## Uses of Class
org.apache.hadoop.mapred.JobConf

Packages that use JobConf
org.apache.hadoop.contrib.index.example
org.apache.hadoop.contrib.index.mapred
org.apache.hadoop.contrib.utils.join
org.apache.hadoop.examples: Hadoop example code.
org.apache.hadoop.examples.dancing: This package is a distributed implementation of Knuth's dancing links algorithm that can run under Hadoop.
org.apache.hadoop.examples.terasort: This package consists of 3 map/reduce applications for Hadoop to compete in the annual terabyte sort competition.
org.apache.hadoop.mapred: A software framework for easily writing applications which process vast amounts of data (multi-terabyte data-sets) parallelly on large clusters (thousands of nodes) built of commodity hardware in a reliable, fault-tolerant manner.
org.apache.hadoop.mapred.jobcontrol: Utilities for managing dependent jobs.
org.apache.hadoop.mapred.join: Given a set of sorted datasets keyed with the same class and yielding equal partitions, it is possible to effect a join of those datasets prior to the map.
org.apache.hadoop.mapred.lib: Library of generally useful mappers, reducers, and partitioners.
org.apache.hadoop.mapred.lib.aggregate: Classes for performing various counting and aggregations.
org.apache.hadoop.mapred.lib.db: org.apache.hadoop.mapred.lib.db Package
org.apache.hadoop.mapred.pipes: Hadoop Pipes allows C++ code to use Hadoop DFS and map/reduce.
org.apache.hadoop.mapreduce
org.apache.hadoop.streaming: `Hadoop Streaming` is a utility which allows users to create and run Map-Reduce jobs with any executables (e.g.

Uses of JobConf in org.apache.hadoop.contrib.index.example

Methods in org.apache.hadoop.contrib.index.example with parameters of type JobConf
`void` `IdentityLocalAnalysis.configure(JobConf job)`
`void` `LineDocLocalAnalysis.configure(JobConf job)`
`RecordReader<DocumentID,LineDocTextAndOp>` `LineDocInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)`

Uses of JobConf in org.apache.hadoop.contrib.index.mapred

Methods in org.apache.hadoop.contrib.index.mapred with parameters of type JobConf
`void` `IndexUpdateMapper.configure(JobConf job)`
`void` `IndexUpdateReducer.configure(JobConf job)`
`void` `IndexUpdatePartitioner.configure(JobConf job)`
`void` `IndexUpdateCombiner.configure(JobConf job)`
`RecordWriter<Shard,Text>` `IndexUpdateOutputFormat.getRecordWriter(FileSystem fs, JobConf job, String name, Progressable progress)`

Uses of JobConf in org.apache.hadoop.contrib.utils.join

Fields in org.apache.hadoop.contrib.utils.join declared as JobConf
`protected JobConf` `DataJoinMapperBase.job`
`protected JobConf` `DataJoinReducerBase.job`

Methods in org.apache.hadoop.contrib.utils.join that return JobConf
`static JobConf` `DataJoinJob.createDataJoinJob(String[] args)`

Methods in org.apache.hadoop.contrib.utils.join with parameters of type JobConf
`TaggedMapOutput` `TaggedMapOutput.clone(JobConf job)`
`void` `DataJoinMapperBase.configure(JobConf job)`
`void` `JobBase.configure(JobConf job)` Initializes a new instance from a `JobConf`.
`void` `DataJoinReducerBase.configure(JobConf job)`
`static boolean` `DataJoinJob.runJob(JobConf job)` Submit/run a map/reduce job.

Uses of JobConf in org.apache.hadoop.examples

Methods in org.apache.hadoop.examples that return JobConf
`JobConf` `SleepJob.setupJobConf(int numMapper, int numReducer, long mapSleepTime, int mapSleepCount, long reduceSleepTime, int reduceSleepCount)`

Methods in org.apache.hadoop.examples with parameters of type JobConf
`void` `SleepJob.configure(JobConf job)`
`void` `PiEstimator.PiReducer.configure(JobConf job)` Store job configuration.
`static BigDecimal` `PiEstimator.estimate(int numMaps, long numPoints, JobConf jobConf)` Run a map/reduce job for estimating Pi.
`RecordReader<IntWritable,IntWritable>` `SleepJob.SleepInputFormat.getRecordReader(InputSplit ignored, JobConf conf, Reporter reporter)`
`RecordReader<MultiFileWordCount.WordOffset,Text>` `MultiFileWordCount.MyInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)`
`InputSplit[]` `SleepJob.SleepInputFormat.getSplits(JobConf conf, int numSplits)`

