org.apache.flink.table.descriptors.Kafka Java Examples
The following examples show how to use
org.apache.flink.table.descriptors.Kafka.
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Example #1
Source File: KafkaTableSourceSinkFactoryTestBase.java From flink with Apache License 2.0 | 6 votes |
protected Map<String, String> createKafkaSourceProperties() { return new TestTableDescriptor( new Kafka() .version(getKafkaVersion()) .topic(TOPIC) .properties(KAFKA_PROPERTIES) .sinkPartitionerRoundRobin() // test if accepted although not needed .startFromSpecificOffsets(OFFSETS)) .withFormat(new TestTableFormat()) .withSchema( new Schema() .field(FRUIT_NAME, DataTypes.STRING()).from(NAME) .field(COUNT, DataTypes.DECIMAL(38, 18)) // no from so it must match with the input .field(EVENT_TIME, DataTypes.TIMESTAMP(3)).rowtime( new Rowtime().timestampsFromField(TIME).watermarksPeriodicAscending()) .field(PROC_TIME, DataTypes.TIMESTAMP(3)).proctime()) .toProperties(); }
Example #2
Source File: KafkaTableSourceSinkFactoryTestBase.java From flink with Apache License 2.0 | 6 votes |
protected Map<String, String> createKafkaSinkProperties() { return new TestTableDescriptor( new Kafka() .version(getKafkaVersion()) .topic(TOPIC) .properties(KAFKA_PROPERTIES) .sinkPartitionerFixed() .startFromSpecificOffsets(OFFSETS)) // test if they accepted although not needed .withFormat(new TestTableFormat()) .withSchema( new Schema() .field(FRUIT_NAME, DataTypes.STRING()) .field(COUNT, DataTypes.DECIMAL(10, 4)) .field(EVENT_TIME, DataTypes.TIMESTAMP(3))) .inAppendMode() .toProperties(); }
Example #3
Source File: KafkaTableSourceSinkFactoryTestBase.java From Flink-CEPplus with Apache License 2.0 | 4 votes |
@Test @SuppressWarnings("unchecked") public void testTableSource() { // prepare parameters for Kafka table source final TableSchema schema = TableSchema.builder() .field(FRUIT_NAME, Types.STRING()) .field(COUNT, Types.DECIMAL()) .field(EVENT_TIME, Types.SQL_TIMESTAMP()) .field(PROC_TIME, Types.SQL_TIMESTAMP()) .build(); final List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors = Collections.singletonList( new RowtimeAttributeDescriptor(EVENT_TIME, new ExistingField(TIME), new AscendingTimestamps())); final Map<String, String> fieldMapping = new HashMap<>(); fieldMapping.put(FRUIT_NAME, NAME); fieldMapping.put(NAME, NAME); fieldMapping.put(COUNT, COUNT); fieldMapping.put(TIME, TIME); final Map<KafkaTopicPartition, Long> specificOffsets = new HashMap<>(); specificOffsets.put(new KafkaTopicPartition(TOPIC, PARTITION_0), OFFSET_0); specificOffsets.put(new KafkaTopicPartition(TOPIC, PARTITION_1), OFFSET_1); final TestDeserializationSchema deserializationSchema = new TestDeserializationSchema( TableSchema.builder() .field(NAME, Types.STRING()) .field(COUNT, Types.DECIMAL()) .field(TIME, Types.SQL_TIMESTAMP()) .build() .toRowType() ); final KafkaTableSourceBase expected = getExpectedKafkaTableSource( schema, Optional.of(PROC_TIME), rowtimeAttributeDescriptors, fieldMapping, TOPIC, KAFKA_PROPERTIES, deserializationSchema, StartupMode.SPECIFIC_OFFSETS, specificOffsets); TableSourceUtil.validateTableSource(expected); // construct table source using descriptors and table source factory final TestTableDescriptor testDesc = new TestTableDescriptor( new Kafka() .version(getKafkaVersion()) .topic(TOPIC) .properties(KAFKA_PROPERTIES) .sinkPartitionerRoundRobin() // test if accepted although not needed .startFromSpecificOffsets(OFFSETS)) .withFormat(new TestTableFormat()) .withSchema( new Schema() .field(FRUIT_NAME, Types.STRING()).from(NAME) .field(COUNT, Types.DECIMAL()) // no from so it must match with the input .field(EVENT_TIME, Types.SQL_TIMESTAMP()).rowtime( new Rowtime().timestampsFromField(TIME).watermarksPeriodicAscending()) .field(PROC_TIME, Types.SQL_TIMESTAMP()).proctime()) .inAppendMode(); final Map<String, String> propertiesMap = testDesc.toProperties(); final TableSource<?