org.apache.flink.table.sources.RowtimeAttributeDescriptor Java Examples

@Override
protected KafkaTableSourceBase createKafkaTableSource(
	TableSchema schema,
	Optional<String> proctimeAttribute,
	List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
	Map<String, String> fieldMapping,
	String topic,
	Properties properties,
	DeserializationSchema<Row> deserializationSchema,
	StartupMode startupMode,
	Map<KafkaTopicPartition, Long> specificStartupOffsets,
	long startupTimestampMillis) {

	return new KafkaTableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets,
		startupTimestampMillis);
}
 

/**
 * Creates a generic Kafka {@link StreamTableSource}.
 *
 * @param schema                      Schema of the produced table.
 * @param proctimeAttribute           Field name of the processing time attribute.
 * @param rowtimeAttributeDescriptors Descriptor for a rowtime attribute
 * @param fieldMapping                Mapping for the fields of the table schema to
 *                                    fields of the physical returned type.
 * @param topic                       Kafka topic to consume.
 * @param properties                  Properties for the Kafka consumer.
 * @param deserializationSchema       Deserialization schema for decoding records from Kafka.
 * @param startupMode                 Startup mode for the contained consumer.
 * @param specificStartupOffsets      Specific startup offsets; only relevant when startup
 *                                    mode is {@link StartupMode#SPECIFIC_OFFSETS}.
 */
public KafkaTableSource(
	TableSchema schema,
	Optional<String> proctimeAttribute,
	List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
	Optional<Map<String, String>> fieldMapping,
	String topic,
	Properties properties,
	DeserializationSchema<Row> deserializationSchema,
	StartupMode startupMode,
	Map<KafkaTopicPartition, Long> specificStartupOffsets,
	long startupTimestampMillis) {

	super(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		fieldMapping,
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets,
		startupTimestampMillis);
}
 

@Test
public void buildKafkaSource() throws Exception {
    File file = ResourceUtils.getFile("classpath:yaml/kafka-source.yaml");
    SourceDescriptor sourceDescriptor = BindPropertiesUtil.bindProperties(file, SourceDescriptor.class);
    Kafka010ConnectorDescriptor connectorDescriptor = BindPropertiesUtil.bindProperties(sourceDescriptor.getConnector(), Kafka010ConnectorDescriptor.class);
    assertThat(connectorDescriptor.getTopic()).isEqualTo("app-log");
    assertThat(connectorDescriptor.getStartupMode()).isEqualTo("earliest-offset");
    assertThat(connectorDescriptor.getSpecificOffsets().get("1")).isEqualTo("1000");
    assertThat(connectorDescriptor.getSpecificOffsets().get("2")).isEqualTo("3000");
    assertThat(connectorDescriptor.getProperties().get("bootstrap.servers")).isEqualTo("127.0.0.1:9092");
    assertThat(connectorDescriptor.getProperties().get("group.id")).isEqualTo("testGroup");
    assertThat(sourceDescriptor.getSchema()).isNotNull();
    FormatDescriptor formatDescriptor = sourceDescriptor.getFormat();
    KafkaTableSourceBase alchemyKafkaTableSource = connectorDescriptor.buildSource(sourceDescriptor.getSchema(), formatDescriptor);
    assertThat(alchemyKafkaTableSource).isNotNull();
    assertThat(alchemyKafkaTableSource.getProctimeAttribute()).isEqualTo("procTime");
    List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors = alchemyKafkaTableSource.getRowtimeAttributeDescriptors();
    assertThat(rowtimeAttributeDescriptors).isNotNull();
    assertThat(rowtimeAttributeDescriptors.get(0).getAttributeName()).isEqualTo("rowTime");
    assertThat(rowtimeAttributeDescriptors.get(0).getTimestampExtractor()).isInstanceOf(ExistingField.class);
    assertThat(rowtimeAttributeDescriptors.get(0).getWatermarkStrategy()).isInstanceOf(BoundedOutOfOrderTimestamps.class);
    DeserializationSchema deserializationSchema = formatDescriptor.transform(new Tuple2<>(alchemyKafkaTableSource.getReturnType(), true));
    assertThat(deserializationSchema).isInstanceOf(GrokRowDeserializationSchema.class);
}
 

@Override
protected KafkaTableSourceBase getExpectedKafkaTableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Map<String, String> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	return new Kafka011TableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets
	);
}
 

