Adding back hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/resources which was missed during merge of MAPREDUCE-279.

git-svn-id: https://svn.apache.org/repos/asf/hadoop/common/branches/branch-0.23@1166973 13f79535-47bb-0310-9956-ffa450edef68

hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/resources/META-INF/services/org.apache.hadoop.mapreduce.protocol.ClientProtocolProvider

@@ -0,0 +1,14 @@
+#
+#   Licensed 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.
+#
+org.apache.hadoop.mapred.JobTrackerClientProtocolProvider

hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/resources/mapred-default.xml

@@ -0,0 +1,1175 @@
+<?xml version="1.0"?>
+<!--
+   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.
+-->
+<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
+
+<!-- Do not modify this file directly.  Instead, copy entries that you -->
+<!-- wish to modify from this file into mapred-site.xml and change them -->
+<!-- there.  If mapred-site.xml does not already exist, create it.      -->
+
+<configuration>
+
+<property>
+  <name>mapreduce.jobtracker.jobhistory.location</name>
+  <value></value>
+  <description> If job tracker is static the history files are stored 
+  in this single well known place. If No value is set here, by default,
+  it is in the local file system at ${hadoop.log.dir}/history.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.jobhistory.task.numberprogresssplits</name>
+  <value>12</value>
+  <description> Every task attempt progresses from 0.0 to 1.0 [unless
+  it fails or is killed].  We record, for each task attempt, certain 
+  statistics over each twelfth of the progress range.  You can change
+  the number of intervals we divide the entire range of progress into
+  by setting this property.  Higher values give more precision to the
+  recorded data, but costs more memory in the job tracker at runtime.
+  Each increment in this attribute costs 16 bytes per running task.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.userhistorylocation</name>
+  <value></value>
+  <description> User can specify a location to store the history files of 
+  a particular job. If nothing is specified, the logs are stored in 
+  output directory. The files are stored in "_logs/history/" in the directory.
+  User can stop logging by giving the value "none". 
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.jobhistory.completed.location</name>
+  <value></value>
+  <description> The completed job history files are stored at this single well 
+  known location. If nothing is specified, the files are stored at 
+  ${mapreduce.jobtracker.jobhistory.location}/done.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.committer.setup.cleanup.needed</name>
+  <value>true</value>
+  <description> true, if job needs job-setup and job-cleanup.
+                false, otherwise  
+  </description>
+</property>
+<!-- i/o properties -->
+
+<property>
+  <name>mapreduce.task.io.sort.factor</name>
+  <value>10</value>
+  <description>The number of streams to merge at once while sorting
+  files.  This determines the number of open file handles.</description>
+</property>
+
+<property>
+  <name>mapreduce.task.io.sort.mb</name>
+  <value>100</value>
+  <description>The total amount of buffer memory to use while sorting 
+  files, in megabytes.  By default, gives each merge stream 1MB, which
+  should minimize seeks.</description>
+</property>
+
+<property>
+  <name>mapreduce.map.sort.spill.percent</name>
+  <value>0.80</value>
+  <description>The soft limit in the serialization buffer. Once reached, a
+  thread will begin to spill the contents to disk in the background. Note that
+  collection will not block if this threshold is exceeded while a spill is
+  already in progress, so spills may be larger than this threshold when it is
+  set to less than .5</description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.address</name>
+  <value>local</value>
+  <description>The host and port that the MapReduce job tracker runs
+  at.  If "local", then jobs are run in-process as a single map
+  and reduce task.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.local.clientfactory.class.name</name>
+  <value>org.apache.hadoop.mapred.LocalClientFactory</value>
+  <description>This the client factory that is responsible for 
+  creating local job runner client</description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.http.address</name>
+  <value>0.0.0.0:50030</value>
+  <description>
+    The job tracker http server address and port the server will listen on.
+    If the port is 0 then the server will start on a free port.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.handler.count</name>
+  <value>10</value>
+  <description>
+    The number of server threads for the JobTracker. This should be roughly
+    4% of the number of tasktracker nodes.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.report.address</name>
+  <value>127.0.0.1:0</value>
+  <description>The interface and port that task tracker server listens on. 
+  Since it is only connected to by the tasks, it uses the local interface.
+  EXPERT ONLY. Should only be changed if your host does not have the loopback 
+  interface.</description>
+</property>
+
+<property>
+  <name>mapreduce.cluster.local.dir</name>
+  <value>${hadoop.tmp.dir}/mapred/local</value>
+  <description>The local directory where MapReduce stores intermediate
+  data files.  May be a comma-separated list of
+  directories on different devices in order to spread disk i/o.
