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Showing content from https://hadoop.apache.org/docs/r1.2.1/api/org/apache/hadoop/mapred/JobConf.html below:

JobConf (Hadoop 1.2.1 API)

java.lang.Object
  org.apache.hadoop.conf.Configuration
      org.apache.hadoop.mapred.JobConf

All Implemented Interfaces:

Iterable<Map.Entry<String,String>>, Writable

public class JobConf
extends Configuration

A map/reduce job configuration.

JobConf is the primary interface for a user to describe a map-reduce job to the Hadoop framework for execution. The framework tries to faithfully execute the job as-is described by JobConf, however:

1. Some configuration parameters might have been marked as final by administrators and hence cannot be altered.
2. While some job parameters are straight-forward to set (e.g. setNumReduceTasks(int)), some parameters interact subtly rest of the framework and/or job-configuration and is relatively more complex for the user to control finely (e.g. setNumMapTasks(int)).

JobConf typically specifies the Mapper, combiner (if any), Partitioner, Reducer, InputFormat and OutputFormat implementations to be used etc.

Optionally JobConf is used to specify other advanced facets of the job such as Comparators to be used, files to be put in the DistributedCache, whether or not intermediate and/or job outputs are to be compressed (and how), debugability via user-provided scripts ( setMapDebugScript(String)/setReduceDebugScript(String)), for doing post-processing on task logs, task's stdout, stderr, syslog. and etc.

Here is an example on how to configure a job via JobConf:

     // Create a new JobConf
     JobConf job = new JobConf(new Configuration(), MyJob.class);
     
     // Specify various job-specific parameters     
     job.setJobName("myjob");
     
     FileInputFormat.setInputPaths(job, new Path("in"));
     FileOutputFormat.setOutputPath(job, new Path("out"));
     
     job.setMapperClass(MyJob.MyMapper.class);
     job.setCombinerClass(MyJob.MyReducer.class);
     job.setReducerClass(MyJob.MyReducer.class);
     
     job.setInputFormat(SequenceFileInputFormat.class);
     job.setOutputFormat(SequenceFileOutputFormat.class);
 

See Also:

JobClient, ClusterStatus, Tool, DistributedCache

@Deprecated
public static final String MAPRED_TASK_MAXVMEM_PROPERTY

Deprecated. Use MAPRED_JOB_MAP_MEMORY_MB_PROPERTY and MAPRED_JOB_REDUCE_MEMORY_MB_PROPERTY

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Constant Field Values

@Deprecated
public static final String UPPER_LIMIT_ON_TASK_VMEM_PROPERTY

Deprecated. 

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Constant Field Values

@Deprecated
public static final String MAPRED_TASK_DEFAULT_MAXVMEM_PROPERTY

Deprecated. 

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Constant Field Values

@Deprecated
public static final String MAPRED_TASK_MAXPMEM_PROPERTY

Deprecated. 

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Constant Field Values

public static final long DISABLED_MEMORY_LIMIT

A value which if set for memory related configuration options, indicates that the options are turned off.

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Constant Field Values

public static final String MAPRED_LOCAL_DIR_PROPERTY

Property name for the configuration property mapred.local.dir

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Constant Field Values

public static final String DEFAULT_QUEUE_NAME

Name of the queue to which jobs will be submitted, if no queue name is mentioned.

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Constant Field Values

public static final String MAPRED_JOB_MAP_MEMORY_MB_PROPERTY

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Constant Field Values

public static final String MAPRED_JOB_REDUCE_MEMORY_MB_PROPERTY

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Constant Field Values

@Deprecated
public static final String MAPRED_TASK_JAVA_OPTS

Deprecated. Use MAPRED_MAP_TASK_JAVA_OPTS or MAPRED_REDUCE_TASK_JAVA_OPTS

Configuration key to set the java command line options for the child map and reduce tasks. Java opts for the task tracker child processes. The following symbol, if present, will be interpolated: @taskid@. It 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_TASK_ULIMIT can be used to control the maximum virtual memory of the child processes. The configuration variable MAPRED_TASK_ENV can be used to pass other environment variables to the child processes.

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Constant Field Values

public static final String MAPRED_MAP_TASK_JAVA_OPTS

Configuration key to set the java command line options for the map tasks. Java opts for the task tracker child map processes. The following symbol, if present, will be interpolated: @taskid@. It 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_MAP_TASK_ULIMIT can be used to control the maximum virtual memory of the map processes. The configuration variable MAPRED_MAP_TASK_ENV can be used to pass other environment variables to the map processes.

