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Example 31 with LogicalType

use of org.apache.flink.table.types.logical.LogicalType 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;
}
Also used : OneInputTransformation(org.apache.flink.streaming.api.transformations.OneInputTransformation) Transformation(org.apache.flink.api.dag.Transformation) TableException(org.apache.flink.table.api.TableException) AggregateInfoList(org.apache.flink.table.planner.plan.utils.AggregateInfoList) ExecEdge(org.apache.flink.table.planner.plan.nodes.exec.ExecEdge) RowType(org.apache.flink.table.types.logical.RowType) LogicalType(org.apache.flink.table.types.logical.LogicalType) GeneratedAggsHandleFunction(org.apache.flink.table.runtime.generated.GeneratedAggsHandleFunction) EqualiserCodeGenerator(org.apache.flink.table.planner.codegen.EqualiserCodeGenerator) GeneratedRecordEqualiser(org.apache.flink.table.runtime.generated.GeneratedRecordEqualiser) RowData(org.apache.flink.table.data.RowData) RowDataKeySelector(org.apache.flink.table.runtime.keyselector.RowDataKeySelector) MiniBatchGlobalGroupAggFunction(org.apache.flink.table.runtime.operators.aggregate.MiniBatchGlobalGroupAggFunction)

Example 32 with LogicalType

use of org.apache.flink.table.types.logical.LogicalType 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;
}
Also used : OneInputTransformation(org.apache.flink.streaming.api.transformations.OneInputTransformation) Transformation(org.apache.flink.api.dag.Transformation) AggregateInfoList(org.apache.flink.table.planner.plan.utils.AggregateInfoList) ExecEdge(org.apache.flink.table.planner.plan.nodes.exec.ExecEdge) CodeGeneratorContext(org.apache.flink.table.planner.codegen.CodeGeneratorContext) GroupAggFunction(org.apache.flink.table.runtime.operators.aggregate.GroupAggFunction) MiniBatchGroupAggFunction(org.apache.flink.table.runtime.operators.aggregate.MiniBatchGroupAggFunction) MiniBatchGroupAggFunction(org.apache.flink.table.runtime.operators.aggregate.MiniBatchGroupAggFunction) RowType(org.apache.flink.table.types.logical.RowType) AggsHandlerCodeGenerator(org.apache.flink.table.planner.codegen.agg.AggsHandlerCodeGenerator) LogicalType(org.apache.flink.table.types.logical.LogicalType) GeneratedAggsHandleFunction(org.apache.flink.table.runtime.generated.GeneratedAggsHandleFunction) EqualiserCodeGenerator(org.apache.flink.table.planner.codegen.EqualiserCodeGenerator) GeneratedRecordEqualiser(org.apache.flink.table.runtime.generated.GeneratedRecordEqualiser) RowData(org.apache.flink.table.data.RowData) RowDataKeySelector(org.apache.flink.table.runtime.keyselector.RowDataKeySelector)

Example 33 with LogicalType

use of org.apache.flink.table.types.logical.LogicalType in project flink by apache.

the class StreamExecGroupWindowAggregate method translateToPlanInternal.

