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

Example 51 with DataType

use of org.apache.flink.table.types.DataType in project flink by apache.

the class KafkaConnectorOptionsUtilTest method testInvalidKeyFormatPrefixProjection.

@Test
public void testInvalidKeyFormatPrefixProjection() {
    final DataType dataType = ROW(FIELD("k_part_1", INT()), FIELD("part_2", STRING()), FIELD("name", STRING()));
    final Map<String, String> options = createTestOptions();
    options.put("key.fields", "k_part_1;part_2");
    options.put("key.fields-prefix", "k_");
    final Configuration config = Configuration.fromMap(options);
    try {
        createKeyFormatProjection(config, dataType);
        fail();
    } catch (ValidationException e) {
        assertThat(e, hasMessage(equalTo("All fields in 'key.fields' must be prefixed with 'k_' when option " + "'key.fields-prefix' is set but field 'part_2' is not prefixed.")));
    }
}

Example 52 with DataType

use of org.apache.flink.table.types.DataType in project flink by apache.

the class CanalJsonDeserializationSchema method createJsonRowType.

// --------------------------------------------------------------------------------------------
private static RowType createJsonRowType(DataType physicalDataType, List<ReadableMetadata> readableMetadata) {
    // Canal JSON contains other information, e.g. "ts", "sql", but we don't need them
    DataType root = DataTypes.ROW(DataTypes.FIELD("data", DataTypes.ARRAY(physicalDataType)), DataTypes.FIELD("old", DataTypes.ARRAY(physicalDataType)), DataTypes.FIELD("type", DataTypes.STRING()), ReadableMetadata.DATABASE.requiredJsonField, ReadableMetadata.TABLE.requiredJsonField);
    // append fields that are required for reading metadata in the root
    final List<DataTypes.Field> rootMetadataFields = readableMetadata.stream().filter(m -> m != ReadableMetadata.DATABASE && m != ReadableMetadata.TABLE).map(m -> m.requiredJsonField).distinct().collect(Collectors.toList());
    return (RowType) DataTypeUtils.appendRowFields(root, rootMetadataFields).getLogicalType();
}

Example 53 with DataType

use of org.apache.flink.table.types.DataType in project flink by apache.

the class DebeziumJsonDeserializationSchema method createJsonRowType.

// --------------------------------------------------------------------------------------------
private static RowType createJsonRowType(DataType physicalDataType, List<ReadableMetadata> readableMetadata, boolean schemaInclude) {
    DataType payload = DataTypes.ROW(DataTypes.FIELD("before", physicalDataType), DataTypes.FIELD("after", physicalDataType), DataTypes.FIELD("op", DataTypes.STRING()));
    // append fields that are required for reading metadata in the payload
    final List<DataTypes.Field> payloadMetadataFields = readableMetadata.stream().filter(m -> m.isJsonPayload).map(m -> m.requiredJsonField).distinct().collect(Collectors.toList());
    payload = DataTypeUtils.appendRowFields(payload, payloadMetadataFields);
    DataType root = payload;
    if (schemaInclude) {
        // when Debezium Kafka connect enables "value.converter.schemas.enable",
        // the JSON will contain "schema" information and we need to extract data from
        // "payload".
        root = DataTypes.ROW(DataTypes.FIELD("payload", payload));
    }
    // append fields that are required for reading metadata in the root
    final List<DataTypes.Field> rootMetadataFields = readableMetadata.stream().filter(m -> !m.isJsonPayload).map(m -> m.requiredJsonField).distinct().collect(Collectors.toList());
    root = DataTypeUtils.appendRowFields(root, rootMetadataFields);
    return (RowType) root.getLogicalType();
}

Example 54 with DataType

use of org.apache.flink.table.types.DataType in project flink by apache.

the class MaxwellJsonDecodingFormat method createRuntimeDecoder.

@Override
public DeserializationSchema<RowData> createRuntimeDecoder(DynamicTableSource.Context context, DataType physicalDataType, int[][] projections) {
    physicalDataType = Projection.of(projections).project(physicalDataType);
    final List<ReadableMetadata> readableMetadata = metadataKeys.stream().map(k -> Stream.of(ReadableMetadata.values()).filter(rm -> rm.key.equals(k)).findFirst().orElseThrow(() -> new IllegalStateException(String.format("Could not find the requested metadata key: %s", k)))).collect(Collectors.toList());
    final List<DataTypes.Field> metadataFields = readableMetadata.stream().map(m -> DataTypes.FIELD(m.key, m.dataType)).collect(Collectors.toList());
    final DataType producedDataType = DataTypeUtils.appendRowFields(physicalDataType, metadataFields);
    final TypeInformation<RowData> producedTypeInfo = context.createTypeInformation(producedDataType);
    return new MaxwellJsonDeserializationSchema(physicalDataType, readableMetadata, producedTypeInfo, ignoreParseErrors, timestampFormat);
}

Example 55 with DataType

use of org.apache.flink.table.types.DataType in project flink by apache.

the class MaxwellJsonFormatFactory method createEncodingFormat.

@Override
public EncodingFormat<SerializationSchema<RowData>> createEncodingFormat(DynamicTableFactory.Context context, ReadableConfig formatOptions) {
    FactoryUtil.validateFactoryOptions(this, formatOptions);
    validateEncodingFormatOptions(formatOptions);
    TimestampFormat timestampFormat = JsonFormatOptionsUtil.getTimestampFormat(formatOptions);
    JsonFormatOptions.MapNullKeyMode mapNullKeyMode = JsonFormatOptionsUtil.getMapNullKeyMode(formatOptions);
    String mapNullKeyLiteral = formatOptions.get(JSON_MAP_NULL_KEY_LITERAL);
    final boolean encodeDecimalAsPlainNumber = formatOptions.get(ENCODE_DECIMAL_AS_PLAIN_NUMBER);
    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 MaxwellJsonSerializationSchema(rowType, timestampFormat, mapNullKeyMode, mapNullKeyLiteral, encodeDecimalAsPlainNumber);
        }
    };
}