Examples with RowType org.apache.flink.table.types.logical.RowType used on opensource projects

Example 41 with RowType

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

the class DebeziumAvroFormatFactory method createEncodingFormat.

@Override
public EncodingFormat<SerializationSchema<RowData>> createEncodingFormat(DynamicTableFactory.Context context, ReadableConfig formatOptions) {
    FactoryUtil.validateFactoryOptions(this, formatOptions);
    String schemaRegistryURL = formatOptions.get(URL);
    Optional<String> subject = formatOptions.getOptional(SUBJECT);
    Map<String, ?> optionalPropertiesMap = buildOptionalPropertiesMap(formatOptions);
    if (!subject.isPresent()) {
        throw new ValidationException(String.format("Option '%s.%s' is required for serialization", IDENTIFIER, SUBJECT.key()));
    }
    return new EncodingFormat<SerializationSchema<RowData>>() {

        @Override
        public ChangelogMode getChangelogMode() {
            return ChangelogMode.newBuilder().addContainedKind(RowKind.INSERT).addContainedKind(RowKind.UPDATE_BEFORE).addContainedKind(RowKind.UPDATE_AFTER).addContainedKind(RowKind.DELETE).build();
        }

        @Override
        public SerializationSchema<RowData> createRuntimeEncoder(DynamicTableSink.Context context, DataType consumedDataType) {
            final RowType rowType = (RowType) consumedDataType.getLogicalType();
            return new DebeziumAvroSerializationSchema(rowType, schemaRegistryURL, subject.get(), optionalPropertiesMap);
        }
    };
}

Example 42 with RowType

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

the class DebeziumAvroFormatFactory method createDecodingFormat.

@Override
public DecodingFormat<DeserializationSchema<RowData>> createDecodingFormat(DynamicTableFactory.Context context, ReadableConfig formatOptions) {
    FactoryUtil.validateFactoryOptions(this, formatOptions);
    String schemaRegistryURL = formatOptions.get(URL);
    Map<String, ?> optionalPropertiesMap = buildOptionalPropertiesMap(formatOptions);
    return new ProjectableDecodingFormat<DeserializationSchema<RowData>>() {

        @Override
        public DeserializationSchema<RowData> createRuntimeDecoder(DynamicTableSource.Context context, DataType producedDataType, int[][] projections) {
            producedDataType = Projection.of(projections).project(producedDataType);
            final RowType rowType = (RowType) producedDataType.getLogicalType();
            final TypeInformation<RowData> producedTypeInfo = context.createTypeInformation(producedDataType);
            return new DebeziumAvroDeserializationSchema(rowType, producedTypeInfo, schemaRegistryURL, optionalPropertiesMap);
        }

        @Override
        public ChangelogMode getChangelogMode() {
            return ChangelogMode.newBuilder().addContainedKind(RowKind.INSERT).addContainedKind(RowKind.UPDATE_BEFORE).addContainedKind(RowKind.UPDATE_AFTER).addContainedKind(RowKind.DELETE).build();
        }
    };
}

Example 43 with RowType

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

the class AbstractBatchArrowPythonAggregateFunctionOperatorTest method getTestHarness.

public OneInputStreamOperatorTestHarness<RowData, RowData> getTestHarness(Configuration config) throws Exception {
    RowType inputType = getInputType();
    RowType outputType = getOutputType();
    AbstractArrowPythonAggregateFunctionOperator operator = getTestOperator(config, new PythonFunctionInfo[] { new PythonFunctionInfo(PythonScalarFunctionOperatorTestBase.DummyPythonFunction.INSTANCE, new Integer[] { 0 }) }, inputType, outputType, new int[] { 0 }, new int[] { 2 });
    OneInputStreamOperatorTestHarness<RowData, RowData> testHarness = new OneInputStreamOperatorTestHarness<>(operator);
    testHarness.getStreamConfig().setManagedMemoryFractionOperatorOfUseCase(ManagedMemoryUseCase.PYTHON, 0.5);
    testHarness.setup(new RowDataSerializer(outputType));
    return testHarness;
}

Example 44 with RowType

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

the class BatchArrowPythonGroupWindowAggregateFunctionOperatorTest method getTestOperator.

@Override
public AbstractArrowPythonAggregateFunctionOperator getTestOperator(Configuration config, PythonFunctionInfo[] pandasAggregateFunctions, RowType inputRowType, RowType outputRowType, int[] groupingSet, int[] udafInputOffsets) {
    RowType udfInputType = (RowType) Projection.of(udafInputOffsets).project(inputRowType);
    RowType udfOutputType = (RowType) Projection.range(groupingSet.length, outputRowType.getFieldCount() - 2).project(outputRowType);
    // SlidingWindow(10000L, 5000L)
    return new PassThroughBatchArrowPythonGroupWindowAggregateFunctionOperator(config, pandasAggregateFunctions, inputRowType, udfInputType, udfOutputType, 3, 100000, 10000L, 5000L, new int[] { 0, 1 }, ProjectionCodeGenerator.generateProjection(CodeGeneratorContext.apply(new TableConfig()), "UdafInputProjection", inputRowType, udfInputType, udafInputOffsets), ProjectionCodeGenerator.generateProjection(CodeGeneratorContext.apply(new TableConfig()), "GroupKey", inputRowType, (RowType) Projection.of(groupingSet).project(inputRowType), groupingSet), ProjectionCodeGenerator.generateProjection(CodeGeneratorContext.apply(new TableConfig()), "GroupSet", inputRowType, (RowType) Projection.of(groupingSet).project(inputRowType), groupingSet));
}

Example 45 with RowType

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

the class AbstractStreamArrowPythonAggregateFunctionOperatorTest method getTestHarness.

public OneInputStreamOperatorTestHarness<RowData, RowData> getTestHarness(Configuration config) throws Exception {
    RowType inputType = getInputType();
    RowType outputType = getOutputType();
    AbstractArrowPythonAggregateFunctionOperator operator = getTestOperator(config, new PythonFunctionInfo[] { new PythonFunctionInfo(PythonScalarFunctionOperatorTestBase.DummyPythonFunction.INSTANCE, new Integer[] { 0 }) }, inputType, outputType, new int[] { 0 }, new int[] { 2 });
    int[] grouping = new int[] { 0 };
    RowDataKeySelector keySelector = KeySelectorUtil.getRowDataSelector(grouping, InternalTypeInfo.of(getInputType()));
    OneInputStreamOperatorTestHarness<RowData, RowData> testHarness = new KeyedOneInputStreamOperatorTestHarness<>(operator, keySelector, keySelector.getProducedType());
    testHarness.getStreamConfig().setManagedMemoryFractionOperatorOfUseCase(ManagedMemoryUseCase.PYTHON, 0.5);
    testHarness.setup(new RowDataSerializer(outputType));
    return testHarness;
}