namevaluedescription
hadoop.tmp.dir/tmp/hadoop-${user.name}A base for other temporary directories.
hadoop.native.libtrueShould native hadoop libraries, if present, be used.
hadoop.http.filter.initializersA comma separated list of class names. Each class in the list must extend org.apache.hadoop.http.FilterInitializer. The corresponding Filter will be initialized. Then, the Filter will be applied to all user facing jsp and servlet web pages. The ordering of the list defines the ordering of the filters.
hadoop.logfile.size10000000The max size of each log file
hadoop.logfile.count10The max number of log files
hadoop.job.history.location 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.
hadoop.job.history.user.location 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".
dfs.namenode.logging.levelinfoThe logging level for dfs namenode. Other values are "dir"(trac e namespace mutations), "block"(trace block under/over replications and block creations/deletions), or "all".
io.sort.factor10The number of streams to merge at once while sorting files. This determines the number of open file handles.
io.sort.mb100The total amount of buffer memory to use while sorting files, in megabytes. By default, gives each merge stream 1MB, which should minimize seeks.
io.sort.record.percent0.05The percentage of io.sort.mb dedicated to tracking record boundaries. Let this value be r, io.sort.mb be x. The maximum number of records collected before the collection thread must block is equal to (r * x) / 4
io.sort.spill.percent0.80The soft limit in either the buffer or record collection buffers. Once reached, a thread will begin to spill the contents to disk in the background. Note that this does not imply any chunking of data to the spill. A value less than 0.5 is not recommended.
io.file.buffer.size4096The size of buffer for use in sequence files. The size of this buffer should probably be a multiple of hardware page size (4096 on Intel x86), and it determines how much data is buffered during read and write operations.
io.bytes.per.checksum512The number of bytes per checksum. Must not be larger than io.file.buffer.size.
io.skip.checksum.errorsfalseIf true, when a checksum error is encountered while reading a sequence file, entries are skipped, instead of throwing an exception.
io.map.index.skip0Number of index entries to skip between each entry. Zero by default. Setting this to values larger than zero can facilitate opening large map files using less memory.
io.compression.codecsorg.apache.hadoop.io.compress.DefaultCodec,org.apache.hadoop.io.compress.GzipCodec,org.apache.hadoop.io.compress.BZip2CodecA list of the compression codec classes that can be used for compression/decompression.
io.serializationsorg.apache.hadoop.io.serializer.WritableSerializationA list of serialization classes that can be used for obtaining serializers and deserializers.
fs.default.namefile:///The name of the default file system. A URI whose scheme and authority determine the FileSystem implementation. The uri's scheme determines the config property (fs.SCHEME.impl) naming the FileSystem implementation class. The uri's authority is used to determine the host, port, etc. for a filesystem.
fs.trash.interval0Number of minutes between trash checkpoints. If zero, the trash feature is disabled.
fs.file.implorg.apache.hadoop.fs.LocalFileSystemThe FileSystem for file: uris.
fs.hdfs.implorg.apache.hadoop.hdfs.DistributedFileSystemThe FileSystem for hdfs: uris.
fs.s3.implorg.apache.hadoop.fs.s3.S3FileSystemThe FileSystem for s3: uris.
fs.s3n.implorg.apache.hadoop.fs.s3native.NativeS3FileSystemThe FileSystem for s3n: (Native S3) uris.
fs.kfs.implorg.apache.hadoop.fs.kfs.KosmosFileSystemThe FileSystem for kfs: uris.
fs.hftp.implorg.apache.hadoop.hdfs.HftpFileSystem
fs.hsftp.implorg.apache.hadoop.hdfs.HsftpFileSystem
fs.ftp.implorg.apache.hadoop.fs.ftp.FTPFileSystemThe FileSystem for ftp: uris.
fs.ramfs.implorg.apache.hadoop.fs.InMemoryFileSystemThe FileSystem for ramfs: uris.
fs.har.implorg.apache.hadoop.fs.HarFileSystemThe filesystem for Hadoop archives.
fs.checkpoint.dir${hadoop.tmp.dir}/dfs/namesecondaryDetermines where on the local filesystem the DFS secondary name node should store the temporary images to merge. If this is a comma-delimited list of directories then the image is replicated in all of the directories for redundancy.
fs.checkpoint.edits.dir${fs.checkpoint.dir}Determines where on the local filesystem the DFS secondary name node should store the temporary edits to merge. If this is a comma-delimited list of directoires then teh edits is replicated in all of the directoires for redundancy. Default value is same as fs.checkpoint.dir
fs.checkpoint.period3600The number of seconds between two periodic checkpoints.