Uses of JobConf in org.apache.hadoop.examples.dancing

Methods in org.apache.hadoop.examples.dancing with parameters of type JobConf
`void` `DistributedPentomino.PentMap.configure(JobConf conf)`

Uses of JobConf in org.apache.hadoop.examples.terasort

Methods in org.apache.hadoop.examples.terasort with parameters of type JobConf
`static boolean` `TeraOutputFormat.getFinalSync(JobConf conf)` Does the user want a final sync at close?
`RecordReader<Text,Text>` `TeraInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)`
`RecordWriter<Text,Text>` `TeraOutputFormat.getRecordWriter(FileSystem ignored, JobConf job, String name, Progressable progress)`
`InputSplit[]` `TeraInputFormat.getSplits(JobConf conf, int splits)`
`static void` `TeraOutputFormat.setFinalSync(JobConf conf, boolean newValue)` Set the requirement for a final sync before the stream is closed.
`static void` `TeraInputFormat.writePartitionFile(JobConf conf, Path partFile)` Use the input splits to take samples of the input and generate sample keys.

Uses of JobConf in org.apache.hadoop.mapred

Fields in org.apache.hadoop.mapred declared as JobConf
`protected JobConf` `Task.conf`
`protected JobConf` `Task.CombinerRunner.job`

Methods in org.apache.hadoop.mapred that return JobConf
`JobConf` `JobTracker.getConf()` Returns a handle to the JobTracker's Configuration
`JobConf` `TaskAttemptContext.getJobConf()`
`JobConf` `JobContext.getJobConf()` Get the job Configuration

