org.apache.flink.streaming.connectors.kafka

类 FlinkKafkaProducer011<IN>

java.lang.Object

org.apache.flink.api.common.functions.AbstractRichFunction

org.apache.flink.streaming.api.functions.sink.RichSinkFunction<IN>

org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011<IN>

所有已实现的接口:

Serializable, org.apache.flink.api.common.functions.Function, org.apache.flink.api.common.functions.RichFunction, org.apache.flink.runtime.state.CheckpointListener, org.apache.flink.streaming.api.checkpoint.CheckpointedFunction, org.apache.flink.streaming.api.functions.sink.SinkFunction<IN>

@PublicEvolving
public class FlinkKafkaProducer011<IN>
extends org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

Flink Sink to produce data into a Kafka topic. This producer is compatible with Kafka 0.11.x. By default producer will use FlinkKafkaProducer011.Semantic.AT_LEAST_ONCE semantic. Before using FlinkKafkaProducer011.Semantic.EXACTLY_ONCE please refer to Flink's Kafka connector documentation.

另请参阅:

序列化表格

嵌套类概要

嵌套类

限定符和类型	类和说明
static class	FlinkKafkaProducer011.ContextStateSerializer TypeSerializer for FlinkKafkaProducer011.KafkaTransactionContext.
static class	FlinkKafkaProducer011.KafkaTransactionContext Context associated to this instance of the FlinkKafkaProducer011.
static class	FlinkKafkaProducer011.NextTransactionalIdHint Keep information required to deduce next safe to use transactional id.
static class	FlinkKafkaProducer011.NextTransactionalIdHintSerializer TypeSerializer for FlinkKafkaProducer011.NextTransactionalIdHint.
static class	FlinkKafkaProducer011.Semantic Semantics that can be chosen.
static class	FlinkKafkaProducer011.TransactionStateSerializer TypeSerializer for KafkaTransactionState.

从类继承的嵌套类/接口 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction

org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction.State<TXN,CONTEXT>, org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction.StateSerializer<TXN,CONTEXT>, org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction.StateSerializerConfigSnapshot<TXN,CONTEXT>, org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction.StateSerializerSnapshot<TXN,CONTEXT>, org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction.TransactionHolder<TXN>

从接口继承的嵌套类/接口 org.apache.flink.streaming.api.functions.sink.SinkFunction

org.apache.flink.streaming.api.functions.sink.SinkFunction.Context<T>

字段概要

字段

限定符和类型	字段和说明
static int	DEFAULT_KAFKA_PRODUCERS_POOL_SIZE Default number of KafkaProducers in the pool.
static org.apache.flink.api.common.time.Time	DEFAULT_KAFKA_TRANSACTION_TIMEOUT Default value for kafka transaction timeout.
static String	KEY_DISABLE_METRICS Configuration key for disabling the metrics reporting.
static int	SAFE_SCALE_DOWN_FACTOR This coefficient determines what is the safe scale down factor.

从类继承的字段 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction

pendingCommitTransactions, state, userContext

构造器概要

构造器

构造器和说明
FlinkKafkaProducer011(String topicId, org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<IN> serializationSchema, Properties producerConfig) Creates a FlinkKafkaProducer for a given topic.
FlinkKafkaProducer011(String topicId, org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<IN> serializationSchema, Properties producerConfig, FlinkKafkaProducer011.Semantic semantic) Creates a FlinkKafkaProducer for a given topic.
FlinkKafkaProducer011(String defaultTopicId, org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<IN> serializationSchema, Properties producerConfig, Optional<org.apache.flink.streaming.connectors.kafka.partitioner.FlinkKafkaPartitioner<IN>> customPartitioner) Creates a FlinkKafkaProducer for a given topic.
FlinkKafkaProducer011(String defaultTopicId, org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<IN> serializationSchema, Properties producerConfig, Optional<org.apache.flink.streaming.connectors.kafka.partitioner.FlinkKafkaPartitioner<IN>> customPartitioner, FlinkKafkaProducer011.Semantic semantic, int kafkaProducersPoolSize) Creates a FlinkKafkaProducer for a given topic.
FlinkKafkaProducer011(String topicId, org.apache.flink.api.common.serialization.SerializationSchema<IN> serializationSchema, Properties producerConfig) Creates a FlinkKafkaProducer for a given topic.
FlinkKafkaProducer011(String topicId, org.apache.flink.api.common.serialization.SerializationSchema<IN> serializationSchema, Properties producerConfig, Optional<org.apache.flink.streaming.connectors.kafka.partitioner.FlinkKafkaPartitioner<IN>> customPartitioner) Creates a FlinkKafkaProducer for a given topic.
FlinkKafkaProducer011(String brokerList, String topicId, org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<IN> serializationSchema) Creates a FlinkKafkaProducer for a given topic.
FlinkKafkaProducer011(String brokerList, String topicId, org.apache.flink.api.common.serialization.SerializationSchema<IN> serializationSchema) Creates a FlinkKafkaProducer for a given topic.