@Override KafkaTableSourceBase newTableSource(TableSchema schema, Optional<String> proctimeAttribute,
    List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors, Optional<Map<String, String>> fieldMapping,
    String topic, Properties properties, DeserializationSchema<Row> deserializationSchema, StartupMode startupMode,
    Map<KafkaTopicPartition, Long> specificStartupOffsets) {
    return  new KafkaTableSource(
        schema,
        proctimeAttribute,
        rowtimeAttributeDescriptors,
        fieldMapping,
        topic,
        properties,
        deserializationSchema,
        startupMode,
        specificStartupOffsets
    );
}
 

/**
 * Finds the rowtime attributes if defined.
 */
public static List<RowtimeAttributeDescriptor> deriveRowtimeAttributes(
		DescriptorProperties properties) {

	Map<String, String> names = properties.getIndexedProperty(SCHEMA, SCHEMA_NAME);

	List<RowtimeAttributeDescriptor> attributes = new ArrayList<>();

	// check for rowtime in every field
	for (int i = 0; i < names.size(); i++) {
		Optional<Tuple2<TimestampExtractor, WatermarkStrategy>> rowtimeComponents = RowtimeValidator
				.getRowtimeComponents(properties, SCHEMA + "." + i + ".");
		int index = i;
		// create descriptor
		rowtimeComponents.ifPresent(tuple2 -> attributes.add(new RowtimeAttributeDescriptor(
				properties.getString(SCHEMA + "." + index + "." + SCHEMA_NAME),
				tuple2.f0,
				tuple2.f1))
		);
	}

	return attributes;
}
 

private static void updateRowtimeIndicators(
		DefinedRowtimeAttributes source,
		String[] fieldNames,
		DataType[] types) {
	List<String> rowtimeAttributes = source.getRowtimeAttributeDescriptors()
		.stream()
		.map(RowtimeAttributeDescriptor::getAttributeName)
		.collect(Collectors.toList());

	for (int i = 0; i < fieldNames.length; i++) {
		if (rowtimeAttributes.contains(fieldNames[i])) {
			// bridged to timestamp for compatible flink-planner
			types[i] = new AtomicDataType(new TimestampType(true, TimestampKind.ROWTIME, 3))
					.bridgedTo(java.sql.Timestamp.class);
		}
	}
}
 

@Override KafkaTableSourceBase newTableSource(TableSchema schema, Optional<String> proctimeAttribute,
    List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors, Optional<Map<String, String>> fieldMapping,
    String topic, Properties properties, DeserializationSchema<Row> deserializationSchema, StartupMode startupMode,
    Map<KafkaTopicPartition, Long> specificStartupOffsets) {
    return new Kafka010TableSource(
        schema,
        proctimeAttribute,
        rowtimeAttributeDescriptors,
        fieldMapping,
        topic,
        properties,
        deserializationSchema,
        startupMode,
        specificStartupOffsets
    );
}
 

@Override
protected KafkaTableSourceBase getExpectedKafkaTableSource(
	TableSchema schema,
	Optional<String> proctimeAttribute,
	List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
	Map<String, String> fieldMapping,
	String topic,
	Properties properties,
	DeserializationSchema<Row> deserializationSchema,
	StartupMode startupMode,
	Map<KafkaTopicPartition, Long> specificStartupOffsets,
	long startupTimestamp) {

	return new KafkaTableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets,
		startupTimestamp);
}
 

/**
 * Creates a Kafka 0.11 {@link StreamTableSource}.
 *
 * @param schema                      Schema of the produced table.
 * @param proctimeAttribute           Field name of the processing time attribute.
 * @param rowtimeAttributeDescriptors Descriptor for a rowtime attribute
 * @param fieldMapping                Mapping for the fields of the table schema to
 *                                    fields of the physical returned type.
 * @param topic                       Kafka topic to consume.
 * @param properties                  Properties for the Kafka consumer.
 * @param deserializationSchema       Deserialization schema for decoding records from Kafka.
 * @param startupMode                 Startup mode for the contained consumer.
 * @param specificStartupOffsets      Specific startup offsets; only relevant when startup
 *                                    mode is {@link StartupMode#SPECIFIC_OFFSETS}.
 * @param startupTimestampMillis	  Startup timestamp for offsets; only relevant when startup
 *                                    mode is {@link StartupMode#TIMESTAMP}.
 */
public Kafka011TableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Optional<Map<String, String>> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets,
		long startupTimestampMillis) {

	super(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		fieldMapping,
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets,
		startupTimestampMillis);
}
 

