use of org.apache.flink.table.planner.codegen.CodeGeneratorContext 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;
}
use of org.apache.flink.table.planner.codegen.CodeGeneratorContext 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);
}
use of org.apache.flink.table.planner.codegen.CodeGeneratorContext 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;
}
use of org.apache.flink.table.planner.codegen.CodeGeneratorContext in project flink by apache.
the class CommonExecLegacySink method translateToTransformation.
/**
* Translates {@link TableSink} into a {@link Transformation}.
*
* @param withChangeFlag Set to true to emit records with change flags.
* @return The {@link Transformation} that corresponds to the translated {@link TableSink}.
*/
@SuppressWarnings("unchecked")
private Transformation<T> translateToTransformation(PlannerBase planner, ExecNodeConfig config, boolean withChangeFlag) {
// if no change flags are requested, verify table is an insert-only (append-only) table.
if (!withChangeFlag && needRetraction) {
throw new TableException("Table is not an append-only table. " + "Use the toRetractStream() in order to handle add and retract messages.");
}
final ExecEdge inputEdge = getInputEdges().get(0);
final Transformation<RowData> inputTransform = (Transformation<RowData>) inputEdge.translateToPlan(planner);
final RowType inputRowType = (RowType) inputEdge.getOutputType();
final RowType convertedInputRowType = checkAndConvertInputTypeIfNeeded(inputRowType);
final DataType resultDataType = tableSink.getConsumedDataType();
if (CodeGenUtils.isInternalClass(resultDataType)) {
return (Transformation<T>) inputTransform;
} else {
final int rowtimeIndex = getRowtimeIndex(inputRowType);
final DataType physicalOutputType = TableSinkUtils.inferSinkPhysicalDataType(resultDataType, convertedInputRowType, withChangeFlag);
final TypeInformation<T> outputTypeInfo = SinkCodeGenerator.deriveSinkOutputTypeInfo(tableSink, physicalOutputType, withChangeFlag);
final CodeGenOperatorFactory<T> converterOperator = SinkCodeGenerator.generateRowConverterOperator(new CodeGeneratorContext(config.getTableConfig()), convertedInputRowType, tableSink, physicalOutputType, withChangeFlag, "SinkConversion", rowtimeIndex);
final String description = "SinkConversion To " + resultDataType.getConversionClass().getSimpleName();
return ExecNodeUtil.createOneInputTransformation(inputTransform, createFormattedTransformationName(description, "SinkConversion", config), createFormattedTransformationDescription(description, config), converterOperator, outputTypeInfo, inputTransform.getParallelism());
}
}
use of org.apache.flink.table.planner.codegen.CodeGeneratorContext in project flink by apache.
the class BatchExecSortMergeJoin method translateToPlanInternal.
@Override
@SuppressWarnings("unchecked")
protected Transformation<RowData> translateToPlanInternal(PlannerBase planner, ExecNodeConfig config) {
ExecEdge leftInputEdge = getInputEdges().get(0);
ExecEdge rightInputEdge = getInputEdges().get(1);
// get input types
RowType leftType = (RowType) leftInputEdge.getOutputType();
RowType rightType = (RowType) rightInputEdge.getOutputType();
LogicalType[] keyFieldTypes = IntStream.of(leftKeys).mapToObj(leftType::getTypeAt).toArray(LogicalType[]::new);
RowType keyType = RowType.of(keyFieldTypes);
GeneratedJoinCondition condFunc = JoinUtil.generateConditionFunction(config.getTableConfig(), nonEquiCondition, leftType, rightType);
long externalBufferMemory = config.get(ExecutionConfigOptions.TABLE_EXEC_RESOURCE_EXTERNAL_BUFFER_MEMORY).getBytes();
long sortMemory = config.get(ExecutionConfigOptions.TABLE_EXEC_RESOURCE_SORT_MEMORY).getBytes();
int externalBufferNum = 1;
if (joinType == FlinkJoinType.FULL) {
externalBufferNum = 2;
}
long managedMemory = externalBufferMemory * externalBufferNum + sortMemory * 2;
SortCodeGenerator leftSortGen = newSortGen(config, leftKeys, leftType);
SortCodeGenerator rightSortGen = newSortGen(config, rightKeys, rightType);
int[] keyPositions = IntStream.range(0, leftKeys.length).toArray();
SortMergeJoinOperator operator = new SortMergeJoinOperator(1.0 * externalBufferMemory / managedMemory, joinType, leftIsSmaller, condFunc, ProjectionCodeGenerator.generateProjection(new CodeGeneratorContext(config.getTableConfig()), "SMJProjection", leftType, keyType, leftKeys), ProjectionCodeGenerator.generateProjection(new CodeGeneratorContext(config.getTableConfig()), "SMJProjection", rightType, keyType, rightKeys), leftSortGen.generateNormalizedKeyComputer("LeftComputer"), leftSortGen.generateRecordComparator("LeftComparator"), rightSortGen.generateNormalizedKeyComputer("RightComputer"), rightSortGen.generateRecordComparator("RightComparator"), newSortGen(config, keyPositions, keyType).generateRecordComparator("KeyComparator"), filterNulls);
Transformation<RowData> leftInputTransform = (Transformation<RowData>) leftInputEdge.translateToPlan(planner);
Transformation<RowData> rightInputTransform = (Transformation<RowData>) rightInputEdge.translateToPlan(planner);
return ExecNodeUtil.createTwoInputTransformation(leftInputTransform, rightInputTransform, createTransformationName(config), createTransformationDescription(config), SimpleOperatorFactory.of(operator), InternalTypeInfo.of(getOutputType()), rightInputTransform.getParallelism(), managedMemory);
}
Aggregations