方法概要

限定符和类型	方法和说明
protected void	abort(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction)
protected org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState	beginTransaction()
void	close()
protected void	commit(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction)
protected void	finishRecoveringContext(Collection<org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState> handledTransactions)
FlinkKafkaProducer011<IN>	ignoreFailuresAfterTransactionTimeout() Disables the propagation of exceptions thrown when committing presumably timed out Kafka transactions during recovery of the job.
void	initializeState(org.apache.flink.runtime.state.FunctionInitializationContext context)
protected Optional<FlinkKafkaProducer011.KafkaTransactionContext>	initializeUserContext()
void	invoke(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction, IN next, org.apache.flink.streaming.api.functions.sink.SinkFunction.Context context)
void	open(org.apache.flink.configuration.Configuration configuration) Initializes the connection to Kafka.
protected void	preCommit(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction)
protected void	recoverAndAbort(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction)
protected void	recoverAndCommit(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction)
void	setLogFailuresOnly(boolean logFailuresOnly) Defines whether the producer should fail on errors, or only log them.
void	setWriteTimestampToKafka(boolean writeTimestampToKafka) If set to true, Flink will write the (event time) timestamp attached to each record into Kafka.
void	snapshotState(org.apache.flink.runtime.state.FunctionSnapshotContext context)

从类继承的方法 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction

currentTransaction, enableTransactionTimeoutWarnings, getUserContext, invoke, invoke, notifyCheckpointComplete, pendingTransactions, setTransactionTimeout

从类继承的方法 org.apache.flink.api.common.functions.AbstractRichFunction

getIterationRuntimeContext, getRuntimeContext, setRuntimeContext

从类继承的方法 java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

字段详细资料

SAFE_SCALE_DOWN_FACTOR

public static final int SAFE_SCALE_DOWN_FACTOR

This coefficient determines what is the safe scale down factor.

If the Flink application previously failed before first checkpoint completed or we are starting new batch of FlinkKafkaProducer011 from scratch without clean shutdown of the previous one, FlinkKafkaProducer011 doesn't know what was the set of previously used Kafka's transactionalId's. In that case, it will try to play safe and abort all of the possible transactionalIds from the range of: [0, getNumberOfParallelSubtasks() * kafkaProducersPoolSize * SAFE_SCALE_DOWN_FACTOR)

The range of available to use transactional ids is: [0, getNumberOfParallelSubtasks() * kafkaProducersPoolSize)

This means that if we decrease getNumberOfParallelSubtasks() by a factor larger than SAFE_SCALE_DOWN_FACTOR we can have a left some lingering transaction.

另请参阅:

常量字段值

DEFAULT_KAFKA_PRODUCERS_POOL_SIZE

public static final int DEFAULT_KAFKA_PRODUCERS_POOL_SIZE

Default number of KafkaProducers in the pool. See FlinkKafkaProducer011.Semantic.EXACTLY_ONCE.

另请参阅:

常量字段值

DEFAULT_KAFKA_TRANSACTION_TIMEOUT

public static final org.apache.flink.api.common.time.Time DEFAULT_KAFKA_TRANSACTION_TIMEOUT

Default value for kafka transaction timeout.

