaseStorageFlowActivity {
         assertEquals(cluster, flowActivity.getCluster());
         assertEquals(user, flowActivity.getUser());
         assertEquals(flow, flowActivity.getFlowName());
-        assertEquals(dayTs, flowActivity.getDate().getTime());
+        assertEquals(dayTs, Long.valueOf(flowActivity.getDate().getTime()));
         Set<FlowRunEntity> flowRuns = flowActivity.getFlowRuns();
         assertEquals(1, flowRuns.size());
       }
@@ -294,7 +294,7 @@ public class TestHBaseStorageFlowActivity {
       assertEquals(cluster, flowActivityRowKey.getClusterId());
       assertEquals(user, flowActivityRowKey.getUserId());
       assertEquals(flow, flowActivityRowKey.getFlowName());
-      long dayTs = TimelineStorageUtils.getTopOfTheDayTimestamp(appCreatedTime);
+      Long dayTs = TimelineStorageUtils.getTopOfTheDayTimestamp(appCreatedTime);
       assertEquals(dayTs, flowActivityRowKey.getDayTimestamp());
       assertEquals(1, values.size());
       checkFlowActivityRunId(runid, flowVersion, values);
@@ -429,7 +429,7 @@ public class TestHBaseStorageFlowActivity {
       assertEquals(cluster, flowActivityRowKey.getClusterId());
       assertEquals(user, flowActivityRowKey.getUserId());
       assertEquals(flow, flowActivityRowKey.getFlowName());
-      long dayTs = TimelineStorageUtils.getTopOfTheDayTimestamp(appCreatedTime);
+      Long dayTs = TimelineStorageUtils.getTopOfTheDayTimestamp(appCreatedTime);
       assertEquals(dayTs, flowActivityRowKey.getDayTimestamp());
 
       Map<byte[], byte[]> values = result

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/reader/filter/TimelineFilterUtils.java

@@ -31,10 +31,14 @@ import org.apache.hadoop.hbase.filter.CompareFilter.CompareOp;
 import org.apache.hadoop.hbase.filter.Filter;
 import org.apache.hadoop.hbase.filter.FilterList;
 import org.apache.hadoop.hbase.filter.FilterList.Operator;
+import org.apache.hadoop.yarn.server.timelineservice.storage.application.ApplicationColumnPrefix;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.Column;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnFamily;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix;
-
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.EventColumnName;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.EventColumnNameConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.StringKeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.entity.EntityColumnPrefix;
 import org.apache.hadoop.hbase.filter.QualifierFilter;
 import org.apache.hadoop.hbase.filter.SingleColumnValueFilter;
 
@@ -205,6 +209,17 @@ public final class TimelineFilterUtils {
     return singleColValFilter;
   }
 
+  private static <T> byte[] createColQualifierPrefix(ColumnPrefix<T> colPrefix,
+      String column) {
+    if (colPrefix == ApplicationColumnPrefix.EVENT ||
+        colPrefix == EntityColumnPrefix.EVENT) {
+      return EventColumnNameConverter.getInstance().encode(
+          new EventColumnName(column, null, null));
+    } else {
+      return StringKeyConverter.getInstance().encode(column);
+    }
+  }
+
   /**
    * Create a filter list of qualifier filters based on passed set of columns.
    *
@@ -219,8 +234,7 @@ public final class TimelineFilterUtils {
     for (String column : columns) {
       // For columns which have compound column qualifiers (eg. events), we need
       // to include the required separator.
-      byte[] compoundColQual =
-          colPrefix.getCompoundColQualBytes(column, (byte[])null);
+      byte[] compoundColQual = createColQualifierPrefix(colPrefix, column);
       list.addFilter(new QualifierFilter(CompareOp.EQUAL,
           new BinaryPrefixComparator(
               colPrefix.getColumnPrefixBytes(compoundColQual))));

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/HBaseTimelineWriterImpl.java

@@ -29,7 +29,6 @@ import org.apache.hadoop.conf.Configuration;
 import org.apache.hadoop.hbase.HBaseConfiguration;
 import org.apache.hadoop.hbase.client.Connection;
 import org.apache.hadoop.hbase.client.ConnectionFactory;
-import org.apache.hadoop.hbase.util.Bytes;
 import org.apache.hadoop.service.AbstractService;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEntities;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEntity;
@@ -37,7 +36,6 @@ import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEvent;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineMetric;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineWriteResponse;
 import org.apache.hadoop.yarn.server.metrics.ApplicationMetricsConstants;
-import org.apache.hadoop.yarn.server.timeline.GenericObjectMapper;
 import org.apache.hadoop.yarn.server.timelineservice.storage.application.ApplicationColumn;
 import org.apache.hadoop.yarn.server.timelineservice.storage.application.ApplicationColumnPrefix;
 import org.apache.hadoop.yarn.server.timelineservice.storage.application.ApplicationRowKey;
@@ -46,7 +44,11 @@ import org.apache.hadoop.yarn.server.timelineservice.storage.apptoflow.AppToFlow
 import org.apache.hadoop.yarn.server.timelineservice.storage.apptoflow.AppToFlowRowKey;
 import org.apache.hadoop.yarn.server.timelineservice.storage.apptoflow.AppToFlowTable;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.EventColumnName;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.EventColumnNameConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.LongKeyConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.StringKeyConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TypedBufferedMutator;
 import org.apache.hadoop.yarn.server.timelineservice.storage.entity.EntityColumn;
@@ -194,7 +196,7 @@ public class HBaseTimelineWriterImpl extends AbstractService implements
       long activityTimeStamp) throws IOException {
     byte[] rowKey = FlowActivityRowKey.getRowKey(clusterId, activityTimeStamp,
         userId, flowName);
-    byte[] qualifier = GenericObjectMapper.write(flowRunId);
+    byte[] qualifier = LongKeyConverter.getInstance().encode(flowRunId);
     FlowActivityColumnPrefix.RUN_ID.store(rowKey, flowActivityTable, qualifier,
         null, flowVersion,
         AggregationCompactionDimension.APPLICATION_ID.getAttribute(appId));
@@ -278,7 +280,8 @@ public class HBaseTimelineWriterImpl extends AbstractService implements
   private void storeFlowMetrics(byte[] rowKey, Set<TimelineMetric> metrics,
       Attribute... attributes) throws IOException {
     for (TimelineMetric metric : metrics) {
-      String metricColumnQualifier = metric.getId();
+      byte[] metricColumnQualifier =
+          StringKeyConverter.getInstance().encode(metric.getId());
       Map<Long, Number> timeseries = metric.getValues();
       for (Map.Entry<Long, Number> timeseriesEntry : timeseries.entrySet()) {
         Long timestamp = timeseriesEntry.getKey();
@@ -316,8 +319,9 @@ public class HBaseTimelineWriterImpl extends AbstractService implements
       // id3?id4?id5
       String compoundValue =
           Separator.VALUES.joinEncoded(connectedEntity.getValue());
-      columnPrefix.store(rowKey, table, connectedEntity.getKey(), null,
-          compoundValue);
+      columnPrefix.store(rowKey, table,
+          StringKeyConverter.getInstance().encode(connectedEntity.getKey()),
+          null, compoundValue);
     }
   }
 
@@ -337,7 +341,8 @@ public class HBaseTimelineWriterImpl extends AbstractService implements
       if (info != null) {
         for (Map.Entry<String, Object> entry : info.entrySet()) {
           ApplicationColumnPrefix.INFO.store(rowKey, applicationTable,
-              entry.getKey(), null, entry.getValue());
+              StringKeyConverter.getInstance().encode(entry.getKey()), null,
+              entry.getValue());
         }
       }
     } else {
@@ -349,8 +354,9 @@ public class HBaseTimelineWriterImpl extends AbstractService implements
       Map<String, Object> info = te.getInfo();
       if (info != null) {
         for (Map.Entry<String, Object> entry : info.entrySet()) {
-          EntityColumnPrefix.INFO.store(rowKey, entityTable, entry.getKey(),
-              null, entry.getValue());
+          EntityColumnPrefix.INFO.store(rowKey, entityTable,
+              StringKeyConverter.getInstance().encode(entry.getKey()), null,
+              entry.getValue());
         }
       }
     }
@@ -365,11 +371,13 @@ public class HBaseTimelineWriterImpl extends AbstractService implements
       return;
     }
     for (Map.Entry<String, String> entry : config.entrySet()) {
+      byte[] configKey =
+          StringKeyConverter.getInstance().encode(entry.getKey());
       if (isApplication) {
         ApplicationColumnPrefix.CONFIG.store(rowKey, applicationTable,
-            entry.getKey(), null, entry.getValue());
+            configKey, null, entry.getValue());
       } else {
-        EntityColumnPrefix.CONFIG.store(rowKey, entityTable, entry.getKey(),
+        EntityColumnPrefix.CONFIG.store(rowKey, entityTable, configKey,
             null, entry.getValue());
       }
     }
@@ -383,7 +391,8 @@ public class HBaseTimelineWriterImpl extends AbstractService implements
       boolean isApplication) throws IOException {
     if (metrics != null) {
       for (TimelineMetric metric : metrics) {
-        String metricColumnQualifier = metric.getId();
+        byte[] metricColumnQualifier =
+            StringKeyConverter.getInstance().encode(metric.getId());
         Map<Long, Number> timeseries = metric.getValues();
         for (Map.Entry<Long, Number> timeseriesEntry : timeseries.entrySet()) {
           Long timestamp = timeseriesEntry.getKey();
@@ -416,41 +425,31 @@ public class HBaseTimelineWriterImpl extends AbstractService implements
                   "! Using the current timestamp");
               eventTimestamp = System.currentTimeMillis();
             }
-            byte[] eventTs =
-                Bytes.toBytes(TimelineStorageUtils.invertLong(eventTimestamp));
+            EventColumnNameConverter converter =
+                EventColumnNameConverter.getInstance();
             Map<String, Object> eventInfo = event.getInfo();
             if ((eventInfo == null) || (eventInfo.size() == 0)) {
+              byte[] columnQualifierBytes = converter.encode(
+                  new EventColumnName(eventId, eventTimestamp, null));
               if (isApplication) {
-                byte[] compoundColumnQualifierBytes =
-                    ApplicationColumnPrefix.EVENT.
-                        getCompoundColQualBytes(eventId, eventTs, null);
                 ApplicationColumnPrefix.EVENT.store(rowKey, applicationTable,
-                    compoundColumnQualifierBytes, null,
-                    TimelineStorageUtils.EMPTY_BYTES);
+                    columnQualifierBytes, null, Separator.EMPTY_BYTES);
               } else {
-                byte[] compoundColumnQualifierBytes =
-                    EntityColumnPrefix.EVENT.
-                        getCompoundColQualBytes(eventId, eventTs, null);
                 EntityColumnPrefix.EVENT.store(rowKey, entityTable,
-                    compoundColumnQualifierBytes, null,
-                    TimelineStorageUtils.EMPTY_BYTES);
+                    columnQualifierBytes, null, Separator.EMPTY_BYTES);
               }
             } else {
               for (Map.Entry<String, Object> info : eventInfo.entrySet()) {
-                // eventId?infoKey
-                byte[] infoKey = Bytes.toBytes(info.getKey());
+                // eventId=infoKey
+                byte[] columnQualifierBytes = converter.encode(
+                    new EventColumnName(eventId, eventTimestamp,
+                        info.getKey()));
                 if (isApplication) {
-                  byte[] compoundColumnQualifierBytes =
-                      ApplicationColumnPrefix.EVENT.
-                          getCompoundColQualBytes(eventId, eventTs, infoKey);
                   ApplicationColumnPrefix.EVENT.store(rowKey, applicationTable,
-                      compoundColumnQualifierBytes, null, info.getValue());
+                      columnQualifierBytes, null, info.getValue());
                 } else {
-                  byte[] compoundColumnQualifierBytes =
-                      EntityColumnPrefix.EVENT.
-                          getCompoundColQualBytes(eventId, eventTs, infoKey);
                   EntityColumnPrefix.EVENT.store(rowKey, entityTable,
-                      compoundColumnQualifierBytes, null, info.getValue());
+                      columnQualifierBytes, null, info.getValue());
                 }
               } // for info: eventInfo
             }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/application/ApplicationColumnPrefix.java

@@ -27,9 +27,10 @@ import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnFamily
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnHelper;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.GenericConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.LongConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TypedBufferedMutator;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.LongConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ValueConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.flow.Attribute;
 
@@ -56,7 +57,7 @@ public enum ApplicationColumnPrefix implements ColumnPrefix<ApplicationTable> {
   /**
    * Lifecycle events for an application.
    */
-  EVENT(ApplicationColumnFamily.INFO, "e", true),
+  EVENT(ApplicationColumnFamily.INFO, "e"),
 
   /**
    * Config column stores configuration with config key as the column name.
@@ -78,7 +79,6 @@ public enum ApplicationColumnPrefix implements ColumnPrefix<ApplicationTable> {
    */
   private final String columnPrefix;
   private final byte[] columnPrefixBytes;
-  private final boolean compoundColQual;
 
   /**
    * Private constructor, meant to be used by the enum definition.
@@ -88,18 +88,7 @@ public enum ApplicationColumnPrefix implements ColumnPrefix<ApplicationTable> {
    */
   private ApplicationColumnPrefix(ColumnFamily<ApplicationTable> columnFamily,
       String columnPrefix) {
-    this(columnFamily, columnPrefix, false, GenericConverter.getInstance());
-  }
-
-  private ApplicationColumnPrefix(ColumnFamily<ApplicationTable> columnFamily,
-      String columnPrefix, boolean compoundColQual) {
-    this(columnFamily, columnPrefix, compoundColQual,
-        GenericConverter.getInstance());
-  }
-
-  private ApplicationColumnPrefix(ColumnFamily<ApplicationTable> columnFamily,
-      String columnPrefix, ValueConverter converter) {
-    this(columnFamily, columnPrefix, false, converter);
+    this(columnFamily, columnPrefix, GenericConverter.getInstance());
   }
 
   /**
@@ -111,7 +100,7 @@ public enum ApplicationColumnPrefix implements ColumnPrefix<ApplicationTable> {
    * this column prefix.
    */
   private ApplicationColumnPrefix(ColumnFamily<ApplicationTable> columnFamily,
-      String columnPrefix, boolean compoundColQual, ValueConverter converter) {
+      String columnPrefix, ValueConverter converter) {
     column = new ColumnHelper<ApplicationTable>(columnFamily, converter);
     this.columnFamily = columnFamily;
     this.columnPrefix = columnPrefix;
@@ -122,7 +111,6 @@ public enum ApplicationColumnPrefix implements ColumnPrefix<ApplicationTable> {
       this.columnPrefixBytes =
           Bytes.toBytes(Separator.SPACE.encode(columnPrefix));
     }
-    this.compoundColQual = compoundColQual;
   }
 
   /**
@@ -149,15 +137,6 @@ public enum ApplicationColumnPrefix implements ColumnPrefix<ApplicationTable> {
     return columnFamily.getBytes();
   }
 
-  @Override
-  public byte[] getCompoundColQualBytes(String qualifier,
-      byte[]...components) {
-    if (!compoundColQual) {
-      return ColumnHelper.getColumnQualifier(null, qualifier);
-    }
-    return ColumnHelper.getCompoundColumnQualifierBytes(qualifier, components);
-  }
-
   /*
    * (non-Javadoc)
    *
@@ -232,25 +211,12 @@ public enum ApplicationColumnPrefix implements ColumnPrefix<ApplicationTable> {
    *
    * @see
    * org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix
-   * #readResults(org.apache.hadoop.hbase.client.Result)
-   */
-  public Map<String, Object> readResults(Result result) throws IOException {
-    return column.readResults(result, columnPrefixBytes);
-  }
-
-  /**
-   * @param result from which to read columns
-   * @return the latest values of columns in the column family. The column
-   *         qualifier is returned as a list of parts, each part a byte[]. This
-   *         is to facilitate returning byte arrays of values that were not
-   *         Strings. If they can be treated as Strings, you should use
-   *         {@link #readResults(Result)} instead.
-   * @throws IOException if any problem occurs while reading results.
+   * #readResults(org.apache.hadoop.hbase.client.Result,
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter)
    */
-  public Map<?, Object> readResultsHavingCompoundColumnQualifiers(Result result)
-      throws IOException {
-    return column.readResultsHavingCompoundColumnQualifiers(result,
-        columnPrefixBytes);
+  public <K> Map<K, Object> readResults(Result result,
+      KeyConverter<K> keyConverter) throws IOException {
+    return column.readResults(result, columnPrefixBytes, keyConverter);
   }
 
   /*
@@ -258,11 +224,14 @@ public enum ApplicationColumnPrefix implements ColumnPrefix<ApplicationTable> {
    *
    * @see
    * org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix
-   * #readResultsWithTimestamps(org.apache.hadoop.hbase.client.Result)
+   * #readResultsWithTimestamps(org.apache.hadoop.hbase.client.Result,
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter)
    */
-  public <V> NavigableMap<String, NavigableMap<Long, V>>
-      readResultsWithTimestamps(Result result) throws IOException {
-    return column.readResultsWithTimestamps(result, columnPrefixBytes);
+  public <K, V> NavigableMap<K, NavigableMap<Long, V>>
+      readResultsWithTimestamps(Result result, KeyConverter<K> keyConverter)
+      throws IOException {
+    return column.readResultsWithTimestamps(result, columnPrefixBytes,
+        keyConverter);
   }
 
   /**

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/application/ApplicationRowKey.java

@@ -15,11 +15,8 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
-package org.apache.hadoop.yarn.server.timelineservice.storage.application;
 
-import org.apache.hadoop.hbase.util.Bytes;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
+package org.apache.hadoop.yarn.server.timelineservice.storage.application;
 