+  Directories that do not exist are ignored.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.system.dir</name>
+  <value>${hadoop.tmp.dir}/mapred/system</value>
+  <description>The directory where MapReduce stores control files.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.staging.root.dir</name>
+  <value>${hadoop.tmp.dir}/mapred/staging</value>
+  <description>The root of the staging area for users' job files
+  In practice, this should be the directory where users' home 
+  directories are located (usually /user)
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.cluster.temp.dir</name>
+  <value>${hadoop.tmp.dir}/mapred/temp</value>
+  <description>A shared directory for temporary files.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.local.dir.minspacestart</name>
+  <value>0</value>
+  <description>If the space in mapreduce.cluster.local.dir drops under this, 
+  do not ask for more tasks.
+  Value in bytes.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.local.dir.minspacekill</name>
+  <value>0</value>
+  <description>If the space in mapreduce.cluster.local.dir drops under this, 
+    do not ask more tasks until all the current ones have finished and 
+    cleaned up. Also, to save the rest of the tasks we have running, 
+    kill one of them, to clean up some space. Start with the reduce tasks,
+    then go with the ones that have finished the least.
+    Value in bytes.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.expire.trackers.interval</name>
+  <value>600000</value>
+  <description>Expert: The time-interval, in miliseconds, after which
+  a tasktracker is declared 'lost' if it doesn't send heartbeats.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.instrumentation</name>
+  <value>org.apache.hadoop.mapred.TaskTrackerMetricsInst</value>
+  <description>Expert: The instrumentation class to associate with each TaskTracker.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.resourcecalculatorplugin</name>
+  <value></value>
+  <description>
+   Name of the class whose instance will be used to query resource information
+   on the tasktracker.
+   
+   The class must be an instance of 
+   org.apache.hadoop.util.ResourceCalculatorPlugin. If the value is null, the
+   tasktracker attempts to use a class appropriate to the platform. 
+   Currently, the only platform supported is Linux.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.taskmemorymanager.monitoringinterval</name>
+  <value>5000</value>
+  <description>The interval, in milliseconds, for which the tasktracker waits
+   between two cycles of monitoring its tasks' memory usage. Used only if
+   tasks' memory management is enabled via mapred.tasktracker.tasks.maxmemory.
+   </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.tasks.sleeptimebeforesigkill</name>
+  <value>5000</value>
+  <description>The time, in milliseconds, the tasktracker waits for sending a
+  SIGKILL to a task, after it has been sent a SIGTERM. This is currently
+  not used on WINDOWS where tasks are just sent a SIGTERM.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.maps</name>
+  <value>2</value>
+  <description>The default number of map tasks per job.
+  Ignored when mapreduce.jobtracker.address is "local".  
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.reduces</name>
+  <value>1</value>
+  <description>The default number of reduce tasks per job. Typically set to 99%
+  of the cluster's reduce capacity, so that if a node fails the reduces can 
+  still be executed in a single wave.
+  Ignored when mapreduce.jobtracker.address is "local".
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.restart.recover</name>
+  <value>false</value>
+  <description>"true" to enable (job) recovery upon restart,
+               "false" to start afresh
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.jobhistory.block.size</name>
+  <value>3145728</value>
+  <description>The block size of the job history file. Since the job recovery
+               uses job history, its important to dump job history to disk as 
+               soon as possible. Note that this is an expert level parameter.
+               The default value is set to 3 MB.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.taskscheduler</name>
+  <value>org.apache.hadoop.mapred.JobQueueTaskScheduler</value>
+  <description>The class responsible for scheduling the tasks.</description>
+</property>
+
+
+<property>
+  <name>mapreduce.job.split.metainfo.maxsize</name>
+  <value>10000000</value>
+  <description>The maximum permissible size of the split metainfo file. 
+  The JobTracker won't attempt to read split metainfo files bigger than
+  the configured value.
+  No limits if set to -1.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.taskscheduler.maxrunningtasks.perjob</name>
+  <value></value>
+  <description>The maximum number of running tasks for a job before
+  it gets preempted. No limits if undefined.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.map.maxattempts</name>
+  <value>4</value>
+  <description>Expert: The maximum number of attempts per map task.
+  In other words, framework will try to execute a map task these many number
+  of times before giving up on it.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.maxattempts</name>
+  <value>4</value>
+  <description>Expert: The maximum number of attempts per reduce task.
