Java DeserializationSchema类代码示例

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
/**
 * Creates a generic Kafka {@link StreamTableSource}.
 *
 * @param topic                 Kafka topic to consume.
 * @param properties            Properties for the Kafka consumer.
 * @param deserializationSchema Deserialization schema to use for Kafka records.
 * @param fieldNames            Row field names.
 * @param fieldTypes            Row field types.
 */
KafkaTableSource(
        String topic,
        Properties properties,
        DeserializationSchema<Row> deserializationSchema,
        String[] fieldNames,
        TypeInformation<?>[] fieldTypes) {

    this.topic = Preconditions.checkNotNull(topic, "Topic");
    this.properties = Preconditions.checkNotNull(properties, "Properties");
    this.deserializationSchema = Preconditions.checkNotNull(deserializationSchema, "Deserialization schema");
    this.fieldNames = Preconditions.checkNotNull(fieldNames, "Field names");
    this.fieldTypes = Preconditions.checkNotNull(fieldTypes, "Field types");

    Preconditions.checkArgument(fieldNames.length == fieldTypes.length,
            "Number of provided field names and types does not match.");
    
    this.typeInfo = new RowTypeInfo(fieldTypes, fieldNames);
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
/**
 * Creates a generic Kafka {@link StreamTableSource}.
 *
 * @param topic                 Kafka topic to consume.
 * @param properties            Properties for the Kafka consumer.
 * @param deserializationSchema Deserialization schema to use for Kafka records.
 * @param fieldNames            Row field names.
 * @param fieldTypes            Row field types.
 */
KafkaTableSource(
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		String[] fieldNames,
		TypeInformation<?>[] fieldTypes) {

	this.topic = Preconditions.checkNotNull(topic, "Topic");
	this.properties = Preconditions.checkNotNull(properties, "Properties");
	this.deserializationSchema = Preconditions.checkNotNull(deserializationSchema, "Deserialization schema");
	this.fieldNames = Preconditions.checkNotNull(fieldNames, "Field names");
	this.fieldTypes = Preconditions.checkNotNull(fieldTypes, "Field types");

	Preconditions.checkArgument(fieldNames.length == fieldTypes.length,
			"Number of provided field names and types does not match.");
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
/**
 * Test case for {@link KafkaConsumerBuilder#deserializationSchema(org.apache.flink.streaming.util.serialization.DeserializationSchema)}
 * being provided a valid schema
 */
@Test
public void testDeserializationSchema_withValidInput() {
	DeserializationSchema<String> schema = new SimpleStringSchema();
	KafkaConsumerBuilder<String> builder = KafkaConsumerBuilder.getInstance();
	Assert.assertNull(builder.getDeserializationSchema());		
	builder = builder.deserializationSchema(schema);
	Assert.assertEquals(schema, builder.getDeserializationSchema());		
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
AMQSourceConfig(ActiveMQConnectionFactory connectionFactory, String destinationName,
                DeserializationSchema<OUT> deserializationSchema, RunningChecker runningChecker,
                DestinationType destinationType) {
    this.connectionFactory = Preconditions.checkNotNull(connectionFactory, "connectionFactory not set");
    this.destinationName = Preconditions.checkNotNull(destinationName, "destinationName not set");
    this.deserializationSchema = Preconditions.checkNotNull(deserializationSchema, "deserializationSchema not set");
    this.runningChecker = Preconditions.checkNotNull(runningChecker, "runningChecker not set");
    this.destinationType = Preconditions.checkNotNull(destinationType, "destinationType not set");
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
protected ZMQSource(ZMQConnectionConfig zmqConnectionConfig, String queueName,
					boolean usesCorrelationId, DeserializationSchema<OUT> deserializationSchema) {
	super(String.class);
	this.zmqConnectionConfig = zmqConnectionConfig;
	this.queueName = queueName;
	this.usesCorrelationId = usesCorrelationId;
	this.schema = deserializationSchema;
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
/**
 * Creates a Kafka 0.9 {@link StreamTableSource}.
 *
 * @param topic                 Kafka topic to consume.
 * @param properties            Properties for the Kafka consumer.
 * @param deserializationSchema Deserialization schema to use for Kafka records.
 * @param fieldNames            Row field names.
 * @param fieldTypes            Row field types.
 */
public Kafka09TableSource(
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		String[] fieldNames,
		TypeInformation<?>[] fieldTypes) {