@SuppressWarnings("unchecked")
@Override
protected Transformation<RowData> translateToPlanInternal(PlannerBase planner, ExecNodeConfig config) {
    final boolean isCountWindow;
    if (window instanceof TumblingGroupWindow) {
        isCountWindow = hasRowIntervalType(((TumblingGroupWindow) window).size());
    } else if (window instanceof SlidingGroupWindow) {
        isCountWindow = hasRowIntervalType(((SlidingGroupWindow) window).size());
    } else {
        isCountWindow = false;
    }
    if (isCountWindow && grouping.length > 0 && config.getStateRetentionTime() < 0) {
        LOGGER.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 int inputTimeFieldIndex;
    if (isRowtimeAttribute(window.timeAttribute())) {
        inputTimeFieldIndex = timeFieldIndex(FlinkTypeFactory.INSTANCE().buildRelNodeRowType(inputRowType), planner.getRelBuilder(), window.timeAttribute());
        if (inputTimeFieldIndex < 0) {
            throw new TableException("Group window must defined on a time attribute, " + "but the time attribute can't be found.\n" + "This should never happen. Please file an issue.");
        }
    } else {
        inputTimeFieldIndex = -1;
    }
    final ZoneId shiftTimeZone = TimeWindowUtil.getShiftTimeZone(window.timeAttribute().getOutputDataType().getLogicalType(), config.getLocalTimeZone());
    final boolean[] aggCallNeedRetractions = new boolean[aggCalls.length];
    Arrays.fill(aggCallNeedRetractions, needRetraction);
    final AggregateInfoList aggInfoList = transformToStreamAggregateInfoList(inputRowType, JavaScalaConversionUtil.toScala(Arrays.asList(aggCalls)), aggCallNeedRetractions, needRetraction, // isStateBackendDataViews
    true, // needDistinctInfo
    true);
    final GeneratedClass<?> aggCodeGenerator = createAggsHandler(aggInfoList, config, planner.getRelBuilder(), inputRowType.getChildren(), shiftTimeZone);
    final LogicalType[] aggResultTypes = extractLogicalTypes(aggInfoList.getActualValueTypes());
    final LogicalType[] windowPropertyTypes = Arrays.stream(namedWindowProperties).map(p -> p.getProperty().getResultType()).toArray(LogicalType[]::new);
    final EqualiserCodeGenerator generator = new EqualiserCodeGenerator(ArrayUtils.addAll(aggResultTypes, windowPropertyTypes));
    final GeneratedRecordEqualiser equaliser = generator.generateRecordEqualiser("WindowValueEqualiser");
    final LogicalType[] aggValueTypes = extractLogicalTypes(aggInfoList.getActualValueTypes());
    final LogicalType[] accTypes = extractLogicalTypes(aggInfoList.getAccTypes());
    final int inputCountIndex = aggInfoList.getIndexOfCountStar();
    final WindowOperator<?, ?> operator = createWindowOperator(config, aggCodeGenerator, equaliser, accTypes, windowPropertyTypes, aggValueTypes, inputRowType.getChildren().toArray(new LogicalType[0]), inputTimeFieldIndex, shiftTimeZone, inputCountIndex);
    final OneInputTransformation<RowData, RowData> transform = ExecNodeUtil.createOneInputTransformation(inputTransform, createTransformationMeta(GROUP_WINDOW_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;
}
Also used : AggregateUtil.isProctimeAttribute(org.apache.flink.table.planner.plan.utils.AggregateUtil.isProctimeAttribute) DataType(org.apache.flink.table.types.DataType) Arrays(java.util.Arrays) InputProperty(org.apache.flink.table.planner.plan.nodes.exec.InputProperty) JsonCreator(org.apache.flink.shaded.jackson2.com.fasterxml.jackson.annotation.JsonCreator) LoggerFactory(org.slf4j.LoggerFactory) TumblingGroupWindow(org.apache.flink.table.planner.plan.logical.TumblingGroupWindow) FlinkTypeFactory(org.apache.flink.table.planner.calcite.FlinkTypeFactory) AggsHandlerCodeGenerator(org.apache.flink.table.planner.codegen.agg.AggsHandlerCodeGenerator) ExecNode(org.apache.flink.table.planner.plan.nodes.exec.ExecNode) SessionGroupWindow(org.apache.flink.table.planner.plan.logical.SessionGroupWindow) RelBuilder(org.apache.calcite.tools.RelBuilder) KeySelectorUtil(org.apache.flink.table.planner.plan.utils.KeySelectorUtil) Duration(java.time.Duration) 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AggregateUtil.hasTimeIntervalType(org.apache.flink.table.planner.plan.utils.AggregateUtil.hasTimeIntervalType) LogicalTypeDataTypeConverter(org.apache.flink.table.runtime.types.LogicalTypeDataTypeConverter) WindowOperator(org.apache.flink.table.runtime.operators.window.WindowOperator) AggregateUtil.isRowtimeAttribute(org.apache.flink.table.planner.plan.utils.AggregateUtil.isRowtimeAttribute) ArrayUtils(org.apache.commons.lang3.ArrayUtils) RowType(org.apache.flink.table.types.logical.RowType) ExecNodeUtil(org.apache.flink.table.planner.plan.nodes.exec.utils.ExecNodeUtil) AggregateUtil.isTableAggregate(org.apache.flink.table.planner.plan.utils.AggregateUtil.isTableAggregate) ReadableConfig(org.apache.flink.configuration.ReadableConfig) FieldReferenceExpression(org.apache.flink.table.expressions.FieldReferenceExpression) FlinkVersion(org.apache.flink.FlinkVersion) TimeWindow(org.apache.flink.table.runtime.operators.window.TimeWindow) 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Example 34 with LogicalType

use of org.apache.flink.table.types.logical.LogicalType in project flink by apache.