KEY_DISABLE_METRICS

public static final String KEY_DISABLE_METRICS

Configuration key for disabling the metrics reporting.

另请参阅:

常量字段值

构造器详细资料

FlinkKafkaProducer011

public FlinkKafkaProducer011(String brokerList,
                             String topicId,
                             org.apache.flink.api.common.serialization.SerializationSchema<IN> serializationSchema)

Creates a FlinkKafkaProducer for a given topic. The sink produces a DataStream to the topic.

参数:

brokerList - Comma separated addresses of the brokers

topicId - ID of the Kafka topic.

serializationSchema - User defined (keyless) serialization schema.

FlinkKafkaProducer011

public FlinkKafkaProducer011(String topicId,
                             org.apache.flink.api.common.serialization.SerializationSchema<IN> serializationSchema,
                             Properties producerConfig)

Creates a FlinkKafkaProducer for a given topic. The sink produces a DataStream to the topic.

Using this constructor, the default FlinkFixedPartitioner will be used as the partitioner. This default partitioner maps each sink subtask to a single Kafka partition (i.e. all records received by a sink subtask will end up in the same Kafka partition).

To use a custom partitioner, please use FlinkKafkaProducer011(String, SerializationSchema, Properties, Optional) instead.

参数:

topicId - ID of the Kafka topic.

serializationSchema - User defined key-less serialization schema.

producerConfig - Properties with the producer configuration.

FlinkKafkaProducer011

public FlinkKafkaProducer011(String topicId,
                             org.apache.flink.api.common.serialization.SerializationSchema<IN> serializationSchema,
                             Properties producerConfig,
                             Optional<org.apache.flink.streaming.connectors.kafka.partitioner.FlinkKafkaPartitioner<IN>> customPartitioner)

Creates a FlinkKafkaProducer for a given topic. The sink produces its input to the topic. It accepts a key-less SerializationSchema and possibly a custom FlinkKafkaPartitioner.

Since a key-less SerializationSchema is used, all records sent to Kafka will not have an attached key. Therefore, if a partitioner is also not provided, records will be distributed to Kafka partitions in a round-robin fashion.

参数:

topicId - The topic to write data to

serializationSchema - A key-less serializable serialization schema for turning user objects into a kafka-consumable byte[]

producerConfig - Configuration properties for the KafkaProducer. 'bootstrap.servers.' is the only required argument.

customPartitioner - A serializable partitioner for assigning messages to Kafka partitions. If a partitioner is not provided, records will be distributed to Kafka partitions in a round-robin fashion.

FlinkKafkaProducer011

public FlinkKafkaProducer011(String brokerList,
                             String topicId,
                             org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<IN> serializationSchema)

Creates a FlinkKafkaProducer for a given topic. The sink produces a DataStream to the topic.

Using this constructor, the default FlinkFixedPartitioner will be used as the partitioner. This default partitioner maps each sink subtask to a single Kafka partition (i.e. all records received by a sink subtask will end up in the same Kafka partition).

To use a custom partitioner, please use FlinkKafkaProducer011(String, KeyedSerializationSchema, Properties, Optional) instead.

参数:

brokerList - Comma separated addresses of the brokers

topicId - ID of the Kafka topic.

serializationSchema - User defined serialization schema supporting key/value messages

FlinkKafkaProducer011

public FlinkKafkaProducer011(String topicId,
                             org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<IN> serializationSchema,
                             Properties producerConfig)

Creates a FlinkKafkaProducer for a given topic. The sink produces a DataStream to the topic.

Using this constructor, the default FlinkFixedPartitioner will be used as the partitioner. This default partitioner maps each sink subtask to a single Kafka partition (i.e. all records received by a sink subtask will end up in the same Kafka partition).

To use a custom partitioner, please use FlinkKafkaProducer011(String, KeyedSerializationSchema, Properties, Optional) instead.