+  In other words, framework will try to execute a reduce task these many number
+  of times before giving up on it.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.shuffle.parallelcopies</name>
+  <value>5</value>
+  <description>The default number of parallel transfers run by reduce
+  during the copy(shuffle) phase.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.shuffle.connect.timeout</name>
+  <value>180000</value>
+  <description>Expert: The maximum amount of time (in milli seconds) reduce
+  task spends in trying to connect to a tasktracker for getting map output.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.shuffle.read.timeout</name>
+  <value>180000</value>
+  <description>Expert: The maximum amount of time (in milli seconds) reduce
+  task waits for map output data to be available for reading after obtaining
+  connection.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.task.timeout</name>
+  <value>600000</value>
+  <description>The number of milliseconds before a task will be
+  terminated if it neither reads an input, writes an output, nor
+  updates its status string.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.map.tasks.maximum</name>
+  <value>2</value>
+  <description>The maximum number of map tasks that will be run
+  simultaneously by a task tracker.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.reduce.tasks.maximum</name>
+  <value>2</value>
+  <description>The maximum number of reduce tasks that will be run
+  simultaneously by a task tracker.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.retiredjobs.cache.size</name>
+  <value>1000</value>
+  <description>The number of retired job status to keep in the cache.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.outofband.heartbeat</name>
+  <value>false</value>
+  <description>Expert: Set this to true to let the tasktracker send an 
+  out-of-band heartbeat on task-completion for better latency.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.jobhistory.lru.cache.size</name>
+  <value>5</value>
+  <description>The number of job history files loaded in memory. The jobs are 
+  loaded when they are first accessed. The cache is cleared based on LRU.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.instrumentation</name>
+  <value>org.apache.hadoop.mapred.JobTrackerMetricsInst</value>
+  <description>Expert: The instrumentation class to associate with each JobTracker.
+  </description>
+</property>
+
+<property>
+  <name>mapred.child.java.opts</name>
+  <value>-Xmx200m</value>
+  <description>Java opts for the task tracker child processes.  
+  The following symbol, if present, will be interpolated: @taskid@ is replaced 
+  by current TaskID. Any other occurrences of '@' will go unchanged.
+  For example, to enable verbose gc logging to a file named for the taskid in
+  /tmp and to set the heap maximum to be a gigabyte, pass a 'value' of:
+        -Xmx1024m -verbose:gc -Xloggc:/tmp/@taskid@.gc
+  
+  The configuration variable mapred.child.ulimit can be used to control the
+  maximum virtual memory of the child processes. 
+  </description>
+</property>
+
+<property>
+  <name>mapred.child.env</name>
+  <value></value>
+  <description>User added environment variables for the task tracker child 
+  processes. Example :
+  1) A=foo  This will set the env variable A to foo
+  2) B=$B:c This is inherit tasktracker's B env variable.  
+  </description>
+</property>
+
+<property>
+  <name>mapred.child.ulimit</name>
+  <value></value>
+  <description>The maximum virtual memory, in KB, of a process launched by the 
+  Map-Reduce framework. This can be used to control both the Mapper/Reducer 
+  tasks and applications using Hadoop Pipes, Hadoop Streaming etc. 
+  By default it is left unspecified to let cluster admins control it via 
+  limits.conf and other such relevant mechanisms.
+  
+  Note: mapred.child.ulimit must be greater than or equal to the -Xmx passed to
+  JavaVM, else the VM might not start. 
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.task.tmp.dir</name>
+  <value>./tmp</value>
+  <description> To set the value of tmp directory for map and reduce tasks.
