Examples of cascading.pipe.GroupBy

cascading.pipe.GroupBy
The GroupBy pipe groups the {@link Tuple} stream by the given groupFields.
If more than one {@link Pipe} instance is provided on the constructor, all branches will be merged. It is requiredthat all Pipe instances output the same field names, otherwise the {@link cascading.flow.FlowConnector} will fail to create a{@link cascading.flow.Flow} instance. Again, the Pipe instances are merged together as if one Tuple stream and not joined.See {@link CoGroup} for joining by common fields.
Typically an {@link Every} follows GroupBy to apply an {@link Aggregator} function to every grouping. The{@link Each} operator may also follow GroupBy to apply a {@link Function} or {@link Filter} to the resultingstream. But an Each cannot come immediately before an Every.
Optionally a stream can be further sorted by providing sortFields. This allows an Aggregator to receive values in the order of the sortedFields.
Note that local sorting always happens on the groupFields, sortFields are a secondary sorting on the grouped values within the current grouping. sortFields is particularly useful if the Aggregators following the GroupBy would like to see their arguments in order.
For more control over sorting at the group or secondary sort level, use {@link cascading.tuple.Fields}containing {@link java.util.Comparator} instances for the appropriate fields when setting the groupFields orsortFields values. Fields allows you to set a custom {@link java.util.Comparator} instance for each field name orposition. It is required that each Comparator class also be {@link java.io.Serializable}.
It should be noted for MapReduce systems, distributed group sorting is not 'total'. That is groups are sorted as seen by each Reducer, but they are not sorted across Reducers. See the MapReduce algorithm for details.
See the {@link cascading.tuple.Hasher} interface when a custom {@link java.util.Comparator} on the grouping keys isbeing provided that makes two values with differing hashCode values equal. For example, {@code new BigDecimal( 100.0D )} and {@code new Double 100.0D )} are equal using a custom Comparator, but{@link Object#hashCode()} will be different, thus forcing each value into differing partitions.
Note that grouping one String key with a lowercase value with another String key with an uppercase value using a "case insensitive" Comparator will not have consistent results. The grouping will execute and be correct, but the actual values in the key columns may be replaced with "equivalent" values from other streams.
That is, if two streams are merged and then grouped on a key, where one stream the key values are uppercase and the other stream values are lowercase, the resulting key value for the grouping may arbitrarily be either upper or lower case.
If the original key values must be retained, consider normalizing the keys with a Function and then grouping on the resulting field.

    // only returns "token"
    Pipe docPipe = new Each( "token", text, splitter, Fields.RESULTS );


    // determine the word counts
    Pipe wcPipe = new Pipe( "wc", docPipe );
    wcPipe = new GroupBy( wcPipe, token );
    wcPipe = new Every( wcPipe, Fields.ALL, new Count(), Fields.ALL );


    // connect the taps, pipes, etc., into a flow
    FlowDef flowDef = FlowDef.flowDef()
     .setName( "wc" )

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    Function splitter = new RegexSplitter( new Fields( "num", "char" ), " " );


    Pipe pipeLower = new Each( new Pipe( "lower" ), new Fields( "line" ), splitter );
    Pipe pipeUpper = new Each( new Pipe( "upper" ), new Fields( "line" ), splitter );
    pipeUpper = new Each( pipeUpper, new Fields( "num" ), new RegexFilter( "^fobar" ) ); // intentionally filtering all
    pipeUpper = new GroupBy( pipeUpper, new Fields( "num" ) );


    Pipe splice = new CoGroup( pipeLower, new Fields( "num" ), pipeUpper, new Fields( "num" ), Fields.size( 4 ), new OuterJoin() );


    Flow flow = getPlatform().getFlowConnector().connect( sources, sink, splice );

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    Tap sink = getPlatform().getTextFile( new Fields( "line" ), getOutputPath( "afterevery" ), SinkMode.REPLACE );


    Function splitter = new RegexSplitter( new Fields( "num", "char" ), " " );


    Pipe pipeLower = new Each( new Pipe( "lower" ), new Fields( "line" ), splitter );
    pipeLower = new GroupBy( pipeLower, new Fields( "num" ) );
    pipeLower = new Every( pipeLower, new Fields( "char" ), new First(), Fields.ALL );


    Pipe pipeUpper = new Each( new Pipe( "upper" ), new Fields( "line" ), splitter );
    pipeUpper = new GroupBy( pipeUpper, new Fields( "num" ) );
    pipeUpper = new Every( pipeUpper, new Fields( "char" ), new First(), Fields.ALL );


    Pipe splice = new CoGroup( pipeLower, new Fields( "num" ), pipeUpper, new Fields( "num" ), Fields.size( 4 ) );