fs.checkpoint.size67108864The size of the current edit log (in bytes) that triggers a periodic checkpoint even if the fs.checkpoint.period hasn't expired.
dfs.secondary.http.address0.0.0.0:50090 The secondary namenode http server address and port. If the port is 0 then the server will start on a free port.
dfs.datanode.address0.0.0.0:50010 The address where the datanode server will listen to. If the port is 0 then the server will start on a free port.
dfs.datanode.http.address0.0.0.0:50075 The datanode http server address and port. If the port is 0 then the server will start on a free port.
dfs.datanode.ipc.address0.0.0.0:50020 The datanode ipc server address and port. If the port is 0 then the server will start on a free port.
dfs.datanode.handler.count3The number of server threads for the datanode.
dfs.http.address0.0.0.0:50070 The address and the base port where the dfs namenode web ui will listen on. If the port is 0 then the server will start on a free port.
dfs.datanode.https.address0.0.0.0:50475
dfs.https.address0.0.0.0:50470
https.keystore.info.rsrcsslinfo.xmlThe name of the resource from which ssl keystore information will be extracted
dfs.datanode.dns.interfacedefaultThe name of the Network Interface from which a data node should report its IP address.
dfs.datanode.dns.nameserverdefaultThe host name or IP address of the name server (DNS) which a DataNode should use to determine the host name used by the NameNode for communication and display purposes.
dfs.replication.considerLoadtrueDecide if chooseTarget considers the target's load or not
dfs.default.chunk.view.size32768The number of bytes to view for a file on the browser.
dfs.datanode.du.reserved0Reserved space in bytes per volume. Always leave this much space free for non dfs use.
dfs.name.dir${hadoop.tmp.dir}/dfs/nameDetermines where on the local filesystem the DFS name node should store the name table(fsimage). If this is a comma-delimited list of directories then the name table is replicated in all of the directories, for redundancy.
dfs.name.edits.dir${dfs.name.dir}Determines where on the local filesystem the DFS name node should store the transaction (edits) file. If this is a comma-delimited list of directories then the transaction file is replicated in all of the directories, for redundancy. Default value is same as dfs.name.dir
dfs.web.ugiwebuser,webgroupThe user account used by the web interface. Syntax: USERNAME,GROUP1,GROUP2, ...
dfs.permissionstrue If "true", enable permission checking in HDFS. If "false", permission checking is turned off, but all other behavior is unchanged. Switching from one parameter value to the other does not change the mode, owner or group of files or directories.
dfs.permissions.supergroupsupergroupThe name of the group of super-users.
dfs.data.dir${hadoop.tmp.dir}/dfs/dataDetermines where on the local filesystem an DFS data node should store its blocks. If this is a comma-delimited list of directories, then data will be stored in all named directories, typically on different devices. Directories that do not exist are ignored.
dfs.replication3Default block replication. The actual number of replications can be specified when the file is created. The default is used if replication is not specified in create time.
dfs.replication.max512Maximal block replication.
dfs.replication.min1Minimal block replication.
dfs.block.size67108864The default block size for new files.
dfs.df.interval60000Disk usage statistics refresh interval in msec.
dfs.client.block.write.retries3The number of retries for writing blocks to the data nodes, before we signal failure to the application.
dfs.blockreport.intervalMsec3600000Determines block reporting interval in milliseconds.
dfs.blockreport.initialDelay0Delay for first block report in seconds.
dfs.heartbeat.interval3Determines datanode heartbeat interval in seconds.
dfs.namenode.handler.count10The number of server threads for the namenode.
dfs.safemode.threshold.pct0.999f Specifies the percentage of blocks that should satisfy the minimal replication requirement defined by dfs.replication.min. Values less than or equal to 0 mean not to start in safe mode. Values greater than 1 will make safe mode permanent.
dfs.safemode.extension30000 Determines extension of safe mode in milliseconds after the threshold level is reached.
dfs.balance.bandwidthPerSec1048576 Specifies the maximum amount of bandwidth that each datanode can utilize for the balancing purpose in term of the number of bytes per second.
dfs.hostsNames a file that contains a list of hosts that are permitted to connect to the namenode. The full pathname of the file must be specified. If the value is empty, all hosts are permitted.