> actualSource = TableFactoryService.find(StreamTableSourceFactory.class, propertiesMap) .createStreamTableSource(propertiesMap); assertEquals(expected, actualSource); // test Kafka consumer final KafkaTableSourceBase actualKafkaSource = (KafkaTableSourceBase) actualSource; final StreamExecutionEnvironmentMock mock = new StreamExecutionEnvironmentMock(); actualKafkaSource.getDataStream(mock); assertTrue(getExpectedFlinkKafkaConsumer().isAssignableFrom(mock.sourceFunction.getClass())); }
Example #4
Source File: KafkaTableSourceSinkFactoryTestBase.java From Flink-CEPplus with Apache License 2.0 | 4 votes |
/** * This test can be unified with the corresponding source test once we have fixed FLINK-9870. */ @Test public void testTableSink() { // prepare parameters for Kafka table sink final TableSchema schema = TableSchema.builder() .field(FRUIT_NAME, Types.STRING()) .field(COUNT, Types.DECIMAL()) .field(EVENT_TIME, Types.SQL_TIMESTAMP()) .build(); final KafkaTableSinkBase expected = getExpectedKafkaTableSink( schema, TOPIC, KAFKA_PROPERTIES, Optional.of(new FlinkFixedPartitioner<>()), new TestSerializationSchema(schema.toRowType())); // construct table sink using descriptors and table sink factory final TestTableDescriptor testDesc = new TestTableDescriptor( new Kafka() .version(getKafkaVersion()) .topic(TOPIC) .properties(KAFKA_PROPERTIES) .sinkPartitionerFixed() .startFromSpecificOffsets(OFFSETS)) // test if they accepted although not needed .withFormat(new TestTableFormat()) .withSchema( new Schema() .field(FRUIT_NAME, Types.STRING()) .field(COUNT, Types.DECIMAL()) .field(EVENT_TIME, Types.SQL_TIMESTAMP())) .inAppendMode(); final Map<String, String> propertiesMap = testDesc.toProperties(); final TableSink<?> actualSink = TableFactoryService.find(StreamTableSinkFactory.class, propertiesMap) .createStreamTableSink(propertiesMap); assertEquals(expected, actualSink); // test Kafka producer final KafkaTableSinkBase actualKafkaSink = (KafkaTableSinkBase) actualSink; final DataStreamMock streamMock = new DataStreamMock(new StreamExecutionEnvironmentMock(), schema.toRowType()); actualKafkaSink.emitDataStream(streamMock); assertTrue(getExpectedFlinkKafkaProducer().isAssignableFrom(streamMock.sinkFunction.getClass())); }
Example #5
Source File: KafkaTableSourceSinkFactoryTestBase.java From flink with Apache License 2.0 | 4 votes |
@Test @SuppressWarnings("unchecked") public void testTableSource() { // prepare parameters for Kafka table source final TableSchema schema = TableSchema.builder() .field(FRUIT_NAME, Types.STRING()) .field(COUNT, Types.DECIMAL()) .field(EVENT_TIME, Types.SQL_TIMESTAMP()) .field(PROC_TIME, Types.SQL_TIMESTAMP()) .build(); final List<RowtimeAttributeDescriptor> rowtimeAttributeDescriptors = Collections.singletonList( new RowtimeAttributeDescriptor(EVENT_TIME, new ExistingField(TIME), new AscendingTimestamps())); final Map<String, String> fieldMapping = new HashMap<>(); fieldMapping.put(FRUIT_NAME, NAME); fieldMapping.put(NAME, NAME); fieldMapping.put(COUNT, COUNT); fieldMapping.put(TIME, TIME); final Map<KafkaTopicPartition, Long> specificOffsets = new HashMap<>(); specificOffsets.put(new KafkaTopicPartition(TOPIC, PARTITION_0), OFFSET_0); specificOffsets.put(new