参数:

topicId - ID of the Kafka topic.

serializationSchema - User defined serialization schema supporting key/value messages

producerConfig - Properties with the producer configuration.

FlinkKafkaProducer011

public FlinkKafkaProducer011(String topicId,
                             org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<IN> serializationSchema,
                             Properties producerConfig,
                             FlinkKafkaProducer011.Semantic semantic)

Creates a FlinkKafkaProducer for a given topic. The sink produces a DataStream to the topic.

Using this constructor, the default FlinkFixedPartitioner will be used as the partitioner. This default partitioner maps each sink subtask to a single Kafka partition (i.e. all records received by a sink subtask will end up in the same Kafka partition).

To use a custom partitioner, please use FlinkKafkaProducer011(String, KeyedSerializationSchema, Properties, Optional, Semantic, int) instead.

参数:

topicId - ID of the Kafka topic.

serializationSchema - User defined serialization schema supporting key/value messages

producerConfig - Properties with the producer configuration.

semantic - Defines semantic that will be used by this producer (see FlinkKafkaProducer011.Semantic).

FlinkKafkaProducer011

public FlinkKafkaProducer011(String defaultTopicId,
                             org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<IN> serializationSchema,
                             Properties producerConfig,
                             Optional<org.apache.flink.streaming.connectors.kafka.partitioner.FlinkKafkaPartitioner<IN>> customPartitioner)

Creates a FlinkKafkaProducer for a given topic. The sink produces its input to the topic. It accepts a keyed KeyedSerializationSchema and possibly a custom FlinkKafkaPartitioner.

If a partitioner is not provided, written records will be partitioned by the attached key of each record (as determined by KeyedSerializationSchema.serializeKey(Object)). If written records do not have a key (i.e., KeyedSerializationSchema.serializeKey(Object) returns null), they will be distributed to Kafka partitions in a round-robin fashion.

参数:

defaultTopicId - The default topic to write data to

serializationSchema - A serializable serialization schema for turning user objects into a kafka-consumable byte[] supporting key/value messages

producerConfig - Configuration properties for the KafkaProducer. 'bootstrap.servers.' is the only required argument.

customPartitioner - A serializable partitioner for assigning messages to Kafka partitions. If a partitioner is not provided, records will be partitioned by the key of each record (determined by KeyedSerializationSchema.serializeKey(Object)). If the keys are null, then records will be distributed to Kafka partitions in a round-robin fashion.

FlinkKafkaProducer011

public FlinkKafkaProducer011(String defaultTopicId,
                             org.apache.flink.streaming.util.serialization.KeyedSerializationSchema<IN> serializationSchema,
                             Properties producerConfig,
                             Optional<org.apache.flink.streaming.connectors.kafka.partitioner.FlinkKafkaPartitioner<IN>> customPartitioner,
                             FlinkKafkaProducer011.Semantic semantic,
                             int kafkaProducersPoolSize)

Creates a FlinkKafkaProducer for a given topic. The sink produces its input to the topic. It accepts a keyed KeyedSerializationSchema and possibly a custom FlinkKafkaPartitioner.

If a partitioner is not provided, written records will be partitioned by the attached key of each record (as determined by KeyedSerializationSchema.serializeKey(Object)). If written records do not have a key (i.e., KeyedSerializationSchema.serializeKey(Object) returns null), they will be distributed to Kafka partitions in a round-robin fashion.

参数:

defaultTopicId - The default topic to write data to

serializationSchema - A serializable serialization schema for turning user objects into a kafka-consumable byte[] supporting key/value messages

producerConfig - Configuration properties for the KafkaProducer. 'bootstrap.servers.' is the only required argument.

customPartitioner - A serializable partitioner for assigning messages to Kafka partitions. If a partitioner is not provided, records will be partitioned by the key of each record (determined by KeyedSerializationSchema.serializeKey(Object)). If the keys are null, then records will be distributed to Kafka partitions in a round-robin fashion.

semantic - Defines semantic that will be used by this producer (see FlinkKafkaProducer011.Semantic).

kafkaProducersPoolSize - Overwrite default KafkaProducers pool size (see FlinkKafkaProducer011.Semantic.EXACTLY_ONCE).