    Flow flow = getPlatform().getFlowConnector().connect( sources, sink, splice );

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    Function splitter1 = new RegexSplitter( new Fields( "num1", "char1" ), " " );


    Pipe pipeLower = new Each( new Pipe( "lower" ), new Fields( "line" ), splitter1 );
    pipeLower = new Each( pipeLower, new Insert( new Fields( "one", "two", "three", "four" ), "one", "two", "three", "four" ), Fields.ALL );
    pipeLower = new GroupBy( pipeLower, new Fields( "num1" ) );
    pipeLower = new Every( pipeLower, new Fields( "char1" ), new First(), Fields.ALL );


    Function splitter2 = new RegexSplitter( new Fields( "num2", "char2" ), " " );


    Pipe pipeUpper = new Each( new Pipe( "upper" ), new Fields( "line" ), splitter2 );
    pipeUpper = new GroupBy( pipeUpper, new Fields( "num2" ) );
    pipeUpper = new Every( pipeUpper, new Fields( "char2" ), new First(), Fields.ALL );


    Pipe splice = new CoGroup( pipeLower, new Fields( "num1" ), pipeUpper, new Fields( "num2" ) );


    Flow flow = getPlatform().getFlowConnector().connect( sources, sink, splice );

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    Pipe pipeLower = new Each( new Pipe( "lower" ), new Fields( "line" ), splitterLower );
    Pipe pipeUpper = new Each( new Pipe( "upper" ), new Fields( "line" ), splitterUpper );


    Pipe cogroup = new CoGroup( pipeLower, new Fields( "numA" ), pipeUpper, new Fields( "numB" ) );


    Pipe groupby = new GroupBy( cogroup, new Fields( "numA" ) );


    Flow flow = getPlatform().getFlowConnector().connect( sources, sink, groupby );


    flow.complete();

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    Pipe uniques = new Pipe( "unique" );


    uniques = new Each( uniques, new Fields( "line" ), new RegexSplitGenerator( new Fields( "word" ), "\\s" ) );


    uniques = new GroupBy( uniques, new Fields( "word" ) );


    uniques = new Every( uniques, new Fields( "word" ), new First( Fields.ARGS ), Fields.REPLACE );


//    uniques = new Each( uniques, new Debug( true ) );

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    Tap source = getPlatform().getTextFile( inputFileApache );


    Pipe pipe = new Pipe( "first" );


    pipe = new Each( pipe, new Fields( "line" ), new RegexParser( new Fields( "ip" ), "^[^ ]*" ), new Fields( "ip" ) );
    pipe = new GroupBy( pipe, new Fields( "ip" ) );
    pipe = new Each( pipe, new Counter( TestEnum.FIRST ) );
    pipe = new GroupBy( pipe, new Fields( "ip" ) );
    pipe = new Each( pipe, new Counter( TestEnum.FIRST ) );
    pipe = new Each( pipe, new Counter( TestEnum.SECOND ) );


    Tap sink1 = getPlatform().getTextFile( getOutputPath( "flowstats1" ), SinkMode.REPLACE );
    Tap sink2 = getPlatform().getTextFile( getOutputPath( "flowstats2" ), SinkMode.REPLACE );

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    Tap source = getPlatform().getTextFile( inputFileApache );


    Pipe pipe = new Pipe( "failing reducer" );
    pipe = new Each( pipe, new Fields( "line" ), new RegexParser( new Fields( "ip" ), "^[^ ]*" ), new Fields( "ip" ) );
    pipe = new GroupBy( pipe, new Fields( "ip" ) );
    pipe = new Every( pipe, new TestFailAggregator( new Fields( "count" ), 1 ) );


    Tap sink = getPlatform().getTextFile( getOutputPath( "reducerfail" ), SinkMode.REPLACE );


    Flow flow = getPlatform().getFlowConnector().connect( "reducer fail test", source, sink, pipe );

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public class EveryAssemblyFactory extends AssemblyFactory
  {
  public Pipe createAssembly( Pipe pipe, Fields argFields, Fields declFields, String fieldValue, Fields selectFields )
    {
    pipe = new GroupBy( pipe, Fields.ALL );


    return new Every( pipe, argFields, new TestAggregator( declFields, new Tuple( fieldValue ) ), selectFields );
    }

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    Pipe pipe = new Pipe( "test" );


    pipe = new Each( pipe, new Fields( "line" ), new RegexParser( new Fields( "ip" ), "^[^ ]*" ), new Fields( "ip" ) );


    pipe = new GroupBy( pipe, new Fields( "ip" ) );


    pipe = new Every( pipe, new Count(), new Fields( "ip", "count" ) );


    Tap sink = getPlatform().getTextFile( getOutputPath( "simple" ), SinkMode.REPLACE );

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