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Constant Field Values

public static final String MAPRED_REDUCE_TASK_JAVA_OPTS

Configuration key to set the java command line options for the reduce tasks. Java opts for the task tracker child reduce processes. The following symbol, if present, will be interpolated: @taskid@. It 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_REDUCE_TASK_ULIMIT can be used to control the maximum virtual memory of the reduce processes. The configuration variable MAPRED_REDUCE_TASK_ENV can be used to pass process environment variables to the reduce processes.

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Constant Field Values

public static final String DEFAULT_MAPRED_TASK_JAVA_OPTS

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Constant Field Values

@Deprecated
public static final String MAPRED_TASK_ULIMIT

Deprecated. Use MAPRED_MAP_TASK_ULIMIT or MAPRED_REDUCE_TASK_ULIMIT

Configuration key to set the maximum virutal memory available to the child map and reduce tasks (in kilo-bytes). Note: This must be greater than or equal to the -Xmx passed to the JavaVM via MAPRED_TASK_JAVA_OPTS, else the VM might not start.

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Constant Field Values

public static final String MAPRED_MAP_TASK_ULIMIT

Configuration key to set the maximum virutal memory available to the map tasks (in kilo-bytes). Note: This must be greater than or equal to the -Xmx passed to the JavaVM via MAPRED_MAP_TASK_JAVA_OPTS, else the VM might not start.

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Constant Field Values

public static final String MAPRED_REDUCE_TASK_ULIMIT

Configuration key to set the maximum virutal memory available to the reduce tasks (in kilo-bytes). Note: This must be greater than or equal to the -Xmx passed to the JavaVM via MAPRED_REDUCE_TASK_JAVA_OPTS, else the VM might not start.

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Constant Field Values

@Deprecated
public static final String MAPRED_TASK_ENV

Deprecated. Use MAPRED_MAP_TASK_ENV or MAPRED_REDUCE_TASK_ENV

Configuration key to set the environment of the child map/reduce tasks. The format of the value is k1=v1,k2=v2. Further it can reference existing environment variables via $key. Example:

• A=foo - This will set the env variable A to foo.
• B=$X:c This is inherit tasktracker's X env variable.

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Constant Field Values

public static final String MAPRED_MAP_TASK_ENV

Configuration key to set the maximum virutal memory available to the map tasks. The format of the value is k1=v1,k2=v2. Further it can reference existing environment variables via $key. Example:

• A=foo - This will set the env variable A to foo.
• B=$X:c This is inherit tasktracker's X env variable.

See Also:

Constant Field Values

public static final String MAPRED_REDUCE_TASK_ENV

Configuration key to set the maximum virutal memory available to the reduce tasks. The format of the value is k1=v1,k2=v2. Further it can reference existing environment variables via $key. Example:

• A=foo - This will set the env variable A to foo.
• B=$X:c This is inherit tasktracker's X env variable.

See Also:

Constant Field Values

public static final String WORKFLOW_ID

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Constant Field Values

public static final String WORKFLOW_NAME

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Constant Field Values

public static final String WORKFLOW_NODE_NAME

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Constant Field Values

public static final String WORKFLOW_ADJACENCY_PREFIX_STRING

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Constant Field Values

public static final String WORKFLOW_ADJACENCY_PREFIX_PATTERN

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Constant Field Values

public static final String WORKFLOW_TAGS

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Constant Field Values

public static final String MAPREDUCE_RECOVER_JOB

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Constant Field Values

public static final boolean DEFAULT_MAPREDUCE_RECOVER_JOB

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Constant Field Values

public JobConf()

Construct a map/reduce job configuration.

public JobConf(Class exampleClass)

Construct a map/reduce job configuration.

Parameters:

exampleClass - a class whose containing jar is used as the job's jar.

public JobConf(Configuration conf)

Construct a map/reduce job configuration.

Parameters:

conf - a Configuration whose settings will be inherited.

public JobConf(Configuration conf,
               Class exampleClass)

Construct a map/reduce job configuration.

Parameters:

conf - a Configuration whose settings will be inherited.

exampleClass - a class whose containing jar is used as the job's jar.

public JobConf(String config)

Construct a map/reduce configuration.

Parameters:

config - a Configuration-format XML job description file.

public JobConf(Path config)

Construct a map/reduce configuration.