Methods in org.apache.hadoop.mapred with parameters of type JobConf
`static void` `FileInputFormat.addInputPath(JobConf conf, Path path)` Add a `Path` to the list of inputs for the map-reduce job.
`static void` `FileInputFormat.addInputPaths(JobConf conf, String commaSeparatedPaths)` Add the given comma separated paths to the list of inputs for the map-reduce job.
`void` `OutputFormat.checkOutputSpecs(FileSystem ignored, JobConf job)` Check for validity of the output-specification for the job.
`void` `FileOutputFormat.checkOutputSpecs(FileSystem ignored, JobConf job)`
`void` `SequenceFileAsBinaryOutputFormat.checkOutputSpecs(FileSystem ignored, JobConf job)`
`void` `JobConfigurable.configure(JobConf job)` Initializes a new instance from a `JobConf`.
`void` `TextInputFormat.configure(JobConf conf)`
`void` `MapReduceBase.configure(JobConf job)` Default implementation that does nothing.
`void` `MapRunner.configure(JobConf job)`
`void` `KeyValueTextInputFormat.configure(JobConf conf)`
`void` `JobLocalizer.createWorkDir(JobConf jConf)`
`static boolean` `FileOutputFormat.getCompressOutput(JobConf conf)` Is the job output compressed?
`static PathFilter` `FileInputFormat.getInputPathFilter(JobConf conf)` Get a PathFilter instance of the filter set for the input paths.
`static Path[]` `FileInputFormat.getInputPaths(JobConf conf)` Get the list of input `Path`s for the map-reduce job.
`static String` `JobHistory.JobInfo.getJobHistoryFileName(JobConf jobConf, JobID id)` Recover the job history filename from the history folder.
`static Path` `JobHistory.JobInfo.getJobHistoryLogLocationForUser(String logFileName, JobConf jobConf)` Get the user job history file path
`static SequenceFile.CompressionType` `SequenceFileOutputFormat.getOutputCompressionType(JobConf conf)` Get the `SequenceFile.CompressionType` for the output `SequenceFile`.
`static Class<? extends CompressionCodec>` `FileOutputFormat.getOutputCompressorClass(JobConf conf, Class<? extends CompressionCodec> defaultValue)` Get the `CompressionCodec` for compressing the job outputs.
`static Path` `FileOutputFormat.getOutputPath(JobConf conf)` Get the `Path` to the output directory for the map-reduce job.
`static Path` `FileOutputFormat.getPathForCustomFile(JobConf conf, String name)` Helper function to generate a `Path` for a file that is unique for the task within the job output directory.
`RecordReader<K,V>` `SequenceFileInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)`
`RecordReader<LongWritable,Text>` `TextInputFormat.getRecordReader(InputSplit genericSplit, JobConf job, Reporter reporter)`
`RecordReader<K,V>` `SequenceFileInputFilter.getRecordReader(InputSplit split, JobConf job, Reporter reporter)` Create a record reader for the given split
`abstract RecordReader<K,V>` `MultiFileInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)` Deprecated.
`RecordReader<BytesWritable,BytesWritable>` `SequenceFileAsBinaryInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)`
`RecordReader<K,V>` `InputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)` Get the `RecordReader` for the given `InputSplit`.
`RecordReader<Text,Text>` `KeyValueTextInputFormat.getRecordReader(InputSplit genericSplit, JobConf job, Reporter reporter)`
`abstract RecordReader<K,V>` `FileInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)`
`RecordReader<Text,Text>` `SequenceFileAsTextInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)`
`RecordWriter<K,V>` `OutputFormat.getRecordWriter(FileSystem ignored, JobConf job, String name, Progressable progress)` Get the `RecordWriter` for the given job.
`abstract RecordWriter<K,V>` `FileOutputFormat.getRecordWriter(FileSystem ignored, JobConf job, String name, Progressable progress)`
`RecordWriter<BytesWritable,BytesWritable>` `SequenceFileAsBinaryOutputFormat.getRecordWriter(FileSystem ignored, JobConf job, String name, Progressable progress)`
`RecordWriter<K,V>` `SequenceFileOutputFormat.getRecordWriter(FileSystem ignored, JobConf job, String name, Progressable progress)`
`RecordWriter<WritableComparable,Writable>` `MapFileOutputFormat.getRecordWriter(FileSystem ignored, JobConf job, String name, Progressable progress)`
`RecordWriter<K,V>` `TextOutputFormat.getRecordWriter(FileSystem ignored, JobConf job, String name, Progressable progress)`
`String` `TaskController.getRunAsUser(JobConf conf)` Returns the local unix user that a given job will run as.
`static Class<? extends WritableComparable>` `SequenceFileAsBinaryOutputFormat.getSequenceFileOutputKeyClass(JobConf conf)` Get the key class for the `SequenceFile`
`static Class<? extends Writable>` `SequenceFileAsBinaryOutputFormat.getSequenceFileOutputValueClass(JobConf conf)` Get the value class for the `SequenceFile`
`InputSplit[]` `MultiFileInputFormat.getSplits(JobConf job, int numSplits)` Deprecated.
`InputSplit[]` `InputFormat.getSplits(JobConf job, int numSplits)` Logically split the set of input files for the job.
`InputSplit[]` `FileInputFormat.getSplits(JobConf job, int numSplits)` Splits files returned by `FileInputFormat.listStatus(JobConf)` when they're too big.
`static long` `TaskLog.getTaskLogLength(JobConf conf)` Get the desired maximum length of task's logs.
`static JobClient.TaskStatusFilter` `JobClient.getTaskOutputFilter(JobConf job)` Get the task output filter out of the JobConf.
`static Path` `FileOutputFormat.getTaskOutputPath(JobConf conf, String name)` Helper function to create the task's temporary output directory and return the path to the task's output file.
`static String` `FileOutputFormat.getUniqueName(JobConf conf, String name)` Helper function to generate a name that is unique for the task.
`static String` `JobHistory.JobInfo.getUserName(JobConf jobConf)` Get the user name from the job conf

`static Path`

`FileOutputFormat.getWorkOutputPath(JobConf conf)`
Get the `Path` to the task's temporary output directory for the map-reduce job

