## Uses of Class
org.apache.hadoop.mapreduce.InputSplit

Packages that use InputSplit
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.mapreduce
org.apache.hadoop.mapreduce.lib.db
org.apache.hadoop.mapreduce.lib.input
org.apache.hadoop.mapreduce.split

Uses of InputSplit in org.apache.hadoop.mapred

Subclasses of InputSplit in org.apache.hadoop.mapred
`class` `FileSplit` A section of an input file.

Uses of InputSplit in org.apache.hadoop.mapreduce

Methods in org.apache.hadoop.mapreduce that return InputSplit
`InputSplit` `MapContext.getInputSplit()` Get the input split for this map.

Methods in org.apache.hadoop.mapreduce that return types with arguments of type InputSplit
`abstract List<InputSplit>` `InputFormat.getSplits(JobContext context)` Logically split the set of input files for the job.

Methods in org.apache.hadoop.mapreduce with parameters of type InputSplit
`abstract RecordReader<K,V>` `InputFormat.createRecordReader(InputSplit split, TaskAttemptContext context)` Create a record reader for a given split.
`abstract void` `RecordReader.initialize(InputSplit split, TaskAttemptContext context)` Called once at initialization.

Constructors in org.apache.hadoop.mapreduce with parameters of type InputSplit
`MapContext(Configuration conf, TaskAttemptID taskid, RecordReader<KEYIN,VALUEIN> reader, RecordWriter<KEYOUT,VALUEOUT> writer, OutputCommitter committer, StatusReporter reporter, InputSplit split)`
`Mapper.Context(Configuration conf, TaskAttemptID taskid, RecordReader<KEYIN,VALUEIN> reader, RecordWriter<KEYOUT,VALUEOUT> writer, OutputCommitter committer, StatusReporter reporter, InputSplit split)`

Uses of InputSplit in org.apache.hadoop.mapreduce.lib.db

Subclasses of InputSplit in org.apache.hadoop.mapreduce.lib.db
`static class` `DataDrivenDBInputFormat.DataDrivenDBInputSplit` A InputSplit that spans a set of rows
`static class` `DBInputFormat.DBInputSplit` A InputSplit that spans a set of rows

Methods in org.apache.hadoop.mapreduce.lib.db that return types with arguments of type InputSplit
`List<InputSplit>` `DBInputFormat.getSplits(JobContext job)` Logically split the set of input files for the job.
`List<InputSplit>` `DataDrivenDBInputFormat.getSplits(JobContext job)` Logically split the set of input files for the job.
`List<InputSplit>` `DateSplitter.split(Configuration conf, ResultSet results, String colName)`
`List<InputSplit>` `BooleanSplitter.split(Configuration conf, ResultSet results, String colName)`
`List<InputSplit>` `DBSplitter.split(Configuration conf, ResultSet results, String colName)` Given a ResultSet containing one record (and already advanced to that record) with two columns (a low value, and a high value, both of the same type), determine a set of splits that span the given values.
`List<InputSplit>` `FloatSplitter.split(Configuration conf, ResultSet results, String colName)`
`List<InputSplit>` `TextSplitter.split(Configuration conf, ResultSet results, String colName)` This method needs to determine the splits between two user-provided strings.
`List<InputSplit>` `IntegerSplitter.split(Configuration conf, ResultSet results, String colName)`
`List<InputSplit>` `BigDecimalSplitter.split(Configuration conf, ResultSet results, String colName)`

Methods in org.apache.hadoop.mapreduce.lib.db with parameters of type InputSplit
`RecordReader<LongWritable,T>` `DBInputFormat.createRecordReader(InputSplit split, TaskAttemptContext context)` Create a record reader for a given split.
`void` `DBRecordReader.initialize(InputSplit split, TaskAttemptContext context)`

Uses of InputSplit in org.apache.hadoop.mapreduce.lib.input

Subclasses of InputSplit in org.apache.hadoop.mapreduce.lib.input
`class` `CombineFileSplit` A sub-collection of input files.

