Examples with GeneratedAggsHandleFunction org.apache.flink.table.runtime.generated.GeneratedAggsHandleFunction used on opensource projects

Example 1 with GeneratedAggsHandleFunction

use of org.apache.flink.table.runtime.generated.GeneratedAggsHandleFunction in project flink by apache.

the class StreamExecGlobalGroupAggregate method translateToPlanInternal.

@SuppressWarnings("unchecked")
@Override
protected Transformation<RowData> translateToPlanInternal(PlannerBase planner, ExecNodeConfig config) {
    if (grouping.length > 0 && config.getStateRetentionTime() < 0) {
        LOG.warn("No state retention interval configured for a query which accumulates state. " + "Please provide a query configuration with valid retention interval to prevent excessive " + "state size. You may specify a retention time of 0 to not clean up the state.");
    }
    final ExecEdge inputEdge = getInputEdges().get(0);
    final Transformation<RowData> inputTransform = (Transformation<RowData>) inputEdge.translateToPlan(planner);
    final RowType inputRowType = (RowType) inputEdge.getOutputType();
    final AggregateInfoList localAggInfoList = AggregateUtil.transformToStreamAggregateInfoList(localAggInputRowType, JavaScalaConversionUtil.toScala(Arrays.asList(aggCalls)), aggCallNeedRetractions, needRetraction, JavaScalaConversionUtil.toScala(Optional.ofNullable(indexOfCountStar)), // isStateBackendDataViews
    false, // needDistinctInfo
    true);
    final AggregateInfoList globalAggInfoList = AggregateUtil.transformToStreamAggregateInfoList(localAggInputRowType, JavaScalaConversionUtil.toScala(Arrays.asList(aggCalls)), aggCallNeedRetractions, needRetraction, JavaScalaConversionUtil.toScala(Optional.ofNullable(indexOfCountStar)), // isStateBackendDataViews
    true, // needDistinctInfo
    true);
    final GeneratedAggsHandleFunction localAggsHandler = generateAggsHandler("LocalGroupAggsHandler", localAggInfoList, grouping.length, localAggInfoList.getAccTypes(), config, planner.getRelBuilder());
    final GeneratedAggsHandleFunction globalAggsHandler = generateAggsHandler("GlobalGroupAggsHandler", globalAggInfoList, // mergedAccOffset
    0, localAggInfoList.getAccTypes(), config, planner.getRelBuilder());
    final int indexOfCountStar = globalAggInfoList.getIndexOfCountStar();
    final LogicalType[] globalAccTypes = Arrays.stream(globalAggInfoList.getAccTypes()).map(LogicalTypeDataTypeConverter::fromDataTypeToLogicalType).toArray(LogicalType[]::new);
    final LogicalType[] globalAggValueTypes = Arrays.stream(globalAggInfoList.getActualValueTypes()).map(LogicalTypeDataTypeConverter::fromDataTypeToLogicalType).toArray(LogicalType[]::new);
    final GeneratedRecordEqualiser recordEqualiser = new EqualiserCodeGenerator(globalAggValueTypes).generateRecordEqualiser("GroupAggValueEqualiser");
    final OneInputStreamOperator<RowData, RowData> operator;
    final boolean isMiniBatchEnabled = config.get(ExecutionConfigOptions.TABLE_EXEC_MINIBATCH_ENABLED);
    if (isMiniBatchEnabled) {
        MiniBatchGlobalGroupAggFunction aggFunction = new MiniBatchGlobalGroupAggFunction(localAggsHandler, globalAggsHandler, recordEqualiser, globalAccTypes, indexOfCountStar, generateUpdateBefore, config.getStateRetentionTime());
        operator = new KeyedMapBundleOperator<>(aggFunction, AggregateUtil.createMiniBatchTrigger(config));
    } else {
        throw new TableException("Local-Global optimization is only worked in miniBatch mode");
    }
    // partitioned aggregation
    final OneInputTransformation<RowData, RowData> transform = ExecNodeUtil.createOneInputTransformation(inputTransform, createTransformationMeta(GLOBAL_GROUP_AGGREGATE_TRANSFORMATION, config), operator, InternalTypeInfo.of(getOutputType()), inputTransform.getParallelism());
    // set KeyType and Selector for state
    final RowDataKeySelector selector = KeySelectorUtil.getRowDataSelector(grouping, InternalTypeInfo.of(inputRowType));
    transform.setStateKeySelector(selector);
    transform.setStateKeyType(selector.getProducedType());
    return transform;
}

Example 2 with GeneratedAggsHandleFunction

use of org.apache.flink.table.runtime.generated.GeneratedAggsHandleFunction in project flink by apache.

the class StreamExecGroupAggregate method translateToPlanInternal.