 /**
  * Represents a rowkey for the application table.
@@ -28,11 +25,11 @@ public class ApplicationRowKey {
   private final String clusterId;
   private final String userId;
   private final String flowName;
-  private final long flowRunId;
+  private final Long flowRunId;
   private final String appId;
 
   public ApplicationRowKey(String clusterId, String userId, String flowName,
-      long flowRunId, String appId) {
+      Long flowRunId, String appId) {
     this.clusterId = clusterId;
     this.userId = userId;
     this.flowName = flowName;
@@ -52,7 +49,7 @@ public class ApplicationRowKey {
     return flowName;
   }
 
-  public long getFlowRunId() {
+  public Long getFlowRunId() {
     return flowRunId;
   }
 
@@ -71,9 +68,8 @@ public class ApplicationRowKey {
    */
   public static byte[] getRowKeyPrefix(String clusterId, String userId,
       String flowName) {
-    byte[] first = Bytes.toBytes(
-        Separator.QUALIFIERS.joinEncoded(clusterId, userId, flowName));
-    return Separator.QUALIFIERS.join(first, new byte[0]);
+    return ApplicationRowKeyConverter.getInstance().encode(
+        new ApplicationRowKey(clusterId, userId, flowName, null, null));
   }
 
   /**
@@ -88,10 +84,8 @@ public class ApplicationRowKey {
    */
   public static byte[] getRowKeyPrefix(String clusterId, String userId,
       String flowName, Long flowRunId) {
-    byte[] first = Bytes.toBytes(
-        Separator.QUALIFIERS.joinEncoded(clusterId, userId, flowName));
-    byte[] second = Bytes.toBytes(TimelineStorageUtils.invertLong(flowRunId));
-    return Separator.QUALIFIERS.join(first, second, new byte[0]);
+    return ApplicationRowKeyConverter.getInstance().encode(
+        new ApplicationRowKey(clusterId, userId, flowName, flowRunId, null));
   }
 
   /**
@@ -107,14 +101,8 @@ public class ApplicationRowKey {
    */
   public static byte[] getRowKey(String clusterId, String userId,
       String flowName, Long flowRunId, String appId) {
-    byte[] first =
-        Bytes.toBytes(Separator.QUALIFIERS.joinEncoded(clusterId, userId,
-            flowName));
-    // Note that flowRunId is a long, so we can't encode them all at the same
-    // time.
-    byte[] second = Bytes.toBytes(TimelineStorageUtils.invertLong(flowRunId));
-    byte[] third = TimelineStorageUtils.encodeAppId(appId);
-    return Separator.QUALIFIERS.join(first, second, third);
+    return ApplicationRowKeyConverter.getInstance().encode(
+        new ApplicationRowKey(clusterId, userId, flowName, flowRunId, appId));
   }
 
   /**
@@ -124,22 +112,6 @@ public class ApplicationRowKey {
    * @return An <cite>ApplicationRowKey</cite> object.
    */
   public static ApplicationRowKey parseRowKey(byte[] rowKey) {
-    byte[][] rowKeyComponents = Separator.QUALIFIERS.split(rowKey);
-
-    if (rowKeyComponents.length < 5) {
-      throw new IllegalArgumentException("the row key is not valid for " +
-          "an application");
-    }
-
-    String clusterId =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[0]));
-    String userId =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[1]));
-    String flowName =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[2]));
-    long flowRunId =
-        TimelineStorageUtils.invertLong(Bytes.toLong(rowKeyComponents[3]));
-    String appId = TimelineStorageUtils.decodeAppId(rowKeyComponents[4]);
-    return new ApplicationRowKey(clusterId, userId, flowName, flowRunId, appId);
+    return ApplicationRowKeyConverter.getInstance().decode(rowKey);
   }
 }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/application/ApplicationRowKeyConverter.java

@@ -0,0 +1,130 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hadoop.yarn.server.timelineservice.storage.application;
+
+import org.apache.hadoop.hbase.util.Bytes;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.AppIdKeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
+
+/**
+ * Encodes and decodes row key for application table.
+ * The row key is of the form : clusterId!userName!flowName!flowRunId!appId.
+ * flowRunId is a long, appId is encoded and decoded using
+ * {@link AppIdKeyConverter} and rest are strings.
+ */
+public final class ApplicationRowKeyConverter implements
+    KeyConverter<ApplicationRowKey> {
+  private static final ApplicationRowKeyConverter INSTANCE =
+      new ApplicationRowKeyConverter();
+
+  public static ApplicationRowKeyConverter getInstance() {
+    return INSTANCE;
+  }
+
+  private ApplicationRowKeyConverter() {
+  }
+
+  // Application row key is of the form
+  // clusterId!userName!flowName!flowRunId!appId with each segment separated
+  // by !. The sizes below indicate sizes of each one of these segements in
+  // sequence. clusterId, userName and flowName are strings. flowrunId is a long
+  // hence 8 bytes in size. app id is represented as 12 bytes with cluster
+  // timestamp part of appid being 8 bytes(long) and seq id being 4 bytes(int).
+  // Strings are variable in size (i.e. end whenever separator is encountered).
+  // This is used while decoding and helps in determining where to split.
+  private static final int[] SEGMENT_SIZES = {
+      Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE,
+      Bytes.SIZEOF_LONG, AppIdKeyConverter.getKeySize() };
+
+  /*
+   * (non-Javadoc)
+   *
+   * Encodes ApplicationRowKey object into a byte array with each
+   * component/field in ApplicationRowKey separated by Separator#QUALIFIERS.
+   * This leads to an application table row key of the form
+   * clusterId!userName!flowName!flowRunId!appId
+   * If flowRunId in passed ApplicationRowKey object is null (and the fields
+   * preceding it i.e. clusterId, userId and flowName are not null), this
+   * returns a row key prefix of the form clusterId!userName!flowName! and if
+   * appId in ApplicationRowKey is null (other 4 components are not null), this
+   * returns a row key prefix of the form clusterId!userName!flowName!flowRunId!
+   * flowRunId is inverted while encoding as it helps maintain a descending
+   * order for row keys in application table.
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #encode(java.lang.Object)
+   */
+  @Override
+  public byte[] encode(ApplicationRowKey rowKey) {
+    byte[] cluster = Separator.encode(rowKey.getClusterId(),
+        Separator.SPACE, Separator.TAB, Separator.QUALIFIERS);
+    byte[] user = Separator.encode(rowKey.getUserId(),
+        Separator.SPACE, Separator.TAB, Separator.QUALIFIERS);
+    byte[] flow = Separator.encode(rowKey.getFlowName(),
+        Separator.SPACE, Separator.TAB, Separator.QUALIFIERS);
+    byte[] first = Separator.QUALIFIERS.join(cluster, user, flow);
+    // Note that flowRunId is a long, so we can't encode them all at the same
+    // time.
+    if (rowKey.getFlowRunId() == null) {
+      return Separator.QUALIFIERS.join(first, Separator.EMPTY_BYTES);
+    }
+    byte[] second = Bytes.toBytes(
+        TimelineStorageUtils.invertLong(rowKey.getFlowRunId()));
+    if (rowKey.getAppId() == null || rowKey.getAppId().isEmpty()) {
+      return Separator.QUALIFIERS.join(first, second, Separator.EMPTY_BYTES);
+    }
+    byte[] third = AppIdKeyConverter.getInstance().encode(rowKey.getAppId());
+    return Separator.QUALIFIERS.join(first, second, third);
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * Decodes an application row key of the form
+   * clusterId!userName!flowName!flowRunId!appId represented in byte format and
+   * converts it into an ApplicationRowKey object.flowRunId is inverted while
+   * decoding as it was inverted while encoding.
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #decode(byte[])
+   */
+  @Override
+  public ApplicationRowKey decode(byte[] rowKey) {
+    byte[][] rowKeyComponents =
+        Separator.QUALIFIERS.split(rowKey, SEGMENT_SIZES);
+    if (rowKeyComponents.length != 5) {
+      throw new IllegalArgumentException("the row key is not valid for " +
+          "an application");
+    }
+    String clusterId = Separator.decode(Bytes.toString(rowKeyComponents[0]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    String userId = Separator.decode(Bytes.toString(rowKeyComponents[1]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    String flowName = Separator.decode(Bytes.toString(rowKeyComponents[2]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    Long flowRunId =
+        TimelineStorageUtils.invertLong(Bytes.toLong(rowKeyComponents[3]));
+    String appId = AppIdKeyConverter.getInstance().decode(rowKeyComponents[4]);
+    return new ApplicationRowKey(clusterId, userId, flowName, flowRunId, appId);
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/apptoflow/AppToFlowRowKey.java

@@ -17,10 +17,6 @@
  */
 package org.apache.hadoop.yarn.server.timelineservice.storage.apptoflow;
 
-import org.apache.hadoop.hbase.util.Bytes;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
-
 /**
  * Represents a rowkey for the app_flow table.
  */
@@ -50,9 +46,8 @@ public class AppToFlowRowKey {
    * @return byte array with the row key
    */
   public static byte[] getRowKey(String clusterId, String appId) {
-    byte[] first = Bytes.toBytes(clusterId);
-    byte[] second = TimelineStorageUtils.encodeAppId(appId);
-    return Separator.QUALIFIERS.join(first, second);
+    return AppToFlowRowKeyConverter.getInstance().encode(
+        new AppToFlowRowKey(clusterId, appId));
   }
 
   /**
@@ -62,15 +57,6 @@ public class AppToFlowRowKey {
    * @return an <cite>AppToFlowRowKey</cite> object.
    */
   public static AppToFlowRowKey parseRowKey(byte[] rowKey) {
-    byte[][] rowKeyComponents = Separator.QUALIFIERS.split(rowKey);
-
-    if (rowKeyComponents.length < 2) {
-      throw new IllegalArgumentException("the row key is not valid for " +
-          "the app-to-flow table");
-    }
-
-    String clusterId = Bytes.toString(rowKeyComponents[0]);
-    String appId = TimelineStorageUtils.decodeAppId(rowKeyComponents[1]);
-    return new AppToFlowRowKey(clusterId, appId);
+    return AppToFlowRowKeyConverter.getInstance().decode(rowKey);
   }
 }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/apptoflow/AppToFlowRowKeyConverter.java

@@ -0,0 +1,96 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hadoop.yarn.server.timelineservice.storage.apptoflow;
+
+import org.apache.hadoop.hbase.util.Bytes;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.AppIdKeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
+
+/**
+ * Encodes and decodes row key for app_flow table.
+ * The row key is of the form : clusterId!appId.
+ * clusterId is a string and appId is encoded/decoded using
+ * {@link AppIdKeyConverter}.
+ */
+public final class AppToFlowRowKeyConverter
+    implements KeyConverter<AppToFlowRowKey> {
+  private static final AppToFlowRowKeyConverter INSTANCE =
+      new AppToFlowRowKeyConverter();
+
+  public static AppToFlowRowKeyConverter getInstance() {
+    return INSTANCE;
+  }
+
+  private AppToFlowRowKeyConverter() {
+  }
+
+  // App to flow row key is of the form clusterId!appId with the 2 segments
+  // separated by !. The sizes below indicate sizes of both of these segments
+  // in sequence. clusterId is a string. appId is represented as 12 bytes with
+  // cluster Timestamp part of appid being 8 bytes(long) and seq id being 4
+  // bytes(int).
+  // Strings are variable in size (i.e. end whenever separator is encountered).
+  // This is used while decoding and helps in determining where to split.
+  private static final int[] SEGMENT_SIZES = {
+      Separator.VARIABLE_SIZE, Bytes.SIZEOF_LONG + Bytes.SIZEOF_INT };
+
+  /*
+   * (non-Javadoc)
+   *
+   * Encodes AppToFlowRowKey object into a byte array with each component/field
+   * in AppToFlowRowKey separated by Separator#QUALIFIERS. This leads to an
+   * app to flow table row key of the form clusterId!appId
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #encode(java.lang.Object)
+   */
+  @Override
+  public byte[] encode(AppToFlowRowKey rowKey) {
+    byte[] first = Separator.encode(rowKey.getClusterId(),
+        Separator.SPACE, Separator.TAB, Separator.QUALIFIERS);
+    byte[] second = AppIdKeyConverter.getInstance().encode(rowKey.getAppId());
+    return Separator.QUALIFIERS.join(first, second);
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * Decodes an app to flow row key of the form clusterId!appId represented in
+   * byte format and converts it into an AppToFlowRowKey object.
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #decode(byte[])
+   */
+  @Override
+  public AppToFlowRowKey decode(byte[] rowKey) {
+    byte[][] rowKeyComponents =
+        Separator.QUALIFIERS.split(rowKey, SEGMENT_SIZES);
+    if (rowKeyComponents.length != 2) {
+      throw new IllegalArgumentException("the row key is not valid for " +
+          "the app-to-flow table");
+    }
+    String clusterId = Separator.decode(Bytes.toString(rowKeyComponents[0]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    String appId = AppIdKeyConverter.getInstance().decode(rowKeyComponents[1]);
+    return new AppToFlowRowKey(clusterId, appId);
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/AppIdKeyConverter.java

@@ -0,0 +1,101 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hadoop.yarn.server.timelineservice.storage.common;
+
+import org.apache.hadoop.hbase.util.Bytes;
+import org.apache.hadoop.yarn.api.records.ApplicationId;
+import org.apache.hadoop.yarn.util.ConverterUtils;
+
+/**
+ * Encodes and decodes {@link ApplicationId} for row keys.
+ * App ID is stored in row key as 12 bytes, cluster timestamp section of app id
+ * (long - 8 bytes) followed by sequence id section of app id (int - 4 bytes).
+ */
+public final class AppIdKeyConverter implements KeyConverter<String> {
+  private static final AppIdKeyConverter INSTANCE = new AppIdKeyConverter();
+
+  public static AppIdKeyConverter getInstance() {
+    return INSTANCE;
+  }
+
+  private AppIdKeyConverter() {
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * Converts/encodes a string app Id into a byte representation for (row) keys.
+   * For conversion, we extract cluster timestamp and sequence id from the
+   * string app id (calls ConverterUtils#toApplicationId(String) for
+   * conversion) and then store it in a byte array of length 12 (8 bytes (long)
+   * for cluster timestamp followed 4 bytes(int) for sequence id). Both cluster
+   * timestamp and sequence id are inverted so that the most recent cluster
+   * timestamp and highest sequence id appears first in the table (i.e.
+   * application id appears in a descending order).
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #encode(java.lang.Object)
+   */
+  @Override
+  public byte[] encode(String appIdStr) {
+    ApplicationId appId = ConverterUtils.toApplicationId(appIdStr);
+    byte[] appIdBytes = new byte[getKeySize()];
+    byte[] clusterTs = Bytes.toBytes(
+        TimelineStorageUtils.invertLong(appId.getClusterTimestamp()));
+    System.arraycopy(clusterTs, 0, appIdBytes, 0, Bytes.SIZEOF_LONG);
+    byte[] seqId = Bytes.toBytes(TimelineStorageUtils.invertInt(appId.getId()));
+    System.arraycopy(seqId, 0, appIdBytes, Bytes.SIZEOF_LONG, Bytes.SIZEOF_INT);
+    return appIdBytes;
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * Converts/decodes a 12 byte representation of app id for (row) keys to an
+   * app id in string format which can be returned back to client.
+   * For decoding, 12 bytes are interpreted as 8 bytes of inverted cluster
+   * timestamp(long) followed by 4 bytes of inverted sequence id(int). Calls
+   * ApplicationId#toString to generate string representation of app id.
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #decode(byte[])
+   */
+  @Override
+  public String decode(byte[] appIdBytes) {
+    if (appIdBytes.length != getKeySize()) {
+      throw new IllegalArgumentException("Invalid app id in byte format");
+    }
+    long clusterTs = TimelineStorageUtils.invertLong(
+        Bytes.toLong(appIdBytes, 0, Bytes.SIZEOF_LONG));
+    int seqId = TimelineStorageUtils.invertInt(
+        Bytes.toInt(appIdBytes, Bytes.SIZEOF_LONG, Bytes.SIZEOF_INT));
+    return ApplicationId.newInstance(clusterTs, seqId).toString();
+  }
+
+  /**
+   * Returns the size of app id after encoding.
+   *
+   * @return size of app id after encoding.
+   */
+  public static int getKeySize() {
+    return Bytes.SIZEOF_LONG + Bytes.SIZEOF_INT;
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/ColumnHelper.java

@@ -166,19 +166,22 @@ public class ColumnHelper<T> {
    * @param result from which to reads data with timestamps
    * @param columnPrefixBytes optional prefix to limit columns. If null all
    *          columns are returned.
+   * @param <K> identifies the type of column name(indicated by type of key
+   *     converter).
    * @param <V> the type of the values. The values will be cast into that type.
+   * @param keyConverter used to convert column bytes to the appropriate key
+   *     type.
    * @return the cell values at each respective time in for form
    *         {@literal {idA={timestamp1->value1}, idA={timestamp2->value2},
    *         idB={timestamp3->value3}, idC={timestamp1->value4}}}
    * @throws IOException if any problem occurs while reading results.
    */
   @SuppressWarnings("unchecked")
-  public <V> NavigableMap<String, NavigableMap<Long, V>>
-      readResultsWithTimestamps(Result result, byte[] columnPrefixBytes)
-          throws IOException {
+  public <K, V> NavigableMap<K, NavigableMap<Long, V>>
+      readResultsWithTimestamps(Result result, byte[] columnPrefixBytes,
+          KeyConverter<K> keyConverter) throws IOException {
 