the class StreamExecMatch 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 inputRowType = (RowType) inputEdge.getOutputType();
    checkOrderKeys(inputRowType);
    final EventComparator<RowData> eventComparator = createEventComparator(config, inputRowType);
    final Transformation<RowData> timestampedInputTransform = translateOrder(inputTransform, inputRowType);
    final Tuple2<Pattern<RowData, RowData>, List<String>> cepPatternAndNames = translatePattern(matchSpec, config.getTableConfig(), planner.getRelBuilder(), inputRowType);
    final Pattern<RowData, RowData> cepPattern = cepPatternAndNames.f0;
    // TODO remove this once it is supported in CEP library
    if (NFACompiler.canProduceEmptyMatches(cepPattern)) {
        throw new TableException("Patterns that can produce empty matches are not supported. There must be at least one non-optional state.");
    }
    // TODO remove this once it is supported in CEP library
    if (cepPattern.getQuantifier().hasProperty(Quantifier.QuantifierProperty.GREEDY)) {
        throw new TableException("Greedy quantifiers are not allowed as the last element of a Pattern yet. " + "Finish your pattern with either a simple variable or reluctant quantifier.");
    }
    if (matchSpec.isAllRows()) {
        throw new TableException("All rows per match mode is not supported yet.");
    }
    final int[] partitionKeys = matchSpec.getPartition().getFieldIndices();
    final SortSpec.SortFieldSpec timeOrderField = matchSpec.getOrderKeys().getFieldSpec(0);
    final LogicalType timeOrderFieldType = inputRowType.getTypeAt(timeOrderField.getFieldIndex());
    final boolean isProctime = TypeCheckUtils.isProcTime(timeOrderFieldType);
    final InternalTypeInfo<RowData> inputTypeInfo = (InternalTypeInfo<RowData>) inputTransform.getOutputType();
    final TypeSerializer<RowData> inputSerializer = inputTypeInfo.createSerializer(planner.getExecEnv().getConfig());
    final NFACompiler.NFAFactory<RowData> nfaFactory = NFACompiler.compileFactory(cepPattern, false);
    final MatchCodeGenerator generator = new MatchCodeGenerator(new CodeGeneratorContext(config.getTableConfig()), planner.getRelBuilder(), // nullableInput
    false, JavaScalaConversionUtil.toScala(cepPatternAndNames.f1), JavaScalaConversionUtil.toScala(Optional.empty()), CodeGenUtils.DEFAULT_COLLECTOR_TERM());
    generator.bindInput(inputRowType, CodeGenUtils.DEFAULT_INPUT1_TERM(), JavaScalaConversionUtil.toScala(Optional.empty()));
    final PatternProcessFunctionRunner patternProcessFunction = generator.generateOneRowPerMatchExpression((RowType) getOutputType(), partitionKeys, matchSpec.getMeasures());
    final CepOperator<RowData, RowData, RowData> operator = new CepOperator<>(inputSerializer, isProctime, nfaFactory, eventComparator, cepPattern.getAfterMatchSkipStrategy(), patternProcessFunction, null);
    final OneInputTransformation<RowData, RowData> transform = ExecNodeUtil.createOneInputTransformation(timestampedInputTransform, createTransformationMeta(MATCH_TRANSFORMATION, config), operator, InternalTypeInfo.of(getOutputType()), timestampedInputTransform.getParallelism());
    final RowDataKeySelector selector = KeySelectorUtil.getRowDataSelector(partitionKeys, inputTypeInfo);
    transform.setStateKeySelector(selector);
    transform.setStateKeyType(selector.getProducedType());
    if (inputsContainSingleton()) {
        transform.setParallelism(1);
        transform.setMaxParallelism(1);
    }
    return transform;
}
Also used : OneInputTransformation(org.apache.flink.streaming.api.transformations.OneInputTransformation) Transformation(org.apache.flink.api.dag.Transformation) ExecEdge(org.apache.flink.table.planner.plan.nodes.exec.ExecEdge) RowType(org.apache.flink.table.types.logical.RowType) LogicalType(org.apache.flink.table.types.logical.LogicalType) NFACompiler(org.apache.flink.cep.nfa.compiler.NFACompiler) RowData(org.apache.flink.table.data.RowData) RowDataKeySelector(org.apache.flink.table.runtime.keyselector.RowDataKeySelector) List(java.util.List) ArrayList(java.util.ArrayList) Pattern(org.apache.flink.cep.pattern.Pattern) TableException(org.apache.flink.table.api.TableException) CodeGeneratorContext(org.apache.flink.table.planner.codegen.CodeGeneratorContext) InternalTypeInfo(org.apache.flink.table.runtime.typeutils.InternalTypeInfo) MatchCodeGenerator(org.apache.flink.table.planner.codegen.MatchCodeGenerator) PatternProcessFunctionRunner(org.apache.flink.table.runtime.operators.match.PatternProcessFunctionRunner) CepOperator(org.apache.flink.cep.operator.CepOperator) SortSpec(org.apache.flink.table.planner.plan.nodes.exec.spec.SortSpec)