Parameters:

config - a Configuration-format XML job description file.

public JobConf(boolean loadDefaults)

A new map/reduce configuration where the behavior of reading from the default resources can be turned off. If the parameter loadDefaults is false, the new instance will not load resources from the default files.

Parameters:

loadDefaults - specifies whether to load from the default files

public Credentials getCredentials()

Get credentials for the job.

Returns:

credentials for the job

public String getJar()

Get the user jar for the map-reduce job.

Returns:

the user jar for the map-reduce job.

public void setJar(String jar)

Set the user jar for the map-reduce job.

Parameters:

jar - the user jar for the map-reduce job.

public void setJarByClass(Class cls)

Set the job's jar file by finding an example class location.

Parameters:

cls - the example class.

public String[] getLocalDirs()
                      throws IOException

Throws:

IOException

public void deleteLocalFiles()
                      throws IOException

Throws:

IOException

public void deleteLocalFiles(String subdir)
                      throws IOException

Throws:

IOException

public Path getLocalPath(String pathString)
                  throws IOException

Constructs a local file name. Files are distributed among configured local directories.

Throws:

IOException

public String getUser()

Get the reported username for this job.

Returns:

the username

public void setUser(String user)

Set the reported username for this job.

Parameters:

user - the username for this job.

public void setKeepFailedTaskFiles(boolean keep)

Set whether the framework should keep the intermediate files for failed tasks.

Parameters:

keep - true if framework should keep the intermediate files for failed tasks, false otherwise.

public boolean getKeepFailedTaskFiles()

Should the temporary files for failed tasks be kept?

Returns:

should the files be kept?

public void setKeepTaskFilesPattern(String pattern)

Set a regular expression for task names that should be kept. The regular expression ".*_m_000123_0" would keep the files for the first instance of map 123 that ran.

Parameters:

pattern - the java.util.regex.Pattern to match against the task names.

public String getKeepTaskFilesPattern()

Get the regular expression that is matched against the task names to see if we need to keep the files.

Returns:

the pattern as a string, if it was set, othewise null.

public void setWorkingDirectory(Path dir)

Set the current working directory for the default file system.

Parameters:

dir - the new current working directory.

public Path getWorkingDirectory()

Get the current working directory for the default file system.

Returns:

the directory name.

public void setNumTasksToExecutePerJvm(int numTasks)

Sets the number of tasks that a spawned task JVM should run before it exits

Parameters:

numTasks - the number of tasks to execute; defaults to 1; -1 signifies no limit

public int getNumTasksToExecutePerJvm()

Get the number of tasks that a spawned JVM should execute

public InputFormat getInputFormat()

Get the InputFormat implementation for the map-reduce job, defaults to TextInputFormat if not specified explicity.

Returns:

the InputFormat implementation for the map-reduce job.

public void setInputFormat(Class<? extends InputFormat> theClass)

Set the InputFormat implementation for the map-reduce job.

Parameters:

theClass - the InputFormat implementation for the map-reduce job.

public OutputFormat getOutputFormat()

Get the OutputFormat implementation for the map-reduce job, defaults to TextOutputFormat if not specified explicity.

Returns:

the OutputFormat implementation for the map-reduce job.

public OutputCommitter getOutputCommitter()

Get the OutputCommitter implementation for the map-reduce job, defaults to FileOutputCommitter if not specified explicitly.

Returns:

the OutputCommitter implementation for the map-reduce job.

public void setOutputCommitter(Class<? extends OutputCommitter> theClass)

Set the OutputCommitter implementation for the map-reduce job.

Parameters:

theClass - the OutputCommitter implementation for the map-reduce job.

public void setOutputFormat(Class<? extends OutputFormat> theClass)

Set the OutputFormat implementation for the map-reduce job.

Parameters:

theClass - the OutputFormat implementation for the map-reduce job.

public void setCompressMapOutput(boolean compress)

Should the map outputs be compressed before transfer? Uses the SequenceFile compression.

Parameters:

compress - should the map outputs be compressed?

public boolean getCompressMapOutput()

Are the outputs of the maps be compressed?

Returns:

true if the outputs of the maps are to be compressed, false otherwise.

public void setMapOutputCompressorClass(Class<? extends CompressionCodec> codecClass)

Set the given class as the CompressionCodec for the map outputs.