-    NavigableMap<String, NavigableMap<Long, V>> results =
-        new TreeMap<String, NavigableMap<Long, V>>();
+    NavigableMap<K, NavigableMap<Long, V>> results = new TreeMap<>();
 
     if (result != null) {
       NavigableMap<
@@ -192,13 +195,17 @@ public class ColumnHelper<T> {
       if (columnCellMap != null) {
         for (Entry<byte[], NavigableMap<Long, byte[]>> entry : columnCellMap
             .entrySet()) {
-          String columnName = null;
+          K converterColumnKey = null;
           if (columnPrefixBytes == null) {
             if (LOG.isDebugEnabled()) {
               LOG.debug("null prefix was specified; returning all columns");
             }
-            // Decode the spaces we encoded in the column name.
-            columnName = Separator.decode(entry.getKey(), Separator.SPACE);
+            try {
+              converterColumnKey = keyConverter.decode(entry.getKey());
+            } catch (IllegalArgumentException iae) {
+              LOG.error("Illegal column found, skipping this column.", iae);
+              continue;
+            }
           } else {
             // A non-null prefix means columns are actually of the form
             // prefix!columnNameRemainder
@@ -207,13 +214,18 @@ public class ColumnHelper<T> {
             byte[] actualColumnPrefixBytes = columnNameParts[0];
             if (Bytes.equals(columnPrefixBytes, actualColumnPrefixBytes)
                 && columnNameParts.length == 2) {
-              // This is the prefix that we want
-              columnName = Separator.decode(columnNameParts[1]);
+              try {
+                // This is the prefix that we want
+                converterColumnKey = keyConverter.decode(columnNameParts[1]);
+              } catch (IllegalArgumentException iae) {
+                LOG.error("Illegal column found, skipping this column.", iae);
+                continue;
+              }
             }
           }
 
           // If this column has the prefix we want
-          if (columnName != null) {
+          if (converterColumnKey != null) {
             NavigableMap<Long, V> cellResults =
                 new TreeMap<Long, V>();
             NavigableMap<Long, byte[]> cells = entry.getValue();
@@ -226,7 +238,7 @@ public class ColumnHelper<T> {
                     value);
               }
             }
-            results.put(columnName, cellResults);
+            results.put(converterColumnKey, cellResults);
           }
         } // for entry : columnCellMap
       } // if columnCellMap != null
@@ -235,20 +247,24 @@ public class ColumnHelper<T> {
   }
 
   /**
+   * @param <K> identifies the type of column name(indicated by type of key
+   *     converter).
    * @param result from which to read columns
    * @param columnPrefixBytes optional prefix to limit columns. If null all
    *        columns are returned.
-   * @return the latest values of columns in the column family. This assumes
-   *         that the column name parts are all Strings by default. If the
-   *         column name parts should be treated natively and not be converted
-   *         back and forth from Strings, you should use
-   *         {@link #readResultsHavingCompoundColumnQualifiers(Result, byte[])}
-   *         instead.
+   * @param keyConverter used to convert column bytes to the appropriate key
+   *          type.
+   * @return the latest values of columns in the column family. If the column
+   *         prefix is null, the column qualifier is returned as Strings. For a
+   *         non-null column prefix bytes, the column qualifier is returned as
+   *         a list of parts, each part a byte[]. This is to facilitate
+   *         returning byte arrays of values that were not Strings.
    * @throws IOException if any problem occurs while reading results.
    */
-  public Map<String, Object> readResults(Result result,
-      byte[] columnPrefixBytes) throws IOException {
-    Map<String, Object> results = new HashMap<String, Object>();
+  public <K> Map<K, Object> readResults(Result result,
+      byte[] columnPrefixBytes, KeyConverter<K> keyConverter)
+      throws IOException {
+    Map<K, Object> results = new HashMap<K, Object>();
 
     if (result != null) {
       Map<byte[], byte[]> columns = result.getFamilyMap(columnFamilyBytes);
@@ -256,84 +272,40 @@ public class ColumnHelper<T> {
         byte[] columnKey = entry.getKey();
         if (columnKey != null && columnKey.length > 0) {
 
-          String columnName = null;
+          K converterColumnKey = null;
           if (columnPrefixBytes == null) {
-            if (LOG.isDebugEnabled()) {
-              LOG.debug("null prefix was specified; returning all columns");
+            try {
+              converterColumnKey = keyConverter.decode(columnKey);
+            } catch (IllegalArgumentException iae) {
+              LOG.error("Illegal column found, skipping this column.", iae);
+              continue;
             }
-            // Decode the spaces we encoded in the column name.
-            columnName = Separator.decode(columnKey, Separator.SPACE);
           } else {
             // A non-null prefix means columns are actually of the form
             // prefix!columnNameRemainder
-            byte[][] columnNameParts =
-                Separator.QUALIFIERS.split(columnKey, 2);
-            byte[] actualColumnPrefixBytes = columnNameParts[0];
-            if (Bytes.equals(columnPrefixBytes, actualColumnPrefixBytes)
-                && columnNameParts.length == 2) {
-              // This is the prefix that we want
-              // if the column name is a compound qualifier
-              // with non string datatypes, the following decode will not
-              // work correctly since it considers all components to be String
-              // invoke the readResultsHavingCompoundColumnQualifiers function
-              columnName = Separator.decode(columnNameParts[1]);
+            byte[][] columnNameParts = Separator.QUALIFIERS.split(columnKey, 2);
+            if (columnNameParts.length > 0) {
+              byte[] actualColumnPrefixBytes = columnNameParts[0];
+              // If this is the prefix that we want
+              if (Bytes.equals(columnPrefixBytes, actualColumnPrefixBytes)
+                  && columnNameParts.length == 2) {
+                try {
+                  converterColumnKey = keyConverter.decode(columnNameParts[1]);
+                } catch (IllegalArgumentException iae) {
+                  LOG.error("Illegal column found, skipping this column.", iae);
+                  continue;
+                }
+              }
             }
-          }
+          } // if-else
 
-          // If this column has the prefix we want
-          if (columnName != null) {
+          // If the columnPrefix is null (we want all columns), or the actual
+          // prefix matches the given prefix we want this column
+          if (converterColumnKey != null) {
             Object value = converter.decodeValue(entry.getValue());
-            results.put(columnName, value);
-          }
-        }
-      } // for entry
-    }
-    return results;
-  }
-
-  /**
-   * @param result from which to read columns
-   * @param columnPrefixBytes optional prefix to limit columns. If null all
-   *        columns are returned.
-   * @return the latest values of columns in the column family. If the column
-   *         prefix is null, the column qualifier is returned as Strings. For a
-   *         non-null column prefix bytes, the column qualifier is returned as
-   *         a list of parts, each part a byte[]. This is to facilitate
-   *         returning byte arrays of values that were not Strings.
-   * @throws IOException if any problem occurs while reading results.
-   */
-  public Map<?, Object> readResultsHavingCompoundColumnQualifiers(Result result,
-      byte[] columnPrefixBytes) throws IOException {
-    // handle the case where the column prefix is null
-    // it is the same as readResults() so simply delegate to that implementation
-    if (columnPrefixBytes == null) {
-      return readResults(result, null);
-    }
-
-    Map<byte[][], Object> results = new HashMap<byte[][], Object>();
-
-    if (result != null) {
-      Map<byte[], byte[]> columns = result.getFamilyMap(columnFamilyBytes);
-      for (Entry<byte[], byte[]> entry : columns.entrySet()) {
-        byte[] columnKey = entry.getKey();
-        if (columnKey != null && columnKey.length > 0) {
-          // A non-null prefix means columns are actually of the form
-          // prefix!columnNameRemainder
-          // with a compound column qualifier, we are presuming existence of a
-          // prefix
-          byte[][] columnNameParts = Separator.QUALIFIERS.split(columnKey, 2);
-          if (columnNameParts.length > 0) {
-            byte[] actualColumnPrefixBytes = columnNameParts[0];
-            if (Bytes.equals(columnPrefixBytes, actualColumnPrefixBytes)
-                && columnNameParts.length == 2) {
-              // This is the prefix that we want
-              byte[][] columnQualifierParts =
-                  Separator.VALUES.split(columnNameParts[1]);
-              Object value = converter.decodeValue(entry.getValue());
-              // we return the columnQualifier in parts since we don't know
-              // which part is of which data type
-              results.put(columnQualifierParts, value);
-            }
+            // we return the columnQualifier in parts since we don't know
+            // which part is of which data type.
+            results.put(converterColumnKey, value);
           }
         }
       } // for entry
@@ -353,8 +325,9 @@ public class ColumnHelper<T> {
   public static byte[] getColumnQualifier(byte[] columnPrefixBytes,
       String qualifier) {
 
-    // We don't want column names to have spaces
-    byte[] encodedQualifier = Bytes.toBytes(Separator.SPACE.encode(qualifier));
+    // We don't want column names to have spaces / tabs.
+    byte[] encodedQualifier =
+        Separator.encode(qualifier, Separator.SPACE, Separator.TAB);
     if (columnPrefixBytes == null) {
       return encodedQualifier;
     }
@@ -366,22 +339,6 @@ public class ColumnHelper<T> {
     return columnQualifier;
   }
 
-  /**
-   * Create a compound column qualifier by combining qualifier and components.
-   *
-   * @param qualifier Column QUalifier.
-   * @param components Other components.
-   * @return a byte array representing compound column qualifier.
-   */
-  public static byte[] getCompoundColumnQualifierBytes(String qualifier,
-      byte[]...components) {
-    byte[] colQualBytes = Bytes.toBytes(Separator.VALUES.encode(qualifier));
-    for (int i = 0; i < components.length; i++) {
-      colQualBytes = Separator.VALUES.join(colQualBytes, components[i]);
-    }
-    return colQualBytes;
-  }
-
   /**
    * @param columnPrefixBytes The byte representation for the column prefix.
    *          Should not contain {@link Separator#QUALIFIERS}.

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/ColumnPrefix.java

@@ -91,37 +91,33 @@ public interface ColumnPrefix<T> {
   Object readResult(Result result, String qualifier) throws IOException;
 
   /**
-   * @param result from which to read columns
+   *
+   * @param <K> identifies the type of key converter.
+   * @param result from which to read columns.
+   * @param keyConverter used to convert column bytes to the appropriate key
+   *          type
    * @return the latest values of columns in the column family with this prefix
    *         (or all of them if the prefix value is null).
    * @throws IOException if there is any exception encountered while reading
-   *     results.
+   *           results.
    */
-  Map<String, Object> readResults(Result result) throws IOException;
+  <K> Map<K, Object> readResults(Result result, KeyConverter<K> keyConverter)
+      throws IOException;
 
   /**
-   * @param result from which to reads data with timestamps
+   * @param result from which to reads data with timestamps.
+   * @param <K> identifies the type of key converter.
    * @param <V> the type of the values. The values will be cast into that type.
+   * @param keyConverter used to convert column bytes to the appropriate key
+   *     type.
    * @return the cell values at each respective time in for form
    *         {@literal {idA={timestamp1->value1}, idA={timestamp2->value2},
    *         idB={timestamp3->value3}, idC={timestamp1->value4}}}
    * @throws IOException if there is any exception encountered while reading
    *     result.
    */
-  <V> NavigableMap<String, NavigableMap<Long, V>>
-      readResultsWithTimestamps(Result result) throws IOException;
-
-  /**
-   * @param result from which to read columns
-   * @return the latest values of columns in the column family. The column
-   *         qualifier is returned as a list of parts, each part a byte[]. This
-   *         is to facilitate returning byte arrays of values that were not
-   *         Strings. If they can be treated as Strings, you should use
-   *         {@link #readResults(Result)} instead.
-   * @throws IOException if any problem occurs while reading results.
-   */
-  Map<?, Object> readResultsHavingCompoundColumnQualifiers(Result result)
-      throws IOException;
+  <K, V> NavigableMap<K, NavigableMap<Long, V>> readResultsWithTimestamps(
+      Result result, KeyConverter<K> keyConverter) throws IOException;
 
   /**
    * @param qualifierPrefix Column qualifier or prefix of qualifier.
@@ -146,15 +142,4 @@ public interface ColumnPrefix<T> {
    * @return a {@link ValueConverter} implementation.
    */
   ValueConverter getValueConverter();
-
-  /**
-   * Get compound column qualifier bytes if the column qualifier is a compound
-   * qualifier. Returns the qualifier passed as bytes if the column is not a
-   * compound column qualifier.
-   *
-   * @param qualifier Column Qualifier.
-   * @param components Other components.
-   * @return byte array representing compound column qualifier.
-   */
-  byte[] getCompoundColQualBytes(String qualifier, byte[]...components);
 }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/EventColumnName.java

@@ -0,0 +1,48 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.hadoop.yarn.server.timelineservice.storage.common;
+
+/**
+ * Encapsulates information about Event column names for application and entity
+ * tables. Used while encoding/decoding event column names.
+ */
+public class EventColumnName {
+
+  private final String id;
+  private final Long timestamp;
+  private final String infoKey;
+
+  public EventColumnName(String id, Long timestamp, String infoKey) {
+    this.id = id;
+    this.timestamp = timestamp;
+    this.infoKey = infoKey;
+  }
+
+  public String getId() {
+    return id;
+  }
+
+  public Long getTimestamp() {
+    return timestamp;
+  }
+
+  public String getInfoKey() {
+    return infoKey;
+  }
+
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/EventColumnNameConverter.java

@@ -0,0 +1,105 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with this
+ * work for additional information regarding copyright ownership. The ASF
+ * licenses this file to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
+ * License for the specific language governing permissions and limitations under
+ * the License.
+ */
+
+package org.apache.hadoop.yarn.server.timelineservice.storage.common;
+
+import org.apache.hadoop.hbase.util.Bytes;
+
+/**
+ * Encodes and decodes event column names for application and entity tables.
+ * The event column name is of the form : eventId=timestamp=infokey.
+ * If info is not associated with the event, event column name is of the form :
+ * eventId=timestamp=
+ * Event timestamp is long and rest are strings.
+ * Column prefixes are not part of the eventcolumn name passed for encoding. It
+ * is added later, if required in the associated ColumnPrefix implementations.
+ */
+public final class EventColumnNameConverter
+    implements KeyConverter<EventColumnName> {
+  private static final EventColumnNameConverter INSTANCE =
+      new EventColumnNameConverter();
+
+  public static EventColumnNameConverter getInstance() {
+    return INSTANCE;
+  }
+
+  private EventColumnNameConverter() {
+  }
+
+  // eventId=timestamp=infokey are of types String, Long String
+  // Strings are variable in size (i.e. end whenever separator is encountered).
+  // This is used while decoding and helps in determining where to split.
+  private static final int[] SEGMENT_SIZES = {
+      Separator.VARIABLE_SIZE, Bytes.SIZEOF_LONG, Separator.VARIABLE_SIZE };
+
+  /*
+   * (non-Javadoc)
+   *
+   * Encodes EventColumnName into a byte array with each component/field in
+   * EventColumnName separated by Separator#VALUES. This leads to an event
+   * column name of the form eventId=timestamp=infokey.
+   * If timestamp in passed EventColumnName object is null (eventId is not null)
+   * this returns a column prefix of the form eventId= and if infokey in
+   * EventColumnName is null (other 2 components are not null), this returns a
+   * column name of the form eventId=timestamp=
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #encode(java.lang.Object)
+   */
+  @Override
+  public byte[] encode(EventColumnName key) {
+    byte[] first = Separator.encode(key.getId(), Separator.SPACE, Separator.TAB,
+        Separator.VALUES);
+    if (key.getTimestamp() == null) {
+      return Separator.VALUES.join(first, Separator.EMPTY_BYTES);
+    }
+    byte[] second = Bytes.toBytes(
+        TimelineStorageUtils.invertLong(key.getTimestamp()));
+    if (key.getInfoKey() == null) {
+      return Separator.VALUES.join(first, second, Separator.EMPTY_BYTES);
+    }
+    return Separator.VALUES.join(first, second, Separator.encode(
+        key.getInfoKey(), Separator.SPACE, Separator.TAB, Separator.VALUES));
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * Decodes an event column name of the form eventId=timestamp= or
+   * eventId=timestamp=infoKey represented in byte format and converts it into
+   * an EventColumnName object.
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #decode(byte[])
+   */
+  @Override
+  public EventColumnName decode(byte[] bytes) {
+    byte[][] components = Separator.VALUES.split(bytes, SEGMENT_SIZES);
+    if (components.length != 3) {
+      throw new IllegalArgumentException("the column name is not valid");
+    }
+    String id = Separator.decode(Bytes.toString(components[0]),
+        Separator.VALUES, Separator.TAB, Separator.SPACE);
+    Long ts = TimelineStorageUtils.invertLong(Bytes.toLong(components[1]));
+    String infoKey = components[2].length == 0 ? null :
+        Separator.decode(Bytes.toString(components[2]),
+            Separator.VALUES, Separator.TAB, Separator.SPACE);
+    return new EventColumnName(id, ts, infoKey);
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/KeyConverter.java

@@ -0,0 +1,41 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.hadoop.yarn.server.timelineservice.storage.common;
+
+/**
+ * Interface which has to be implemented for encoding and decoding row keys and
+ * columns.
+ */
+public interface KeyConverter<T> {
+  /**
+   * Encodes a key as a byte array.
+   *
+   * @param key key to be encoded.
+   * @return a byte array.
+   */
+  byte[] encode(T key);
+
+  /**
+   * Decodes a byte array and returns a key of type T.
+   *
+   * @param bytes byte representation
+   * @return an object(key) of type T which has been constructed after decoding
+   * the bytes.
+   */
+  T decode(byte[] bytes);
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/LongKeyConverter.java

@@ -0,0 +1,68 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hadoop.yarn.server.timelineservice.storage.common;
+
+import java.io.IOException;
+/**
+ * Encodes and decodes column names / row keys which are long.
+ */
+public final class LongKeyConverter implements KeyConverter<Long> {
+  private static final LongKeyConverter INSTANCE = new LongKeyConverter();
+
+  public static LongKeyConverter getInstance() {
+    return INSTANCE;
+  }
+
+  private LongKeyConverter() {
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #encode(java.lang.Object)
+   */
+  @Override
+  public byte[] encode(Long key) {
+    try {
+      // IOException will not be thrown here as we are explicitly passing
+      // Long.
+      return LongConverter.getInstance().encodeValue(key);
+    } catch (IOException e) {
+      return null;
+    }
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #decode(byte[])
+   */
+  @Override
+  public Long decode(byte[] bytes) {
+    try {
+      return (Long) LongConverter.getInstance().decodeValue(bytes);
+    } catch (IOException e) {
+      return null;
+    }
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/Separator.java