@Override
protected KafkaTableSourceBase getExpectedKafkaTableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Map<String, String> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets,
		long startupTimestampMillis) {

	return new Kafka011TableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets,
		startupTimestampMillis
	);
}
 

/**
 * Creates a Kafka 0.10 {@link StreamTableSource}.
 *
 * @param schema                      Schema of the produced table.
 * @param proctimeAttribute           Field name of the processing time attribute.
 * @param rowtimeAttributeDescriptors Descriptor for a rowtime attribute
 * @param fieldMapping                Mapping for the fields of the table schema to
 *                                    fields of the physical returned type.
 * @param topic                       Kafka topic to consume.
 * @param properties                  Properties for the Kafka consumer.
 * @param deserializationSchema       Deserialization schema for decoding records from Kafka.
 * @param startupMode                 Startup mode for the contained consumer.
 * @param specificStartupOffsets      Specific startup offsets; only relevant when startup
 *                                    mode is {@link StartupMode#SPECIFIC_OFFSETS}.
 * @param startupTimestampMillis	  Startup timestamp for offsets; only relevant when startup
 *                                    mode is {@link StartupMode#TIMESTAMP}.
 */
public Kafka010TableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Optional<Map<String, String>> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets,
		long startupTimestampMillis) {

	super(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		fieldMapping,
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets,
		startupTimestampMillis);
}
 

@Override
protected KafkaTableSourceBase getExpectedKafkaTableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Map<String, String> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets,
		long startupTimestampMillis) {

	return new Kafka010TableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets,
		startupTimestampMillis
	);
}
 

/**
 * Creates a generic Kafka {@link StreamTableSource}.
 *
 * @param schema                      Schema of the produced table.
 * @param proctimeAttribute           Field name of the processing time attribute.
 * @param rowtimeAttributeDescriptors Descriptor for a rowtime attribute
 * @param fieldMapping                Mapping for the fields of the table schema to
 *                                    fields of the physical returned type.
 * @param topic                       Kafka topic to consume.
 * @param properties                  Properties for the Kafka consumer.
 * @param deserializationSchema       Deserialization schema for decoding records from Kafka.
 * @param startupMode                 Startup mode for the contained consumer.
 * @param specificStartupOffsets      Specific startup offsets; only relevant when startup
 *                                    mode is {@link StartupMode#SPECIFIC_OFFSETS}.
 * @param startupTimestampMillis	  Startup timestamp for offsets; only relevant when startup
 *                                    mode is {@link StartupMode#TIMESTAMP}.
 */
protected KafkaTableSourceBase(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Optional<Map<String, String>> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets,
		long startupTimestampMillis) {
	this.schema = TableSchemaUtils.checkNoGeneratedColumns(schema);
	this.proctimeAttribute = validateProctimeAttribute(proctimeAttribute);
	this.rowtimeAttributeDescriptors = validateRowtimeAttributeDescriptors(rowtimeAttributeDescriptors);
	this.fieldMapping = fieldMapping;
	this.topic = Preconditions.checkNotNull(topic, "Topic must not be null.");
	this.properties = Preconditions.checkNotNull(properties, "Properties must not be null.");
	this.deserializationSchema = Preconditions.checkNotNull(
		deserializationSchema, "Deserialization schema must not be null.");
	this.startupMode = Preconditions.checkNotNull(startupMode, "Startup mode must not be null.");
	this.specificStartupOffsets = Preconditions.checkNotNull(
		specificStartupOffsets, "Specific offsets must not be null.");
	this.startupTimestampMillis = startupTimestampMillis;
}
 

@Override
public StreamTableSink<Row> createStreamTableSink(Map<String, String> properties) {
	final DescriptorProperties descriptorProperties = getValidatedProperties(properties);

	final TableSchema schema = TableSchemaUtils.getPhysicalSchema(
		descriptorProperties.getTableSchema(SCHEMA));
	final String topic = descriptorProperties.getString(CONNECTOR_TOPIC);
	final Optional<String> proctime = SchemaValidator.deriveProctimeAttribute(descriptorProperties);
	final List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors =
		SchemaValidator.deriveRowtimeAttributes(descriptorProperties);