@SuppressWarnings("unchecked")
@Override
protected Transformation<RowData> translateToPlanInternal(PlannerBase planner, ExecNodeConfig config) {
    if (grouping.length > 0 && config.getStateRetentionTime() < 0) {
        LOG.warn("No state retention interval configured for a query which accumulates state. " + "Please provide a query configuration with valid retention interval to prevent excessive " + "state size. You may specify a retention time of 0 to not clean up the state.");
    }
    final ExecEdge inputEdge = getInputEdges().get(0);
    final Transformation<RowData> inputTransform = (Transformation<RowData>) inputEdge.translateToPlan(planner);
    final RowType inputRowType = (RowType) inputEdge.getOutputType();
    final AggsHandlerCodeGenerator generator = new AggsHandlerCodeGenerator(new CodeGeneratorContext(config.getTableConfig()), planner.getRelBuilder(), JavaScalaConversionUtil.toScala(inputRowType.getChildren()), // TODO: but other operators do not copy this input field.....
    true).needAccumulate();
    if (needRetraction) {
        generator.needRetract();
    }
    final AggregateInfoList aggInfoList = AggregateUtil.transformToStreamAggregateInfoList(inputRowType, JavaScalaConversionUtil.toScala(Arrays.asList(aggCalls)), aggCallNeedRetractions, needRetraction, true, true);
    final GeneratedAggsHandleFunction aggsHandler = generator.generateAggsHandler("GroupAggsHandler", aggInfoList);
    final LogicalType[] accTypes = Arrays.stream(aggInfoList.getAccTypes()).map(LogicalTypeDataTypeConverter::fromDataTypeToLogicalType).toArray(LogicalType[]::new);
    final LogicalType[] aggValueTypes = Arrays.stream(aggInfoList.getActualValueTypes()).map(LogicalTypeDataTypeConverter::fromDataTypeToLogicalType).toArray(LogicalType[]::new);
    final GeneratedRecordEqualiser recordEqualiser = new EqualiserCodeGenerator(aggValueTypes).generateRecordEqualiser("GroupAggValueEqualiser");
    final int inputCountIndex = aggInfoList.getIndexOfCountStar();
    final boolean isMiniBatchEnabled = config.get(ExecutionConfigOptions.TABLE_EXEC_MINIBATCH_ENABLED);
    final OneInputStreamOperator<RowData, RowData> operator;
    if (isMiniBatchEnabled) {
        MiniBatchGroupAggFunction aggFunction = new MiniBatchGroupAggFunction(aggsHandler, recordEqualiser, accTypes, inputRowType, inputCountIndex, generateUpdateBefore, config.getStateRetentionTime());
        operator = new KeyedMapBundleOperator<>(aggFunction, AggregateUtil.createMiniBatchTrigger(config));
    } else {
        GroupAggFunction aggFunction = new GroupAggFunction(aggsHandler, recordEqualiser, accTypes, inputCountIndex, generateUpdateBefore, config.getStateRetentionTime());
        operator = new KeyedProcessOperator<>(aggFunction);
    }
    // partitioned aggregation
    final OneInputTransformation<RowData, RowData> transform = ExecNodeUtil.createOneInputTransformation(inputTransform, createTransformationMeta(GROUP_AGGREGATE_TRANSFORMATION, config), operator, InternalTypeInfo.of(getOutputType()), inputTransform.getParallelism());
    // set KeyType and Selector for state
    final RowDataKeySelector selector = KeySelectorUtil.getRowDataSelector(grouping, InternalTypeInfo.of(inputRowType));
    transform.setStateKeySelector(selector);
    transform.setStateKeyType(selector.getProducedType());
    return transform;
}

Example 3 with GeneratedAggsHandleFunction

use of org.apache.flink.table.runtime.generated.GeneratedAggsHandleFunction in project flink by apache.

the class StreamExecIncrementalGroupAggregate method translateToPlanInternal.