Parameters:

codecClass - the CompressionCodec class that will compress the map outputs.

public Class<? extends CompressionCodec> getMapOutputCompressorClass(Class<? extends CompressionCodec> defaultValue)

Get the CompressionCodec for compressing the map outputs.

Parameters:

defaultValue - the CompressionCodec to return if not set

Returns:

the CompressionCodec class that should be used to compress the map outputs.

Throws:

IllegalArgumentException - if the class was specified, but not found

public Class<?> getMapOutputKeyClass()

Get the key class for the map output data. If it is not set, use the (final) output key class. This allows the map output key class to be different than the final output key class.

Returns:

the map output key class.

public void setMapOutputKeyClass(Class<?> theClass)

Set the key class for the map output data. This allows the user to specify the map output key class to be different than the final output value class.

Parameters:

theClass - the map output key class.

public Class<?> getMapOutputValueClass()

Get the value class for the map output data. If it is not set, use the (final) output value class This allows the map output value class to be different than the final output value class.

Returns:

the map output value class.

public void setMapOutputValueClass(Class<?> theClass)

Set the value class for the map output data. This allows the user to specify the map output value class to be different than the final output value class.

Parameters:

theClass - the map output value class.

public Class<?> getOutputKeyClass()

Get the key class for the job output data.

Returns:

the key class for the job output data.

public void setOutputKeyClass(Class<?> theClass)

Set the key class for the job output data.

Parameters:

theClass - the key class for the job output data.

public RawComparator getOutputKeyComparator()

Get the RawComparator comparator used to compare keys.

Returns:

the RawComparator comparator used to compare keys.

public void setOutputKeyComparatorClass(Class<? extends RawComparator> theClass)

Set the RawComparator comparator used to compare keys.

Parameters:

theClass - the RawComparator comparator used to compare keys.

See Also:

setOutputValueGroupingComparator(Class)

public void setKeyFieldComparatorOptions(String keySpec)

Set the KeyFieldBasedComparator options used to compare keys.

Parameters:

keySpec - the key specification of the form -k pos1[,pos2], where, pos is of the form f[.c][opts], where f is the number of the key field to use, and c is the number of the first character from the beginning of the field. Fields and character posns are numbered starting with 1; a character position of zero in pos2 indicates the field's last character. If '.c' is omitted from pos1, it defaults to 1 (the beginning of the field); if omitted from pos2, it defaults to 0 (the end of the field). opts are ordering options. The supported options are: -n, (Sort numerically) -r, (Reverse the result of comparison)

public String getKeyFieldComparatorOption()

Get the KeyFieldBasedComparator options

public void setKeyFieldPartitionerOptions(String keySpec)

Set the KeyFieldBasedPartitioner options used for Partitioner

Parameters:

keySpec - the key specification of the form -k pos1[,pos2], where, pos is of the form f[.c][opts], where f is the number of the key field to use, and c is the number of the first character from the beginning of the field. Fields and character posns are numbered starting with 1; a character position of zero in pos2 indicates the field's last character. If '.c' is omitted from pos1, it defaults to 1 (the beginning of the field); if omitted from pos2, it defaults to 0 (the end of the field).

public String getKeyFieldPartitionerOption()

Get the KeyFieldBasedPartitioner options

public RawComparator getOutputValueGroupingComparator()

Get the user defined WritableComparable comparator for grouping keys of inputs to the reduce.

Returns:

comparator set by the user for grouping values.

See Also:

for details.

public void setOutputValueGroupingComparator(Class<? extends RawComparator> theClass)

Set the user defined RawComparator comparator for grouping keys in the input to the reduce.

This comparator should be provided if the equivalence rules for keys for sorting the intermediates are different from those for grouping keys before each call to Reducer.reduce(Object, java.util.Iterator, OutputCollector, Reporter).

For key-value pairs (K1,V1) and (K2,V2), the values (V1, V2) are passed in a single call to the reduce function if K1 and K2 compare as equal.

Since setOutputKeyComparatorClass(Class) can be used to control how keys are sorted, this can be used in conjunction to simulate secondary sort on values.

Note: This is not a guarantee of the reduce sort being stable in any sense. (In any case, with the order of available map-outputs to the reduce being non-deterministic, it wouldn't make that much sense.)

Parameters:

theClass - the comparator class to be used for grouping keys. It should implement RawComparator.

See Also:

setOutputKeyComparatorClass(Class)

public boolean getUseNewMapper()

Should the framework use the new context-object code for running the mapper?

