org.apache.flink.streaming.connectors.kafka

类 FlinkKafkaConsumer<T>

java.lang.Object

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

org.apache.flink.streaming.api.functions.source.RichParallelSourceFunction<T>

org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase<T>

org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer<T>

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.api.common.state.CheckpointListener, org.apache.flink.api.java.typeutils.ResultTypeQueryable<T>, org.apache.flink.streaming.api.checkpoint.CheckpointedFunction, org.apache.flink.streaming.api.functions.source.ParallelSourceFunction<T>, org.apache.flink.streaming.api.functions.source.SourceFunction<T>

直接已知子类:

FlinkKafkaShuffleConsumer

已过时。

@PublicEvolving
 @Deprecated
public class FlinkKafkaConsumer<T>
extends FlinkKafkaConsumerBase<T>

The Flink Kafka Consumer is a streaming data source that pulls a parallel data stream from Apache Kafka. The consumer can run in multiple parallel instances, each of which will pull data from one or more Kafka partitions.

The Flink Kafka Consumer participates in checkpointing and guarantees that no data is lost during a failure, and that the computation processes elements "exactly once". (Note: These guarantees naturally assume that Kafka itself does not lose any data.)

Please note that Flink snapshots the offsets internally as part of its distributed checkpoints. The offsets committed to Kafka are only to bring the outside view of progress in sync with Flink's view of the progress. That way, monitoring and other jobs can get a view of how far the Flink Kafka consumer has consumed a topic.

Please refer to Kafka's documentation for the available configuration properties: http://kafka.apache.org/documentation.html#newconsumerconfigs

另请参阅:

序列化表格

嵌套类概要

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

org.apache.flink.streaming.api.functions.source.SourceFunction.SourceContext<T>

字段概要

字段

限定符和类型	字段和说明
static long	DEFAULT_POLL_TIMEOUT 已过时。 From Kafka's Javadoc: The time, in milliseconds, spent waiting in poll if data is not available.
static String	KEY_POLL_TIMEOUT 已过时。 Configuration key to change the polling timeout
protected long	pollTimeout 已过时。 From Kafka's Javadoc: The time, in milliseconds, spent waiting in poll if data is not available.
protected Properties	properties 已过时。 User-supplied properties for Kafka

从类继承的字段 org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase

deserializer, KEY_DISABLE_METRICS, KEY_PARTITION_DISCOVERY_INTERVAL_MILLIS, LOG, MAX_NUM_PENDING_CHECKPOINTS, PARTITION_DISCOVERY_DISABLED

构造器概要

构造器

构造器和说明
FlinkKafkaConsumer(List<String> topics, org.apache.flink.api.common.serialization.DeserializationSchema<T> deserializer, Properties props) 已过时。 Creates a new Kafka streaming source consumer.
FlinkKafkaConsumer(List<String> topics, KafkaDeserializationSchema<T> deserializer, Properties props) 已过时。 Creates a new Kafka streaming source consumer.
FlinkKafkaConsumer(Pattern subscriptionPattern, org.apache.flink.api.common.serialization.DeserializationSchema<T> valueDeserializer, Properties props) 已过时。 Creates a new Kafka streaming source consumer.
FlinkKafkaConsumer(Pattern subscriptionPattern, KafkaDeserializationSchema<T> deserializer, Properties props) 已过时。 Creates a new Kafka streaming source consumer.
FlinkKafkaConsumer(String topic, org.apache.flink.api.common.serialization.DeserializationSchema<T> valueDeserializer, Properties props) 已过时。 Creates a new Kafka streaming source consumer.
FlinkKafkaConsumer(String topic, KafkaDeserializationSchema<T> deserializer, Properties props) 已过时。 Creates a new Kafka streaming source consumer.

