Package com.facebook.presto.operator.aggregation

Examples of com.facebook.presto.operator.aggregation.InternalAggregationFunction

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    @Test
    public void testHashAggregation()
            throws Exception
    {
        MetadataManager metadata = new MetadataManager();
        InternalAggregationFunction countVarcharColumn = metadata.resolveFunction(QualifiedName.of("count"), ImmutableList.of(StandardTypes.VARCHAR), false).getAggregationFunction();
        InternalAggregationFunction countBooleanColumn = metadata.resolveFunction(QualifiedName.of("count"), ImmutableList.of(StandardTypes.BOOLEAN), false).getAggregationFunction();
        List<Page> input = rowPagesBuilder(VARCHAR, VARCHAR, VARCHAR, BIGINT, BOOLEAN)
                .addSequencePage(10, 100, 0, 100, 0, 500)
                .addSequencePage(10, 100, 0, 200, 0, 500)
                .addSequencePage(10, 100, 0, 300, 0, 500)
                .build();

        HashAggregationOperatorFactory operatorFactory = new HashAggregationOperatorFactory(
                0,
                ImmutableList.of(VARCHAR),
                Ints.asList(1),
                Step.SINGLE,
                ImmutableList.of(COUNT.bind(ImmutableList.of(0), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        LONG_SUM.bind(ImmutableList.of(3), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        LONG_AVERAGE.bind(ImmutableList.of(3), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        VAR_BINARY_MAX.bind(ImmutableList.of(2), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        countVarcharColumn.bind(ImmutableList.of(0), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        countBooleanColumn.bind(ImmutableList.of(4), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0)),
                100_000);

        Operator operator = operatorFactory.createOperator(driverContext);

        MaterializedResult expected = resultBuilder(driverContext.getSession(), VARCHAR, BIGINT, BIGINT, DOUBLE, VARCHAR, BIGINT, BIGINT)
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    @Test
    public void testAggregation()
            throws Exception
    {
        MetadataManager metadata = new MetadataManager();
        InternalAggregationFunction countVarcharColumn = metadata.resolveFunction(QualifiedName.of("count"), ImmutableList.of(StandardTypes.VARCHAR), false).getAggregationFunction();
        List<Page> input = rowPagesBuilder(VARCHAR, BIGINT, VARCHAR, BIGINT, DOUBLE, VARCHAR)
                .addSequencePage(100, 0, 0, 300, 500, 500, 500)
                .build();

        OperatorFactory operatorFactory = new AggregationOperatorFactory(
                0,
                Step.SINGLE,
                ImmutableList.of(COUNT.bind(ImmutableList.of(0), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        LONG_SUM.bind(ImmutableList.of(1), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        LONG_AVERAGE.bind(ImmutableList.of(1), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        VAR_BINARY_MAX.bind(ImmutableList.of(2), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        countVarcharColumn.bind(ImmutableList.of(0), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        LONG_SUM.bind(ImmutableList.of(3), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        DOUBLE_SUM.bind(ImmutableList.of(4), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0),
                        VAR_BINARY_MAX.bind(ImmutableList.of(5), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0)));
        Operator operator = operatorFactory.createOperator(driverContext);
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        TypeRegistry typeRegistry = new TypeRegistry();
        typeRegistry.addType(new ClassifierType());
        typeRegistry.addType(new RegressorType());
        typeRegistry.addType(new ModelType());
        metadata.addFunctions(new MLFunctionFactory(typeRegistry).listFunctions());
        InternalAggregationFunction aggregation = metadata.getExactFunction(new Signature("evaluate_classifier_predictions", StandardTypes.VARCHAR, StandardTypes.BIGINT, StandardTypes.BIGINT)).getAggregationFunction();
        Accumulator accumulator = aggregation.bind(ImmutableList.of(0, 1), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0).createAccumulator();
        accumulator.addInput(getPage());
        Block block = accumulator.evaluateFinal();