@@ -45,7 +45,13 @@ public enum Separator {
    * getting a + for a space, which may already occur in strings, so we don't
    * want that.
    */
-  SPACE(" ", "%2$");
+  SPACE(" ", "%2$"),
+
+  /**
+   * separator in values, often used to avoid having these in qualifiers and
+   * names.
+   */
+  TAB("\t", "%3$");
 
   /**
    * The string value of this separator.
@@ -67,7 +73,22 @@ public enum Separator {
    */
   private final String quotedValue;
 
-  private static final byte[] EMPTY_BYTES = new byte[0];
+  /**
+   * Indicator for variable size of an individual segment in a split. The
+   * segment ends wherever separator is encountered.
+   * Typically used for string.
+   * Also used to indicate that there is no fixed number of splits which need to
+   * be returned. If split limit is specified as this, all possible splits are
+   * returned.
+   */
+  public static final int VARIABLE_SIZE = 0;
+
+
+  /** empty string. */
+  public static final String EMPTY_STRING = "";
+
+  /** empty bytes. */
+  public static final byte[] EMPTY_BYTES = new byte[0];
 
   /**
    * @param value of the separator to use. Cannot be null or empty string.
@@ -222,7 +243,6 @@ public enum Separator {
         System.arraycopy(this.bytes, 0, buf, offset, this.value.length());
         offset += this.value.length();
       }
-
     }
     return buf;
   }
@@ -307,7 +327,25 @@ public enum Separator {
    * @return source split by this separator.
    */
   public byte[][] split(byte[] source, int limit) {
-    return TimelineStorageUtils.split(source, this.bytes, limit);
+    return split(source, this.bytes, limit);
+  }
+
+  /**
+   * Splits the source array into multiple array segments using this separator.
+   * The sizes indicate the sizes of the relative components/segments.
+   * In case one of the segments contains this separator before the specified
+   * size is reached, the separator will be considered part of that segment and
+   * we will continue till size is reached.
+   * Variable length strings cannot contain this separator and are indiced with
+   * a size of {@value #VARIABLE_SIZE}. Such strings are encoded for this
+   * separator and decoded after the results from split is returned.
+   *
+   * @param source byte array to be split.
+   * @param sizes sizes of relative components/segments.
+   * @return source split by this separator as per the sizes specified..
+   */
+  public byte[][] split(byte[] source, int[] sizes) {
+    return split(source, this.bytes, sizes);
   }
 
   /**
@@ -315,10 +353,158 @@ public enum Separator {
    * as many times as splits are found. This will naturally produce copied byte
    * arrays for each of the split segments.
    *
-   * @param source to be split
+   * @param source byte array to be split
    * @return source split by this separator.
    */
   public byte[][] split(byte[] source) {
-    return TimelineStorageUtils.split(source, this.bytes);
+    return split(source, this.bytes);
+  }
+
+  /**
+   * Returns a list of ranges identifying [start, end) -- closed, open --
+   * positions within the source byte array that would be split using the
+   * separator byte array.
+   * The sizes indicate the sizes of the relative components/segments.
+   * In case one of the segments contains this separator before the specified
+   * size is reached, the separator will be considered part of that segment and
+   * we will continue till size is reached.
+   * Variable length strings cannot contain this separator and are indiced with
+   * a size of {@value #VARIABLE_SIZE}. Such strings are encoded for this
+   * separator and decoded after the results from split is returned.
+   *
+   * @param source the source data
+   * @param separator the separator pattern to look for
+   * @param sizes indicate the sizes of the relative components/segments.
+   * @return a list of ranges.
+   */
+  private static List<Range> splitRanges(byte[] source, byte[] separator,
+      int[] sizes) {
+    List<Range> segments = new ArrayList<Range>();
+    if (source == null || separator == null) {
+      return segments;
+    }
+    // VARIABLE_SIZE here indicates that there is no limit to number of segments
+    // to return.
+    int limit = VARIABLE_SIZE;
+    if (sizes != null && sizes.length > 0) {
+      limit = sizes.length;
+    }
+    int start = 0;
+    int currentSegment = 0;
+    itersource: for (int i = 0; i < source.length; i++) {
+      for (int j = 0; j < separator.length; j++) {
+        if (source[i + j] != separator[j]) {
+          continue itersource;
+        }
+      }
+      // all separator elements matched
+      if (limit > VARIABLE_SIZE) {
+        if (segments.size() >= (limit - 1)) {
+          // everything else goes in one final segment
+          break;
+        }
+        if (sizes != null) {
+          int currentSegExpectedSize = sizes[currentSegment];
+          if (currentSegExpectedSize > VARIABLE_SIZE) {
+            int currentSegSize = i - start;
+            if (currentSegSize < currentSegExpectedSize) {
+              // Segment not yet complete. More bytes to parse.
+              continue itersource;
+            } else if (currentSegSize > currentSegExpectedSize) {
+              // Segment is not as per size.
+              throw new IllegalArgumentException(
+                  "Segments not separated as per expected sizes");
+            }
+          }
+        }
+      }
+      segments.add(new Range(start, i));
+      start = i + separator.length;
+      // i will be incremented again in outer for loop
+      i += separator.length - 1;
+      currentSegment++;
+    }
+    // add in remaining to a final range
+    if (start <= source.length) {
+      if (sizes != null) {
+        // Check if final segment is as per size specified.
+        if (sizes[currentSegment] > VARIABLE_SIZE &&
+            source.length - start > sizes[currentSegment]) {
+          // Segment is not as per size.
+          throw new IllegalArgumentException(
+              "Segments not separated as per expected sizes");
+        }
+      }
+      segments.add(new Range(start, source.length));
+    }
+    return segments;
+  }
+
+  /**
+   * Splits based on segments calculated based on limit/sizes specified for the
+   * separator.
+   *
+   * @param source byte array to be split.
+   * @param segments specifies the range for each segment.
+   * @return a byte[][] split as per the segment ranges.
+   */
+  private static byte[][] split(byte[] source, List<Range> segments) {
+    byte[][] splits = new byte[segments.size()][];
+    for (int i = 0; i < segments.size(); i++) {
+      Range r = segments.get(i);
+      byte[] tmp = new byte[r.length()];
+      if (tmp.length > 0) {
+        System.arraycopy(source, r.start(), tmp, 0, r.length());
+      }
+      splits[i] = tmp;
+    }
+    return splits;
+  }
+
+  /**
+   * Splits the source array into multiple array segments using the given
+   * separator based on the sizes. This will naturally produce copied byte
+   * arrays for each of the split segments.
+   *
+   * @param source source array.
+   * @param separator separator represented as a byte array.
+   * @param sizes sizes of relative components/segments.
+   * @return byte[][] after splitting the source.
+   */
+  private static byte[][] split(byte[] source, byte[] separator, int[] sizes) {
+    List<Range> segments = splitRanges(source, separator, sizes);
+    return split(source, segments);
+  }
+
+  /**
+   * Splits the source array into multiple array segments using the given
+   * separator. This will naturally produce copied byte arrays for each of the
+   * split segments.
+   *
+   * @param source Source array.
+   * @param separator Separator represented as a byte array.
+   * @return byte[][] after splitting the source.
+   */
+  private static byte[][] split(byte[] source, byte[] separator) {
+    return split(source, separator, (int[]) null);
+  }
+
+  /**
+   * Splits the source array into multiple array segments using the given
+   * separator, up to a maximum of count items. This will naturally produce
+   * copied byte arrays for each of the split segments.
+   *
+   * @param source Source array.
+   * @param separator Separator represented as a byte array.
+   * @param limit a non-positive value indicates no limit on number of segments.
+   * @return byte[][] after splitting the input source.
+   */
+  private static byte[][] split(byte[] source, byte[] separator, int limit) {
+    int[] sizes = null;
+    if (limit > VARIABLE_SIZE) {
+      sizes = new int[limit];
+    }
+    List<Range> segments = splitRanges(source, separator, sizes);
+    return split(source, segments);
   }
 }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/StringKeyConverter.java

@@ -0,0 +1,59 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hadoop.yarn.server.timelineservice.storage.common;
+
+/**
+ * Encodes and decodes column names / row keys which are merely strings.
+ * Column prefixes are not part of the column name passed for encoding. It is
+ * added later, if required in the associated ColumnPrefix implementations.
+ */
+public final class StringKeyConverter implements KeyConverter<String> {
+  private static final StringKeyConverter INSTANCE = new StringKeyConverter();
+
+  public static StringKeyConverter getInstance() {
+    return INSTANCE;
+  }
+
+  private StringKeyConverter() {
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #encode(java.lang.Object)
+   */
+  @Override
+  public byte[] encode(String key) {
+    return Separator.encode(key, Separator.SPACE, Separator.TAB);
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #decode(byte[])
+   */
+  @Override
+  public String decode(byte[] bytes) {
+    return Separator.decode(bytes, Separator.TAB, Separator.SPACE);
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/TimelineStorageUtils.java

@@ -18,7 +18,6 @@
 package org.apache.hadoop.yarn.server.timelineservice.storage.common;
 
 import java.io.IOException;
-import java.util.ArrayList;
 import java.util.EnumSet;
 import java.util.HashMap;
 import java.util.HashSet;
@@ -40,7 +39,6 @@ import org.apache.hadoop.hbase.KeyValue;
 import org.apache.hadoop.hbase.Tag;
 import org.apache.hadoop.hbase.client.Result;
 import org.apache.hadoop.hbase.util.Bytes;
-import org.apache.hadoop.yarn.api.records.ApplicationId;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEntity;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEntityType;
 import org.apache.hadoop.yarn.api.records.timelineservice.TimelineEvent;
@@ -48,18 +46,17 @@ import org.apache.hadoop.yarn.api.records.timelineservice.TimelineMetric;
 import org.apache.hadoop.yarn.server.metrics.ApplicationMetricsConstants;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineCompareFilter;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineCompareOp;
-import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineKeyValueFilter;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineExistsFilter;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineFilter;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineFilter.TimelineFilterType;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineFilterList;
+import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineKeyValueFilter;
 import org.apache.hadoop.yarn.server.timelineservice.reader.filter.TimelineKeyValuesFilter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.TimelineReader.Field;
 import org.apache.hadoop.yarn.server.timelineservice.storage.flow.AggregationCompactionDimension;
 import org.apache.hadoop.yarn.server.timelineservice.storage.flow.AggregationOperation;
 import org.apache.hadoop.yarn.server.timelineservice.storage.flow.Attribute;
 import org.apache.hadoop.yarn.server.timelineservice.storage.flow.FlowRunTable;
-import org.apache.hadoop.yarn.util.ConverterUtils;
 
 /**
  * A bunch of utility functions used across TimelineReader and TimelineWriter.
@@ -72,108 +69,9 @@ public final class TimelineStorageUtils {
 
   private static final Log LOG = LogFactory.getLog(TimelineStorageUtils.class);
 
-  /** empty bytes. */
-  public static final byte[] EMPTY_BYTES = new byte[0];
-
-  /** indicator for no limits for splitting. */
-  public static final int NO_LIMIT_SPLIT = -1;
-
   /** milliseconds in one day. */
   public static final long MILLIS_ONE_DAY = 86400000L;
 
-  /**
-   * Splits the source array into multiple array segments using the given
-   * separator, up to a maximum of count items. This will naturally produce
-   * copied byte arrays for each of the split segments. To identify the split
-   * ranges without the array copies, see {@link #splitRanges(byte[], byte[])}.
-   *
-   * @param source Source array.
-   * @param separator Separator represented as a byte array.
-   * @return byte[][] after splitting the source
-   */
-  public static byte[][] split(byte[] source, byte[] separator) {
-    return split(source, separator, NO_LIMIT_SPLIT);
-  }
-
-  /**
-   * Splits the source array into multiple array segments using the given
-   * separator, up to a maximum of count items. This will naturally produce
-   * copied byte arrays for each of the split segments. To identify the split
-   * ranges without the array copies, see {@link #splitRanges(byte[], byte[])}.
-   *
-   * @param source Source array.
-   * @param separator Separator represented as a byte array.
-   * @param limit a non-positive value indicates no limit on number of segments.
-   * @return byte[][] after splitting the input source.
-   */
-  public static byte[][] split(byte[] source, byte[] separator, int limit) {
-    List<Range> segments = splitRanges(source, separator, limit);
-
-    byte[][] splits = new byte[segments.size()][];
-    for (int i = 0; i < segments.size(); i++) {
-      Range r = segments.get(i);
-      byte[] tmp = new byte[r.length()];
-      if (tmp.length > 0) {
-        System.arraycopy(source, r.start(), tmp, 0, r.length());
-      }
-      splits[i] = tmp;
-    }
-    return splits;
-  }
-
-  /**
-   * Returns a list of ranges identifying [start, end) -- closed, open --
-   * positions within the source byte array that would be split using the
-   * separator byte array.
-   *
-   * @param source Source array.
-   * @param separator Separator represented as a byte array.
-   * @return a list of ranges.
-   */
-  public static List<Range> splitRanges(byte[] source, byte[] separator) {
-    return splitRanges(source, separator, NO_LIMIT_SPLIT);
-  }
-
-  /**
-   * Returns a list of ranges identifying [start, end) -- closed, open --
-   * positions within the source byte array that would be split using the
-   * separator byte array.
-   *
-   * @param source the source data
-   * @param separator the separator pattern to look for
-   * @param limit the maximum number of splits to identify in the source
-   * @return a list of ranges.
-   */
-  public static List<Range> splitRanges(byte[] source, byte[] separator,
-      int limit) {
-    List<Range> segments = new ArrayList<Range>();
-    if ((source == null) || (separator == null)) {
-      return segments;
-    }
-    int start = 0;
-    itersource: for (int i = 0; i < source.length; i++) {
-      for (int j = 0; j < separator.length; j++) {
-        if (source[i + j] != separator[j]) {
-          continue itersource;
-        }
-      }
-      // all separator elements matched
-      if (limit > 0 && segments.size() >= (limit - 1)) {
-        // everything else goes in one final segment
-        break;
-      }
-      segments.add(new Range(start, i));
-      start = i + separator.length;
-      // i will be incremented again in outer for loop
-      i += separator.length - 1;
-    }
-    // add in remaining to a final range
-    if (start <= source.length) {
-      segments.add(new Range(start, source.length));
-    }
-    return segments;
-  }
-
   /**
    * Converts a timestamp into it's inverse timestamp to be used in (row) keys
    * where we want to have the most recent timestamp in the top of the table
@@ -200,53 +98,6 @@ public final class TimelineStorageUtils {
     return Integer.MAX_VALUE - key;
   }
 
-
-  /**
-   * Converts/encodes a string app Id into a byte representation for (row) keys.
-   * For conversion, we extract cluster timestamp and sequence id from the
-   * string app id (calls {@link ConverterUtils#toApplicationId(String)} for
-   * conversion) and then store it in a byte array of length 12 (8 bytes (long)
-   * for cluster timestamp followed 4 bytes(int) for sequence id). Both cluster
-   * timestamp and sequence id are inverted so that the most recent cluster
-   * timestamp and highest sequence id appears first in the table (i.e.
-   * application id appears in a descending order).
-   *
-   * @param appIdStr application id in string format i.e.
-   * application_{cluster timestamp}_{sequence id with min 4 digits}
-   *
-   * @return encoded byte representation of app id.
-   */
-  public static byte[] encodeAppId(String appIdStr) {
-    ApplicationId appId = ConverterUtils.toApplicationId(appIdStr);
-    byte[] appIdBytes = new byte[Bytes.SIZEOF_LONG + Bytes.SIZEOF_INT];
-    byte[] clusterTs = Bytes.toBytes(invertLong(appId.getClusterTimestamp()));
-    System.arraycopy(clusterTs, 0, appIdBytes, 0, Bytes.SIZEOF_LONG);
-    byte[] seqId = Bytes.toBytes(invertInt(appId.getId()));
-    System.arraycopy(seqId, 0, appIdBytes, Bytes.SIZEOF_LONG, Bytes.SIZEOF_INT);
-    return appIdBytes;
-  }
-
-  /**
-   * Converts/decodes a 12 byte representation of app id for (row) keys to an
-   * app id in string format which can be returned back to client.
-   * For decoding, 12 bytes are interpreted as 8 bytes of inverted cluster
-   * timestamp(long) followed by 4 bytes of inverted sequence id(int). Calls
-   * {@link ApplicationId#toString} to generate string representation of app id.
-   *
-   * @param appIdBytes application id in byte representation.
-   *
-   * @return decoded app id in string format.
-   */
-  public static String decodeAppId(byte[] appIdBytes) {
-    if (appIdBytes.length != (Bytes.SIZEOF_LONG + Bytes.SIZEOF_INT)) {
-      throw new IllegalArgumentException("Invalid app id in byte format");
-    }
-    long clusterTs = invertLong(Bytes.toLong(appIdBytes, 0, Bytes.SIZEOF_LONG));
-    int seqId =
-        invertInt(Bytes.toInt(appIdBytes, Bytes.SIZEOF_LONG, Bytes.SIZEOF_INT));
-    return ApplicationId.newInstance(clusterTs, seqId).toString();
-  }
-
   /**
    * returns the timestamp of that day's start (which is midnight 00:00:00 AM)
    * for a given input timestamp.
@@ -810,7 +661,8 @@ public final class TimelineStorageUtils {
       TimelineEntity entity, Result result, ColumnPrefix<T> prefix,
       boolean isRelatedTo) throws IOException {
     // isRelatedTo and relatesTo are of type Map<String, Set<String>>
-    Map<String, Object> columns = prefix.readResults(result);
+    Map<String, Object> columns =
+        prefix.readResults(result, StringKeyConverter.getInstance());
     for (Map.Entry<String, Object> column : columns.entrySet()) {
       for (String id : Separator.VALUES.splitEncoded(
           column.getValue().toString())) {
@@ -837,7 +689,8 @@ public final class TimelineStorageUtils {
       TimelineEntity entity, Result result, ColumnPrefix<T> prefix,
       boolean isConfig) throws IOException {
     // info and configuration are of type Map<String, Object or String>
-    Map<String, Object> columns = prefix.readResults(result);
+    Map<String, Object> columns =
+        prefix.readResults(result, StringKeyConverter.getInstance());
     if (isConfig) {
       for (Map.Entry<String, Object> column : columns.entrySet()) {
         entity.addConfig(column.getKey(), column.getValue().toString());
@@ -861,30 +714,24 @@ public final class TimelineStorageUtils {
   public static <T> void readEvents(TimelineEntity entity, Result result,
       ColumnPrefix<T> prefix) throws IOException {
     Map<String, TimelineEvent> eventsMap = new HashMap<>();
-    Map<?, Object> eventsResult =
-        prefix.readResultsHavingCompoundColumnQualifiers(result);
-    for (Map.Entry<?, Object> eventResult : eventsResult.entrySet()) {
-      byte[][] karr = (byte[][])eventResult.getKey();
-      // the column name is of the form "eventId=timestamp=infoKey"
-      if (karr.length == 3) {
-        String id = Bytes.toString(karr[0]);
-        long ts = TimelineStorageUtils.invertLong(Bytes.toLong(karr[1]));
-        String key = Separator.VALUES.joinEncoded(id, Long.toString(ts));
-        TimelineEvent event = eventsMap.get(key);
-        if (event == null) {
-          event = new TimelineEvent();
-          event.setId(id);
-          event.setTimestamp(ts);
-          eventsMap.put(key, event);
-        }
-        // handle empty info
-        String infoKey = karr[2].length == 0 ? null : Bytes.toString(karr[2]);
-        if (infoKey != null) {
-          event.addInfo(infoKey, eventResult.getValue());
-        }
-      } else {
-        LOG.warn("incorrectly formatted column name: it will be discarded");
-        continue;
+    Map<EventColumnName, Object> eventsResult =
+        prefix.readResults(result, EventColumnNameConverter.getInstance());
+    for (Map.Entry<EventColumnName, Object>
+             eventResult : eventsResult.entrySet()) {
+      EventColumnName eventColumnName = eventResult.getKey();
+      String key = eventColumnName.getId() +
+          Long.toString(eventColumnName.getTimestamp());
+      // Retrieve previously seen event to add to it
+      TimelineEvent event = eventsMap.get(key);
+      if (event == null) {
+        // First time we're seeing this event, add it to the eventsMap
+        event = new TimelineEvent();
+        event.setId(eventColumnName.getId());
+        event.setTimestamp(eventColumnName.getTimestamp());
+        eventsMap.put(key, event);
+      }
+      if (eventColumnName.getInfoKey() != null) {
+        event.addInfo(eventColumnName.getInfoKey(), eventResult.getValue());
       }
     }
     Set<TimelineEvent> eventsSet = new HashSet<>(eventsMap.values());

