Examples with NonBufferOverWindowOperator org.apache.flink.table.runtime.operators.over.NonBufferOverWindowOperator used on opensource projects

Example 1 with NonBufferOverWindowOperator

use of org.apache.flink.table.runtime.operators.over.NonBufferOverWindowOperator 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);
}