Returns:

true, if the new api should be used

public void setUseNewMapper(boolean flag)

Set whether the framework should use the new api for the mapper. This is the default for jobs submitted with the new Job api.

Parameters:

flag - true, if the new api should be used

public boolean getUseNewReducer()

Should the framework use the new context-object code for running the reducer?

Returns:

true, if the new api should be used

public void setUseNewReducer(boolean flag)

Set whether the framework should use the new api for the reducer. This is the default for jobs submitted with the new Job api.

Parameters:

flag - true, if the new api should be used

public Class<?> getOutputValueClass()

Get the value class for job outputs.

Returns:

the value class for job outputs.

public void setOutputValueClass(Class<?> theClass)

Set the value class for job outputs.

Parameters:

theClass - the value class for job outputs.

public Class<? extends Mapper> getMapperClass()

Get the Mapper class for the job.

Returns:

the Mapper class for the job.

public void setMapperClass(Class<? extends Mapper> theClass)

Set the Mapper class for the job.

Parameters:

theClass - the Mapper class for the job.

public Class<? extends MapRunnable> getMapRunnerClass()

Get the MapRunnable class for the job.

Returns:

the MapRunnable class for the job.

public void setMapRunnerClass(Class<? extends MapRunnable> theClass)

Expert: Set the MapRunnable class for the job. Typically used to exert greater control on Mappers.

Parameters:

theClass - the MapRunnable class for the job.

public Class<? extends Partitioner> getPartitionerClass()

Get the Partitioner used to partition Mapper-outputs to be sent to the Reducers.

Returns:

the Partitioner used to partition map-outputs.

public void setPartitionerClass(Class<? extends Partitioner> theClass)

Set the Partitioner class used to partition Mapper-outputs to be sent to the Reducers.

Parameters:

theClass - the Partitioner used to partition map-outputs.

public Class<? extends Reducer> getReducerClass()

Get the Reducer class for the job.

Returns:

the Reducer class for the job.

public void setReducerClass(Class<? extends Reducer> theClass)

Set the Reducer class for the job.

Parameters:

theClass - the Reducer class for the job.

public Class<? extends Reducer> getCombinerClass()

Get the user-defined combiner class used to combine map-outputs before being sent to the reducers. Typically the combiner is same as the the Reducer for the job i.e. getReducerClass().

Returns:

the user-defined combiner class used to combine map-outputs.

public void setCombinerClass(Class<? extends Reducer> theClass)

Set the user-defined combiner class used to combine map-outputs before being sent to the reducers.

The combiner is an application-specified aggregation operation, which can help cut down the amount of data transferred between the Mapper and the Reducer, leading to better performance.

The framework may invoke the combiner 0, 1, or multiple times, in both the mapper and reducer tasks. In general, the combiner is called as the sort/merge result is written to disk. The combiner must:

• be side-effect free
• have the same input and output key types and the same input and output value types

Typically the combiner is same as the Reducer for the job i.e. setReducerClass(Class).

Parameters:

theClass - the user-defined combiner class used to combine map-outputs.

public boolean getSpeculativeExecution()

Should speculative execution be used for this job? Defaults to true.

Returns:

true if speculative execution be used for this job, false otherwise.

public void setSpeculativeExecution(boolean speculativeExecution)

Turn speculative execution on or off for this job.

Parameters:

speculativeExecution - true if speculative execution should be turned on, else false.

public boolean getMapSpeculativeExecution()

Should speculative execution be used for this job for map tasks? Defaults to true.

Returns:

true if speculative execution be used for this job for map tasks, false otherwise.

public void setMapSpeculativeExecution(boolean speculativeExecution)

Turn speculative execution on or off for this job for map tasks.

Parameters:

speculativeExecution - true if speculative execution should be turned on for map tasks, else false.

public boolean getReduceSpeculativeExecution()

Should speculative execution be used for this job for reduce tasks? Defaults to true.

Returns:

true if speculative execution be used for reduce tasks for this job, false otherwise.

public void setReduceSpeculativeExecution(boolean speculativeExecution)

Turn speculative execution on or off for this job for reduce tasks.

Parameters:

speculativeExecution - true if speculative execution should be turned on for reduce tasks, else false.

public int getNumMapTasks()

Get configured the number of reduce tasks for this job. Defaults to 1.

Returns:

the number of reduce tasks for this job.

public void setNumMapTasks(int n)

Set the number of map tasks for this job.