dfs.hosts.excludeNames a file that contains a list of hosts that are not permitted to connect to the namenode. The full pathname of the file must be specified. If the value is empty, no hosts are excluded.
dfs.max.objects0The maximum number of files, directories and blocks dfs supports. A value of zero indicates no limit to the number of objects that dfs supports.
dfs.namenode.decommission.interval30Namenode periodicity in seconds to check if decommission is complete.
dfs.namenode.decommission.nodes.per.interval5The number of nodes namenode checks if decommission is complete in each dfs.namenode.decommission.interval.
dfs.replication.interval3The periodicity in seconds with which the namenode computes repliaction work for datanodes.
dfs.access.time.precision3600000The access time for HDFS file is precise upto this value. The default value is 1 hour. Setting a value of 0 disables access times for HDFS.
fs.s3.block.size67108864Block size to use when writing files to S3.
fs.s3.buffer.dir${hadoop.tmp.dir}/s3Determines where on the local filesystem the S3 filesystem should store files before sending them to S3 (or after retrieving them from S3).
fs.s3.maxRetries4The maximum number of retries for reading or writing files to S3, before we signal failure to the application.
fs.s3.sleepTimeSeconds10The number of seconds to sleep between each S3 retry.
mapred.job.trackerlocalThe host and port that the MapReduce job tracker runs at. If "local", then jobs are run in-process as a single map and reduce task.
mapred.job.tracker.http.address0.0.0.0:50030 The job tracker http server address and port the server will listen on. If the port is 0 then the server will start on a free port.
mapred.job.tracker.handler.count10 The number of server threads for the JobTracker. This should be roughly 4% of the number of tasktracker nodes.
mapred.task.tracker.report.address127.0.0.1:0The interface and port that task tracker server listens on. Since it is only connected to by the tasks, it uses the local interface. EXPERT ONLY. Should only be changed if your host does not have the loopback interface.
mapred.local.dir${hadoop.tmp.dir}/mapred/localThe 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.
local.cache.size10737418240The limit on the size of cache you want to keep, set by default to 10GB. This will act as a soft limit on the cache directory for out of band data.
mapred.system.dir${hadoop.tmp.dir}/mapred/systemThe shared directory where MapReduce stores control files.
mapred.temp.dir${hadoop.tmp.dir}/mapred/tempA shared directory for temporary files.
mapred.local.dir.minspacestart0If the space in mapred.local.dir drops under this, do not ask for more tasks. Value in bytes.
mapred.local.dir.minspacekill0If the space in mapred.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.
mapred.tasktracker.expiry.interval600000Expert: The time-interval, in miliseconds, after which a tasktracker is declared 'lost' if it doesn't send heartbeats.
mapred.tasktracker.instrumentationorg.apache.hadoop.mapred.TaskTrackerMetricsInstExpert: The instrumentation class to associate with each TaskTracker.
mapred.tasktracker.vmem.reserved-1Configuration property to specify the amount of virtual memory that has to be reserved by the TaskTracker for system usage (OS, TT etc). The reserved virtual memory should be a part of the total virtual memory available on the TaskTracker. The reserved virtual memory and the total virtual memory values are reported by the TaskTracker as part of heart-beat so that they can considered by a scheduler. Please refer to the documentation of the configured scheduler to see how this property is used. These two values are also used by a TaskTracker for tracking tasks' memory usage. Memory management functionality on a TaskTracker is disabled if this property is set to -1, if it more than the total virtual memory on the tasktracker, or if either of the values is negative.
mapred.tasktracker.pmem.reserved-1Configuration property to specify the amount of physical memory that has to be reserved by the TaskTracker for system usage (OS, TT etc). The reserved physical memory should be a part of the total physical memory available on the TaskTracker. The reserved physical memory and the total physical memory values are reported by the TaskTracker as part of heart-beat so that they can considered by a scheduler. Please refer to the documentation of the configured scheduler to see how this property is used.
mapred.task.default.maxvmem-1 Cluster-wide configuration in bytes to be set by the administrators that provides default amount of maximum virtual memory for job's tasks. This has to be set on both the JobTracker node for the sake of scheduling decisions and on the TaskTracker nodes for the sake of memory management. If a job doesn't specify its virtual memory requirement by setting mapred.task.maxvmem to -1, tasks are assured a memory limit set to this property. This property is set to -1 by default. This value should in general be less than the cluster-wide configuration mapred.task.limit.maxvmem. If not or if it is not set, TaskTracker's memory management will be disabled and a scheduler's memory based scheduling decisions may be affected. Please refer to the documentation of the configured scheduler to see how this property is used.