+  If the value is an absolute path, it is directly assigned. Otherwise, it is
+  prepended with task's working directory. The java tasks are executed with
+  option -Djava.io.tmpdir='the absolute path of the tmp dir'. Pipes and
+  streaming are set with environment variable,
+   TMPDIR='the absolute path of the tmp dir'
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.map.log.level</name>
+  <value>INFO</value>
+  <description>The logging level for the map task. The allowed levels are:
+  OFF, FATAL, ERROR, WARN, INFO, DEBUG, TRACE and ALL.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.log.level</name>
+  <value>INFO</value>
+  <description>The logging level for the reduce task. The allowed levels are:
+  OFF, FATAL, ERROR, WARN, INFO, DEBUG, TRACE and ALL.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.merge.inmem.threshold</name>
+  <value>1000</value>
+  <description>The threshold, in terms of the number of files 
+  for the in-memory merge process. When we accumulate threshold number of files
+  we initiate the in-memory merge and spill to disk. A value of 0 or less than
+  0 indicates we want to DON'T have any threshold and instead depend only on
+  the ramfs's memory consumption to trigger the merge.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.shuffle.merge.percent</name>
+  <value>0.66</value>
+  <description>The usage threshold at which an in-memory merge will be
+  initiated, expressed as a percentage of the total memory allocated to
+  storing in-memory map outputs, as defined by
+  mapreduce.reduce.shuffle.input.buffer.percent.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.shuffle.input.buffer.percent</name>
+  <value>0.70</value>
+  <description>The percentage of memory to be allocated from the maximum heap
+  size to storing map outputs during the shuffle.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.input.buffer.percent</name>
+  <value>0.0</value>
+  <description>The percentage of memory- relative to the maximum heap size- to
+  retain map outputs during the reduce. When the shuffle is concluded, any
+  remaining map outputs in memory must consume less than this threshold before
+  the reduce can begin.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.markreset.buffer.percent</name>
+  <value>0.0</value>
+  <description>The percentage of memory -relative to the maximum heap size- to
+  be used for caching values when using the mark-reset functionality.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.map.speculative</name>
+  <value>true</value>
+  <description>If true, then multiple instances of some map tasks 
+               may be executed in parallel.</description>
+</property>
+
+<property>
+  <name>mapreduce.reduce.speculative</name>
+  <value>true</value>
+  <description>If true, then multiple instances of some reduce tasks 
+               may be executed in parallel.</description>
+</property>
+<property>
+  <name>mapreduce.job.speculative.speculativecap</name>
+  <value>0.1</value>
+  <description>The max percent (0-1) of running tasks that
+  can be speculatively re-executed at any time.</description>
+</property>
+ 
+<property>
+  <name>mapreduce.job.speculative.slowtaskthreshold</name>
+  <value>1.0</value>The number of standard deviations by which a task's 
+  ave progress-rates must be lower than the average of all running tasks'
+  for the task to be considered too slow.
+  <description>
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.speculative.slownodethreshold</name>
+  <value>1.0</value>
+  <description>The number of standard deviations by which a Task 
+  Tracker's ave map and reduce progress-rates (finishTime-dispatchTime)
+  must be lower than the average of all successful map/reduce task's for
+  the TT to be considered too slow to give a speculative task to.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.jvm.numtasks</name>
+  <value>1</value>
+  <description>How many tasks to run per jvm. If set to -1, there is
+  no limit. 
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.ubertask.enable</name>
+  <value>false</value>
+  <description>Whether to enable the small-jobs "ubertask" optimization,
+  which runs "sufficiently small" jobs sequentially within a single JVM.
+  "Small" is defined by the following maxmaps, maxreduces, and maxbytes
+  settings.  Users may override this value.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.ubertask.maxmaps</name>
+  <value>9</value>
+  <description>Threshold for number of maps, beyond which job is considered
+  too big for the ubertasking optimization.  Users may override this value,
+  but only downward.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.ubertask.maxreduces</name>
+  <value>1</value>
+  <description>Threshold for number of reduces, beyond which job is considered
+  too big for the ubertasking optimization.  CURRENTLY THE CODE CANNOT SUPPORT
+  MORE THAN ONE REDUCE and will ignore larger values.  (Zero is a valid max,
+  however.)  Users may override this value, but only downward.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.ubertask.maxbytes</name>
+  <value></value>
+  <description>Threshold for number of input bytes, beyond which job is
+  considered too big for the ubertasking optimization.  If no value is
+  specified, dfs.block.size is used as a default.  Be sure to specify a
+  default value in mapred-site.xml if the underlying filesystem is not HDFS.
+  Users may override this value, but only downward.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.input.fileinputformat.split.minsize</name>
+  <value>0</value>
+  <description>The minimum size chunk that map input should be split
+  into.  Note that some file formats may have minimum split sizes that
+  take priority over this setting.</description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.maxtasks.perjob</name>
+  <value>-1</value>
+  <description>The maximum number of tasks for a single job.
+  A value of -1 indicates that there is no maximum.  </description>
+</property>
+
+<property>
+  <name>mapreduce.client.submit.file.replication</name>
+  <value>10</value>
+  <description>The replication level for submitted job files.  This
+  should be around the square root of the number of nodes.