Note: This is only a hint to the framework. The actual number of spawned map tasks depends on the number of InputSplits generated by the job's InputFormat.getSplits(JobConf, int). A custom InputFormat is typically used to accurately control the number of map tasks for the job.

How many maps?

The number of maps is usually driven by the total size of the inputs i.e. total number of blocks of the input files.

The right level of parallelism for maps seems to be around 10-100 maps per-node, although it has been set up to 300 or so for very cpu-light map tasks. Task setup takes awhile, so it is best if the maps take at least a minute to execute.

The default behavior of file-based InputFormats is to split the input into logical InputSplits based on the total size, in bytes, of input files. However, the FileSystem blocksize of the input files is treated as an upper bound for input splits. A lower bound on the split size can be set via mapred.min.split.size.

Thus, if you expect 10TB of input data and have a blocksize of 128MB, you'll end up with 82,000 maps, unless setNumMapTasks(int) is used to set it even higher.

Parameters:

n - the number of map tasks for this job.

See Also:

InputFormat.getSplits(JobConf, int), FileInputFormat, FileSystem.getDefaultBlockSize(), FileStatus.getBlockSize()

public int getNumReduceTasks()

Get configured the number of reduce tasks for this job. Defaults to 1.

Returns:

the number of reduce tasks for this job.

public void setNumReduceTasks(int n)

Set the requisite number of reduce tasks for this job. How many reduces?

The right number of reduces seems to be 0.95 or 1.75 multiplied by (<no. of nodes> * mapred.tasktracker.reduce.tasks.maximum).

With 0.95 all of the reduces can launch immediately and start transfering map outputs as the maps finish. With 1.75 the faster nodes will finish their first round of reduces and launch a second wave of reduces doing a much better job of load balancing.

Increasing the number of reduces increases the framework overhead, but increases load balancing and lowers the cost of failures.

The scaling factors above are slightly less than whole numbers to reserve a few reduce slots in the framework for speculative-tasks, failures etc.

Reducer NONE

It is legal to set the number of reduce-tasks to zero.

In this case the output of the map-tasks directly go to distributed file-system, to the path set by FileOutputFormat.setOutputPath(JobConf, Path). Also, the framework doesn't sort the map-outputs before writing it out to HDFS.

Parameters:

n - the number of reduce tasks for this job.

public int getMaxMapAttempts()

Get the configured number of maximum attempts that will be made to run a map task, as specified by the mapred.map.max.attempts property. If this property is not already set, the default is 4 attempts.

Returns:

the max number of attempts per map task.

public void setMaxMapAttempts(int n)

Expert: Set the number of maximum attempts that will be made to run a map task.

Parameters:

n - the number of attempts per map task.

public int getMaxReduceAttempts()

Get the configured number of maximum attempts that will be made to run a reduce task, as specified by the mapred.reduce.max.attempts property. If this property is not already set, the default is 4 attempts.

Returns:

the max number of attempts per reduce task.

public void setMaxReduceAttempts(int n)

Expert: Set the number of maximum attempts that will be made to run a reduce task.

Parameters:

n - the number of attempts per reduce task.

public String getJobName()

Get the user-specified job name. This is only used to identify the job to the user.

Returns:

the job's name, defaulting to "".

public void setJobName(String name)

Set the user-specified job name.

Parameters:

name - the job's new name.

public String getSessionId()

Get the user-specified session identifier. The default is the empty string. The session identifier is used to tag metric data that is reported to some performance metrics system via the org.apache.hadoop.metrics API. The session identifier is intended, in particular, for use by Hadoop-On-Demand (HOD) which allocates a virtual Hadoop cluster dynamically and transiently. HOD will set the session identifier by modifying the mapred-site.xml file before starting the cluster. When not running under HOD, this identifer is expected to remain set to the empty string.

Returns:

the session identifier, defaulting to "".

public void setSessionId(String sessionId)

Set the user-specified session identifier.

Parameters:

sessionId - the new session id.

public void setMaxTaskFailuresPerTracker(int noFailures)

Set the maximum no. of failures of a given job per tasktracker. If the no. of task failures exceeds noFailures, the tasktracker is blacklisted for this job.

Parameters:

noFailures - maximum no. of failures of a given job per tasktracker.

public int getMaxTaskFailuresPerTracker()

Expert: Get the maximum no. of failures of a given job per tasktracker. If the no. of task failures exceeds this, the tasktracker is blacklisted for this job.