#### Tasks' Side-Effect Files

`void` `JobClient.init(JobConf conf)` Connect to the default `JobTracker`.
`static void` `JobHistory.init(JobTracker jobTracker, JobConf conf, String hostname, long jobTrackerStartTime)` Initialize JobHistory files.
`void` `Task.initialize(JobConf job, JobID id, Reporter reporter, boolean useNewApi)`
`protected void` `TaskTracker.launchTaskForJob(org.apache.hadoop.mapred.TaskTracker.TaskInProgress tip, JobConf jobConf, org.apache.hadoop.mapred.TaskTracker.RunningJob rjob)`
`protected FileStatus[]` `SequenceFileInputFormat.listStatus(JobConf job)`
`protected FileStatus[]` `FileInputFormat.listStatus(JobConf job)` List input directories.
`void` `Task.localizeConfiguration(JobConf conf)` Localize the given JobConf to be specific for this task.
`void` `JobLocalizer.localizeJobFiles(JobID jobid, JobConf jConf, Path localJobFile, Path localJobTokenFile, TaskUmbilicalProtocol taskTracker)`
`void` `JobLocalizer.localizeJobFiles(JobID jobid, JobConf jConf, Path localJobTokenFile, TaskUmbilicalProtocol taskTracker)`
`static void` `JobEndNotifier.localRunnerNotification(JobConf conf, JobStatus status)`
`static void` `JobHistory.JobInfo.logSubmitted(JobID jobId, JobConf jobConf, String jobConfPath, long submitTime)` Deprecated. Use `JobHistory.JobInfo.logSubmitted(JobID, JobConf, String, long, boolean)` instead.
`static void` `JobHistory.JobInfo.logSubmitted(JobID jobId, JobConf jobConf, String jobConfPath, long submitTime, boolean restarted)`
`boolean` `JobClient.monitorAndPrintJob(JobConf conf, RunningJob job)` Monitor a job and print status in real-time as progress is made and tasks fail.
`static Path` `JobHistory.JobInfo.recoverJobHistoryFile(JobConf conf, Path logFilePath)` Selects one of the two files generated as a part of recovery.
`static void` `JobEndNotifier.registerNotification(JobConf jobConf, JobStatus status)`
`abstract void` `Task.run(JobConf job, TaskUmbilicalProtocol umbilical)` Run this task as a part of the named job.
`static RunningJob` `JobClient.runJob(JobConf job)` Utility that submits a job, then polls for progress until the job is complete.
`static void` `FileOutputFormat.setCompressOutput(JobConf conf, boolean compress)` Set whether the output of the job is compressed.
`static void` `FileInputFormat.setInputPathFilter(JobConf conf, Class<? extends PathFilter> filter)` Set a PathFilter to be applied to the input paths for the map-reduce job.
`static void` `FileInputFormat.setInputPaths(JobConf conf, Path... inputPaths)` Set the array of `Path`s as the list of inputs for the map-reduce job.
`static void` `FileInputFormat.setInputPaths(JobConf conf, String commaSeparatedPaths)` Sets the given comma separated paths as the list of inputs for the map-reduce job.
`static void` `SequenceFileOutputFormat.setOutputCompressionType(JobConf conf, SequenceFile.CompressionType style)` Set the `SequenceFile.CompressionType` for the output `SequenceFile`.
`static void` `FileOutputFormat.setOutputCompressorClass(JobConf conf, Class<? extends CompressionCodec> codecClass)` Set the `CompressionCodec` to be used to compress job outputs.
`static void` `FileOutputFormat.setOutputPath(JobConf conf, Path outputDir)` Set the `Path` of the output directory for the map-reduce job.
`static void` `SequenceFileAsBinaryOutputFormat.setSequenceFileOutputKeyClass(JobConf conf, Class<?> theClass)` Set the key class for the `SequenceFile`
`static void` `SequenceFileAsBinaryOutputFormat.setSequenceFileOutputValueClass(JobConf conf, Class<?> theClass)` Set the value class for the `SequenceFile`
`static void` `SkipBadRecords.setSkipOutputPath(JobConf conf, Path path)` Set the directory to which skipped records are written.
`static void` `JobClient.setTaskOutputFilter(JobConf job, JobClient.TaskStatusFilter newValue)` Modify the JobConf to set the task output filter.
`static JobTracker` `JobTracker.startTracker(JobConf conf)` Start the JobTracker with given configuration.
`static JobTracker` `JobTracker.startTracker(JobConf conf, String identifier)`
`RunningJob` `JobClient.submitJob(JobConf job)` Submit a job to the MR system.
`RunningJob` `JobClient.submitJobInternal(JobConf job)` Internal method for submitting jobs to the system.
`protected boolean` `Task.supportIsolationRunner(JobConf conf)`
`static void` `JobLocalizer.writeLocalJobFile(Path jobFile, JobConf conf)` Write the task specific job-configuration file.