方法详细资料

setWriteTimestampToKafka

public void setWriteTimestampToKafka(boolean writeTimestampToKafka)

If set to true, Flink will write the (event time) timestamp attached to each record into Kafka. Timestamps must be positive for Kafka to accept them.

参数:

writeTimestampToKafka - Flag indicating if Flink's internal timestamps are written to Kafka.

setLogFailuresOnly

public void setLogFailuresOnly(boolean logFailuresOnly)

Defines whether the producer should fail on errors, or only log them. If this is set to true, then exceptions will be only logged, if set to false, exceptions will be eventually thrown and cause the streaming program to fail (and enter recovery).

参数:

logFailuresOnly - The flag to indicate logging-only on exceptions.

ignoreFailuresAfterTransactionTimeout

public FlinkKafkaProducer011<IN> ignoreFailuresAfterTransactionTimeout()

Disables the propagation of exceptions thrown when committing presumably timed out Kafka transactions during recovery of the job. If a Kafka transaction is timed out, a commit will never be successful. Hence, use this feature to avoid recovery loops of the Job. Exceptions will still be logged to inform the user that data loss might have occurred.

Note that we use System.currentTimeMillis() to track the age of a transaction. Moreover, only exceptions thrown during the recovery are caught, i.e., the producer will attempt at least one commit of the transaction before giving up.

覆盖:

ignoreFailuresAfterTransactionTimeout 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

open

public void open(org.apache.flink.configuration.Configuration configuration)
          throws Exception

Initializes the connection to Kafka.

指定者:

open 在接口中 org.apache.flink.api.common.functions.RichFunction

覆盖:

open 在类中 org.apache.flink.api.common.functions.AbstractRichFunction

抛出:

Exception

invoke

public void invoke(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction,
                   IN next,
                   org.apache.flink.streaming.api.functions.sink.SinkFunction.Context context)
            throws FlinkKafka011Exception

指定者:

invoke 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

抛出:

FlinkKafka011Exception

close

public void close()
           throws FlinkKafka011Exception

指定者:

close 在接口中 org.apache.flink.api.common.functions.RichFunction

覆盖:

close 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

抛出:

FlinkKafka011Exception

beginTransaction

protected org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState beginTransaction()
                                                                                                            throws FlinkKafka011Exception

指定者:

beginTransaction 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

抛出:

FlinkKafka011Exception

preCommit

protected void preCommit(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction)
                  throws FlinkKafka011Exception

指定者:

preCommit 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

抛出:

FlinkKafka011Exception

commit

protected void commit(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction)

指定者:

commit 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

recoverAndCommit

protected void recoverAndCommit(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction)

覆盖:

recoverAndCommit 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

abort

protected void abort(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction)

指定者:

abort 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

recoverAndAbort

protected void recoverAndAbort(org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState transaction)

覆盖:

recoverAndAbort 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

snapshotState

public void snapshotState(org.apache.flink.runtime.state.FunctionSnapshotContext context)
                   throws Exception

指定者:

snapshotState 在接口中 org.apache.flink.streaming.api.checkpoint.CheckpointedFunction

覆盖:

snapshotState 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

抛出:

Exception

initializeState

public void initializeState(org.apache.flink.runtime.state.FunctionInitializationContext context)
                     throws Exception

指定者:

initializeState 在接口中 org.apache.flink.streaming.api.checkpoint.CheckpointedFunction

覆盖:

initializeState 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

抛出:

Exception

initializeUserContext

protected Optional<FlinkKafkaProducer011.KafkaTransactionContext> initializeUserContext()

覆盖:

initializeUserContext 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>

finishRecoveringContext

protected void finishRecoveringContext(Collection<org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState> handledTransactions)

覆盖:

finishRecoveringContext 在类中 org.apache.flink.streaming.api.functions.sink.TwoPhaseCommitSinkFunction<IN,org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011.KafkaTransactionState,FlinkKafkaProducer011.KafkaTransactionContext>