+  </description>
+</property>
+
+
+<property>
+  <name>mapreduce.tasktracker.dns.interface</name>
+  <value>default</value>
+  <description>The name of the Network Interface from which a task
+  tracker should report its IP address.
+  </description>
+ </property>
+ 
+<property>
+  <name>mapreduce.tasktracker.dns.nameserver</name>
+  <value>default</value>
+  <description>The host name or IP address of the name server (DNS)
+  which a TaskTracker should use to determine the host name used by
+  the JobTracker for communication and display purposes.
+  </description>
+ </property>
+ 
+<property>
+  <name>mapreduce.tasktracker.http.threads</name>
+  <value>40</value>
+  <description>The number of worker threads that for the http server. This is
+               used for map output fetching
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.http.address</name>
+  <value>0.0.0.0:50060</value>
+  <description>
+    The task tracker http server address and port.
+    If the port is 0 then the server will start on a free port.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.task.files.preserve.failedtasks</name>
+  <value>false</value>
+  <description>Should the files for failed tasks be kept. This should only be 
+               used on jobs that are failing, because the storage is never
+               reclaimed. It also prevents the map outputs from being erased
+               from the reduce directory as they are consumed.</description>
+</property>
+
+
+<!-- 
+  <property>
+  <name>mapreduce.task.files.preserve.filepattern</name>
+  <value>.*_m_123456_0</value>
+  <description>Keep all files from tasks whose task names match the given
+               regular expression. Defaults to none.</description>
+  </property>
+-->
+
+<property>
+  <name>mapreduce.output.fileoutputformat.compress</name>
+  <value>false</value>
+  <description>Should the job outputs be compressed?
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.output.fileoutputformat.compression.type</name>
+  <value>RECORD</value>
+  <description>If the job outputs are to compressed as SequenceFiles, how should
+               they be compressed? Should be one of NONE, RECORD or BLOCK.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.output.fileoutputformat.compression.codec</name>
+  <value>org.apache.hadoop.io.compress.DefaultCodec</value>
+  <description>If the job outputs are compressed, how should they be compressed?
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.map.output.compress</name>
+  <value>false</value>
+  <description>Should the outputs of the maps be compressed before being
+               sent across the network. Uses SequenceFile compression.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.map.output.compress.codec</name>
+  <value>org.apache.hadoop.io.compress.DefaultCodec</value>
+  <description>If the map outputs are compressed, how should they be 
+               compressed?
+  </description>
+</property>
+
+<property>
+  <name>map.sort.class</name>
+  <value>org.apache.hadoop.util.QuickSort</value>
+  <description>The default sort class for sorting keys.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.task.userlog.limit.kb</name>
+  <value>0</value>
+  <description>The maximum size of user-logs of each task in KB. 0 disables the cap.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.userlog.retain.hours</name>
+  <value>24</value>
+  <description>The maximum time, in hours, for which the user-logs are to be 
+               retained after the job completion.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.hosts.filename</name>
+  <value></value>
+  <description>Names a file that contains the list of nodes that may
+  connect to the jobtracker.  If the value is empty, all hosts are
+  permitted.</description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.hosts.exclude.filename</name>
+  <value></value>
+  <description>Names a file that contains the list of hosts that
+  should be excluded by the jobtracker.  If the value is empty, no
+  hosts are excluded.</description>
+</property>
+
+<property>
+  <name>mapreduce.jobtracker.heartbeats.in.second</name>
+  <value>100</value>
+  <description>Expert: Approximate number of heart-beats that could arrive 
+               at JobTracker in a second. Assuming each RPC can be processed 
+               in 10msec, the default value is made 100 RPCs in a second.
+  </description>
+</property> 
+
+<property>
+  <name>mapreduce.jobtracker.tasktracker.maxblacklists</name>
+  <value>4</value>
+  <description>The number of blacklists for a taskTracker by various jobs
+               after which the task tracker could be blacklisted across
+               all jobs. The tracker will be given a tasks later
+               (after a day). The tracker will become a healthy
+               tracker after a restart.
+  </description>
+</property> 
+
+<property>
+  <name>mapreduce.job.maxtaskfailures.per.tracker</name>
+  <value>4</value>
+  <description>The number of task-failures on a tasktracker of a given job 
+               after which new tasks of that job aren't assigned to it.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.client.output.filter</name>
+  <value>FAILED</value>
+  <description>The filter for controlling the output of the task's userlogs sent
+               to the console of the JobClient. 
+               The permissible options are: NONE, KILLED, FAILED, SUCCEEDED and 
+               ALL.