mapred.task.limit.maxvmem-1 Cluster-wide configuration in bytes to be set by the site administrators that provides an upper limit on the maximum virtual memory that can be specified by a job via mapred.task.maxvmem. This has to be set on both the JobTracker node for the sake of scheduling decisions and on the TaskTracker nodes for the sake of memory management. The job configuration mapred.task.maxvmem should not be more than this value, otherwise depending on the scheduler being configured, the job may be rejected or the job configuration may just be ignored. Please refer to the documentation of the configured scheduler to see how this property is used. If it is not set a TaskTracker, TaskTracker's memory management will be disabled.
mapred.task.maxvmem-1 The maximum amount of virtual memory any task of a job will use, in bytes. This value will be used by TaskTrackers for monitoring the memory usage of tasks of this jobs. If a TaskTracker's memory management functionality is enabled, each task of this job will be allowed to use a maximum virtual memory specified by this property. If the task's memory usage goes over this value, the task will be failed by the TT. If not set, the cluster-wide configuration mapred.task.default.maxvmem is used as the default value for memory requirements. If this property cascaded with mapred.task.default.maxvmem becomes equal to -1, the job's tasks will not be assured any particular amount of virtual memory and may be killed by a TT that intends to control the total memory usage of the tasks via memory management functionality. If the memory management functionality is disabled on a TT, this value is ignored. This value should not be more than the cluster-wide configuration mapred.task.limit.maxvmem. This value may be used by schedulers that support scheduling based on job's memory requirements. Please refer to the documentation of the scheduler being configured to see if it does memory based scheduling and if it does, how this property is used by that scheduler.
mapred.task.maxpmem-1 The maximum amount of physical memory any task of a job will use in bytes. This value may be used by schedulers that support scheduling based on job's memory requirements. In general, a task of this job will be scheduled on a TaskTracker, only if the amount of physical memory still unoccupied on the TaskTracker is greater than or equal to this value. Different schedulers can take different decisions, some might just ignore this value. Please refer to the documentation of the scheduler being configured to see if it does memory based scheduling and if it does, how this variable is used by that scheduler.
mapred.tasktracker.memory_calculator_plugin Name of the class whose instance will be used to query memory information on the tasktracker. The class must be an instance of org.apache.hadoop.util.MemoryCalculatorPlugin. If the value is null, the tasktracker attempts to use a class appropriate to the platform. Currently, the only platform supported is Linux.
mapred.tasktracker.taskmemorymanager.monitoring-interval5000The 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.
mapred.tasktracker.procfsbasedprocesstree.sleeptime-before-sigkill5000The time, in milliseconds, the tasktracker waits for sending a SIGKILL to a process that has overrun memory limits, after it has been sent a SIGTERM. Used only if tasks' memory management is enabled via mapred.tasktracker.tasks.maxmemory.
mapred.map.tasks2The default number of map tasks per job. Typically set to a prime several times greater than number of available hosts. Ignored when mapred.job.tracker is "local".
mapred.reduce.tasks1The default number of reduce tasks per job. Typically set to a prime close to the number of available hosts. Ignored when mapred.job.tracker is "local".
mapred.jobtracker.restart.recoverfalse"true" to enable (job) recovery upon restart, "false" to start afresh
mapred.jobtracker.job.history.block.size3145728The 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.
mapred.jobtracker.taskSchedulerorg.apache.hadoop.mapred.JobQueueTaskSchedulerThe class responsible for scheduling the tasks.
mapred.jobtracker.taskScheduler.maxRunningTasksPerJobThe maximum number of running tasks for a job before it gets preempted. No limits if undefined.
mapred.map.max.attempts4Expert: 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.
mapred.reduce.max.attempts4Expert: 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.
mapred.reduce.parallel.copies5The default number of parallel transfers run by reduce during the copy(shuffle) phase.
mapred.reduce.copy.backoff300The maximum amount of time (in seconds) a reducer spends on fetching one map output before declaring it as failed.
mapred.task.timeout600000The number of milliseconds before a task will be terminated if it neither reads an input, writes an output, nor updates its status string.
mapred.tasktracker.map.tasks.maximum2The maximum number of map tasks that will be run simultaneously by a task tracker.
mapred.tasktracker.reduce.tasks.maximum2The maximum number of reduce tasks that will be run simultaneously by a task tracker.