	// see also FLINK-9870
	if (proctime.isPresent() || !rowtimeAttributeDescriptors.isEmpty() ||
			checkForCustomFieldMapping(descriptorProperties, schema)) {
		throw new TableException("Time attributes and custom field mappings are not supported yet.");
	}

	return createKafkaTableSink(
		schema,
		topic,
		getKafkaProperties(descriptorProperties),
		getFlinkKafkaPartitioner(descriptorProperties),
		getSerializationSchema(properties));
}
 

/**
 * Finds the rowtime attributes if defined.
 */
public static List<RowtimeAttributeDescriptor> deriveRowtimeAttributes(
		DescriptorProperties properties) {

	Map<String, String> names = properties.getIndexedProperty(SCHEMA, SCHEMA_NAME);

	List<RowtimeAttributeDescriptor> attributes = new ArrayList<>();

	// check for rowtime in every field
	for (int i = 0; i < names.size(); i++) {
		Optional<Tuple2<TimestampExtractor, WatermarkStrategy>> rowtimeComponents = RowtimeValidator
				.getRowtimeComponents(properties, SCHEMA + "." + i + ".");
		int index = i;
		// create descriptor
		rowtimeComponents.ifPresent(tuple2 -> attributes.add(new RowtimeAttributeDescriptor(
				properties.getString(SCHEMA + "." + index + "." + SCHEMA_NAME),
				tuple2.f0,
				tuple2.f1))
		);
	}

	return attributes;
}
 

@Override
public StreamTableSink<Row> createStreamTableSink(Map<String, String> properties) {
	final DescriptorProperties descriptorProperties = getValidatedProperties(properties);

	final TableSchema schema = descriptorProperties.getTableSchema(SCHEMA);
	final String topic = descriptorProperties.getString(CONNECTOR_TOPIC);
	final Optional<String> proctime = SchemaValidator.deriveProctimeAttribute(descriptorProperties);
	final List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors =
		SchemaValidator.deriveRowtimeAttributes(descriptorProperties);

	// see also FLINK-9870
	if (proctime.isPresent() || !rowtimeAttributeDescriptors.isEmpty() ||
			checkForCustomFieldMapping(descriptorProperties, schema)) {
		throw new TableException("Time attributes and custom field mappings are not supported yet.");
	}

	return createKafkaTableSink(
		schema,
		topic,
		getKafkaProperties(descriptorProperties),
		getFlinkKafkaPartitioner(descriptorProperties),
		getSerializationSchema(properties));
}
 

/**
 * Creates a generic Kafka {@link StreamTableSource}.
 *
 * @param schema                      Schema of the produced table.
 * @param proctimeAttribute           Field name of the processing time attribute.
 * @param rowtimeAttributeDescriptors Descriptor for a rowtime attribute
 * @param fieldMapping                Mapping for the fields of the table schema to
 *                                    fields of the physical returned type.
 * @param topic                       Kafka topic to consume.
 * @param properties                  Properties for the Kafka consumer.
 * @param deserializationSchema       Deserialization schema for decoding records from Kafka.
 * @param startupMode                 Startup mode for the contained consumer.
 * @param specificStartupOffsets      Specific startup offsets; only relevant when startup
 *                                    mode is {@link StartupMode#SPECIFIC_OFFSETS}.
 */
protected KafkaTableSourceBase(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Optional<Map<String, String>> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {
	this.schema = Preconditions.checkNotNull(schema, "Schema must not be null.");
	this.proctimeAttribute = validateProctimeAttribute(proctimeAttribute);
	this.rowtimeAttributeDescriptors = validateRowtimeAttributeDescriptors(rowtimeAttributeDescriptors);
	this.fieldMapping = fieldMapping;
	this.topic = Preconditions.checkNotNull(topic, "Topic must not be null.");
	this.properties = Preconditions.checkNotNull(properties, "Properties must not be null.");
	this.deserializationSchema = Preconditions.checkNotNull(
		deserializationSchema, "Deserialization schema must not be null.");
	this.startupMode = Preconditions.checkNotNull(startupMode, "Startup mode must not be null.");
	this.specificStartupOffsets = Preconditions.checkNotNull(
		specificStartupOffsets, "Specific offsets must not be null.");
}
 

@Override
protected KafkaTableSourceBase getExpectedKafkaTableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Map<String, String> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	return new Kafka010TableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets
	);
}
 