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/entity/EntityColumnPrefix.java

@@ -27,9 +27,10 @@ import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnFamily
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnHelper;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.GenericConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.LongConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TypedBufferedMutator;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.LongConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ValueConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.flow.Attribute;
 
@@ -78,7 +79,6 @@ public enum EntityColumnPrefix implements ColumnPrefix<EntityTable> {
    */
   private final String columnPrefix;
   private final byte[] columnPrefixBytes;
-  private final boolean compoundColQual;
 
   /**
    * Private constructor, meant to be used by the enum definition.
@@ -122,7 +122,6 @@ public enum EntityColumnPrefix implements ColumnPrefix<EntityTable> {
       this.columnPrefixBytes =
           Bytes.toBytes(Separator.SPACE.encode(columnPrefix));
     }
-    this.compoundColQual = compondColQual;
   }
 
   /**
@@ -154,14 +153,6 @@ public enum EntityColumnPrefix implements ColumnPrefix<EntityTable> {
     return column.getValueConverter();
   }
 
-  public byte[] getCompoundColQualBytes(String qualifier,
-      byte[]...components) {
-    if (!compoundColQual) {
-      return ColumnHelper.getColumnQualifier(null, qualifier);
-    }
-    return ColumnHelper.getCompoundColumnQualifierBytes(qualifier, components);
-  }
-
   /*
    * (non-Javadoc)
    *
@@ -233,26 +224,12 @@ public enum EntityColumnPrefix implements ColumnPrefix<EntityTable> {
    *
    * @see
    * org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix
-   * #readResults(org.apache.hadoop.hbase.client.Result)
+   * #readResults(org.apache.hadoop.hbase.client.Result,
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter)
    */
-  public Map<String, Object> readResults(Result result) throws IOException {
-    return column.readResults(result, columnPrefixBytes);
-  }
-
-  /**
-   * @param result from which to read columns
-   * @return the latest values of columns in the column family. The column
-   *         qualifier is returned as a list of parts, each part a byte[]. This
-   *         is to facilitate returning byte arrays of values that were not
-   *         Strings. If they can be treated as Strings, you should use
-   *         {@link #readResults(Result)} instead.
-   * @throws IOException if there is any exception encountered while reading
-   *     result.
-   */
-  public Map<?, Object> readResultsHavingCompoundColumnQualifiers(Result result)
-          throws IOException {
-    return column.readResultsHavingCompoundColumnQualifiers(result,
-        columnPrefixBytes);
+  public <K> Map<K, Object> readResults(Result result,
+      KeyConverter<K> keyConverter) throws IOException {
+    return column.readResults(result, columnPrefixBytes, keyConverter);
   }
 
   /*
@@ -260,11 +237,14 @@ public enum EntityColumnPrefix implements ColumnPrefix<EntityTable> {
    *
    * @see
    * org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix
-   * #readResultsWithTimestamps(org.apache.hadoop.hbase.client.Result)
+   * #readResultsWithTimestamps(org.apache.hadoop.hbase.client.Result,
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter)
    */
-  public <V> NavigableMap<String, NavigableMap<Long, V>>
-      readResultsWithTimestamps(Result result) throws IOException {
-    return column.readResultsWithTimestamps(result, columnPrefixBytes);
+  public <K, V> NavigableMap<K, NavigableMap<Long, V>>
+      readResultsWithTimestamps(Result result, KeyConverter<K> keyConverter)
+      throws IOException {
+    return column.readResultsWithTimestamps(result, columnPrefixBytes,
+        keyConverter);
   }
 
   /**

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/entity/EntityRowKey.java

@@ -17,10 +17,6 @@
  */
 package org.apache.hadoop.yarn.server.timelineservice.storage.entity;
 
-import org.apache.hadoop.hbase.util.Bytes;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
-
 /**
  * Represents a rowkey for the entity table.
  */
@@ -28,13 +24,13 @@ public class EntityRowKey {
   private final String clusterId;
   private final String userId;
   private final String flowName;
-  private final long flowRunId;
+  private final Long flowRunId;
   private final String appId;
   private final String entityType;
   private final String entityId;
 
   public EntityRowKey(String clusterId, String userId, String flowName,
-      long flowRunId, String appId, String entityType, String entityId) {
+      Long flowRunId, String appId, String entityType, String entityId) {
     this.clusterId = clusterId;
     this.userId = userId;
     this.flowName = flowName;
@@ -56,7 +52,7 @@ public class EntityRowKey {
     return flowName;
   }
 
-  public long getFlowRunId() {
+  public Long getFlowRunId() {
     return flowRunId;
   }
 
@@ -85,14 +81,8 @@ public class EntityRowKey {
    */
   public static byte[] getRowKeyPrefix(String clusterId, String userId,
       String flowName, Long flowRunId, String appId) {
-    byte[] first =
-        Bytes.toBytes(Separator.QUALIFIERS.joinEncoded(userId, clusterId,
-            flowName));
-    // Note that flowRunId is a long, so we can't encode them all at the same
-    // time.
-    byte[] second = Bytes.toBytes(TimelineStorageUtils.invertLong(flowRunId));
-    byte[] third = TimelineStorageUtils.encodeAppId(appId);
-    return Separator.QUALIFIERS.join(first, second, third, new byte[0]);
+    return EntityRowKeyConverter.getInstance().encode(new EntityRowKey(
+        clusterId, userId, flowName, flowRunId, appId, null, null));
   }
 
   /**
@@ -111,16 +101,8 @@ public class EntityRowKey {
    */
   public static byte[] getRowKeyPrefix(String clusterId, String userId,
       String flowName, Long flowRunId, String appId, String entityType) {
-    byte[] first =
-        Bytes.toBytes(Separator.QUALIFIERS.joinEncoded(userId, clusterId,
-            flowName));
-    // Note that flowRunId is a long, so we can't encode them all at the same
-    // time.
-    byte[] second = Bytes.toBytes(TimelineStorageUtils.invertLong(flowRunId));
-    byte[] third = TimelineStorageUtils.encodeAppId(appId);
-    byte[] fourth =
-        Bytes.toBytes(Separator.QUALIFIERS.joinEncoded(entityType, ""));
-    return Separator.QUALIFIERS.join(first, second, third, fourth);
+    return EntityRowKeyConverter.getInstance().encode(new EntityRowKey(
+        clusterId, userId, flowName, flowRunId, appId, entityType, null));
   }
 
   /**
@@ -140,16 +122,8 @@ public class EntityRowKey {
   public static byte[] getRowKey(String clusterId, String userId,
       String flowName, Long flowRunId, String appId, String entityType,
       String entityId) {
-    byte[] first =
-        Bytes.toBytes(Separator.QUALIFIERS.joinEncoded(userId, clusterId,
-            flowName));
-    // Note that flowRunId is a long, so we can't encode them all at the same
-    // time.
-    byte[] second = Bytes.toBytes(TimelineStorageUtils.invertLong(flowRunId));
-    byte[] third = TimelineStorageUtils.encodeAppId(appId);
-    byte[] fourth =
-        Bytes.toBytes(Separator.QUALIFIERS.joinEncoded(entityType, entityId));
-    return Separator.QUALIFIERS.join(first, second, third, fourth);
+    return EntityRowKeyConverter.getInstance().encode(new EntityRowKey(
+        clusterId, userId, flowName, flowRunId, appId, entityType, entityId));
   }
 
   /**
@@ -159,27 +133,6 @@ public class EntityRowKey {
    * @return An <cite>EntityRowKey</cite> object.
    */
   public static EntityRowKey parseRowKey(byte[] rowKey) {
-    byte[][] rowKeyComponents = Separator.QUALIFIERS.split(rowKey);
-
-    if (rowKeyComponents.length < 7) {
-      throw new IllegalArgumentException("the row key is not valid for " +
-          "an entity");
-    }
-
-    String userId =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[0]));
-    String clusterId =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[1]));
-    String flowName =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[2]));
-    long flowRunId =
-        TimelineStorageUtils.invertLong(Bytes.toLong(rowKeyComponents[3]));
-    String appId = TimelineStorageUtils.decodeAppId(rowKeyComponents[4]);
-    String entityType =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[5]));
-    String entityId =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[6]));
-    return new EntityRowKey(clusterId, userId, flowName, flowRunId, appId,
-        entityType, entityId);
+    return EntityRowKeyConverter.getInstance().decode(rowKey);
   }
 }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/entity/EntityRowKeyConverter.java

@@ -0,0 +1,143 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hadoop.yarn.server.timelineservice.storage.entity;
+
+import org.apache.hadoop.hbase.util.Bytes;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.AppIdKeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
+
+/**
+ * Encodes and decodes row key for entity table.
+ * The row key is of the form :
+ * userName!clusterId!flowName!flowRunId!appId!entityType!entityId.
+ * flowRunId is a long, appId is encoded/decoded using
+ * {@link AppIdKeyConverter} and rest are strings.
+ */
+public final class EntityRowKeyConverter implements KeyConverter<EntityRowKey> {
+  private static final EntityRowKeyConverter INSTANCE =
+      new EntityRowKeyConverter();
+
+  public static EntityRowKeyConverter getInstance() {
+    return INSTANCE;
+  }
+
+  private EntityRowKeyConverter() {
+  }
+
+  // Entity row key is of the form
+  // userName!clusterId!flowName!flowRunId!appId!entityType!entityId with each
+  // segment separated by !. The sizes below indicate sizes of each one of these
+  // segements in sequence. clusterId, userName, flowName, entityType and
+  // entityId are strings. flowrunId is a long hence 8 bytes in size. app id is
+  // represented as 12 bytes with cluster timestamp part of appid being 8 bytes
+  // (long) and seq id being 4 bytes(int).
+  // Strings are variable in size (i.e. end whenever separator is encountered).
+  // This is used while decoding and helps in determining where to split.
+  private static final int[] SEGMENT_SIZES = {
+      Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE,
+      Bytes.SIZEOF_LONG, AppIdKeyConverter.getKeySize(),
+      Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE };
+
+  /*
+   * (non-Javadoc)
+   *
+   * Encodes EntityRowKey object into a byte array with each component/field in
+   * EntityRowKey separated by Separator#QUALIFIERS. This leads to an entity
+   * table row key of the form
+   * userName!clusterId!flowName!flowRunId!appId!entityType!entityId
+   * If entityType in passed EntityRowKey object is null (and the fields
+   * preceding it i.e. clusterId, userId and flowName, flowRunId and appId are
+   * not null), this returns a row key prefix of the form
+   * userName!clusterId!flowName!flowRunId!appId! and if entityId in
+   * EntityRowKey is null (other 6 components are not null), this returns a row
+   * key prefix of the form
+   * userName!clusterId!flowName!flowRunId!appId!entityType!
+   * flowRunId is inverted while encoding as it helps maintain a descending
+   * order for row keys in entity table.
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #encode(java.lang.Object)
+   */
+  @Override
+  public byte[] encode(EntityRowKey rowKey) {
+    byte[] user = Separator.encode(rowKey.getUserId(),
+        Separator.SPACE, Separator.TAB, Separator.QUALIFIERS);
+    byte[] cluster = Separator.encode(rowKey.getClusterId(),
+        Separator.SPACE, Separator.TAB, Separator.QUALIFIERS);
+    byte[] flow = Separator.encode(rowKey.getFlowName(),
+        Separator.SPACE, Separator.TAB, Separator.QUALIFIERS);
+    byte[] first = Separator.QUALIFIERS.join(user, cluster, flow);
+    // Note that flowRunId is a long, so we can't encode them all at the same
+    // time.
+    byte[] second = Bytes.toBytes(TimelineStorageUtils.invertLong(
+        rowKey.getFlowRunId()));
+    byte[] third = AppIdKeyConverter.getInstance().encode(rowKey.getAppId());
+    if (rowKey.getEntityType() == null) {
+      return Separator.QUALIFIERS.join(
+          first, second, third, Separator.EMPTY_BYTES);
+    }
+    byte[] entityType = Separator.encode(rowKey.getEntityType(),
+        Separator.SPACE, Separator.TAB, Separator.QUALIFIERS);
+    byte[] entityId = rowKey.getEntityId() == null ? Separator.EMPTY_BYTES :
+        Separator.encode(rowKey.getEntityId(), Separator.SPACE, Separator.TAB,
+        Separator.QUALIFIERS);
+    byte[] fourth = Separator.QUALIFIERS.join(entityType, entityId);
+    return Separator.QUALIFIERS.join(first, second, third, fourth);
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * Decodes an application row key of the form
+   * userName!clusterId!flowName!flowRunId!appId!entityType!entityId represented
+   * in byte format and converts it into an EntityRowKey object. flowRunId is
+   * inverted while decoding as it was inverted while encoding.
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #decode(byte[])
+   */
+  @Override
+  public EntityRowKey decode(byte[] rowKey) {
+    byte[][] rowKeyComponents =
+        Separator.QUALIFIERS.split(rowKey, SEGMENT_SIZES);
+    if (rowKeyComponents.length != 7) {
+      throw new IllegalArgumentException("the row key is not valid for " +
+          "an entity");
+    }
+    String userId = Separator.decode(Bytes.toString(rowKeyComponents[0]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    String clusterId = Separator.decode(Bytes.toString(rowKeyComponents[1]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    String flowName = Separator.decode(Bytes.toString(rowKeyComponents[2]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    Long flowRunId =
+        TimelineStorageUtils.invertLong(Bytes.toLong(rowKeyComponents[3]));
+    String appId = AppIdKeyConverter.getInstance().decode(rowKeyComponents[4]);
+    String entityType = Separator.decode(Bytes.toString(rowKeyComponents[5]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    String entityId =Separator.decode(Bytes.toString(rowKeyComponents[6]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    return new EntityRowKey(clusterId, userId, flowName, flowRunId, appId,
+        entityType, entityId);
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/flow/FlowActivityColumnPrefix.java

@@ -26,6 +26,7 @@ import org.apache.hadoop.hbase.util.Bytes;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnFamily;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnHelper;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TypedBufferedMutator;
@@ -51,7 +52,6 @@ public enum FlowActivityColumnPrefix
    */
   private final String columnPrefix;
   private final byte[] columnPrefixBytes;
-  private final boolean compoundColQual;
 
   private final AggregationOperation aggOp;
 
@@ -83,7 +83,6 @@ public enum FlowActivityColumnPrefix
           .encode(columnPrefix));
     }
     this.aggOp = aggOp;
-    this.compoundColQual = compoundColQual;
   }
 
   /**
@@ -169,10 +168,12 @@ public enum FlowActivityColumnPrefix
    *
    * @see
    * org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix
-   * #readResults(org.apache.hadoop.hbase.client.Result)
+   * #readResults(org.apache.hadoop.hbase.client.Result,
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter)
    */
-  public Map<String, Object> readResults(Result result) throws IOException {
-    return column.readResults(result, columnPrefixBytes);
+  public <K> Map<K, Object> readResults(Result result,
+      KeyConverter<K> keyConverter) throws IOException {
+    return column.readResults(result, columnPrefixBytes, keyConverter);
   }
 