Constructors in org.apache.hadoop.mapred with parameters of type JobConf
`FileSplit(Path file, long start, long length, JobConf conf)` Deprecated.
`JobClient(JobConf conf)` Build a job client with the given `JobConf`, and connect to the default `JobTracker`.
`JobHistoryServer(JobConf conf)` Starts job history server as a independent process * Initializes ACL Manager * Starts a webapp to service history requests
`JobHistoryServer(JobConf conf, org.apache.hadoop.mapred.ACLsManager aclsManager, HttpServer httpServer)` Starts job history server as a embedded server within job tracker * Starts a webapp to service history requests
`JobInProgress(JobID jobid, JobConf conf, JobTracker tracker)` Create an almost empty JobInProgress, which can be used only for tests
`JobLocalizer(JobConf ttConf, String user, String jobid)`
`JobLocalizer(JobConf ttConf, String user, String jobid, String... localDirs)`
`MultiFileSplit(JobConf job, Path[] files, long[] lengths)` Deprecated.
`Task.OldCombinerRunner(Class<? extends Reducer<K,V,K,V>> cls, JobConf conf, Counters.Counter inputCounter, Task.TaskReporter reporter)`
`TaskTracker(JobConf conf)` Start with the local machine name, and the default JobTracker

Uses of JobConf in org.apache.hadoop.mapred.jobcontrol

Methods in org.apache.hadoop.mapred.jobcontrol that return JobConf
`JobConf` `Job.getJobConf()`

Methods in org.apache.hadoop.mapred.jobcontrol with parameters of type JobConf
`void` `Job.setJobConf(JobConf jobConf)` Set the mapred job conf for this job.

Constructors in org.apache.hadoop.mapred.jobcontrol with parameters of type JobConf
`Job(JobConf jobConf)` Construct a job.
`Job(JobConf jobConf, ArrayList<Job> dependingJobs)` Construct a job.

Uses of JobConf in org.apache.hadoop.mapred.join

Methods in org.apache.hadoop.mapred.join with parameters of type JobConf
`ComposableRecordReader<K,V>` `ComposableInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)`
`ComposableRecordReader<K,TupleWritable>` `CompositeInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)` Construct a CompositeRecordReader for the children of this InputFormat as defined in the init expression.
`InputSplit[]` `CompositeInputFormat.getSplits(JobConf job, int numSplits)` Build a CompositeInputSplit from the child InputFormats by assigning the ith split from each child to the ith composite split.
`void` `CompositeInputFormat.setFormat(JobConf job)` Interpret a given string as a composite expression.

Constructors in org.apache.hadoop.mapred.join with parameters of type JobConf
`JoinRecordReader(int id, JobConf conf, int capacity, Class<? extends WritableComparator> cmpcl)`
`MultiFilterRecordReader(int id, JobConf conf, int capacity, Class<? extends WritableComparator> cmpcl)`

Uses of JobConf in org.apache.hadoop.mapred.lib

Fields in org.apache.hadoop.mapred.lib declared as JobConf
`protected JobConf` `CombineFileRecordReader.jc`

Methods in org.apache.hadoop.mapred.lib that return JobConf
`JobConf` `CombineFileSplit.getJob()`

Methods in org.apache.hadoop.mapred.lib with parameters of type JobConf
`static void` `MultipleInputs.addInputPath(JobConf conf, Path path, Class<? extends InputFormat> inputFormatClass)` Add a `Path` with a custom `InputFormat` to the list of inputs for the map-reduce job.
`static void` `MultipleInputs.addInputPath(JobConf conf, Path path, Class<? extends InputFormat> inputFormatClass, Class<? extends Mapper> mapperClass)` Add a `Path` with a custom `InputFormat` and `Mapper` to the list of inputs for the map-reduce job.

`static

`<K1,V1,K2,V2> void`

`

`ChainReducer.addMapper(JobConf job, Class<? extends Mapper<K1,V1,K2,V2>> klass, Class<? extends K1> inputKeyClass, Class<? extends V1> inputValueClass, Class<? extends K2> outputKeyClass, Class<? extends V2> outputValueClass, boolean byValue, JobConf mapperConf)`
Adds a Mapper class to the chain job's JobConf.

`static

`<K1,V1,K2,V2> void`

`

`ChainMapper.addMapper(JobConf job, Class<? extends Mapper<K1,V1,K2,V2>> klass, Class<? extends K1> inputKeyClass, Class<? extends V1> inputValueClass, Class<? extends K2> outputKeyClass, Class<? extends V2> outputValueClass, boolean byValue, JobConf mapperConf)`
Adds a Mapper class to the chain job's JobConf.