方法概要

限定符和类型	方法和说明
protected AbstractFetcher<T,?>	createFetcher(org.apache.flink.streaming.api.functions.source.SourceFunction.SourceContext<T> sourceContext, Map<KafkaTopicPartition,Long> assignedPartitionsWithInitialOffsets, org.apache.flink.util.SerializedValue<org.apache.flink.api.common.eventtime.WatermarkStrategy<T>> watermarkStrategy, org.apache.flink.streaming.api.operators.StreamingRuntimeContext runtimeContext, OffsetCommitMode offsetCommitMode, org.apache.flink.metrics.MetricGroup consumerMetricGroup, boolean useMetrics) 已过时。 Creates the fetcher that connect to the Kafka brokers, pulls data, deserialized the data, and emits it into the data streams.
protected AbstractPartitionDiscoverer	createPartitionDiscoverer(KafkaTopicsDescriptor topicsDescriptor, int indexOfThisSubtask, int numParallelSubtasks) 已过时。 Creates the partition discoverer that is used to find new partitions for this subtask.
protected Map<KafkaTopicPartition,Long>	fetchOffsetsWithTimestamp(Collection<KafkaTopicPartition> partitions, long timestamp) 已过时。
protected boolean	getIsAutoCommitEnabled() 已过时。

从类继承的方法 org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase

adjustAutoCommitConfig, assignTimestampsAndWatermarks, assignTimestampsAndWatermarks, assignTimestampsAndWatermarks, cancel, close, disableFilterRestoredPartitionsWithSubscribedTopics, getEnableCommitOnCheckpoints, getProducedType, initializeState, notifyCheckpointAborted, notifyCheckpointComplete, open, run, setCommitOffsetsOnCheckpoints, setStartFromEarliest, setStartFromGroupOffsets, setStartFromLatest, setStartFromSpecificOffsets, setStartFromTimestamp, snapshotState

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

KEY_POLL_TIMEOUT

public static final String KEY_POLL_TIMEOUT

已过时。

Configuration key to change the polling timeout. *

另请参阅:

常量字段值

DEFAULT_POLL_TIMEOUT

public static final long DEFAULT_POLL_TIMEOUT

已过时。

From Kafka's Javadoc: The time, in milliseconds, spent waiting in poll if data is not available. If 0, returns immediately with any records that are available now.

另请参阅:

常量字段值

properties

protected final Properties properties

已过时。

User-supplied properties for Kafka. *

pollTimeout

protected final long pollTimeout

已过时。

From Kafka's Javadoc: The time, in milliseconds, spent waiting in poll if data is not available. If 0, returns immediately with any records that are available now

构造器详细资料

FlinkKafkaConsumer

public FlinkKafkaConsumer(String topic,
                          org.apache.flink.api.common.serialization.DeserializationSchema<T> valueDeserializer,
                          Properties props)

已过时。

Creates a new Kafka streaming source consumer.

参数:

topic - The name of the topic that should be consumed.

valueDeserializer - The de-/serializer used to convert between Kafka's byte messages and Flink's objects.

props -

FlinkKafkaConsumer

public FlinkKafkaConsumer(String topic,
                          KafkaDeserializationSchema<T> deserializer,
                          Properties props)

已过时。

Creates a new Kafka streaming source consumer.

This constructor allows passing a KafkaDeserializationSchema for reading key/value pairs, offsets, and topic names from Kafka.

参数:

topic - The name of the topic that should be consumed.

deserializer - The keyed de-/serializer used to convert between Kafka's byte messages and Flink's objects.

props -

FlinkKafkaConsumer

public FlinkKafkaConsumer(List<String> topics,
                          org.apache.flink.api.common.serialization.DeserializationSchema<T> deserializer,
                          Properties props)

已过时。

Creates a new Kafka streaming source consumer.

This constructor allows passing multiple topics to the consumer.

参数:

topics - The Kafka topics to read from.

deserializer - The de-/serializer used to convert between Kafka's byte messages and Flink's objects.

props -

FlinkKafkaConsumer

public FlinkKafkaConsumer(List<String> topics,
                          KafkaDeserializationSchema<T> deserializer,
                          Properties props)

已过时。

Creates a new Kafka streaming source consumer.

This constructor allows passing multiple topics and a key/value deserialization schema.

参数:

topics - The Kafka topics to read from.

deserializer - The keyed de-/serializer used to convert between Kafka's byte messages and Flink's objects.

props -

FlinkKafkaConsumer

public FlinkKafkaConsumer(Pattern subscriptionPattern,
                          org.apache.flink.api.common.serialization.DeserializationSchema<T> valueDeserializer,
                          Properties props)

已过时。

Creates a new Kafka streaming source consumer. Use this constructor to subscribe to multiple topics based on a regular expression pattern.