+  </description>
+</property>
+
+  <property>
+    <name>mapreduce.client.completion.pollinterval</name>
+    <value>5000</value>
+    <description>The interval (in milliseconds) between which the JobClient
+    polls the JobTracker for updates about job status. You may want to set this
+    to a lower value to make tests run faster on a single node system. Adjusting
+    this value in production may lead to unwanted client-server traffic.
+    </description>
+  </property>
+
+  <property>
+    <name>mapreduce.client.progressmonitor.pollinterval</name>
+    <value>1000</value>
+    <description>The interval (in milliseconds) between which the JobClient
+    reports status to the console and checks for job completion. You may want to set this
+    to a lower value to make tests run faster on a single node system. Adjusting
+    this value in production may lead to unwanted client-server traffic.
+    </description>
+  </property>
+
+  <property>
+    <name>mapreduce.jobtracker.persist.jobstatus.active</name>
+    <value>true</value>
+    <description>Indicates if persistency of job status information is
+      active or not.
+    </description>
+  </property>
+
+  <property>
+  <name>mapreduce.jobtracker.persist.jobstatus.hours</name>
+  <value>1</value>
+  <description>The number of hours job status information is persisted in DFS.
+    The job status information will be available after it drops of the memory
+    queue and between jobtracker restarts. With a zero value the job status
+    information is not persisted at all in DFS.
+  </description>
+</property>
+
+  <property>
+    <name>mapreduce.jobtracker.persist.jobstatus.dir</name>
+    <value>/jobtracker/jobsInfo</value>
+    <description>The directory where the job status information is persisted
+      in a file system to be available after it drops of the memory queue and
+      between jobtracker restarts.
+    </description>
+  </property>
+
+  <property>
+    <name>mapreduce.task.profile</name>
+    <value>false</value>
+    <description>To set whether the system should collect profiler
+     information for some of the tasks in this job? The information is stored
+     in the user log directory. The value is "true" if task profiling
+     is enabled.</description>
+  </property>
+
+  <property>
+    <name>mapreduce.task.profile.maps</name>
+    <value>0-2</value>
+    <description> To set the ranges of map tasks to profile.
+    mapreduce.task.profile has to be set to true for the value to be accounted.
+    </description>
+  </property>
+
+  <property>
+    <name>mapreduce.task.profile.reduces</name>
+    <value>0-2</value>
+    <description> To set the ranges of reduce tasks to profile.
+    mapreduce.task.profile has to be set to true for the value to be accounted.
+    </description>
+  </property>
+
+  <property>
+    <name>mapreduce.task.skip.start.attempts</name>
+    <value>2</value>
+    <description> The number of Task attempts AFTER which skip mode 
+    will be kicked off. When skip mode is kicked off, the 
+    tasks reports the range of records which it will process 
+    next, to the TaskTracker. So that on failures, TT knows which 
+    ones are possibly the bad records. On further executions, 
+    those are skipped.
+    </description>
+  </property>
+  
+  <property>
+    <name>mapreduce.map.skip.proc.count.autoincr</name>
+    <value>true</value>
+    <description> The flag which if set to true, 
+    SkipBadRecords.COUNTER_MAP_PROCESSED_RECORDS is incremented 
+    by MapRunner after invoking the map function. This value must be set to 
+    false for applications which process the records asynchronously 
+    or buffer the input records. For example streaming. 
+    In such cases applications should increment this counter on their own.
+    </description>
+  </property>
+  
+  <property>
+    <name>mapreduce.reduce.skip.proc.count.autoincr</name>
+    <value>true</value>
+    <description> The flag which if set to true, 
+    SkipBadRecords.COUNTER_REDUCE_PROCESSED_GROUPS is incremented 
+    by framework after invoking the reduce function. This value must be set to 
+    false for applications which process the records asynchronously 
+    or buffer the input records. For example streaming. 
+    In such cases applications should increment this counter on their own.
+    </description>
+  </property>
+  
+  <property>
+    <name>mapreduce.job.skip.outdir</name>
+    <value></value>
+    <description> If no value is specified here, the skipped records are 
+    written to the output directory at _logs/skip.
+    User can stop writing skipped records by giving the value "none". 
+    </description>
+  </property>
+
+  <property>
+    <name>mapreduce.map.skip.maxrecords</name>
+    <value>0</value>
+    <description> The number of acceptable skip records surrounding the bad 
+    record PER bad record in mapper. The number includes the bad record as well.