@SuppressWarnings("unchecked")
@Override
protected Transformation<RowData> translateToPlanInternal(PlannerBase planner, ExecNodeConfig config) {
    final ExecEdge inputEdge = getInputEdges().get(0);
    final Transformation<RowData> inputTransform = (Transformation<RowData>) inputEdge.translateToPlan(planner);
    final AggregateInfoList partialLocalAggInfoList = AggregateUtil.createPartialAggInfoList(partialLocalAggInputType, JavaScalaConversionUtil.toScala(Arrays.asList(partialOriginalAggCalls)), partialAggCallNeedRetractions, partialAggNeedRetraction, false);
    final GeneratedAggsHandleFunction partialAggsHandler = generateAggsHandler("PartialGroupAggsHandler", partialLocalAggInfoList, partialAggGrouping.length, partialLocalAggInfoList.getAccTypes(), config, planner.getRelBuilder(), // the partial aggregate accumulators will be buffered, so need copy
    true);
    final AggregateInfoList incrementalAggInfo = AggregateUtil.createIncrementalAggInfoList(partialLocalAggInputType, JavaScalaConversionUtil.toScala(Arrays.asList(partialOriginalAggCalls)), partialAggCallNeedRetractions, partialAggNeedRetraction);
    final GeneratedAggsHandleFunction finalAggsHandler = generateAggsHandler("FinalGroupAggsHandler", incrementalAggInfo, 0, partialLocalAggInfoList.getAccTypes(), config, planner.getRelBuilder(), // the final aggregate accumulators is not buffered
    false);
    final RowDataKeySelector partialKeySelector = KeySelectorUtil.getRowDataSelector(partialAggGrouping, InternalTypeInfo.of(inputEdge.getOutputType()));
    final RowDataKeySelector finalKeySelector = KeySelectorUtil.getRowDataSelector(finalAggGrouping, partialKeySelector.getProducedType());
    final MiniBatchIncrementalGroupAggFunction aggFunction = new MiniBatchIncrementalGroupAggFunction(partialAggsHandler, finalAggsHandler, finalKeySelector, config.getStateRetentionTime());
    final OneInputStreamOperator<RowData, RowData> operator = new KeyedMapBundleOperator<>(aggFunction, AggregateUtil.createMiniBatchTrigger(config));
    // partitioned aggregation
    final OneInputTransformation<RowData, RowData> transform = ExecNodeUtil.createOneInputTransformation(inputTransform, createTransformationMeta(INCREMENTAL_GROUP_AGGREGATE_TRANSFORMATION, config), operator, InternalTypeInfo.of(getOutputType()), inputTransform.getParallelism());
    // set KeyType and Selector for state
    transform.setStateKeySelector(partialKeySelector);
    transform.setStateKeyType(partialKeySelector.getProducedType());
    return transform;
}

Example 4 with GeneratedAggsHandleFunction

use of org.apache.flink.table.runtime.generated.GeneratedAggsHandleFunction in project flink by apache.

the class BatchExecOverAggregate method createOverWindowFrames.