`static void` `MultipleOutputs.addMultiNamedOutput(JobConf conf, String namedOutput, Class<? extends OutputFormat> outputFormatClass, Class<?> keyClass, Class<?> valueClass)` Adds a multi named output for the job.
`static void` `MultipleOutputs.addNamedOutput(JobConf conf, String namedOutput, Class<? extends OutputFormat> outputFormatClass, Class<?> keyClass, Class<?> valueClass)` Adds a named output for the job.
`void` `NullOutputFormat.checkOutputSpecs(FileSystem ignored, JobConf job)`
`void` `KeyFieldBasedComparator.configure(JobConf job)`
`void` `HashPartitioner.configure(JobConf job)`
`void` `RegexMapper.configure(JobConf job)`
`void` `NLineInputFormat.configure(JobConf conf)`
`void` `DelegatingMapper.configure(JobConf conf)`
`void` `ChainReducer.configure(JobConf job)` Configures the ChainReducer, the Reducer and all the Mappers in the chain.
`void` `TotalOrderPartitioner.configure(JobConf job)` Read in the partition file and build indexing data structures.
`void` `ChainMapper.configure(JobConf job)` Configures the ChainMapper and all the Mappers in the chain.
`void` `MultithreadedMapRunner.configure(JobConf jobConf)`
`void` `FieldSelectionMapReduce.configure(JobConf job)`
`void` `KeyFieldBasedPartitioner.configure(JobConf job)`
`protected void` `CombineFileInputFormat.createPool(JobConf conf, List<PathFilter> filters)` Create a new pool and add the filters to it.
`protected void` `CombineFileInputFormat.createPool(JobConf conf, PathFilter... filters)` Create a new pool and add the filters to it.
`protected RecordWriter<K,V>` `MultipleTextOutputFormat.getBaseRecordWriter(FileSystem fs, JobConf job, String name, Progressable arg3)`
`protected RecordWriter<K,V>` `MultipleSequenceFileOutputFormat.getBaseRecordWriter(FileSystem fs, JobConf job, String name, Progressable arg3)`
`protected abstract RecordWriter<K,V>` `MultipleOutputFormat.getBaseRecordWriter(FileSystem fs, JobConf job, String name, Progressable arg3)`
`static boolean` `MultipleOutputs.getCountersEnabled(JobConf conf)` Returns if the counters for the named outputs are enabled or not.
`protected String` `MultipleOutputFormat.getInputFileBasedOutputFileName(JobConf job, String name)` Generate the outfile name based on a given anme and the input file name.
`static Class<? extends OutputFormat>` `MultipleOutputs.getNamedOutputFormatClass(JobConf conf, String namedOutput)` Returns the named output OutputFormat.
`static Class<? extends WritableComparable>` `MultipleOutputs.getNamedOutputKeyClass(JobConf conf, String namedOutput)` Returns the key class for a named output.
`static List<String>` `MultipleOutputs.getNamedOutputsList(JobConf conf)` Returns list of channel names.
`static Class<? extends Writable>` `MultipleOutputs.getNamedOutputValueClass(JobConf conf, String namedOutput)` Returns the value class for a named output.
`static String` `TotalOrderPartitioner.getPartitionFile(JobConf job)` Get the path to the SequenceFile storing the sorted partition keyset.
`RecordReader<LongWritable,Text>` `NLineInputFormat.getRecordReader(InputSplit genericSplit, JobConf job, Reporter reporter)`
`abstract RecordReader<K,V>` `CombineFileInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)` This is not implemented yet.
`RecordReader<K,V>` `DelegatingInputFormat.getRecordReader(InputSplit split, JobConf conf, Reporter reporter)`
`RecordWriter<K,V>` `NullOutputFormat.getRecordWriter(FileSystem ignored, JobConf job, String name, Progressable progress)`
`RecordWriter<K,V>` `MultipleOutputFormat.getRecordWriter(FileSystem fs, JobConf job, String name, Progressable arg3)` Create a composite record writer that can write key/value data to different output files
`K[]` `InputSampler.Sampler.getSample(InputFormat<K,V> inf, JobConf job)` For a given job, collect and return a subset of the keys from the input data.
`K[]` `InputSampler.SplitSampler.getSample(InputFormat<K,V> inf, JobConf job)` From each split sampled, take the first numSamples / numSplits records.
`K[]` `InputSampler.RandomSampler.getSample(InputFormat<K,V> inf, JobConf job)` Randomize the split order, then take the specified number of keys from each split sampled, where each key is selected with the specified probability and possibly replaced by a subsequently selected key when the quota of keys from that split is satisfied.
`K[]` `InputSampler.IntervalSampler.getSample(InputFormat<K,V> inf, JobConf job)` For each split sampled, emit when the ratio of the number of records retained to the total record count is less than the specified frequency.
`InputSplit[]` `NLineInputFormat.getSplits(JobConf job, int numSplits)` Logically splits the set of input files for the job, splits N lines of the input as one split.
`InputSplit[]` `CombineFileInputFormat.getSplits(JobConf job, int numSplits)`
`InputSplit[]` `DelegatingInputFormat.getSplits(JobConf conf, int numSplits)`
`static boolean` `MultipleOutputs.isMultiNamedOutput(JobConf conf, String namedOutput)` Returns if a named output is multiple.
`static void` `MultipleOutputs.setCountersEnabled(JobConf conf, boolean enabled)` Enables or disables counters for the named outputs.
`static void` `TotalOrderPartitioner.setPartitionFile(JobConf job, Path p)` Set the path to the SequenceFile storing the sorted partition keyset.