If partition discovery is enabled (by setting a non-negative value for FlinkKafkaConsumerBase.KEY_PARTITION_DISCOVERY_INTERVAL_MILLIS in the properties), topics with names matching the pattern will also be subscribed to as they are created on the fly.

参数:

subscriptionPattern - The regular expression for a pattern of topic names to subscribe to.

valueDeserializer - The de-/serializer used to convert between Kafka's byte messages and Flink's objects.

props -

FlinkKafkaConsumer

public FlinkKafkaConsumer(Pattern subscriptionPattern,
                          KafkaDeserializationSchema<T> deserializer,
                          Properties props)

已过时。

Creates a new Kafka streaming source consumer. Use this constructor to subscribe to multiple topics based on a regular expression pattern.

If partition discovery is enabled (by setting a non-negative value for FlinkKafkaConsumerBase.KEY_PARTITION_DISCOVERY_INTERVAL_MILLIS in the properties), topics with names matching the pattern will also be subscribed to as they are created on the fly.

This constructor allows passing a KafkaDeserializationSchema for reading key/value pairs, offsets, and topic names from Kafka.

参数:

subscriptionPattern - The regular expression for a pattern of topic names to subscribe to.

deserializer - The keyed de-/serializer used to convert between Kafka's byte messages and Flink's objects.

props -

方法详细资料

createFetcher

protected AbstractFetcher<T,?> createFetcher(org.apache.flink.streaming.api.functions.source.SourceFunction.SourceContext<T> sourceContext,
                                             Map<KafkaTopicPartition,Long> assignedPartitionsWithInitialOffsets,
                                             org.apache.flink.util.SerializedValue<org.apache.flink.api.common.eventtime.WatermarkStrategy<T>> watermarkStrategy,
                                             org.apache.flink.streaming.api.operators.StreamingRuntimeContext runtimeContext,
                                             OffsetCommitMode offsetCommitMode,
                                             org.apache.flink.metrics.MetricGroup consumerMetricGroup,
                                             boolean useMetrics)
                                      throws Exception

已过时。

从类复制的说明: FlinkKafkaConsumerBase

Creates the fetcher that connect to the Kafka brokers, pulls data, deserialized the data, and emits it into the data streams.

指定者:

createFetcher 在类中 FlinkKafkaConsumerBase<T>

参数:

sourceContext - The source context to emit data to.

assignedPartitionsWithInitialOffsets - The set of partitions that this subtask should handle, with their start offsets.

watermarkStrategy - Optional, a serialized WatermarkStrategy.

runtimeContext - The task's runtime context.

返回:

The instantiated fetcher

抛出:

Exception - The method should forward exceptions

createPartitionDiscoverer

protected AbstractPartitionDiscoverer createPartitionDiscoverer(KafkaTopicsDescriptor topicsDescriptor,
                                                                int indexOfThisSubtask,
                                                                int numParallelSubtasks)

已过时。

从类复制的说明: FlinkKafkaConsumerBase

Creates the partition discoverer that is used to find new partitions for this subtask.

指定者:

createPartitionDiscoverer 在类中 FlinkKafkaConsumerBase<T>

参数:

topicsDescriptor - Descriptor that describes whether we are discovering partitions for fixed topics or a topic pattern.

indexOfThisSubtask - The index of this consumer subtask.

numParallelSubtasks - The total number of parallel consumer subtasks.

返回:

The instantiated partition discoverer

fetchOffsetsWithTimestamp

protected Map<KafkaTopicPartition,Long> fetchOffsetsWithTimestamp(Collection<KafkaTopicPartition> partitions,
                                                                  long timestamp)

已过时。

指定者:

fetchOffsetsWithTimestamp 在类中 FlinkKafkaConsumerBase<T>

getIsAutoCommitEnabled

protected boolean getIsAutoCommitEnabled()

已过时。

指定者:

getIsAutoCommitEnabled 在类中 FlinkKafkaConsumerBase<T>