   /*
@@ -180,11 +181,14 @@ public enum FlowActivityColumnPrefix
    *
    * @see
    * org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix
-   * #readResultsWithTimestamps(org.apache.hadoop.hbase.client.Result)
+   * #readResultsWithTimestamps(org.apache.hadoop.hbase.client.Result,
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter)
    */
-  public <T> NavigableMap<String, NavigableMap<Long, T>>
-      readResultsWithTimestamps(Result result) throws IOException {
-    return column.readResultsWithTimestamps(result, columnPrefixBytes);
+  public <K, V> NavigableMap<K, NavigableMap<Long, V>>
+      readResultsWithTimestamps(Result result, KeyConverter<K> keyConverter)
+      throws IOException {
+    return column.readResultsWithTimestamps(result, columnPrefixBytes,
+        keyConverter);
   }
 
   /**
@@ -270,20 +274,4 @@ public enum FlowActivityColumnPrefix
     column.store(rowKey, tableMutator, columnQualifier, null, inputValue,
         combinedAttributes);
   }
-
-  @Override
-  public byte[] getCompoundColQualBytes(String qualifier,
-      byte[]...components) {
-    if (!compoundColQual) {
-      return ColumnHelper.getColumnQualifier(null, qualifier);
-    }
-    return ColumnHelper.getCompoundColumnQualifierBytes(qualifier, components);
-  }
-
-  @Override
-  public Map<?, Object> readResultsHavingCompoundColumnQualifiers(Result result)
-      throws IOException {
-    // There are no compound column qualifiers for flow activity table.
-    return null;
-  }
 }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/flow/FlowActivityRowKey.java

@@ -17,8 +17,6 @@
  */
 package org.apache.hadoop.yarn.server.timelineservice.storage.flow;
 
-import org.apache.hadoop.hbase.util.Bytes;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
 
 /**
@@ -27,11 +25,11 @@ import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStor
 public class FlowActivityRowKey {
 
   private final String clusterId;
-  private final long dayTs;
+  private final Long dayTs;
   private final String userId;
   private final String flowName;
 
-  public FlowActivityRowKey(String clusterId, long dayTs, String userId,
+  public FlowActivityRowKey(String clusterId, Long dayTs, String userId,
       String flowName) {
     this.clusterId = clusterId;
     this.dayTs = dayTs;
@@ -43,7 +41,7 @@ public class FlowActivityRowKey {
     return clusterId;
   }
 
-  public long getDayTimestamp() {
+  public Long getDayTimestamp() {
     return dayTs;
   }
 
@@ -63,7 +61,8 @@ public class FlowActivityRowKey {
    * @return byte array with the row key prefix
    */
   public static byte[] getRowKeyPrefix(String clusterId) {
-    return Bytes.toBytes(Separator.QUALIFIERS.joinEncoded(clusterId, ""));
+    return FlowActivityRowKeyConverter.getInstance().encode(
+        new FlowActivityRowKey(clusterId, null, null, null));
   }
 
   /**
@@ -75,9 +74,8 @@ public class FlowActivityRowKey {
    * @return byte array with the row key prefix
    */
   public static byte[] getRowKeyPrefix(String clusterId, long dayTs) {
-    return Separator.QUALIFIERS.join(
-        Bytes.toBytes(Separator.QUALIFIERS.encode(clusterId)),
-        Bytes.toBytes(TimelineStorageUtils.invertLong(dayTs)), new byte[0]);
+    return FlowActivityRowKeyConverter.getInstance().encode(
+        new FlowActivityRowKey(clusterId, dayTs, null, null));
   }
 
   /**
@@ -94,12 +92,8 @@ public class FlowActivityRowKey {
       String flowName) {
     // convert it to Day's time stamp
     eventTs = TimelineStorageUtils.getTopOfTheDayTimestamp(eventTs);
-
-    return Separator.QUALIFIERS.join(
-        Bytes.toBytes(Separator.QUALIFIERS.encode(clusterId)),
-        Bytes.toBytes(TimelineStorageUtils.invertLong(eventTs)),
-        Bytes.toBytes(Separator.QUALIFIERS.encode(userId)),
-        Bytes.toBytes(Separator.QUALIFIERS.encode(flowName)));
+    return FlowActivityRowKeyConverter.getInstance().encode(
+        new FlowActivityRowKey(clusterId, eventTs, userId, flowName));
   }
 
   /**
@@ -109,21 +103,6 @@ public class FlowActivityRowKey {
    * @return A <cite>FlowActivityRowKey</cite> object.
    */
   public static FlowActivityRowKey parseRowKey(byte[] rowKey) {
-    byte[][] rowKeyComponents = Separator.QUALIFIERS.split(rowKey);
-
-    if (rowKeyComponents.length < 4) {
-      throw new IllegalArgumentException("the row key is not valid for "
-          + "a flow activity");
-    }
-
-    String clusterId = Separator.QUALIFIERS.decode(Bytes
-        .toString(rowKeyComponents[0]));
-    long dayTs =
-        TimelineStorageUtils.invertLong(Bytes.toLong(rowKeyComponents[1]));
-    String userId = Separator.QUALIFIERS.decode(Bytes
-        .toString(rowKeyComponents[2]));
-    String flowName = Separator.QUALIFIERS.decode(Bytes
-        .toString(rowKeyComponents[3]));
-    return new FlowActivityRowKey(clusterId, dayTs, userId, flowName);
+    return FlowActivityRowKeyConverter.getInstance().decode(rowKey);
   }
 }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/flow/FlowActivityRowKeyConverter.java

@@ -0,0 +1,115 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hadoop.yarn.server.timelineservice.storage.flow;
+
+import org.apache.hadoop.hbase.util.Bytes;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
+
+/**
+ * Encodes and decodes row key for flow activity table.
+ * The row key is of the form : clusterId!dayTimestamp!user!flowName.
+ * dayTimestamp(top of the day timestamp) is a long and rest are strings.
+ */
+public final class FlowActivityRowKeyConverter implements
+    KeyConverter<FlowActivityRowKey> {
+  private static final FlowActivityRowKeyConverter INSTANCE =
+      new FlowActivityRowKeyConverter();
+
+  public static FlowActivityRowKeyConverter getInstance() {
+    return INSTANCE;
+  }
+
+  private FlowActivityRowKeyConverter() {
+  }
+
+  // Flow activity row key is of the form clusterId!dayTimestamp!user!flowName
+  // with each segment separated by !. The sizes below indicate sizes of each
+  // one of these segements in sequence. clusterId, user and flowName are
+  // strings. Top of the day timestamp is a long hence 8 bytes in size.
+  // Strings are variable in size (i.e. end whenever separator is encountered).
+  // This is used while decoding and helps in determining where to split.
+  private static final int[] SEGMENT_SIZES = {
+      Separator.VARIABLE_SIZE, Bytes.SIZEOF_LONG, Separator.VARIABLE_SIZE,
+      Separator.VARIABLE_SIZE };
+
+  /*
+   * (non-Javadoc)
+   *
+   * Encodes FlowActivityRowKey object into a byte array with each
+   * component/field in FlowActivityRowKey separated by Separator#QUALIFIERS.
+   * This leads to an flow activity table row key of the form
+   * clusterId!dayTimestamp!user!flowName
+   * If dayTimestamp in passed FlowActivityRowKey object is null and clusterId
+   * is not null, this returns a row key prefix as clusterId! and if userId in
+   * FlowActivityRowKey is null (and the fields preceding it i.e. clusterId and
+   * dayTimestamp are not null), this returns a row key prefix as
+   * clusterId!dayTimeStamp!
+   * dayTimestamp is inverted while encoding as it helps maintain a descending
+   * order for row keys in flow activity table.
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #encode(java.lang.Object)
+   */
+
+  @Override
+  public byte[] encode(FlowActivityRowKey rowKey) {
+    if (rowKey.getDayTimestamp() == null) {
+      return Separator.QUALIFIERS.join(Separator.encode(rowKey.getClusterId(),
+          Separator.SPACE, Separator.TAB, Separator.QUALIFIERS),
+              Separator.EMPTY_BYTES);
+    }
+    if (rowKey.getUserId() == null) {
+      return Separator.QUALIFIERS.join(Separator.encode(rowKey.getClusterId(),
+          Separator.SPACE, Separator.TAB, Separator.QUALIFIERS),
+          Bytes.toBytes(TimelineStorageUtils.invertLong(
+              rowKey.getDayTimestamp())), Separator.EMPTY_BYTES);
+    }
+    return Separator.QUALIFIERS.join(
+        Separator.encode(rowKey.getClusterId(), Separator.SPACE, Separator.TAB,
+            Separator.QUALIFIERS),
+        Bytes.toBytes(
+            TimelineStorageUtils.invertLong(rowKey.getDayTimestamp())),
+        Separator.encode(rowKey.getUserId(), Separator.SPACE, Separator.TAB,
+            Separator.QUALIFIERS),
+        Separator.encode(rowKey.getFlowName(), Separator.SPACE, Separator.TAB,
+            Separator.QUALIFIERS));
+  }
+
+  @Override
+  public FlowActivityRowKey decode(byte[] rowKey) {
+    byte[][] rowKeyComponents =
+        Separator.QUALIFIERS.split(rowKey, SEGMENT_SIZES);
+    if (rowKeyComponents.length != 4) {
+      throw new IllegalArgumentException("the row key is not valid for "
+          + "a flow activity");
+    }
+    String clusterId = Separator.decode(Bytes.toString(rowKeyComponents[0]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    Long dayTs =
+        TimelineStorageUtils.invertLong(Bytes.toLong(rowKeyComponents[1]));
+    String userId = Separator.decode(Bytes.toString(rowKeyComponents[2]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    String flowName = Separator.decode(Bytes.toString(rowKeyComponents[3]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    return new FlowActivityRowKey(clusterId, dayTs, userId, flowName);
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/flow/FlowRunColumnPrefix.java

@@ -26,10 +26,11 @@ import org.apache.hadoop.hbase.util.Bytes;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnFamily;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnHelper;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.LongConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TypedBufferedMutator;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.LongConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ValueConverter;
 
 /**
@@ -40,8 +41,7 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
   /**
    * To store flow run info values.
    */
-  METRIC(FlowRunColumnFamily.INFO, "m", null,
-      LongConverter.getInstance());
+  METRIC(FlowRunColumnFamily.INFO, "m", null, LongConverter.getInstance());
 
   private final ColumnHelper<FlowRunTable> column;
   private final ColumnFamily<FlowRunTable> columnFamily;
@@ -52,17 +52,14 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
    */
   private final String columnPrefix;
   private final byte[] columnPrefixBytes;
-  private final boolean compoundColQual;
 
   private final AggregationOperation aggOp;
 
   /**
    * Private constructor, meant to be used by the enum definition.
    *
-   * @param columnFamily
-   *          that this column is stored in.
-   * @param columnPrefix
-   *          for this column.
+   * @param columnFamily that this column is stored in.
+   * @param columnPrefix for this column.
    */
   private FlowRunColumnPrefix(ColumnFamily<FlowRunTable> columnFamily,
       String columnPrefix, AggregationOperation fra, ValueConverter converter) {
@@ -79,11 +76,10 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
       this.columnPrefixBytes = null;
     } else {
       // Future-proof by ensuring the right column prefix hygiene.
-      this.columnPrefixBytes = Bytes.toBytes(Separator.SPACE
-          .encode(columnPrefix));
+      this.columnPrefixBytes =
+          Bytes.toBytes(Separator.SPACE.encode(columnPrefix));
     }
     this.aggOp = fra;
-    this.compoundColQual = compoundColQual;
   }
 
   /**
@@ -99,14 +95,14 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
 
   @Override
   public byte[] getColumnPrefixBytes(byte[] qualifierPrefix) {
-    return ColumnHelper.getColumnQualifier(
-        this.columnPrefixBytes, qualifierPrefix);
+    return ColumnHelper.getColumnQualifier(this.columnPrefixBytes,
+        qualifierPrefix);
   }
 
   @Override
   public byte[] getColumnPrefixBytes(String qualifierPrefix) {
-    return ColumnHelper.getColumnQualifier(
-        this.columnPrefixBytes, qualifierPrefix);
+    return ColumnHelper.getColumnQualifier(this.columnPrefixBytes,
+        qualifierPrefix);
   }
 
   @Override
@@ -139,8 +135,8 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
     }
 
     byte[] columnQualifier = getColumnPrefixBytes(qualifier);
-    Attribute[] combinedAttributes = TimelineStorageUtils.combineAttributes(
-        attributes, this.aggOp);
+    Attribute[] combinedAttributes =
+        TimelineStorageUtils.combineAttributes(attributes, this.aggOp);
     column.store(rowKey, tableMutator, columnQualifier, timestamp, inputValue,
         combinedAttributes);
   }
@@ -166,8 +162,8 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
     }
 
     byte[] columnQualifier = getColumnPrefixBytes(qualifier);
-    Attribute[] combinedAttributes = TimelineStorageUtils.combineAttributes(
-        attributes, this.aggOp);
+    Attribute[] combinedAttributes =
+        TimelineStorageUtils.combineAttributes(attributes, this.aggOp);
     column.store(rowKey, tableMutator, columnQualifier, timestamp, inputValue,
         combinedAttributes);
   }
@@ -180,8 +176,8 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
    * #readResult(org.apache.hadoop.hbase.client.Result, java.lang.String)
    */
   public Object readResult(Result result, String qualifier) throws IOException {
-    byte[] columnQualifier = ColumnHelper.getColumnQualifier(
-        this.columnPrefixBytes, qualifier);
+    byte[] columnQualifier =
+        ColumnHelper.getColumnQualifier(this.columnPrefixBytes, qualifier);
     return column.readResult(result, columnQualifier);
   }
 
@@ -190,10 +186,12 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
    *
    * @see
    * org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix
-   * #readResults(org.apache.hadoop.hbase.client.Result)
+   * #readResults(org.apache.hadoop.hbase.client.Result,
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter)
    */
-  public Map<String, Object> readResults(Result result) throws IOException {
-    return column.readResults(result, columnPrefixBytes);
+  public <K> Map<K, Object> readResults(Result result,
+      KeyConverter<K> keyConverter) throws IOException {
+    return column.readResults(result, columnPrefixBytes, keyConverter);
   }
 
   /*
@@ -201,11 +199,14 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
    *
    * @see
    * org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix
-   * #readResultsWithTimestamps(org.apache.hadoop.hbase.client.Result)
+   * #readResultsWithTimestamps(org.apache.hadoop.hbase.client.Result,
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter)
    */
-  public <T> NavigableMap<String, NavigableMap<Long, T>>
-      readResultsWithTimestamps(Result result) throws IOException {
-    return column.readResultsWithTimestamps(result, columnPrefixBytes);
+  public <K, V> NavigableMap<K, NavigableMap<Long, V>>
+      readResultsWithTimestamps(Result result, KeyConverter<K> keyConverter)
+      throws IOException {
+    return column.readResultsWithTimestamps(result, columnPrefixBytes,
+        keyConverter);
   }
 
   /**
@@ -213,8 +214,7 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
    * no match. The following holds true: {@code columnFor(x) == columnFor(y)} if
    * and only if {@code x.equals(y)} or {@code (x == y == null)}
    *
-   * @param columnPrefix
-   *          Name of the column to retrieve
+   * @param columnPrefix Name of the column to retrieve
    * @return the corresponding {@link FlowRunColumnPrefix} or null
    */
   public static final FlowRunColumnPrefix columnFor(String columnPrefix) {
@@ -242,10 +242,8 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
    * {@code columnFor(a,x) == columnFor(b,y)} if and only if
    * {@code (x == y == null)} or {@code a.equals(b) & x.equals(y)}
    *
-   * @param columnFamily
-   *          The columnFamily for which to retrieve the column.
-   * @param columnPrefix
-   *          Name of the column to retrieve
+   * @param columnFamily The columnFamily for which to retrieve the column.
+   * @param columnPrefix Name of the column to retrieve
    * @return the corresponding {@link FlowRunColumnPrefix} or null if both
    *         arguments don't match.
    */
@@ -267,20 +265,4 @@ public enum FlowRunColumnPrefix implements ColumnPrefix<FlowRunTable> {
     // Default to null
     return null;
   }
-
-  @Override
-  public byte[] getCompoundColQualBytes(String qualifier,
-      byte[]...components) {
-    if (!compoundColQual) {
-      return ColumnHelper.getColumnQualifier(null, qualifier);
-    }
-    return ColumnHelper.getCompoundColumnQualifierBytes(qualifier, components);
-  }
-
-  @Override
-  public Map<?, Object> readResultsHavingCompoundColumnQualifiers(Result result)
-      throws IOException {
-    // There are no compound column qualifiers for flow run table.
-    return null;
-  }
 }

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/flow/FlowRunRowKey.java

@@ -17,10 +17,6 @@
  */
 package org.apache.hadoop.yarn.server.timelineservice.storage.flow;
 
-import org.apache.hadoop.hbase.util.Bytes;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
-
 /**
  * Represents a rowkey for the flow run table.
  */
@@ -28,10 +24,10 @@ public class FlowRunRowKey {
   private final String clusterId;
   private final String userId;
   private final String flowName;
-  private final long flowRunId;
+  private final Long flowRunId;
 
   public FlowRunRowKey(String clusterId, String userId, String flowName,
-      long flowRunId) {
+      Long flowRunId) {
     this.clusterId = clusterId;
     this.userId = userId;
     this.flowName = flowName;
@@ -50,7 +46,7 @@ public class FlowRunRowKey {
     return flowName;
   }
 
-  public long getFlowRunId() {
+  public Long getFlowRunId() {
     return flowRunId;
   }
 
@@ -65,13 +61,13 @@ public class FlowRunRowKey {
    */
   public static byte[] getRowKeyPrefix(String clusterId, String userId,
       String flowName) {
-    return Bytes.toBytes(Separator.QUALIFIERS.joinEncoded(clusterId, userId,
-        flowName, ""));
+    return FlowRunRowKeyConverter.getInstance().encode(new FlowRunRowKey(
+        clusterId, userId, flowName, null));
   }
 