Returns:

the maximum no. of failures of a given job per tasktracker.

public int getMaxMapTaskFailuresPercent()

Get the maximum percentage of map tasks that can fail without the job being aborted. Each map task is executed a minimum of getMaxMapAttempts() attempts before being declared as failed. Defaults to zero, i.e. any failed map-task results in the job being declared as JobStatus.FAILED.

Returns:

the maximum percentage of map tasks that can fail without the job being aborted.

public void setMaxMapTaskFailuresPercent(int percent)

Expert: Set the maximum percentage of map tasks that can fail without the job being aborted. Each map task is executed a minimum of getMaxMapAttempts() attempts before being declared as failed.

Parameters:

percent - the maximum percentage of map tasks that can fail without the job being aborted.

public int getMaxReduceTaskFailuresPercent()

Get the maximum percentage of reduce tasks that can fail without the job being aborted. Each reduce task is executed a minimum of getMaxReduceAttempts() attempts before being declared as failed. Defaults to zero, i.e. any failed reduce-task results in the job being declared as JobStatus.FAILED.

Returns:

the maximum percentage of reduce tasks that can fail without the job being aborted.

public void setMaxReduceTaskFailuresPercent(int percent)

Set the maximum percentage of reduce tasks that can fail without the job being aborted. Each reduce task is executed a minimum of getMaxReduceAttempts() attempts before being declared as failed.

Parameters:

percent - the maximum percentage of reduce tasks that can fail without the job being aborted.

public void setJobPriority(JobPriority prio)

Set JobPriority for this job.

Parameters:

prio - the JobPriority for this job.

public JobPriority getJobPriority()

Get the JobPriority for this job.

Returns:

the JobPriority for this job.

public boolean getProfileEnabled()

Get whether the task profiling is enabled.

Returns:

true if some tasks will be profiled

public void setProfileEnabled(boolean newValue)

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.

Parameters:

newValue - true means it should be gathered

public String getProfileParams()

Get the profiler configuration arguments. The default value for this property is "-agentlib:hprof=cpu=samples,heap=sites,force=n,thread=y,verbose=n,file=%s"

Returns:

the parameters to pass to the task child to configure profiling

public void setProfileParams(String value)

Set the profiler configuration arguments. If the string contains a '%s' it will be replaced with the name of the profiling output file when the task runs. This value is passed to the task child JVM on the command line.

Parameters:

value - the configuration string

public Configuration.IntegerRanges getProfileTaskRange(boolean isMap)

Get the range of maps or reduces to profile.

Parameters:

isMap - is the task a map?

Returns:

the task ranges

public void setProfileTaskRange(boolean isMap,
                                String newValue)

Set the ranges of maps or reduces to profile. setProfileEnabled(true) must also be called.

Parameters:

newValue - a set of integer ranges of the map ids

public void setMapDebugScript(String mDbgScript)

Set the debug script to run when the map tasks fail.

The debug script can aid debugging of failed map tasks. The script is given task's stdout, stderr, syslog, jobconf files as arguments.

The debug command, run on the node where the map failed, is:

 
 $script $stdout $stderr $syslog $jobconf.
 

The script file is distributed through DistributedCache APIs. The script needs to be symlinked.

Here is an example on how to submit a script

 job.setMapDebugScript("./myscript");
 DistributedCache.createSymlink(job);
 DistributedCache.addCacheFile("/debug/scripts/myscript#myscript");
 

Parameters:

mDbgScript - the script name

public String getMapDebugScript()

Get the map task's debug script.

Returns:

the debug Script for the mapred job for failed map tasks.

See Also:

setMapDebugScript(String)

public void setReduceDebugScript(String rDbgScript)

Set the debug script to run when the reduce tasks fail.

The debug script can aid debugging of failed reduce tasks. The script is given task's stdout, stderr, syslog, jobconf files as arguments.

The debug command, run on the node where the map failed, is:

 
 $script $stdout $stderr $syslog $jobconf.
 

The script file is distributed through DistributedCache APIs. The script file needs to be symlinked

Here is an example on how to submit a script

 job.setReduceDebugScript("./myscript");
 DistributedCache.createSymlink(job);
 DistributedCache.addCacheFile("/debug/scripts/myscript#myscript");
 

Parameters:

rDbgScript - the script name

public String getReduceDebugScript()

Get the reduce task's debug Script

Returns:

the debug script for the mapred job for failed reduce tasks.