mapred.jobtracker.completeuserjobs.maximum100The maximum number of complete jobs per user to keep around before delegating them to the job history.
mapred.jobtracker.instrumentationorg.apache.hadoop.mapred.JobTrackerMetricsInstExpert: The instrumentation class to associate with each JobTracker.
mapred.child.java.opts-Xmx200mJava 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.
mapred.child.ulimitThe 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.
mapred.child.tmp./tmp 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'
mapred.inmem.merge.threshold1000The 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.
mapred.job.shuffle.merge.percent0.66The 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 mapred.job.shuffle.input.buffer.percent.
mapred.job.shuffle.input.buffer.percent0.70The percentage of memory to be allocated from the maximum heap size to storing map outputs during the shuffle.
mapred.job.reduce.input.buffer.percent0.0The 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.
mapred.map.tasks.speculative.executiontrueIf true, then multiple instances of some map tasks may be executed in parallel.
mapred.reduce.tasks.speculative.executiontrueIf true, then multiple instances of some reduce tasks may be executed in parallel.
mapred.job.reuse.jvm.num.tasks1How many tasks to run per jvm. If set to -1, there is no limit.
mapred.min.split.size0The 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.
mapred.jobtracker.maxtasks.per.job-1The maximum number of tasks for a single job. A value of -1 indicates that there is no maximum.
mapred.submit.replication10The replication level for submitted job files. This should be around the square root of the number of nodes.
mapred.tasktracker.dns.interfacedefaultThe name of the Network Interface from which a task tracker should report its IP address.
mapred.tasktracker.dns.nameserverdefaultThe 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.
tasktracker.http.threads40The number of worker threads that for the http server. This is used for map output fetching
mapred.task.tracker.http.address0.0.0.0:50060 The task tracker http server address and port. If the port is 0 then the server will start on a free port.
keep.failed.task.filesfalseShould 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.
mapred.output.compressfalseShould the job outputs be compressed?
mapred.output.compression.typeRECORDIf the job outputs are to compressed as SequenceFiles, how should they be compressed? Should be one of NONE, RECORD or BLOCK.
mapred.output.compression.codecorg.apache.hadoop.io.compress.DefaultCodecIf the job outputs are compressed, how should they be compressed?
mapred.compress.map.outputfalseShould the outputs of the maps be compressed before being sent across the network. Uses SequenceFile compression.
mapred.map.output.compression.codecorg.apache.hadoop.io.compress.DefaultCodecIf the map outputs are compressed, how should they be compressed?
io.seqfile.compress.blocksize1000000The minimum block size for compression in block compressed SequenceFiles.
io.seqfile.lazydecompresstrueShould values of block-compressed SequenceFiles be decompressed only when necessary.
io.seqfile.sorter.recordlimit1000000The limit on number of records to be kept in memory in a spill in SequenceFiles.Sorter
map.sort.classorg.apache.hadoop.util.QuickSortThe default sort class for sorting keys.
mapred.userlog.limit.kb0The maximum size of user-logs of each task in KB. 0 disables the cap.
mapred.userlog.retain.hours24The maximum time, in hours, for which the user-logs are to be retained.
mapred.hostsNames a file that contains the list of nodes that may connect to the jobtracker. If the value is empty, all hosts are permitted.
mapred.hosts.excludeNames a file that contains the list of hosts that should be excluded by the jobtracker. If the value is empty, no hosts are excluded.
mapred.max.tracker.blacklists4The 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.
mapred.max.tracker.failures4The number of task-failures on a tasktracker of a given job after which new tasks of that job aren't assigned to it.
jobclient.output.filterFAILEDThe 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.
mapred.job.tracker.persist.jobstatus.activefalseIndicates if persistency of job status information is active or not.
mapred.job.tracker.persist.jobstatus.hours0The 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.
mapred.job.tracker.persist.jobstatus.dir/jobtracker/jobsInfoThe 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.
mapred.task.profilefalseTo 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.
mapred.task.profile.maps0-2 To set the ranges of map tasks to profile. mapred.task.profile has to be set to true for the value to be accounted.
mapred.task.profile.reduces0-2 To set the ranges of reduce tasks to profile. mapred.task.profile has to be set to true for the value to be accounted.
mapred.line.input.format.linespermap1 Number of lines per split in NLineInputFormat.
mapred.skip.attempts.to.start.skipping2 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.
mapred.skip.map.auto.incr.proc.counttrue 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.
mapred.skip.reduce.auto.incr.proc.counttrue 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.