/**
 * Creates a Kafka 0.10 {@link StreamTableSource}.
 *
 * @param schema                      Schema of the produced table.
 * @param proctimeAttribute           Field name of the processing time attribute.
 * @param rowtimeAttributeDescriptors Descriptor for a rowtime attribute
 * @param fieldMapping                Mapping for the fields of the table schema to
 *                                    fields of the physical returned type.
 * @param topic                       Kafka topic to consume.
 * @param properties                  Properties for the Kafka consumer.
 * @param deserializationSchema       Deserialization schema for decoding records from Kafka.
 * @param startupMode                 Startup mode for the contained consumer.
 * @param specificStartupOffsets      Specific startup offsets; only relevant when startup
 *                                    mode is {@link StartupMode#SPECIFIC_OFFSETS}.
 */
public Kafka010TableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Optional<Map<String, String>> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	super(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		fieldMapping,
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets);
}
 

@Override
protected KafkaTableSourceBase createKafkaTableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Map<String, String> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	return new Kafka010TableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets);
}
 

@Override
protected KafkaTableSourceBase createKafkaTableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Map<String, String> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	return new Kafka09TableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets);
}
 

/**
 * Creates a Kafka 0.11 {@link StreamTableSource}.
 *
 * @param schema                      Schema of the produced table.
 * @param proctimeAttribute           Field name of the processing time attribute.
 * @param rowtimeAttributeDescriptors Descriptor for a rowtime attribute
 * @param fieldMapping                Mapping for the fields of the table schema to
 *                                    fields of the physical returned type.
 * @param topic                       Kafka topic to consume.
 * @param properties                  Properties for the Kafka consumer.
 * @param deserializationSchema       Deserialization schema for decoding records from Kafka.
 * @param startupMode                 Startup mode for the contained consumer.
 * @param specificStartupOffsets      Specific startup offsets; only relevant when startup
 *                                    mode is {@link StartupMode#SPECIFIC_OFFSETS}.
 */
public Kafka011TableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Optional<Map<String, String>> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	super(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		fieldMapping,
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets);
}
 

@Override
protected KafkaTableSourceBase createKafkaTableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Map<String, String> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	return new Kafka011TableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets);
}
 

@Override
protected KafkaTableSourceBase getExpectedKafkaTableSource(
	TableSchema schema,
	Optional<String> proctimeAttribute,
	List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
	Map<String, String> fieldMapping,
	String topic,
	Properties properties,
	DeserializationSchema<Row> deserializationSchema,
	StartupMode startupMode,
	Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	return new KafkaTableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets);
}
 

@Override
protected KafkaTableSourceBase createKafkaTableSource(
	TableSchema schema,
	Optional<String> proctimeAttribute,
	List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
	Map<String, String> fieldMapping,
	String topic,
	Properties properties,
	DeserializationSchema<Row> deserializationSchema,
	StartupMode startupMode,
	Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	return new KafkaTableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets);
}
 

@Override
protected KafkaTableSourceBase getExpectedKafkaTableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Map<String, String> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	return new Kafka08TableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets
	);
}
 

@Override
protected KafkaTableSourceBase createKafkaTableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Map<String, String> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	return new Kafka08TableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets);
}
 

/**
 * Creates a Kafka 0.8 {@link StreamTableSource}.
 *
 * @param schema                      Schema of the produced table.
 * @param proctimeAttribute           Field name of the processing time attribute.
 * @param rowtimeAttributeDescriptors Descriptor for a rowtime attribute
 * @param fieldMapping                Mapping for the fields of the table schema to
 *                                    fields of the physical returned type.
 * @param topic                       Kafka topic to consume.
 * @param properties                  Properties for the Kafka consumer.
 * @param deserializationSchema       Deserialization schema for decoding records from Kafka.
 * @param startupMode                 Startup mode for the contained consumer.
 * @param specificStartupOffsets      Specific startup offsets; only relevant when startup
 *                                    mode is {@link StartupMode#SPECIFIC_OFFSETS}.
 */
public Kafka08TableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Optional<Map<String, String>> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	super(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		fieldMapping,
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets);
}
 

@Override
protected KafkaTableSourceBase getExpectedKafkaTableSource(
		TableSchema schema,
		Optional<String> proctimeAttribute,
		List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors,
		Map<String, String> fieldMapping,
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		StartupMode startupMode,
		Map<KafkaTopicPartition, Long> specificStartupOffsets) {

	return new Kafka09TableSource(
		schema,
		proctimeAttribute,
		rowtimeAttributeDescriptors,
		Optional.of(fieldMapping),
		topic,
		properties,
		deserializationSchema,
		startupMode,
		specificStartupOffsets
	);
}