`static

`<K1,V1,K2,V2> void`

`

`ChainReducer.setReducer(JobConf job, Class<? extends Reducer<K1,V1,K2,V2>> klass, Class<? extends K1> inputKeyClass, Class<? extends V1> inputValueClass, Class<? extends K2> outputKeyClass, Class<? extends V2> outputValueClass, boolean byValue, JobConf reducerConf)`
Sets the Reducer class to the chain job's JobConf.

`static

`<K,V> void`

`

`InputSampler.writePartitionFile(JobConf job, InputSampler.Sampler<K,V> sampler)`
Write a partition file for the given job, using the Sampler provided.

Constructors in org.apache.hadoop.mapred.lib with parameters of type JobConf
`CombineFileRecordReader(JobConf job, CombineFileSplit split, Reporter reporter, Class<RecordReader<K,V>> rrClass)` A generic RecordReader that can hand out different recordReaders for each chunk in the CombineFileSplit.
`CombineFileSplit(JobConf job, Path[] files, long[] lengths)`
`CombineFileSplit(JobConf job, Path[] files, long[] start, long[] lengths, String[] locations)`
`InputSampler(JobConf conf)`
`MultipleOutputs(JobConf job)` Creates and initializes multiple named outputs support, it should be instantiated in the Mapper/Reducer configure method.

Uses of JobConf in org.apache.hadoop.mapred.lib.aggregate

Methods in org.apache.hadoop.mapred.lib.aggregate that return JobConf
`static JobConf` `ValueAggregatorJob.createValueAggregatorJob(String[] args)` Create an Aggregate based map/reduce job.
`static JobConf` `ValueAggregatorJob.createValueAggregatorJob(String[] args, Class<? extends ValueAggregatorDescriptor>[] descriptors)`

Methods in org.apache.hadoop.mapred.lib.aggregate with parameters of type JobConf
`void` `ValueAggregatorDescriptor.configure(JobConf job)` Configure the object
`void` `ValueAggregatorBaseDescriptor.configure(JobConf job)` get the input file name.
`void` `ValueAggregatorCombiner.configure(JobConf job)` Combiner does not need to configure.
`void` `UserDefinedValueAggregatorDescriptor.configure(JobConf job)` Do nothing.
`void` `ValueAggregatorJobBase.configure(JobConf job)`
`static void` `ValueAggregatorJob.setAggregatorDescriptors(JobConf job, Class<? extends ValueAggregatorDescriptor>[] descriptors)`

Constructors in org.apache.hadoop.mapred.lib.aggregate with parameters of type JobConf
`UserDefinedValueAggregatorDescriptor(String className, JobConf job)`

Uses of JobConf in org.apache.hadoop.mapred.lib.db

Methods in org.apache.hadoop.mapred.lib.db with parameters of type JobConf
`void` `DBOutputFormat.checkOutputSpecs(FileSystem filesystem, JobConf job)` Check for validity of the output-specification for the job.
`void` `DBInputFormat.configure(JobConf job)` Initializes a new instance from a `JobConf`.
`static void` `DBConfiguration.configureDB(JobConf job, String driverClass, String dbUrl)` Sets the DB access related fields in the JobConf.
`static void` `DBConfiguration.configureDB(JobConf job, String driverClass, String dbUrl, String userName, String passwd)` Sets the DB access related fields in the JobConf.
`RecordReader<LongWritable,T>` `DBInputFormat.getRecordReader(InputSplit split, JobConf job, Reporter reporter)` Get the `RecordReader` for the given `InputSplit`.
`RecordWriter<K,V>` `DBOutputFormat.getRecordWriter(FileSystem filesystem, JobConf job, String name, Progressable progress)` Get the `RecordWriter` for the given job.
`InputSplit[]` `DBInputFormat.getSplits(JobConf job, int chunks)` Logically split the set of input files for the job.
`static void` `DBInputFormat.setInput(JobConf job, Class<? extends DBWritable> inputClass, String inputQuery, String inputCountQuery)` Initializes the map-part of the job with the appropriate input settings.
`static void` `DBInputFormat.setInput(JobConf job, Class<? extends DBWritable> inputClass, String tableName, String conditions, String orderBy, String... fieldNames)` Initializes the map-part of the job with the appropriate input settings.
`static void` `DBOutputFormat.setOutput(JobConf job, String tableName, String... fieldNames)` Initializes the reduce-part of the job with the appropriate output settings

