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@@ -165,18 +165,64 @@ New configuration parameters that are introduced with v.2 are marked bold.
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### <a name="Enabling_Timeline_Service_v2"></a>Enabling Timeline Service v.2
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#### Preparing Apache HBase cluster for storage
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+There are a few steps to be done for preparing the storage for Timeline Service v.2:
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+
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+Step 1) [Set up the HBase cluster](#Set_up_the_HBase_cluster)
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+
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+Step 2) [Enable the coprocessor](#Enable_the_coprocessor)
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+
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+Step 3) [Create the schema for Timeline Service v.2](#Create_schema)
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+
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+Each step is explained in more detail below.
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+
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+##### <a name="Set_up_the_HBase_cluster"> </a>Step 1) Set up the HBase cluster
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The first part is to set up or pick an Apache HBase cluster to use as the storage cluster. The
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-version of Apache HBase that is supported with Timeline Service v.2 is 1.1.x. The 1.0.x versions
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-do not work with Timeline Service v.2. The 1.2.x versions have not been tested.
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+version of Apache HBase that is supported with Timeline Service v.2 is 1.2.4. The 1.0.x versions
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+do not work with Timeline Service v.2. Later versions of HBase have not been tested with
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+Timeline Service.
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+
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+HBase has different deployment modes. Refer to the HBase book for understanding them and pick a
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+mode that is suitable for your setup.
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+(http://hbase.apache.org/book.html#standalone_dist)
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+
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+##### Simple deployment for HBase
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+If you are intent on a simple deploy profile for the Apache HBase cluster
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+where the data loading is light but the data needs to persist across node
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+comings and goings, you could consider the "Standalone HBase over HDFS" deploy mode.
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+
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+This is a useful variation on the standalone HBase setup and has all HBase daemons running inside
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+one JVM but rather than persisting to the local filesystem, it persists to an HDFS instance.
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+Writing to HDFS where data is replicated ensures that data is persisted across node
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+comings and goings. To configure this standalone variant, edit your `hbase-site.xml` setting
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+the `hbase.rootdir` to point at a directory in your HDFS instance but then set
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+`hbase.cluster.distributed` to false. For example:
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+
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+```
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+<configuration>
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+ <property>
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+ <name>hbase.rootdir</name>
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+ <value>hdfs://namenode.example.org:8020/hbase</value>
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+ </property>
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+ <property>
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+ <name>hbase.cluster.distributed</name>
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+ <value>false</value>
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+ </property>
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+</configuration>
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+```
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+
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+For more details on this mode, refer to
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+http://hbase.apache.org/book.html#standalone.over.hdfs .
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+
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+Once you have an Apache HBase cluster ready to use, perform the following steps.
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-Once you have an Apache HBase cluster ready to use for this purpose, perform the following steps.
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+##### <a name="Enable_the_coprocessor"> </a>Step 2) Enable the coprocessor
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-First, add the timeline service jar to the HBase classpath in all HBase machines in the cluster. It
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+Step 2.1) Add the timeline service jar to the HBase classpath in all HBase machines in the cluster. It
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is needed for the coprocessor as well as the schema creator. For example,
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cp hadoop-yarn-server-timelineservice-3.0.0-alpha1-SNAPSHOT.jar /usr/hbase/lib/
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-Then, enable the coprocessor that handles the aggregation. To enable it, add the following entry in
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+Step 2.2) Enable the coprocessor that handles the aggregation. To enable it, add the following entry in
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region servers' `hbase-site.xml` file (generally located in the `conf` directory) as follows:
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```
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@@ -186,10 +232,11 @@ region servers' `hbase-site.xml` file (generally located in the `conf` directory
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</property>
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```
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-Restart the region servers and the master to pick up the timeline service jar as well as the config
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-change. In this version, the coprocessor is loaded statically (i.e. system coprocessor) as opposed
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-to a dynamically (table coprocessor).
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+Step 2.3) Restart the region servers and the master to pick up the timeline service jar as well
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+as the config change. In this version, the coprocessor is loaded statically
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+(i.e. system coprocessor) as opposed to a dynamically (table coprocessor).
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+##### <a name="Create_schema"> </a>Step 3) Create the timeline service schema
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Finally, run the schema creator tool to create the necessary tables:
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bin/hbase org.apache.hadoop.yarn.server.timelineservice.storage.TimelineSchemaCreator
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Sangjin Lee