   /**
    * Constructs a row key for the entity table as follows: {
-   * clusterId!userI!flowName!Inverted Flow Run Id}.
+   * clusterId!userId!flowName!Inverted Flow Run Id}.
    *
    * @param clusterId Cluster Id.
    * @param userId User Id.
@@ -81,12 +77,8 @@ public class FlowRunRowKey {
    */
   public static byte[] getRowKey(String clusterId, String userId,
       String flowName, Long flowRunId) {
-    byte[] first = Bytes.toBytes(Separator.QUALIFIERS.joinEncoded(clusterId,
-        userId, flowName));
-    // Note that flowRunId is a long, so we can't encode them all at the same
-    // time.
-    byte[] second = Bytes.toBytes(TimelineStorageUtils.invertLong(flowRunId));
-    return Separator.QUALIFIERS.join(first, second);
+    return FlowRunRowKeyConverter.getInstance().encode(new FlowRunRowKey(
+        clusterId, userId, flowName, flowRunId));
   }
 
   /**
@@ -96,22 +88,7 @@ public class FlowRunRowKey {
    * @return A <cite>FlowRunRowKey</cite> object.
    */
   public static FlowRunRowKey parseRowKey(byte[] rowKey) {
-    byte[][] rowKeyComponents = Separator.QUALIFIERS.split(rowKey);
-
-    if (rowKeyComponents.length < 4) {
-      throw new IllegalArgumentException("the row key is not valid for " +
-          "a flow run");
-    }
-
-    String clusterId =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[0]));
-    String userId =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[1]));
-    String flowName =
-        Separator.QUALIFIERS.decode(Bytes.toString(rowKeyComponents[2]));
-    long flowRunId =
-        TimelineStorageUtils.invertLong(Bytes.toLong(rowKeyComponents[3]));
-    return new FlowRunRowKey(clusterId, userId, flowName, flowRunId);
+    return FlowRunRowKeyConverter.getInstance().decode(rowKey);
   }
 
   /**

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/flow/FlowRunRowKeyConverter.java

@@ -0,0 +1,120 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hadoop.yarn.server.timelineservice.storage.flow;
+
+import org.apache.hadoop.hbase.util.Bytes;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
+
+/**
+ * Encodes and decodes row key for flow run table.
+ * The row key is of the form : clusterId!userId!flowName!flowrunId.
+ * flowrunId is a long and rest are strings.
+ */
+public final class FlowRunRowKeyConverter implements
+    KeyConverter<FlowRunRowKey> {
+  private static final FlowRunRowKeyConverter INSTANCE =
+      new FlowRunRowKeyConverter();
+
+  public static FlowRunRowKeyConverter getInstance() {
+    return INSTANCE;
+  }
+
+  private FlowRunRowKeyConverter() {
+  }
+
+  // Flow run row key is of the form
+  // clusterId!userId!flowName!flowrunId with each segment separated by !.
+  // The sizes below indicate sizes of each one of these segments in sequence.
+  // clusterId, userId and flowName are strings. flowrunId is a long hence 8
+  // bytes in size. Strings are variable in size (i.e. end whenever separator is
+  // encountered). This is used while decoding and helps in determining where to
+  // split.
+  private static final int[] SEGMENT_SIZES = {
+      Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE,
+      Bytes.SIZEOF_LONG };
+
+  /*
+   * (non-Javadoc)
+   *
+   * Encodes FlowRunRowKey object into a byte array with each component/field in
+   * FlowRunRowKey separated by Separator#QUALIFIERS. This leads to an
+   * flow run row key of the form clusterId!userId!flowName!flowrunId
+   * If flowRunId in passed FlowRunRowKey object is null (and the fields
+   * preceding it i.e. clusterId, userId and flowName are not null), this
+   * returns a row key prefix of the form clusterId!userName!flowName!
+   * flowRunId is inverted while encoding as it helps maintain a descending
+   * order for flow keys in flow run table.
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #encode(java.lang.Object)
+   */
+  @Override
+  public byte[] encode(FlowRunRowKey rowKey) {
+    byte[] first = Separator.QUALIFIERS.join(
+        Separator.encode(rowKey.getClusterId(), Separator.SPACE, Separator.TAB,
+            Separator.QUALIFIERS),
+        Separator.encode(rowKey.getUserId(), Separator.SPACE, Separator.TAB,
+            Separator.QUALIFIERS),
+        Separator.encode(rowKey.getFlowName(), Separator.SPACE, Separator.TAB,
+            Separator.QUALIFIERS));
+    if (rowKey.getFlowRunId() == null) {
+      return Separator.QUALIFIERS.join(first, Separator.EMPTY_BYTES);
+    } else {
+      // Note that flowRunId is a long, so we can't encode them all at the same
+      // time.
+      byte[] second = Bytes.toBytes(TimelineStorageUtils.invertLong(
+          rowKey.getFlowRunId()));
+      return Separator.QUALIFIERS.join(first, second);
+    }
+  }
+
+  /*
+   * (non-Javadoc)
+   *
+   * Decodes an flow run row key of the form
+   * clusterId!userId!flowName!flowrunId represented in byte format and converts
+   * it into an FlowRunRowKey object. flowRunId is inverted while decoding as
+   * it was inverted while encoding.
+   *
+   * @see
+   * org.apache.hadoop.yarn.server.timelineservice.storage.common.KeyConverter
+   * #decode(byte[])
+   */
+  @Override
+  public FlowRunRowKey decode(byte[] rowKey) {
+    byte[][] rowKeyComponents =
+        Separator.QUALIFIERS.split(rowKey, SEGMENT_SIZES);
+    if (rowKeyComponents.length != 4) {
+      throw new IllegalArgumentException("the row key is not valid for " +
+          "a flow run");
+    }
+    String clusterId = Separator.decode(Bytes.toString(rowKeyComponents[0]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    String userId = Separator.decode(Bytes.toString(rowKeyComponents[1]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    String flowName = Separator.decode(Bytes.toString(rowKeyComponents[2]),
+        Separator.QUALIFIERS, Separator.TAB, Separator.SPACE);
+    Long flowRunId =
+        TimelineStorageUtils.invertLong(Bytes.toLong(rowKeyComponents[3]));
+    return new FlowRunRowKey(clusterId, userId, flowName, flowRunId);
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/flow/FlowScanner.java

@@ -44,9 +44,10 @@ import org.apache.hadoop.hbase.util.Bytes.ByteArrayComparator;
 import org.apache.hadoop.yarn.conf.YarnConfiguration;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.GenericConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.NumericValueConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.Separator;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimelineStorageUtils;
-import org.apache.hadoop.yarn.server.timelineservice.storage.common.ValueConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.TimestampGenerator;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.ValueConverter;
 
 import com.google.common.annotations.VisibleForTesting;
 
@@ -193,7 +194,7 @@ class FlowScanner implements RegionScanner, Closeable {
     // So all cells in one qualifier come one after the other before we see the
     // next column qualifier
     ByteArrayComparator comp = new ByteArrayComparator();
-    byte[] currentColumnQualifier = TimelineStorageUtils.EMPTY_BYTES;
+    byte[] currentColumnQualifier = Separator.EMPTY_BYTES;
     AggregationOperation currentAggOp = null;
     SortedSet<Cell> currentColumnCells = new TreeSet<>(KeyValue.COMPARATOR);
     Set<String> alreadySeenAggDim = new HashSet<>();
@@ -314,7 +315,7 @@ class FlowScanner implements RegionScanner, Closeable {
             + " cell qualifier="
             + Bytes.toString(CellUtil.cloneQualifier(cell))
             + " cell value= "
-            + (Number) converter.decodeValue(CellUtil.cloneValue(cell))
+            + converter.decodeValue(CellUtil.cloneValue(cell))
             + " timestamp=" + cell.getTimestamp());
       }
 
@@ -480,7 +481,7 @@ class FlowScanner implements RegionScanner, Closeable {
             LOG.trace("MAJOR COMPACTION loop sum= " + sum
                 + " discarding now: " + " qualifier="
                 + Bytes.toString(CellUtil.cloneQualifier(cell)) + " value="
-                + (Number) converter.decodeValue(CellUtil.cloneValue(cell))
+                + converter.decodeValue(CellUtil.cloneValue(cell))
                 + " timestamp=" + cell.getTimestamp() + " " + this.action);
           }
         } else {

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/reader/FlowActivityEntityReader.java

@@ -35,6 +35,7 @@ import org.apache.hadoop.yarn.server.timelineservice.reader.TimelineDataToRetrie
 import org.apache.hadoop.yarn.server.timelineservice.reader.TimelineEntityFilters;
 import org.apache.hadoop.yarn.server.timelineservice.reader.TimelineReaderContext;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.BaseTable;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.LongKeyConverter;
 import org.apache.hadoop.yarn.server.timelineservice.storage.flow.FlowActivityColumnPrefix;
 import org.apache.hadoop.yarn.server.timelineservice.storage.flow.FlowActivityRowKey;
 import org.apache.hadoop.yarn.server.timelineservice.storage.flow.FlowActivityTable;
@@ -125,7 +126,7 @@ class FlowActivityEntityReader extends TimelineEntityReader {
   protected TimelineEntity parseEntity(Result result) throws IOException {
     FlowActivityRowKey rowKey = FlowActivityRowKey.parseRowKey(result.getRow());
 
-    long time = rowKey.getDayTimestamp();
+    Long time = rowKey.getDayTimestamp();
     String user = rowKey.getUserId();
     String flowName = rowKey.getFlowName();
 
@@ -135,10 +136,11 @@ class FlowActivityEntityReader extends TimelineEntityReader {
     flowActivity.setId(flowActivity.getId());
     // get the list of run ids along with the version that are associated with
     // this flow on this day
-    Map<String, Object> runIdsMap =
-        FlowActivityColumnPrefix.RUN_ID.readResults(result);
-    for (Map.Entry<String, Object> e : runIdsMap.entrySet()) {
-      Long runId = Long.valueOf(e.getKey());
+    Map<Long, Object> runIdsMap =
+        FlowActivityColumnPrefix.RUN_ID.readResults(result,
+            LongKeyConverter.getInstance());
+    for (Map.Entry<Long, Object> e : runIdsMap.entrySet()) {
+      Long runId = e.getKey();
       String version = (String)e.getValue();
       FlowRunEntity flowRun = new FlowRunEntity();
       flowRun.setUser(user);

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/main/java/org/apache/hadoop/yarn/server/timelineservice/storage/reader/TimelineEntityReader.java

@@ -38,6 +38,7 @@ import org.apache.hadoop.yarn.server.timelineservice.reader.TimelineEntityFilter
 import org.apache.hadoop.yarn.server.timelineservice.reader.TimelineReaderContext;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.BaseTable;
 import org.apache.hadoop.yarn.server.timelineservice.storage.common.ColumnPrefix;
+import org.apache.hadoop.yarn.server.timelineservice.storage.common.StringKeyConverter;
 
 /**
  * The base class for reading and deserializing timeline entities from the
@@ -329,7 +330,8 @@ public abstract class TimelineEntityReader {
   protected void readMetrics(TimelineEntity entity, Result result,
       ColumnPrefix<?> columnPrefix) throws IOException {
     NavigableMap<String, NavigableMap<Long, Number>> metricsResult =
-        columnPrefix.readResultsWithTimestamps(result);
+        columnPrefix.readResultsWithTimestamps(
+            result, StringKeyConverter.getInstance());
     for (Map.Entry<String, NavigableMap<Long, Number>> metricResult:
         metricsResult.entrySet()) {
       TimelineMetric metric = new TimelineMetric();

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/test/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/TestKeyConverters.java