See Also:

setReduceDebugScript(String)

public String getJobEndNotificationURI()

Get the uri to be invoked in-order to send a notification after the job has completed (success/failure).

Returns:

the job end notification uri, null if it hasn't been set.

See Also:

setJobEndNotificationURI(String)

public void setJobEndNotificationURI(String uri)

Set the uri to be invoked in-order to send a notification after the job has completed (success/failure).

The uri can contain 2 special parameters: $jobId and $jobStatus. Those, if present, are replaced by the job's identifier and completion-status respectively.

This is typically used by application-writers to implement chaining of Map-Reduce jobs in an asynchronous manner.

Parameters:

uri - the job end notification uri

See Also:

JobStatus, Job Completion and Chaining

public String getJobLocalDir()

Get job-specific shared directory for use as scratch space

When a job starts, a shared directory is created at location ${mapred.local.dir}/taskTracker/$user/jobcache/$jobid/work/ . This directory is exposed to the users through job.local.dir . So, the tasks can use this space as scratch space and share files among them.

This value is available as System property also.

Returns:

The localized job specific shared directory

public long getMemoryForMapTask()

Get memory required to run a map task of the job, in MB. If a value is specified in the configuration, it is returned. Else, it returns DISABLED_MEMORY_LIMIT. For backward compatibility, if the job configuration sets the key MAPRED_TASK_MAXVMEM_PROPERTY to a value different from DISABLED_MEMORY_LIMIT, that value will be used after converting it from bytes to MB.

Returns:

memory required to run a map task of the job, in MB, or DISABLED_MEMORY_LIMIT if unset.

public void setMemoryForMapTask(long mem)

public long getMemoryForReduceTask()

Get memory required to run a reduce task of the job, in MB. If a value is specified in the configuration, it is returned. Else, it returns DISABLED_MEMORY_LIMIT. For backward compatibility, if the job configuration sets the key MAPRED_TASK_MAXVMEM_PROPERTY to a value different from DISABLED_MEMORY_LIMIT, that value will be used after converting it from bytes to MB.

Returns:

memory required to run a reduce task of the job, in MB, or DISABLED_MEMORY_LIMIT if unset.

public void setMemoryForReduceTask(long mem)

public String getQueueName()

Return the name of the queue to which this job is submitted. Defaults to 'default'.

Returns:

name of the queue

public void setQueueName(String queueName)

Set the name of the queue to which this job should be submitted.

Parameters:

queueName - Name of the queue

public static long normalizeMemoryConfigValue(long val)

Normalize the negative values in configuration

Parameters:

val -

Returns:

normalized value

@Deprecated
public long getMaxVirtualMemoryForTask()

Deprecated. Use getMemoryForMapTask() and getMemoryForReduceTask()

Get the memory required to run a task of this job, in bytes. See MAPRED_TASK_MAXVMEM_PROPERTY This method is deprecated. Now, different memory limits can be set for map and reduce tasks of a job, in MB. For backward compatibility, if the job configuration sets the key MAPRED_TASK_MAXVMEM_PROPERTY to a value different from DISABLED_MEMORY_LIMIT, that value is returned. Otherwise, this method will return the larger of the values returned by getMemoryForMapTask() and getMemoryForReduceTask() after converting them into bytes.

Returns:

Memory required to run a task of this job, in bytes, or DISABLED_MEMORY_LIMIT, if unset.

See Also:

setMaxVirtualMemoryForTask(long)

@Deprecated
public void setMaxVirtualMemoryForTask(long vmem)

Deprecated. Use setMemoryForMapTask(long mem) and Use setMemoryForReduceTask(long mem)

Set the maximum amount of memory any task of this job can use. See MAPRED_TASK_MAXVMEM_PROPERTY mapred.task.maxvmem is split into mapred.job.map.memory.mb and mapred.job.map.memory.mb,mapred each of the new key are set as mapred.task.maxvmem / 1024 as new values are in MB

Parameters:

vmem - Maximum amount of virtual memory in bytes any task of this job can use.

See Also:

getMaxVirtualMemoryForTask()

@Deprecated
public long getMaxPhysicalMemoryForTask()

Deprecated. this variable is deprecated and nolonger in use.

@Deprecated
public void setMaxPhysicalMemoryForTask(long mem)

Deprecated. 

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