Example 35 with LogicalType

use of org.apache.flink.table.types.logical.LogicalType in project flink by apache.

the class StreamExecMatch method translateOrder.

private Transformation<RowData> translateOrder(Transformation<RowData> inputTransform, RowType inputRowType) {
    SortSpec.SortFieldSpec timeOrderField = matchSpec.getOrderKeys().getFieldSpec(0);
    int timeOrderFieldIdx = timeOrderField.getFieldIndex();
    LogicalType timeOrderFieldType = inputRowType.getTypeAt(timeOrderFieldIdx);
    if (TypeCheckUtils.isRowTime(timeOrderFieldType)) {
        // copy the rowtime field into the StreamRecord timestamp field
        int precision = getPrecision(timeOrderFieldType);
        Transformation<RowData> transform = ExecNodeUtil.createOneInputTransformation(inputTransform, new TransformationMetadata(createTransformationUid(TIMESTAMP_INSERTER_TRANSFORMATION), "StreamRecordTimestampInserter", String.format("StreamRecordTimestampInserter(rowtime field: %s)", timeOrderFieldIdx)), new StreamRecordTimestampInserter(timeOrderFieldIdx, precision), inputTransform.getOutputType(), inputTransform.getParallelism());
        if (inputsContainSingleton()) {
            transform.setParallelism(1);
            transform.setMaxParallelism(1);
        }
        return transform;
    } else {
        return inputTransform;
    }
}
Also used : RowData(org.apache.flink.table.data.RowData) TransformationMetadata(org.apache.flink.table.planner.plan.nodes.exec.utils.TransformationMetadata) StreamRecordTimestampInserter(org.apache.flink.table.runtime.operators.sink.StreamRecordTimestampInserter) LogicalType(org.apache.flink.table.types.logical.LogicalType) SortSpec(org.apache.flink.table.planner.plan.nodes.exec.spec.SortSpec)

Aggregations

LogicalType (org.apache.flink.table.types.logical.LogicalType)192 DataType (org.apache.flink.table.types.DataType)53 RowType (org.apache.flink.table.types.logical.RowType)53 RowData (org.apache.flink.table.data.RowData)45 List (java.util.List)29 ArrayList (java.util.ArrayList)28 TableException (org.apache.flink.table.api.TableException)25 TimestampType (org.apache.flink.table.types.logical.TimestampType)25 Internal (org.apache.flink.annotation.Internal)21 IntType (org.apache.flink.table.types.logical.IntType)21 Map (java.util.Map)20 ValidationException (org.apache.flink.table.api.ValidationException)20 ArrayType (org.apache.flink.table.types.logical.ArrayType)19 DecimalType (org.apache.flink.table.types.logical.DecimalType)19 LocalZonedTimestampType (org.apache.flink.table.types.logical.LocalZonedTimestampType)17 Test (org.junit.Test)17 BigIntType (org.apache.flink.table.types.logical.BigIntType)16 LegacyTypeInformationType (org.apache.flink.table.types.logical.LegacyTypeInformationType)16 GenericRowData (org.apache.flink.table.data.GenericRowData)15 Arrays (java.util.Arrays)14