KafkaTopicPartition(TOPIC, PARTITION_1), OFFSET_1); final TestDeserializationSchema deserializationSchema = new TestDeserializationSchema( TableSchema.builder() .field(NAME, Types.STRING()) .field(COUNT, Types.DECIMAL()) .field(TIME, Types.SQL_TIMESTAMP()) .build() .toRowType() ); final KafkaTableSourceBase expected = getExpectedKafkaTableSource( schema, Optional.of(PROC_TIME), rowtimeAttributeDescriptors, fieldMapping, TOPIC, KAFKA_PROPERTIES, deserializationSchema, StartupMode.SPECIFIC_OFFSETS, specificOffsets); TableSourceValidation.validateTableSource(expected); // construct table source using descriptors and table source factory final TestTableDescriptor testDesc = new TestTableDescriptor( new Kafka() .version(getKafkaVersion()) .topic(TOPIC) .properties(KAFKA_PROPERTIES) .sinkPartitionerRoundRobin() // test if accepted although not needed .startFromSpecificOffsets(OFFSETS)) .withFormat(new TestTableFormat()) .withSchema( new Schema() .field(FRUIT_NAME, Types.STRING()).from(NAME) .field(COUNT, Types.DECIMAL()) // no from so it must match with the input .field(EVENT_TIME, Types.SQL_TIMESTAMP()).rowtime( new Rowtime().timestampsFromField(TIME).watermarksPeriodicAscending()) .field(PROC_TIME, Types.SQL_TIMESTAMP()).proctime()) .inAppendMode(); final Map<String, String> propertiesMap = testDesc.toProperties(); final TableSource<?> actualSource = TableFactoryService.find(StreamTableSourceFactory.class, propertiesMap) .createStreamTableSource(propertiesMap); assertEquals(expected, actualSource); // test Kafka consumer final KafkaTableSourceBase actualKafkaSource = (KafkaTableSourceBase) actualSource; final StreamExecutionEnvironmentMock mock = new StreamExecutionEnvironmentMock(); actualKafkaSource.getDataStream(mock); assertTrue(getExpectedFlinkKafkaConsumer().isAssignableFrom(mock.sourceFunction.getClass())); }
Example #6
Source File: KafkaTableSourceSinkFactoryTestBase.java From flink with Apache License 2.0 | 4 votes |
/** * This test can be unified with the corresponding source test once we have fixed FLINK-9870. */ @Test public void testTableSink() { // prepare parameters for Kafka table sink final TableSchema schema = TableSchema.builder() .field(FRUIT_NAME, Types.STRING()) .field(COUNT, Types.DECIMAL()) .field(EVENT_TIME, Types.SQL_TIMESTAMP()) .build(); final KafkaTableSinkBase expected = getExpectedKafkaTableSink( schema, TOPIC, KAFKA_PROPERTIES, Optional.of(new FlinkFixedPartitioner<>()), new TestSerializationSchema(schema.toRowType())); // construct table sink using descriptors and table sink factory final TestTableDescriptor testDesc = new TestTableDescriptor( new Kafka() .version(getKafkaVersion()) .topic(TOPIC) .properties(KAFKA_PROPERTIES) .sinkPartitionerFixed() .startFromSpecificOffsets(OFFSETS)) // test if they accepted although not needed .withFormat(new TestTableFormat()) .withSchema( new Schema() .field(FRUIT_NAME, Types.STRING()) .field(COUNT, Types.DECIMAL()) .field(EVENT_TIME, Types.SQL_TIMESTAMP())) .inAppendMode(); final Map<String, String> propertiesMap = testDesc.toProperties(); final TableSink<?> actualSink = TableFactoryService.find(StreamTableSinkFactory.class, propertiesMap) .createStreamTableSink(propertiesMap); assertEquals(expected, actualSink); // test Kafka producer final KafkaTableSinkBase actualKafkaSink = (KafkaTableSinkBase) actualSink; final DataStreamMock streamMock = new DataStreamMock(new StreamExecutionEnvironmentMock(), schema.toRowType()); actualKafkaSink.emitDataStream(streamMock); assertTrue(getExpectedFlinkKafkaProducer().isAssignableFrom(streamMock.sinkFunction.getClass())); }