mapred.skip.out.dir 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".
mapred.skip.map.max.skip.records0 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.
mapred.skip.reduce.max.skip.groups0 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.
ipc.client.idlethreshold4000Defines the threshold number of connections after which connections will be inspected for idleness.
ipc.client.kill.max10Defines the maximum number of clients to disconnect in one go.
ipc.client.connection.maxidletime10000The maximum time in msec after which a client will bring down the connection to the server.
ipc.client.connect.max.retries10Indicates the number of retries a client will make to establish a server connection.
ipc.server.listen.queue.size128Indicates the length of the listen queue for servers accepting client connections.
ipc.server.tcpnodelayfalseTurn on/off Nagle's algorithm for the TCP socket connection on the server. Setting to true disables the algorithm and may decrease latency with a cost of more/smaller packets.
ipc.client.tcpnodelayfalseTurn on/off Nagle's algorithm for the TCP socket connection on the client. Setting to true disables the algorithm and may decrease latency with a cost of more/smaller packets.
job.end.retry.attempts0Indicates how many times hadoop should attempt to contact the notification URL
job.end.retry.interval30000Indicates time in milliseconds between notification URL retry calls
webinterface.private.actionsfalse If set to true, the web interfaces of JT and NN may contain actions, such as kill job, delete file, etc., that should not be exposed to public. Enable this option if the interfaces are only reachable by those who have the right authorization.
hadoop.rpc.socket.factory.class.defaultorg.apache.hadoop.net.StandardSocketFactory Default SocketFactory to use. This parameter is expected to be formatted as "package.FactoryClassName".
hadoop.rpc.socket.factory.class.ClientProtocol SocketFactory to use to connect to a DFS. If null or empty, use hadoop.rpc.socket.class.default. This socket factory is also used by DFSClient to create sockets to DataNodes.
hadoop.rpc.socket.factory.class.JobSubmissionProtocol SocketFactory to use to connect to a Map/Reduce master (JobTracker). If null or empty, then use hadoop.rpc.socket.class.default.
hadoop.socks.server Address (host:port) of the SOCKS server to be used by the SocksSocketFactory.
topology.node.switch.mapping.implorg.apache.hadoop.net.ScriptBasedMapping The default implementation of the DNSToSwitchMapping. It invokes a script specified in topology.script.file.name to resolve node names. If the value for topology.script.file.name is not set, the default value of DEFAULT_RACK is returned for all node names.
topology.script.file.name The script name that should be invoked to resolve DNS names to NetworkTopology names. Example: the script would take host.foo.bar as an argument, and return /rack1 as the output.
topology.script.number.args100 The max number of args that the script configured with topology.script.file.name should be run with. Each arg is an IP address.
mapred.task.cache.levels2 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.
mapred.queue.namesdefault Comma separated list of queues configured for this jobtracker. Jobs are added to queues and schedulers can configure different scheduling properties for the various queues. To configure a property for a queue, the name of the queue must match the name specified in this value. Queue properties that are common to all schedulers are configured here with the naming convention, mapred.queue.$QUEUE-NAME.$PROPERTY-NAME, for e.g. mapred.queue.default.submit-job-acl. The number of queues configured in this parameter could depend on the type of scheduler being used, as specified in mapred.jobtracker.taskScheduler. For example, the JobQueueTaskScheduler supports only a single queue, which is the default configured here. Before adding more queues, ensure that the scheduler you've configured supports multiple queues.
mapred.acls.enabledfalse Specifies whether ACLs are enabled, and should be checked for various operations.
mapred.queue.default.acl-submit-job* Comma separated list of user and group names that are allowed to submit jobs to the 'default' queue. The user list and the group list are separated by a blank. For e.g. alice,bob group1,group2. If set to the special value '*', it means all users are allowed to submit jobs.
mapred.queue.default.acl-administer-jobs* Comma separated list of user and group names that are allowed to delete jobs or modify job's priority for jobs not owned by the current user in the 'default' queue. The user list and the group list are separated by a blank. For e.g. alice,bob group1,group2. If set to the special value '*', it means all users are allowed to do this operation.
mapred.job.queue.namedefault Queue to which a job is submitted. This must match one of the queues defined in mapred.queue.names 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.
mapred.tasktracker.indexcache.mb10 The maximum memory that a task tracker allows for the index cache that is used when serving map outputs to reducers.
mapred.merge.recordsBeforeProgress10000 The number of records to process during merge before sending a progress notification to the TaskTracker.