+    To turn the feature of detection/skipping of bad records off, set the 
+    value to 0.
+    The framework tries to narrow down the skipped range by retrying  
+    until this threshold is met OR all attempts get exhausted for this task. 
+    Set the value to Long.MAX_VALUE to indicate that framework need not try to 
+    narrow down. Whatever records(depends on application) get skipped are 
+    acceptable.
+    </description>
+  </property>
+  
+  <property>
+    <name>mapreduce.reduce.skip.maxgroups</name>
+    <value>0</value>
+    <description> The number of acceptable skip groups surrounding the bad 
+    group PER bad group in reducer. The number includes the bad group as well.
+    To turn the feature of detection/skipping of bad groups off, set the 
+    value to 0.
+    The framework tries to narrow down the skipped range by retrying  
+    until this threshold is met OR all attempts get exhausted for this task. 
+    Set the value to Long.MAX_VALUE to indicate that framework need not try to 
+    narrow down. Whatever groups(depends on application) get skipped are 
+    acceptable.
+    </description>
+  </property>
+  
+<!-- Job Notification Configuration -->
+
+<!--
+<property>
+ <name>mapreduce.job.end-notification.url</name>
+ <value>http://localhost:8080/jobstatus.php?jobId=$jobId&amp;jobStatus=$jobStatus</value>
+ <description>Indicates url which will be called on completion of job to inform
+              end status of job.
+              User can give at most 2 variables with URI : $jobId and $jobStatus.
+              If they are present in URI, then they will be replaced by their
+              respective values.
+</description>
+</property>
+-->
+
+<property>
+  <name>mapreduce.job.end-notification.retry.attempts</name>
+  <value>0</value>
+  <description>Indicates how many times hadoop should attempt to contact the
+               notification URL </description>
+</property>
+
+<property>
+  <name>mapreduce.job.end-notification.retry.interval</name>
+   <value>30000</value>
+   <description>Indicates time in milliseconds between notification URL retry
+                calls</description>
+</property>
+  
+<!-- Proxy Configuration -->
+<property>
+  <name>mapreduce.jobtracker.taskcache.levels</name>
+  <value>2</value>
+  <description> This is the max level of the task cache. For example, if
+    the level is 2, the tasks cached are at the host level and at the rack
+    level.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.queuename</name>
+  <value>default</value>
+  <description> Queue to which a job is submitted. This must match one of the
+    queues defined in mapred-queues.xml for the system. Also, the ACL setup
+    for the queue must allow the current user to submit a job to the queue.
+    Before specifying a queue, ensure that the system is configured with 
+    the queue, and access is allowed for submitting jobs to the queue.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.cluster.acls.enabled</name>
+  <value>false</value>
+  <description> Specifies whether ACLs should be checked
+    for authorization of users for doing various queue and job level operations.
+    ACLs are disabled by default. If enabled, access control checks are made by
+    JobTracker and TaskTracker when requests are made by users for queue
+    operations like submit job to a queue and kill a job in the queue and job
+    operations like viewing the job-details (See mapreduce.job.acl-view-job)
+    or for modifying the job (See mapreduce.job.acl-modify-job) using
+    Map/Reduce APIs, RPCs or via the console and web user interfaces.
+    For enabling this flag(mapreduce.cluster.acls.enabled), this is to be set
+    to true in mapred-site.xml on JobTracker node and on all TaskTracker nodes.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.acl-modify-job</name>
+  <value> </value>
+  <description> Job specific access-control list for 'modifying' the job. It
+    is only used if authorization is enabled in Map/Reduce by setting the
+    configuration property mapreduce.cluster.acls.enabled to true.
+    This specifies the list of users and/or groups who can do modification
+    operations on the job. For specifying a list of users and groups the
+    format to use is "user1,user2 group1,group". If set to '*', it allows all
+    users/groups to modify this job. If set to ' '(i.e. space), it allows
+    none. This configuration is used to guard all the modifications with respect
+    to this job and takes care of all the following operations:
+      o killing this job
+      o killing a task of this job, failing a task of this job
+      o setting the priority of this job
+    Each of these operations are also protected by the per-queue level ACL
+    "acl-administer-jobs" configured via mapred-queues.xml. So a caller should
+    have the authorization to satisfy either the queue-level ACL or the
+    job-level ACL.