Methods in org.apache.hadoop.mapreduce.lib.input that return types with arguments of type InputSplit
`List<InputSplit>` `DelegatingInputFormat.getSplits(JobContext job)`
`List<InputSplit>` `CombineFileInputFormat.getSplits(JobContext job)`
`List<InputSplit>` `NLineInputFormat.getSplits(JobContext job)` Logically splits the set of input files for the job, splits N lines of the input as one split.
`List<InputSplit>` `FileInputFormat.getSplits(JobContext job)` Generate the list of files and make them into FileSplits.

Methods in org.apache.hadoop.mapreduce.lib.input with parameters of type InputSplit
`RecordReader<K,V>` `DelegatingInputFormat.createRecordReader(InputSplit split, TaskAttemptContext context)`
`RecordReader<BytesWritable,BytesWritable>` `SequenceFileAsBinaryInputFormat.createRecordReader(InputSplit split, TaskAttemptContext context)`
`abstract RecordReader<K,V>` `CombineFileInputFormat.createRecordReader(InputSplit split, TaskAttemptContext context)` This is not implemented yet.
`RecordReader<K,V>` `SequenceFileInputFilter.createRecordReader(InputSplit split, TaskAttemptContext context)` Create a record reader for the given split
`RecordReader<LongWritable,Text>` `NLineInputFormat.createRecordReader(InputSplit genericSplit, TaskAttemptContext context)`
`RecordReader<K,V>` `SequenceFileInputFormat.createRecordReader(InputSplit split, TaskAttemptContext context)`
`RecordReader<LongWritable,Text>` `TextInputFormat.createRecordReader(InputSplit split, TaskAttemptContext context)`
`RecordReader<Text,Text>` `SequenceFileAsTextInputFormat.createRecordReader(InputSplit split, TaskAttemptContext context)`
`RecordReader<Text,Text>` `KeyValueTextInputFormat.createRecordReader(InputSplit genericSplit, TaskAttemptContext context)`
`void` `SequenceFileRecordReader.initialize(InputSplit split, TaskAttemptContext context)`
`void` `SequenceFileAsBinaryInputFormat.SequenceFileAsBinaryRecordReader.initialize(InputSplit split, TaskAttemptContext context)`
`void` `SequenceFileAsTextRecordReader.initialize(InputSplit split, TaskAttemptContext context)`
`void` `DelegatingRecordReader.initialize(InputSplit split, TaskAttemptContext context)`
`void` `LineRecordReader.initialize(InputSplit genericSplit, TaskAttemptContext context)`
`void` `CombineFileRecordReader.initialize(InputSplit split, TaskAttemptContext context)`
`void` `KeyValueLineRecordReader.initialize(InputSplit genericSplit, TaskAttemptContext context)`

Constructors in org.apache.hadoop.mapreduce.lib.input with parameters of type InputSplit
`DelegatingRecordReader(InputSplit split, TaskAttemptContext context)` Constructs the DelegatingRecordReader.

Uses of InputSplit in org.apache.hadoop.mapreduce.split

Methods in org.apache.hadoop.mapreduce.split with type parameters of type InputSplit

`static

`<T extends InputSplit> void`

`

`JobSplitWriter.createSplitFiles(Path jobSubmitDir, Configuration conf, FileSystem fs, List<InputSplit> splits)`

`static

`<T extends InputSplit> void`

`

`JobSplitWriter.createSplitFiles(Path jobSubmitDir, Configuration conf, FileSystem fs, T[] splits)`

Methods in org.apache.hadoop.mapreduce.split with parameters of type InputSplit

`static

`<T extends InputSplit> void`

`

`JobSplitWriter.createSplitFiles(Path jobSubmitDir, Configuration conf, FileSystem fs, T[] splits)`

Method parameters in org.apache.hadoop.mapreduce.split with type arguments of type InputSplit

`static

`<T extends InputSplit> void`

`

`JobSplitWriter.createSplitFiles(Path jobSubmitDir, Configuration conf, FileSystem fs, List<InputSplit> splits)`

Constructors in org.apache.hadoop.mapreduce.split with parameters of type InputSplit
`JobSplit.SplitMetaInfo(InputSplit split, long startOffset)`
`JobSplit.TaskSplitMetaInfo(InputSplit split, long startOffset)`

Copyright © 2009 The Apache Software Foundation