@@ -0,0 +1,293 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hadoop.yarn.server.timelineservice.storage.common;
+
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertNull;
+import static org.junit.Assert.assertTrue;
+
+import org.apache.hadoop.hbase.util.Bytes;
+import org.apache.hadoop.yarn.api.records.ApplicationId;
+import org.apache.hadoop.yarn.server.timelineservice.storage.application.ApplicationRowKey;
+import org.apache.hadoop.yarn.server.timelineservice.storage.application.ApplicationRowKeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.apptoflow.AppToFlowRowKey;
+import org.apache.hadoop.yarn.server.timelineservice.storage.apptoflow.AppToFlowRowKeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.entity.EntityRowKey;
+import org.apache.hadoop.yarn.server.timelineservice.storage.entity.EntityRowKeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.flow.FlowActivityRowKey;
+import org.apache.hadoop.yarn.server.timelineservice.storage.flow.FlowActivityRowKeyConverter;
+import org.apache.hadoop.yarn.server.timelineservice.storage.flow.FlowRunRowKey;
+import org.apache.hadoop.yarn.server.timelineservice.storage.flow.FlowRunRowKeyConverter;
+import org.junit.Test;
+
+public class TestKeyConverters {
+  private final static String QUALIFIER_SEP = Separator.QUALIFIERS.getValue();
+  private final static byte[] QUALIFIER_SEP_BYTES =
+      Bytes.toBytes(QUALIFIER_SEP);
+  private final static String CLUSTER = "cl" + QUALIFIER_SEP + "uster";
+  private final static String USER = QUALIFIER_SEP + "user";
+  private final static String FLOW_NAME =
+      "dummy_" + QUALIFIER_SEP + "flow" + QUALIFIER_SEP;
+  private final static Long FLOW_RUN_ID;
+  private final static String APPLICATION_ID;
+  static {
+    long runid = Long.MAX_VALUE - 900L;
+    byte[] longMaxByteArr = Bytes.toBytes(Long.MAX_VALUE);
+    byte[] byteArr = Bytes.toBytes(runid);
+    int sepByteLen = QUALIFIER_SEP_BYTES.length;
+    if (sepByteLen <= byteArr.length) {
+      for (int i = 0; i < sepByteLen; i++) {
+        byteArr[i] = (byte)(longMaxByteArr[i] - QUALIFIER_SEP_BYTES[i]);
+      }
+    }
+    FLOW_RUN_ID = Bytes.toLong(byteArr);
+    long clusterTs = System.currentTimeMillis();
+    byteArr = Bytes.toBytes(clusterTs);
+    if (sepByteLen <= byteArr.length) {
+      for (int i = 0; i < sepByteLen; i++) {
+        byteArr[byteArr.length - sepByteLen + i] =
+            (byte)(longMaxByteArr[byteArr.length - sepByteLen + i] -
+                QUALIFIER_SEP_BYTES[i]);
+      }
+    }
+    clusterTs = Bytes.toLong(byteArr);
+    int seqId = 222;
+    APPLICATION_ID = ApplicationId.newInstance(clusterTs, seqId).toString();
+  }
+
+  private static void verifyRowPrefixBytes(byte[] byteRowKeyPrefix) {
+    int sepLen = QUALIFIER_SEP_BYTES.length;
+    for (int i = 0; i < sepLen; i++) {
+      assertTrue("Row key prefix not encoded properly.",
+        byteRowKeyPrefix[byteRowKeyPrefix.length - sepLen  + i] ==
+            QUALIFIER_SEP_BYTES[i]);
+    }
+  }
+
+  @Test
+  public void testFlowActivityRowKeyConverter() {
+    Long ts = TimelineStorageUtils.getTopOfTheDayTimestamp(1459900830000L);
+    byte[] byteRowKey = FlowActivityRowKeyConverter.getInstance().encode(
+        new FlowActivityRowKey(CLUSTER, ts, USER, FLOW_NAME));
+    FlowActivityRowKey rowKey =
+        FlowActivityRowKeyConverter.getInstance().decode(byteRowKey);
+    assertEquals(CLUSTER, rowKey.getClusterId());
+    assertEquals(ts, rowKey.getDayTimestamp());
+    assertEquals(USER, rowKey.getUserId());
+    assertEquals(FLOW_NAME, rowKey.getFlowName());
+
+    byte[] byteRowKeyPrefix = FlowActivityRowKeyConverter.getInstance().encode(
+        new FlowActivityRowKey(CLUSTER, null, null, null));
+    byte[][] splits = Separator.QUALIFIERS.split(byteRowKeyPrefix, new int[] {
+        Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE });
+    assertEquals(2, splits.length);
+    assertEquals(0, splits[1].length);
+    assertEquals(CLUSTER,
+        Separator.QUALIFIERS.decode(Bytes.toString(splits[0])));
+    verifyRowPrefixBytes(byteRowKeyPrefix);
+
+    byteRowKeyPrefix = FlowActivityRowKeyConverter.getInstance().encode(
+        new FlowActivityRowKey(CLUSTER, ts, null, null));
+    splits = Separator.QUALIFIERS.split(byteRowKeyPrefix, new int[] {
+        Separator.VARIABLE_SIZE, Bytes.SIZEOF_LONG, Separator.VARIABLE_SIZE });
+    assertEquals(3, splits.length);
+    assertEquals(0, splits[2].length);
+    assertEquals(CLUSTER,
+        Separator.QUALIFIERS.decode(Bytes.toString(splits[0])));
+    assertEquals(ts, (Long) TimelineStorageUtils.invertLong(
+        Bytes.toLong(splits[1])));
+    verifyRowPrefixBytes(byteRowKeyPrefix);
+  }
+
+  @Test
+  public void testFlowRunRowKeyConverter() {
+    byte[] byteRowKey = FlowRunRowKeyConverter.getInstance().encode(
+        new FlowRunRowKey(CLUSTER, USER, FLOW_NAME, FLOW_RUN_ID));
+    FlowRunRowKey rowKey =
+        FlowRunRowKeyConverter.getInstance().decode(byteRowKey);
+    assertEquals(CLUSTER, rowKey.getClusterId());
+    assertEquals(USER, rowKey.getUserId());
+    assertEquals(FLOW_NAME, rowKey.getFlowName());
+    assertEquals(FLOW_RUN_ID, rowKey.getFlowRunId());
+
+    byte[] byteRowKeyPrefix = FlowRunRowKeyConverter.getInstance().encode(
+        new FlowRunRowKey(CLUSTER, USER, FLOW_NAME, null));
+    byte[][] splits = Separator.QUALIFIERS.split(byteRowKeyPrefix, new int[] {
+        Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE,
+        Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE });
+    assertEquals(4, splits.length);
+    assertEquals(0, splits[3].length);
+    assertEquals(FLOW_NAME,
+        Separator.QUALIFIERS.decode(Bytes.toString(splits[2])));
+    verifyRowPrefixBytes(byteRowKeyPrefix);
+  }
+
+  @Test
+  public void testApplicationRowKeyConverter() {
+    byte[] byteRowKey = ApplicationRowKeyConverter.getInstance().encode(
+        new ApplicationRowKey(CLUSTER, USER, FLOW_NAME, FLOW_RUN_ID,
+            APPLICATION_ID));
+    ApplicationRowKey rowKey =
+        ApplicationRowKeyConverter.getInstance().decode(byteRowKey);
+    assertEquals(CLUSTER, rowKey.getClusterId());
+    assertEquals(USER, rowKey.getUserId());
+    assertEquals(FLOW_NAME, rowKey.getFlowName());
+    assertEquals(FLOW_RUN_ID, rowKey.getFlowRunId());
+    assertEquals(APPLICATION_ID, rowKey.getAppId());
+
+    byte[] byteRowKeyPrefix = ApplicationRowKeyConverter.getInstance().encode(
+        new ApplicationRowKey(CLUSTER, USER, FLOW_NAME, FLOW_RUN_ID, null));
+    byte[][] splits =
+        Separator.QUALIFIERS.split(byteRowKeyPrefix, new int[] {
+            Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE,
+            Separator.VARIABLE_SIZE, Bytes.SIZEOF_LONG,
+            Separator.VARIABLE_SIZE });
+    assertEquals(5, splits.length);
+    assertEquals(0, splits[4].length);
+    assertEquals(FLOW_NAME,
+        Separator.QUALIFIERS.decode(Bytes.toString(splits[2])));
+    assertEquals(FLOW_RUN_ID, (Long)TimelineStorageUtils.invertLong(
+        Bytes.toLong(splits[3])));
+    verifyRowPrefixBytes(byteRowKeyPrefix);
+
+    byteRowKeyPrefix = ApplicationRowKeyConverter.getInstance().encode(
+        new ApplicationRowKey(CLUSTER, USER, FLOW_NAME, null, null));
+    splits = Separator.QUALIFIERS.split(byteRowKeyPrefix, new int[] {
+        Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE,
+        Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE });
+    assertEquals(4, splits.length);
+    assertEquals(0, splits[3].length);
+    assertEquals(FLOW_NAME,
+        Separator.QUALIFIERS.decode(Bytes.toString(splits[2])));
+    verifyRowPrefixBytes(byteRowKeyPrefix);
+  }
+
+  @Test
+  public void testEntityRowKeyConverter() {
+    String entityId = "!ent!ity!!id!";
+    String entityType = "entity!Type";
+    byte[] byteRowKey = EntityRowKeyConverter.getInstance().encode(
+        new EntityRowKey(CLUSTER, USER, FLOW_NAME, FLOW_RUN_ID, APPLICATION_ID,
+            entityType, entityId));
+    EntityRowKey rowKey =
+        EntityRowKeyConverter.getInstance().decode(byteRowKey);
+    assertEquals(CLUSTER, rowKey.getClusterId());
+    assertEquals(USER, rowKey.getUserId());
+    assertEquals(FLOW_NAME, rowKey.getFlowName());
+    assertEquals(FLOW_RUN_ID, rowKey.getFlowRunId());
+    assertEquals(APPLICATION_ID, rowKey.getAppId());
+    assertEquals(entityType, rowKey.getEntityType());
+    assertEquals(entityId, rowKey.getEntityId());
+
+    byte[] byteRowKeyPrefix = EntityRowKeyConverter.getInstance().encode(
+        new EntityRowKey(CLUSTER, USER, FLOW_NAME, FLOW_RUN_ID, APPLICATION_ID,
+            entityType, null));
+    byte[][] splits =
+        Separator.QUALIFIERS.split(byteRowKeyPrefix, new int[] {
+            Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE,
+            Separator.VARIABLE_SIZE, Bytes.SIZEOF_LONG,
+            AppIdKeyConverter.getKeySize(), Separator.VARIABLE_SIZE,
+            Separator.VARIABLE_SIZE });
+    assertEquals(7, splits.length);
+    assertEquals(0, splits[6].length);
+    assertEquals(APPLICATION_ID,
+        AppIdKeyConverter.getInstance().decode(splits[4]));
+    assertEquals(entityType, Separator.QUALIFIERS.decode(
+        Bytes.toString(splits[5])));
+    verifyRowPrefixBytes(byteRowKeyPrefix);
+
+    byteRowKeyPrefix = EntityRowKeyConverter.getInstance().encode(
+        new EntityRowKey(CLUSTER, USER, FLOW_NAME, FLOW_RUN_ID, APPLICATION_ID,
+        null, null));
+    splits = Separator.QUALIFIERS.split(byteRowKeyPrefix, new int[] {
+        Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE,
+        Separator.VARIABLE_SIZE, Bytes.SIZEOF_LONG,
+        AppIdKeyConverter.getKeySize(), Separator.VARIABLE_SIZE });
+    assertEquals(6, splits.length);
+    assertEquals(0, splits[5].length);
+    assertEquals(APPLICATION_ID,
+        AppIdKeyConverter.getInstance().decode(splits[4]));
+    verifyRowPrefixBytes(byteRowKeyPrefix);
+  }
+
+  @Test
+  public void testAppToFlowRowKeyConverter() {
+    byte[] byteRowKey = AppToFlowRowKeyConverter.getInstance().encode(
+        new AppToFlowRowKey(CLUSTER, APPLICATION_ID));
+    AppToFlowRowKey rowKey =
+        AppToFlowRowKeyConverter.getInstance().decode(byteRowKey);
+    assertEquals(CLUSTER, rowKey.getClusterId());
+    assertEquals(APPLICATION_ID, rowKey.getAppId());
+  }
+
+  @Test
+  public void testAppIdKeyConverter() {
+    long currentTs = System.currentTimeMillis();
+    ApplicationId appId1 = ApplicationId.newInstance(currentTs, 1);
+    ApplicationId appId2 = ApplicationId.newInstance(currentTs, 2);
+    ApplicationId appId3 = ApplicationId.newInstance(currentTs + 300, 1);
+    String appIdStr1 = appId1.toString();
+    String appIdStr2 = appId2.toString();
+    String appIdStr3 = appId3.toString();
+    byte[] appIdBytes1 = AppIdKeyConverter.getInstance().encode(appIdStr1);
+    byte[] appIdBytes2 = AppIdKeyConverter.getInstance().encode(appIdStr2);
+    byte[] appIdBytes3 = AppIdKeyConverter.getInstance().encode(appIdStr3);
+    // App ids' should be encoded in a manner wherein descending order
+    // is maintained.
+    assertTrue("Ordering of app ids' is incorrect",
+        Bytes.compareTo(appIdBytes1, appIdBytes2) > 0 &&
+        Bytes.compareTo(appIdBytes1, appIdBytes3) > 0 &&
+        Bytes.compareTo(appIdBytes2, appIdBytes3) > 0);
+    String decodedAppId1 = AppIdKeyConverter.getInstance().decode(appIdBytes1);
+    String decodedAppId2 = AppIdKeyConverter.getInstance().decode(appIdBytes2);
+    String decodedAppId3 = AppIdKeyConverter.getInstance().decode(appIdBytes3);
+    assertTrue("Decoded app id is not same as the app id encoded",
+        appIdStr1.equals(decodedAppId1));
+    assertTrue("Decoded app id is not same as the app id encoded",
+        appIdStr2.equals(decodedAppId2));
+    assertTrue("Decoded app id is not same as the app id encoded",
+        appIdStr3.equals(decodedAppId3));
+  }
+
+  @Test
+  public void testEventColumnNameConverter() {
+    String eventId = "=foo_=eve=nt=";
+    byte[] valSepBytes = Bytes.toBytes(Separator.VALUES.getValue());
+    byte[] maxByteArr =
+        Bytes.createMaxByteArray(Bytes.SIZEOF_LONG - valSepBytes.length);
+    byte[] ts = Bytes.add(valSepBytes, maxByteArr);
+    Long eventTs = Bytes.toLong(ts);
+    byte[] byteEventColName = EventColumnNameConverter.getInstance().encode(
+        new EventColumnName(eventId, eventTs, null));
+    EventColumnName eventColName =
+        EventColumnNameConverter.getInstance().decode(byteEventColName);
+    assertEquals(eventId, eventColName.getId());
+    assertEquals(eventTs, eventColName.getTimestamp());
+    assertNull(eventColName.getInfoKey());
+
+    String infoKey = "f=oo_event_in=fo=_key";
+    byteEventColName = EventColumnNameConverter.getInstance().encode(
+        new EventColumnName(eventId, eventTs, infoKey));
+    eventColName =
+        EventColumnNameConverter.getInstance().decode(byteEventColName);
+    assertEquals(eventId, eventColName.getId());
+    assertEquals(eventTs, eventColName.getTimestamp());
+    assertEquals(infoKey, eventColName.getInfoKey());
+  }
+}

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/test/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/TestSeparator.java

@@ -19,11 +19,13 @@ package org.apache.hadoop.yarn.server.timelineservice.storage.common;
 import static org.junit.Assert.assertEquals;
 import static org.junit.Assert.assertNull;
 import static org.junit.Assert.assertTrue;
+import static org.junit.Assert.fail;
 
 import java.util.ArrayList;
 import java.util.Arrays;
 import java.util.List;
 
+import org.apache.hadoop.hbase.util.Bytes;
 import org.junit.Test;
 
 import com.google.common.collect.Iterables;
@@ -32,7 +34,7 @@ public class TestSeparator {
 
   private static String villain = "Dr. Heinz Doofenshmirtz";
   private static String special =
-      ".   *   |   ?   +   (   )   [   ]   {   }   ^   $  \\ \"";
+      ".   *   |   ?   +   \t   (   )   [   ]   {   }   ^   $  \\ \"";
 
   /**
    *
@@ -47,6 +49,7 @@ public class TestSeparator {
       testEncodeDecode(separator, "?");
       testEncodeDecode(separator, "&");
       testEncodeDecode(separator, "+");
+      testEncodeDecode(separator, "\t");
       testEncodeDecode(separator, "Dr.");
       testEncodeDecode(separator, "Heinz");
       testEncodeDecode(separator, "Doofenshmirtz");
@@ -79,6 +82,83 @@ public class TestSeparator {
 
   }
 
+  @Test
+  public void testSplits() {
+    byte[] maxLongBytes = Bytes.toBytes(Long.MAX_VALUE);
+    byte[] maxIntBytes = Bytes.toBytes(Integer.MAX_VALUE);
+    for (Separator separator : Separator.values()) {
+      String str1 = "cl" + separator.getValue() + "us";
+      String str2 = separator.getValue() + "rst";
+      byte[] sepByteArr = Bytes.toBytes(separator.getValue());
+      byte[] longVal1Arr = Bytes.add(sepByteArr, Bytes.copy(maxLongBytes,
+          sepByteArr.length, Bytes.SIZEOF_LONG - sepByteArr.length));
+      byte[] intVal1Arr = Bytes.add(sepByteArr, Bytes.copy(maxIntBytes,
+          sepByteArr.length, Bytes.SIZEOF_INT - sepByteArr.length));
+      byte[] arr = separator.join(
+          Bytes.toBytes(separator.encode(str1)),longVal1Arr,
+          Bytes.toBytes(separator.encode(str2)), intVal1Arr);
+      int[] sizes = { Separator.VARIABLE_SIZE, Bytes.SIZEOF_LONG,
+          Separator.VARIABLE_SIZE, Bytes.SIZEOF_INT };
+      byte[][] splits = separator.split(arr, sizes);
+      assertEquals(4, splits.length);
+      assertEquals(str1, separator.decode(Bytes.toString(splits[0])));
+      assertEquals(Bytes.toLong(longVal1Arr), Bytes.toLong(splits[1]));
+      assertEquals(str2, separator.decode(Bytes.toString(splits[2])));
+      assertEquals(Bytes.toInt(intVal1Arr), Bytes.toInt(splits[3]));
+
+      longVal1Arr = Bytes.add(Bytes.copy(maxLongBytes, 0, Bytes.SIZEOF_LONG -
+          sepByteArr.length), sepByteArr);
+      intVal1Arr = Bytes.add(Bytes.copy(maxIntBytes, 0, Bytes.SIZEOF_INT -
+          sepByteArr.length), sepByteArr);
+      arr = separator.join(Bytes.toBytes(separator.encode(str1)),longVal1Arr,
+          Bytes.toBytes(separator.encode(str2)), intVal1Arr);
+      splits = separator.split(arr, sizes);
+      assertEquals(4, splits.length);
+      assertEquals(str1, separator.decode(Bytes.toString(splits[0])));
+      assertEquals(Bytes.toLong(longVal1Arr), Bytes.toLong(splits[1]));
+      assertEquals(str2, separator.decode(Bytes.toString(splits[2])));
+      assertEquals(Bytes.toInt(intVal1Arr), Bytes.toInt(splits[3]));
+
+      longVal1Arr = Bytes.add(sepByteArr, Bytes.copy(maxLongBytes,
+          sepByteArr.length, 4 - sepByteArr.length), sepByteArr);
+      longVal1Arr = Bytes.add(longVal1Arr, Bytes.copy(maxLongBytes, 4, 3 -
+              sepByteArr.length), sepByteArr);
+      arr = separator.join(Bytes.toBytes(separator.encode(str1)),longVal1Arr,
+          Bytes.toBytes(separator.encode(str2)), intVal1Arr);
+      splits = separator.split(arr, sizes);
+      assertEquals(4, splits.length);
+      assertEquals(str1, separator.decode(Bytes.toString(splits[0])));
+      assertEquals(Bytes.toLong(longVal1Arr), Bytes.toLong(splits[1]));
+      assertEquals(str2, separator.decode(Bytes.toString(splits[2])));
+      assertEquals(Bytes.toInt(intVal1Arr), Bytes.toInt(splits[3]));
+
+      arr = separator.join(Bytes.toBytes(separator.encode(str1)),
+          Bytes.toBytes(separator.encode(str2)), intVal1Arr, longVal1Arr);
+      int[] sizes1 = { Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE,
+          Bytes.SIZEOF_INT, Bytes.SIZEOF_LONG };
+      splits = separator.split(arr, sizes1);
+      assertEquals(4, splits.length);
+      assertEquals(str1, separator.decode(Bytes.toString(splits[0])));
+      assertEquals(str2, separator.decode(Bytes.toString(splits[1])));
+      assertEquals(Bytes.toInt(intVal1Arr), Bytes.toInt(splits[2]));
+      assertEquals(Bytes.toLong(longVal1Arr), Bytes.toLong(splits[3]));
+
+      try {
+        int[] sizes2 = { Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE,
+            Bytes.SIZEOF_INT, 7 };
+        splits = separator.split(arr, sizes2);
+        fail("Exception should have been thrown.");
+      } catch (IllegalArgumentException e) {}
+
+      try {
+        int[] sizes2 = { Separator.VARIABLE_SIZE, Separator.VARIABLE_SIZE, 2,
+            Bytes.SIZEOF_LONG };
+        splits = separator.split(arr, sizes2);
+        fail("Exception should have been thrown.");
+      } catch (IllegalArgumentException e) {}
+    }
+  }
+
   /**
    * Simple test to encode and decode using the same separators and confirm that
    * we end up with the same as what we started with.

hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-timelineservice/src/test/java/org/apache/hadoop/yarn/server/timelineservice/storage/common/TestTimelineStorageUtils.java

@@ -1,56 +0,0 @@
-/**
- * Licensed to the Apache Software Foundation (ASF) under one or more
- * contributor license agreements. See the NOTICE file distributed with this
- * work for additional information regarding copyright ownership. The ASF
- * licenses this file to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
- * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
- * License for the specific language governing permissions and limitations under
- * the License.
- */
-
-package org.apache.hadoop.yarn.server.timelineservice.storage.common;
-
-import static org.junit.Assert.assertTrue;
-
-import org.apache.hadoop.hbase.util.Bytes;
-import org.apache.hadoop.yarn.api.records.ApplicationId;
-import org.junit.Test;
-
-public class TestTimelineStorageUtils {
-
-  @Test
-  public void testEncodeDecodeAppId() {
-    long currentTs = System.currentTimeMillis();
-    ApplicationId appId1 = ApplicationId.newInstance(currentTs, 1);
-    ApplicationId appId2 = ApplicationId.newInstance(currentTs, 2);
-    ApplicationId appId3 = ApplicationId.newInstance(currentTs + 300, 1);
-    String appIdStr1 = appId1.toString();
-    String appIdStr2 = appId2.toString();
-    String appIdStr3 = appId3.toString();
-    byte[] appIdBytes1 = TimelineStorageUtils.encodeAppId(appIdStr1);
-    byte[] appIdBytes2 = TimelineStorageUtils.encodeAppId(appIdStr2);
-    byte[] appIdBytes3 = TimelineStorageUtils.encodeAppId(appIdStr3);
-    // App ids' should be encoded in a manner wherein descending order
-    // is maintained.
-    assertTrue("Ordering of app ids' is incorrect",
-        Bytes.compareTo(appIdBytes1, appIdBytes2) > 0 &&
-        Bytes.compareTo(appIdBytes1, appIdBytes3) > 0 &&
-        Bytes.compareTo(appIdBytes2, appIdBytes3) > 0);
-    String decodedAppId1 = TimelineStorageUtils.decodeAppId(appIdBytes1);
-    String decodedAppId2 = TimelineStorageUtils.decodeAppId(appIdBytes2);
-    String decodedAppId3 = TimelineStorageUtils.decodeAppId(appIdBytes3);
-    assertTrue("Decoded app id is not same as the app id encoded",
-        appIdStr1.equals(decodedAppId1));
-    assertTrue("Decoded app id is not same as the app id encoded",
-        appIdStr2.equals(decodedAppId2));
-    assertTrue("Decoded app id is not same as the app id encoded",
-        appIdStr3.equals(decodedAppId3));
-  }
-}