Examples with Transformation org.apache.flink.api.dag.Transformation used on opensource projects

Example 21 with Transformation

use of org.apache.flink.api.dag.Transformation in project flink by apache.

the class StreamExecGroupTableAggregate 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, // isStateBackendDataViews
    true, // needDistinctInfo
    true);
    final GeneratedTableAggsHandleFunction aggsHandler = generator.generateTableAggsHandler("GroupTableAggHandler", aggInfoList);
    final LogicalType[] accTypes = Arrays.stream(aggInfoList.getAccTypes()).map(LogicalTypeDataTypeConverter::fromDataTypeToLogicalType).toArray(LogicalType[]::new);
    final int inputCountIndex = aggInfoList.getIndexOfCountStar();
    final GroupTableAggFunction aggFunction = new GroupTableAggFunction(aggsHandler, accTypes, inputCountIndex, generateUpdateBefore, config.getStateRetentionTime());
    final OneInputStreamOperator<RowData, RowData> operator = new KeyedProcessOperator<>(aggFunction);
    // partitioned aggregation
    final OneInputTransformation<RowData, RowData> transform = ExecNodeUtil.createOneInputTransformation(inputTransform, createTransformationMeta(GROUP_TABLE_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 22 with Transformation

use of org.apache.flink.api.dag.Transformation in project flink by apache.

the class StreamExecSort method translateToPlanInternal.

@SuppressWarnings("unchecked")
@Override
protected Transformation<RowData> translateToPlanInternal(PlannerBase planner, ExecNodeConfig config) {
    if (!config.get(InternalConfigOptions.TABLE_EXEC_NON_TEMPORAL_SORT_ENABLED)) {
        throw new TableException("Sort on a non-time-attribute field is not supported.");
    }
    ExecEdge inputEdge = getInputEdges().get(0);
    RowType inputType = (RowType) inputEdge.getOutputType();
    // sort code gen
    GeneratedRecordComparator rowComparator = ComparatorCodeGenerator.gen(config.getTableConfig(), "StreamExecSortComparator", inputType, sortSpec);
    StreamSortOperator sortOperator = new StreamSortOperator(InternalTypeInfo.of(inputType), rowComparator);
    Transformation<RowData> inputTransform = (Transformation<RowData>) inputEdge.translateToPlan(planner);
    return ExecNodeUtil.createOneInputTransformation(inputTransform, createTransformationMeta(SORT_TRANSFORMATION, config), sortOperator, InternalTypeInfo.of(inputType), inputTransform.getParallelism());
}

Example 23 with Transformation

use of org.apache.flink.api.dag.Transformation in project flink by apache.

the class StreamGraphGeneratorTest method testSetSlotSharingResource.

@Test
public void testSetSlotSharingResource() {
    final String slotSharingGroup1 = "a";
    final String slotSharingGroup2 = "b";
    final ResourceProfile resourceProfile1 = ResourceProfile.fromResources(1, 10);
    final ResourceProfile resourceProfile2 = ResourceProfile.fromResources(2, 20);
    final ResourceProfile resourceProfile3 = ResourceProfile.fromResources(3, 30);
    final Map<String, ResourceProfile> slotSharingGroupResource = new HashMap<>();
    slotSharingGroupResource.put(slotSharingGroup1, resourceProfile1);
    slotSharingGroupResource.put(slotSharingGroup2, resourceProfile2);
    slotSharingGroupResource.put(StreamGraphGenerator.DEFAULT_SLOT_SHARING_GROUP, resourceProfile3);
    final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    final DataStream<Integer> sourceDataStream = env.fromElements(1, 2, 3).slotSharingGroup(slotSharingGroup1);
    final DataStream<Integer> mapDataStream1 = sourceDataStream.map(x -> x + 1).slotSharingGroup(slotSharingGroup2);
    final DataStream<Integer> mapDataStream2 = mapDataStream1.map(x -> x * 2);
    final List<Transformation<?>> transformations = new ArrayList<>();
    transformations.add(sourceDataStream.getTransformation());
    transformations.add(mapDataStream1.getTransformation());
    transformations.add(mapDataStream2.getTransformation());
    // all stream nodes share default group by default
    final StreamGraph streamGraph = new StreamGraphGenerator(transformations, env.getConfig(), env.getCheckpointConfig()).setSlotSharingGroupResource(slotSharingGroupResource).generate();
    assertThat(streamGraph.getSlotSharingGroupResource(slotSharingGroup1).get(), equalTo(resourceProfile1));
    assertThat(streamGraph.getSlotSharingGroupResource(slotSharingGroup2).get(), equalTo(resourceProfile2));
    assertThat(streamGraph.getSlotSharingGroupResource(StreamGraphGenerator.DEFAULT_SLOT_SHARING_GROUP).get(), equalTo(resourceProfile3));
}