Constructors in org.apache.hadoop.mapred.lib.db with parameters of type JobConf
`DBInputFormat.DBRecordReader(DBInputFormat.DBInputSplit split, Class<T> inputClass, JobConf job)`

Uses of JobConf in org.apache.hadoop.mapred.pipes

Methods in org.apache.hadoop.mapred.pipes with parameters of type JobConf
`static String` `Submitter.getExecutable(JobConf conf)` Get the URI of the application's executable.
`static boolean` `Submitter.getIsJavaMapper(JobConf conf)` Check whether the job is using a Java Mapper.
`static boolean` `Submitter.getIsJavaRecordReader(JobConf conf)` Check whether the job is using a Java RecordReader
`static boolean` `Submitter.getIsJavaRecordWriter(JobConf conf)` Will the reduce use a Java RecordWriter?
`static boolean` `Submitter.getIsJavaReducer(JobConf conf)` Check whether the job is using a Java Reducer.
`static boolean` `Submitter.getKeepCommandFile(JobConf conf)` Does the user want to keep the command file for debugging? If this is true, pipes will write a copy of the command data to a file in the task directory named "downlink.data", which may be used to run the C++ program under the debugger.
`static RunningJob` `Submitter.jobSubmit(JobConf conf)` Submit a job to the Map-Reduce framework.
`static RunningJob` `Submitter.runJob(JobConf conf)` Submit a job to the map/reduce cluster.
`static void` `Submitter.setExecutable(JobConf conf, String executable)` Set the URI for the application's executable.
`static void` `Submitter.setIsJavaMapper(JobConf conf, boolean value)` Set whether the Mapper is written in Java.
`static void` `Submitter.setIsJavaRecordReader(JobConf conf, boolean value)` Set whether the job is using a Java RecordReader.
`static void` `Submitter.setIsJavaRecordWriter(JobConf conf, boolean value)` Set whether the job will use a Java RecordWriter.
`static void` `Submitter.setIsJavaReducer(JobConf conf, boolean value)` Set whether the Reducer is written in Java.
`static void` `Submitter.setKeepCommandFile(JobConf conf, boolean keep)` Set whether to keep the command file for debugging
`static RunningJob` `Submitter.submitJob(JobConf conf)` Deprecated. Use `Submitter.runJob(JobConf)`

Uses of JobConf in org.apache.hadoop.mapreduce

Fields in org.apache.hadoop.mapreduce declared as JobConf
`protected JobConf` `JobContext.conf`

Uses of JobConf in org.apache.hadoop.streaming

Fields in org.apache.hadoop.streaming declared as JobConf
`protected JobConf` `StreamJob.jobConf_`

Methods in org.apache.hadoop.streaming that return JobConf
`static JobConf` `StreamJob.createJob(String[] argv)` This method creates a streaming job from the given argument list.

Methods in org.apache.hadoop.streaming with parameters of type JobConf
`void` `PipeMapRed.configure(JobConf job)`
`void` `PipeReducer.configure(JobConf job)`
`void` `PipeMapper.configure(JobConf job)`
`static FileSplit` `StreamUtil.getCurrentSplit(JobConf job)`
`RecordReader<Text,Text>` `StreamInputFormat.getRecordReader(InputSplit genericSplit, JobConf job, Reporter reporter)`
`static org.apache.hadoop.streaming.StreamUtil.TaskId` `StreamUtil.getTaskInfo(JobConf job)`
`static boolean` `StreamUtil.isLocalJobTracker(JobConf job)`

Constructors in org.apache.hadoop.streaming with parameters of type JobConf
`StreamBaseRecordReader(FSDataInputStream in, FileSplit split, Reporter reporter, JobConf job, FileSystem fs)`
`StreamXmlRecordReader(FSDataInputStream in, FileSplit split, Reporter reporter, JobConf job, FileSystem fs)`

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