	super(topic, properties, deserializationSchema, fieldNames, fieldTypes);
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
/**
 * Creates a Kafka 0.8 {@link StreamTableSource}.
 *
 * @param topic                 Kafka topic to consume.
 * @param properties            Properties for the Kafka consumer.
 * @param deserializationSchema Deserialization schema to use for Kafka records.
 * @param fieldNames            Row field names.
 * @param fieldTypes            Row field types.
 */
public Kafka08TableSource(
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		String[] fieldNames,
		TypeInformation<?>[] fieldTypes) {

	super(topic, properties, deserializationSchema, fieldNames, fieldTypes);
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
/**
 * Creates a Kafka 0.10 {@link StreamTableSource}.
 *
 * @param topic                 Kafka topic to consume.
 * @param properties            Properties for the Kafka consumer.
 * @param deserializationSchema Deserialization schema to use for Kafka records.
 * @param fieldNames            Row field names.
 * @param fieldTypes            Row field types.
 */
public Kafka010TableSource(
		String topic,
		Properties properties,
		DeserializationSchema<Row> deserializationSchema,
		String[] fieldNames,
		TypeInformation<?>[] fieldTypes) {

	super(topic, properties, deserializationSchema, fieldNames, fieldTypes);
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
private static void printTopic(String topicName, ConsumerConfig config,
							DeserializationSchema<?> deserializationSchema,
							int stopAfter) throws IOException {

	List<MessageAndMetadata<byte[], byte[]>> contents = readTopicToList(topicName, config, stopAfter);
	LOG.info("Printing contents of topic {} in consumer grouo {}", topicName, config.groupId());

	for (MessageAndMetadata<byte[], byte[]> message: contents) {
		Object out = deserializationSchema.deserialize(message.message());
		LOG.info("Message: partition: {} offset: {} msg: {}", message.partition(), message.offset(), out.toString());
	}
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
public ConstructorTestClass(RMQConnectionConfig rmqConnectionConfig,
							String queueName,
							boolean usesCorrelationId,
							DeserializationSchema<String> deserializationSchema) throws Exception {
	super(rmqConnectionConfig, queueName, usesCorrelationId, deserializationSchema);
	RMQConnectionConfig.Builder builder = new RMQConnectionConfig.Builder();
	builder.setHost("hostTest").setPort(999).setUserName("userTest").setPassword("passTest").setVirtualHost("/");
	factory = Mockito.spy(builder.build().getConnectionFactory());
	try {
		Mockito.doThrow(new RuntimeException()).when(factory).newConnection();
	} catch (IOException e) {
		fail("Failed to stub connection method");
	}
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
public FlinkConsumer(String topic, DeserializationSchema schema,
        Properties props) {
  super(topic, schema, props);
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
public DeserializationSchema<OUT> getDeserializationSchema() {
    return deserializationSchema;
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
public AMQSourceConfigBuilder<OUT> setDeserializationSchema(DeserializationSchema<OUT> deserializationSchema) {
    this.deserializationSchema = Preconditions.checkNotNull(deserializationSchema);
    return this;
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
@Override
FlinkKafkaConsumerBase<Row> getKafkaConsumer(String topic, Properties properties, DeserializationSchema<Row> deserializationSchema) {
    return new FlinkKafkaConsumer010<>(topic, deserializationSchema, properties);
}
 

import org.apache.flink.streaming.util.serialization.DeserializationSchema; //导入依赖的package包/类
@Override
FlinkKafkaConsumerBase<Row> getKafkaConsumer(String topic, Properties properties, DeserializationSchema<Row> deserializationSchema) {
    return new FlinkKafkaConsumer09<>(topic, deserializationSchema, properties);
}