private List<OverWindowFrame> createOverWindowFrames(FlinkRelBuilder relBuilder, ExecNodeConfig config, RowType inputType, SortSpec sortSpec, RowType inputTypeWithConstants) {
    final List<OverWindowFrame> windowFrames = new ArrayList<>();
    for (GroupSpec group : overSpec.getGroups()) {
        OverWindowMode mode = inferGroupMode(group);
        if (mode == OverWindowMode.OFFSET) {
            for (AggregateCall aggCall : group.getAggCalls()) {
                AggregateInfoList aggInfoList = AggregateUtil.transformToBatchAggregateInfoList(inputTypeWithConstants, JavaScalaConversionUtil.toScala(Collections.singletonList(aggCall)), new boolean[] { true }, /* needRetraction = true, See LeadLagAggFunction */
                sortSpec.getFieldIndices());
                AggsHandlerCodeGenerator generator = new AggsHandlerCodeGenerator(new CodeGeneratorContext(config.getTableConfig()), relBuilder, JavaScalaConversionUtil.toScala(inputType.getChildren()), // copyInputField
                false);
                // over agg code gen must pass the constants
                GeneratedAggsHandleFunction genAggsHandler = generator.needAccumulate().needRetract().withConstants(JavaScalaConversionUtil.toScala(getConstants())).generateAggsHandler("BoundedOverAggregateHelper", aggInfoList);
                // LEAD is behind the currentRow, so we need plus offset.
                // LAG is in front of the currentRow, so we need minus offset.
                long flag = aggCall.getAggregation().kind == SqlKind.LEAD ? 1L : -1L;
                final Long offset;
                final OffsetOverFrame.CalcOffsetFunc calcOffsetFunc;
                // The second arg mean the offset arg index for leag/lag function, default is 1.
                if (aggCall.getArgList().size() >= 2) {
                    int constantIndex = aggCall.getArgList().get(1) - overSpec.getOriginalInputFields();
                    if (constantIndex < 0) {
                        offset = null;
                        int rowIndex = aggCall.getArgList().get(1);
                        switch(inputType.getTypeAt(rowIndex).getTypeRoot()) {
                            case BIGINT:
                                calcOffsetFunc = row -> row.getLong(rowIndex) * flag;
                                break;
                            case INTEGER:
                                calcOffsetFunc = row -> (long) row.getInt(rowIndex) * flag;
                                break;
                            case SMALLINT:
                                calcOffsetFunc = row -> (long) row.getShort(rowIndex) * flag;
                                break;
                            default:
                                throw new RuntimeException("The column type must be in long/int/short.");
                        }
                    } else {
                        long constantOffset = getConstants().get(constantIndex).getValueAs(Long.class);
                        offset = constantOffset * flag;
                        calcOffsetFunc = null;
                    }
                } else {
                    offset = flag;
                    calcOffsetFunc = null;
                }
                windowFrames.add(new OffsetOverFrame(genAggsHandler, offset, calcOffsetFunc));
            }
        } else {
            AggregateInfoList aggInfoList = AggregateUtil.transformToBatchAggregateInfoList(// inputSchema.relDataType
            inputTypeWithConstants, JavaScalaConversionUtil.toScala(group.getAggCalls()), // aggCallNeedRetractions
            null, sortSpec.getFieldIndices());
            AggsHandlerCodeGenerator generator = new AggsHandlerCodeGenerator(new CodeGeneratorContext(config.getTableConfig()), relBuilder, JavaScalaConversionUtil.toScala(inputType.getChildren()), // copyInputField
            false);
            // over agg code gen must pass the constants
            GeneratedAggsHandleFunction genAggsHandler = generator.needAccumulate().withConstants(JavaScalaConversionUtil.toScala(getConstants())).generateAggsHandler("BoundedOverAggregateHelper", aggInfoList);
            RowType valueType = generator.valueType();
            final OverWindowFrame frame;
            switch(mode) {
                case RANGE:
                    if (isUnboundedWindow(group)) {
                        frame = new UnboundedOverWindowFrame(genAggsHandler, valueType);
                    } else if (isUnboundedPrecedingWindow(group)) {
                        GeneratedRecordComparator genBoundComparator = createBoundComparator(relBuilder, config, sortSpec, group.getUpperBound(), false, inputType);
                        frame = new RangeUnboundedPrecedingOverFrame(genAggsHandler, genBoundComparator);
                    } else if (isUnboundedFollowingWindow(group)) {
                        GeneratedRecordComparator genBoundComparator = createBoundComparator(relBuilder, config, sortSpec, group.getLowerBound(), true, inputType);
                        frame = new RangeUnboundedFollowingOverFrame(valueType, genAggsHandler, genBoundComparator);
                    } else if (isSlidingWindow(group)) {
                        GeneratedRecordComparator genLeftBoundComparator = createBoundComparator(relBuilder, config, sortSpec, group.getLowerBound(), true, inputType);
                        GeneratedRecordComparator genRightBoundComparator = createBoundComparator(relBuilder, config, sortSpec, group.getUpperBound(), false, inputType);
                        frame = new RangeSlidingOverFrame(inputType, valueType, genAggsHandler, genLeftBoundComparator, genRightBoundComparator);
                    } else {
                        throw new TableException("This should not happen.");
                    }
                    break;
                case ROW:
                    if (isUnboundedWindow(group)) {
                        frame = new UnboundedOverWindowFrame(genAggsHandler, valueType);
                    } else if (isUnboundedPrecedingWindow(group)) {
                        frame = new RowUnboundedPrecedingOverFrame(genAggsHandler, OverAggregateUtil.getLongBoundary(overSpec, group.getUpperBound()));
                    } else if (isUnboundedFollowingWindow(group)) {
                        frame = new RowUnboundedFollowingOverFrame(valueType, genAggsHandler, OverAggregateUtil.getLongBoundary(overSpec, group.getLowerBound()));
                    } else if (isSlidingWindow(group)) {
                        frame = new RowSlidingOverFrame(inputType, valueType, genAggsHandler, OverAggregateUtil.getLongBoundary(overSpec, group.getLowerBound()), OverAggregateUtil.getLongBoundary(overSpec, group.getUpperBound()));
                    } else {
                        throw new TableException("This should not happen.");
                    }
                    break;
                case INSENSITIVE:
                    frame = new InsensitiveOverFrame(genAggsHandler);
                    break;
                default:
                    throw new TableException("This should not happen.");
            }
            windowFrames.add(frame);
        }
    }
    return windowFrames;
}

Example 5 with GeneratedAggsHandleFunction

use of org.apache.flink.table.runtime.generated.GeneratedAggsHandleFunction in project flink by apache.

the class BatchExecOverAggregate method translateToPlanInternal.