+
+    Irrespective of this ACL configuration, (a) job-owner, (b) the user who
+    started the cluster, (c) members of an admin configured supergroup
+    configured via mapreduce.cluster.permissions.supergroup and (d) queue
+    administrators of the queue to which this job was submitted to configured
+    via acl-administer-jobs for the specific queue in mapred-queues.xml can
+    do all the modification operations on a job.
+
+    By default, nobody else besides job-owner, the user who started the cluster,
+    members of supergroup and queue administrators can perform modification
+    operations on a job.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.acl-view-job</name>
+  <value> </value>
+  <description> Job specific access-control list for 'viewing' the job. It is
+    only used if authorization is enabled in Map/Reduce by setting the
+    configuration property mapreduce.cluster.acls.enabled to true.
+    This specifies the list of users and/or groups who can view private details
+    about the job. For specifying a list of users and groups the
+    format to use is "user1,user2 group1,group". If set to '*', it allows all
+    users/groups to modify this job. If set to ' '(i.e. space), it allows
+    none. This configuration is used to guard some of the job-views and at
+    present only protects APIs that can return possibly sensitive information
+    of the job-owner like
+      o job-level counters
+      o task-level counters
+      o tasks' diagnostic information
+      o task-logs displayed on the TaskTracker web-UI and
+      o job.xml showed by the JobTracker's web-UI
+    Every other piece of information of jobs is still accessible by any other
+    user, for e.g., JobStatus, JobProfile, list of jobs in the queue, etc.
+
+    Irrespective of this ACL configuration, (a) job-owner, (b) the user who
+    started the cluster, (c) members of an admin configured supergroup
+    configured via mapreduce.cluster.permissions.supergroup and (d) queue
+    administrators of the queue to which this job was submitted to configured
+    via acl-administer-jobs for the specific queue in mapred-queues.xml can
+    do all the view operations on a job.
+
+    By default, nobody else besides job-owner, the user who started the
+    cluster, memebers of supergroup and queue administrators can perform
+    view operations on a job.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.indexcache.mb</name>
+  <value>10</value>
+  <description> The maximum memory that a task tracker allows for the 
+    index cache that is used when serving map outputs to reducers.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.task.merge.progress.records</name>
+  <value>10000</value>
+  <description> The number of records to process during merge before
+   sending a progress notification to the TaskTracker.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.job.reduce.slowstart.completedmaps</name>
+  <value>0.05</value>
+  <description>Fraction of the number of maps in the job which should be 
+  complete before reduces are scheduled for the job. 
+  </description>
+</property>
+
+<property>
+<name>mapreduce.job.complete.cancel.delegation.tokens</name>
+  <value>true</value>
+  <description> if false - do not unregister/cancel delegation tokens from 
+    renewal, because same tokens may be used by spawned jobs
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.taskcontroller</name>
+  <value>org.apache.hadoop.mapred.DefaultTaskController</value>
+  <description>TaskController which is used to launch and manage task execution 
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.group</name>
+  <value></value>
+  <description>Expert: Group to which TaskTracker belongs. If 
+   LinuxTaskController is configured via mapreduce.tasktracker.taskcontroller,
+   the group owner of the task-controller binary should be same as this group.
+  </description>
+</property>
+
+<!--  Node health script variables -->
+
+<property>
+  <name>mapreduce.tasktracker.healthchecker.script.path</name>
+  <value></value>
+  <description>Absolute path to the script which is
+  periodicallyrun by the node health monitoring service to determine if
+  the node is healthy or not. If the value of this key is empty or the
+  file does not exist in the location configured here, the node health
+  monitoring service is not started.</description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.healthchecker.interval</name>
+  <value>60000</value>
+  <description>Frequency of the node health script to be run,
+  in milliseconds</description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.healthchecker.script.timeout</name>
+  <value>600000</value>
+  <description>Time after node health script should be killed if 
+  unresponsive and considered that the script has failed.</description>
+</property>
+
+<property>
+  <name>mapreduce.tasktracker.healthchecker.script.args</name>
+  <value></value>
+  <description>List of arguments which are to be passed to 
+  node health script when it is being launched comma seperated.
+  </description>
+</property>
+
+<!--  end of node health script variables -->
+
+<property>
+ <name>mapreduce.job.counters.limit</name>
+  <value>120</value>
+  <description>Limit on the number of user counters allowed per job.
+  </description>
+</property>
+
+<property>
+  <name>mapreduce.framework.name</name>
+  <value>yarn</value>
+  <description>The runtime framework for executing MapReduce jobs.
+  Can be one of local, classic or yarn.
+  </description>
+</property>
+
+</configuration>