Example 24 with Transformation

use of org.apache.flink.api.dag.Transformation in project flink by apache.

the class StreamGraphGeneratorTest method testEnableSlotSharing.

/**
 * Test slot sharing is enabled.
 */
@Test
public void testEnableSlotSharing() {
    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    DataStream<Integer> sourceDataStream = env.fromElements(1, 2, 3);
    DataStream<Integer> mapDataStream = sourceDataStream.map(x -> x + 1);
    final List<Transformation<?>> transformations = new ArrayList<>();
    transformations.add(sourceDataStream.getTransformation());
    transformations.add(mapDataStream.getTransformation());
    // all stream nodes share default group by default
    StreamGraph streamGraph = new StreamGraphGenerator(transformations, env.getConfig(), env.getCheckpointConfig()).generate();
    Collection<StreamNode> streamNodes = streamGraph.getStreamNodes();
    for (StreamNode streamNode : streamNodes) {
        assertEquals(StreamGraphGenerator.DEFAULT_SLOT_SHARING_GROUP, streamNode.getSlotSharingGroup());
    }
}

Example 25 with Transformation

use of org.apache.flink.api.dag.Transformation in project flink by apache.

the class BatchExecHashWindowAggregate 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 aggInfos = AggregateUtil.transformToBatchAggregateInfoList(aggInputRowType, JavaScalaConversionUtil.toScala(Arrays.asList(aggCalls)), // aggCallNeedRetractions
    null, // orderKeyIndexes
    null);
    final RowType inputRowType = (RowType) inputEdge.getOutputType();
    final HashWindowCodeGenerator hashWindowCodeGenerator = new HashWindowCodeGenerator(new CodeGeneratorContext(config.getTableConfig()), planner.getRelBuilder(), window, inputTimeFieldIndex, inputTimeIsDate, JavaScalaConversionUtil.toScala(Arrays.asList(namedWindowProperties)), aggInfos, inputRowType, grouping, auxGrouping, enableAssignPane, isMerge, isFinal);
    final int groupBufferLimitSize = config.get(ExecutionConfigOptions.TABLE_EXEC_WINDOW_AGG_BUFFER_SIZE_LIMIT);
    final Tuple2<Long, Long> windowSizeAndSlideSize = WindowCodeGenerator.getWindowDef(window);
    final GeneratedOperator<OneInputStreamOperator<RowData, RowData>> generatedOperator = hashWindowCodeGenerator.gen(inputRowType, (RowType) getOutputType(), groupBufferLimitSize, // windowStart
    0, windowSizeAndSlideSize.f0, windowSizeAndSlideSize.f1);
    final long managedMemory = config.get(ExecutionConfigOptions.TABLE_EXEC_RESOURCE_HASH_AGG_MEMORY).getBytes();
    return ExecNodeUtil.createOneInputTransformation(inputTransform, createTransformationName(config), createTransformationDescription(config), new CodeGenOperatorFactory<>(generatedOperator), InternalTypeInfo.of(getOutputType()), inputTransform.getParallelism(), managedMemory);
}