@SuppressWarnings("unchecked")
@Override
protected Transformation<RowData> translateToPlanInternal(PlannerBase planner, ExecNodeConfig config) {
    final ExecEdge inputEdge = getInputEdges().get(0);
    final Transformation<RowData> inputTransform = (Transformation<RowData>) inputEdge.translateToPlan(planner);
    final RowType inputType = (RowType) inputEdge.getOutputType();
    // The generated sort is used for generating the comparator among partitions.
    // So here not care the ASC or DESC for the grouping fields.
    // TODO just replace comparator to equaliser
    final int[] partitionFields = overSpec.getPartition().getFieldIndices();
    final GeneratedRecordComparator genComparator = ComparatorCodeGenerator.gen(config.getTableConfig(), "SortComparator", inputType, SortUtil.getAscendingSortSpec(partitionFields));
    // use aggInputType which considers constants as input instead of inputType
    final RowType inputTypeWithConstants = getInputTypeWithConstants();
    // Over operator could support different order-by keys with collation satisfied.
    // Currently, this operator requires all order keys (combined with partition keys) are
    // the same, but order-by keys may be different. Consider the following sql:
    // select *, sum(b) over partition by a order by a, count(c) over partition by a from T
    // So we can use any one from the groups. To keep the behavior with the rule, we use the
    // last one.
    final SortSpec sortSpec = overSpec.getGroups().get(overSpec.getGroups().size() - 1).getSort();
    final TableStreamOperator<RowData> operator;
    final long managedMemory;
    if (!needBufferData()) {
        // operator needn't cache data
        final int numOfGroup = overSpec.getGroups().size();
        final GeneratedAggsHandleFunction[] aggsHandlers = new GeneratedAggsHandleFunction[numOfGroup];
        final boolean[] resetAccumulators = new boolean[numOfGroup];
        for (int i = 0; i < numOfGroup; ++i) {
            GroupSpec group = overSpec.getGroups().get(i);
            AggregateInfoList aggInfoList = AggregateUtil.transformToBatchAggregateInfoList(inputTypeWithConstants, JavaScalaConversionUtil.toScala(group.getAggCalls()), // aggCallNeedRetractions
            null, sortSpec.getFieldIndices());
            AggsHandlerCodeGenerator generator = new AggsHandlerCodeGenerator(new CodeGeneratorContext(config.getTableConfig()), planner.getRelBuilder(), JavaScalaConversionUtil.toScala(inputType.getChildren()), // copyInputField
            false);
            // over agg code gen must pass the constants
            aggsHandlers[i] = generator.needAccumulate().withConstants(JavaScalaConversionUtil.toScala(getConstants())).generateAggsHandler("BoundedOverAggregateHelper", aggInfoList);
            OverWindowMode mode = inferGroupMode(group);
            resetAccumulators[i] = mode == OverWindowMode.ROW && group.getLowerBound().isCurrentRow() && group.getUpperBound().isCurrentRow();
        }
        operator = new NonBufferOverWindowOperator(aggsHandlers, genComparator, resetAccumulators);
        managedMemory = 0L;
    } else {
        List<OverWindowFrame> windowFrames = createOverWindowFrames(planner.getRelBuilder(), config, inputType, sortSpec, inputTypeWithConstants);
        operator = new BufferDataOverWindowOperator(windowFrames.toArray(new OverWindowFrame[0]), genComparator, inputType.getChildren().stream().allMatch(BinaryRowData::isInFixedLengthPart));
        managedMemory = config.get(ExecutionConfigOptions.TABLE_EXEC_RESOURCE_EXTERNAL_BUFFER_MEMORY).getBytes();
    }
    return ExecNodeUtil.createOneInputTransformation(inputTransform, createTransformationName(config), createTransformationDescription(config), SimpleOperatorFactory.of(operator), InternalTypeInfo.of(getOutputType()), inputTransform.getParallelism(), managedMemory);
}