        String output = VARCHAR.getSlice(block, 0).toStringUtf8();
        List<String> parts = ImmutableList.copyOf(Splitter.on('\n').split(output));
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        private final int intermediateChannel;

        private Aggregator(AggregationFunctionDefinition functionDefinition, Step step)
        {
            InternalAggregationFunction function = functionDefinition.getFunction();

            if (step == Step.FINAL) {
                checkArgument(functionDefinition.getInputs().size() == 1, "Expected a single input for an intermediate aggregation");
                intermediateChannel = functionDefinition.getInputs().get(0);
                aggregation = function.createGroupedIntermediateAggregation(functionDefinition.getConfidence());
            }
            else {
                int[] argumentChannels = new int[functionDefinition.getInputs().size()];
                for (int i = 0; i < argumentChannels.length; i++) {
                    argumentChannels[i] = functionDefinition.getInputs().get(i);
                }
                intermediateChannel = -1;
                aggregation = function.createGroupedAggregation(
                        functionDefinition.getMask(),
                        functionDefinition.getSampleWeight(),
                        functionDefinition.getConfidence(),
                        argumentChannels);
            }
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        private final int intermediateChannel;

        private Aggregator(AggregationFunctionDefinition functionDefinition, Step step, MemoryManager memoryManager)
        {
            InternalAggregationFunction function = functionDefinition.getFunction();

            if (step != Step.FINAL) {
                int[] argumentChannels = new int[functionDefinition.getInputs().size()];
                for (int i = 0; i < argumentChannels.length; i++) {
                    argumentChannels[i] = functionDefinition.getInputs().get(i);
                }
                intermediateChannel = -1;
                aggregation = function.createAggregation(
                        functionDefinition.getMask(),
                        functionDefinition.getSampleWeight(),
                        functionDefinition.getConfidence(),
                        argumentChannels);
            }
            else {
                checkArgument(functionDefinition.getInputs().size() == 1, "Expected a single input for an intermediate aggregation");
                intermediateChannel = functionDefinition.getInputs().get(0);
                aggregation = function.createIntermediateAggregation(functionDefinition.getConfidence());
            }
            this.step = step;
            this.memoryManager = memoryManager;
        }
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        TypeRegistry typeRegistry = new TypeRegistry();
        typeRegistry.addType(new ClassifierType());
        typeRegistry.addType(new RegressorType());
        typeRegistry.addType(new ModelType());
        metadata.addFunctions(new MLFunctionFactory(typeRegistry).listFunctions());
        InternalAggregationFunction aggregation = metadata.getExactFunction(new Signature("evaluate_classifier_predictions", StandardTypes.VARCHAR, StandardTypes.BIGINT, StandardTypes.BIGINT)).getAggregationFunction();
        Accumulator accumulator = aggregation.bind(ImmutableList.of(0, 1), Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0).createAccumulator();
        accumulator.addInput(getPage());
        Block block = accumulator.evaluateFinal();

        String output = VARCHAR.getSlice(block, 0).toStringUtf8();
        List<String> parts = ImmutableList.copyOf(Splitter.on('\n').split(output));
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    public void testEvaluateClassifierPredictions()
            throws Exception
    {
        MetadataManager metadata = new MetadataManager();
        metadata.addFunctions(new MLFunctionFactory().listFunctions());
        InternalAggregationFunction aggregation = metadata.getExactFunction(new Signature("evaluate_classifier_predictions", VARCHAR, BIGINT, BIGINT)).getAggregationFunction();
        Accumulator accumulator = aggregation.createAggregation(Optional.<Integer>absent(), Optional.<Integer>absent(), 1.0, 0, 1);
        accumulator.addInput(getPage());
        Block block = accumulator.evaluateFinal();

        String output = VARCHAR.getSlice(block, 0).toStringUtf8();
        List<String> parts = ImmutableList.copyOf(Splitter.on('\n').split(output));
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Related Classes of com.facebook.presto.operator.aggregation.InternalAggregationFunction

  • com.facebook.presto.ml.TestEvaluateClassifierPredictions
  • com.facebook.presto.operator.AggregationOperator$Aggregator
  • com.facebook.presto.operator.HashAggregationOperator$Aggregator
  • com.facebook.presto.operator.TestAggregationOperator
  • com.facebook.presto.operator.TestHashAggregationOperator
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