yanghua commented on a change in pull request #6703: [FLINK-9697] Provide connector for Kafka 2.0.0 URL: https://github.com/apache/flink/pull/6703#discussion_r224976123
########## File path: flink-connectors/flink-connector-kafka/src/main/java/org/apache/flink/streaming/connectors/kafka/internal/KafkaFetcher.java ########## @@ -0,0 +1,238 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.flink.streaming.connectors.kafka.internal; + +import org.apache.flink.annotation.Internal; +import org.apache.flink.metrics.MetricGroup; +import org.apache.flink.streaming.api.functions.AssignerWithPeriodicWatermarks; +import org.apache.flink.streaming.api.functions.AssignerWithPunctuatedWatermarks; +import org.apache.flink.streaming.api.functions.source.SourceFunction; +import org.apache.flink.streaming.connectors.kafka.internals.AbstractFetcher; +import org.apache.flink.streaming.connectors.kafka.internals.KafkaCommitCallback; +import org.apache.flink.streaming.connectors.kafka.internals.KafkaTopicPartition; +import org.apache.flink.streaming.connectors.kafka.internals.KafkaTopicPartitionState; +import org.apache.flink.streaming.runtime.tasks.ProcessingTimeService; +import org.apache.flink.streaming.util.serialization.KeyedDeserializationSchema; +import org.apache.flink.util.SerializedValue; + +import org.apache.kafka.clients.consumer.ConsumerRecord; +import org.apache.kafka.clients.consumer.ConsumerRecords; +import org.apache.kafka.clients.consumer.OffsetAndMetadata; +import org.apache.kafka.common.TopicPartition; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import javax.annotation.Nonnull; + +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.Properties; + +import static org.apache.flink.util.Preconditions.checkState; + +/** + * A fetcher that fetches data from Kafka brokers via the Kafka 2.0 consumer API. + * + * @param <T> The type of elements produced by the fetcher. + */ +@Internal +public class KafkaFetcher<T> extends AbstractFetcher<T, TopicPartition> { + + private static final Logger LOG = LoggerFactory.getLogger(KafkaFetcher.class); + + // ------------------------------------------------------------------------ + + /** The schema to convert between Kafka's byte messages, and Flink's objects. */ + private final KeyedDeserializationSchema<T> deserializer; + + /** The handover of data and exceptions between the consumer thread and the task thread. */ + private final Handover handover; + + /** The thread that runs the actual KafkaConsumer and hand the record batches to this fetcher. */ + private final KafkaConsumerThread consumerThread; + + /** Flag to mark the main work loop as alive. */ + private volatile boolean running = true; + + // ------------------------------------------------------------------------ + + public KafkaFetcher( + SourceFunction.SourceContext<T> sourceContext, + Map<KafkaTopicPartition, Long> assignedPartitionsWithInitialOffsets, + SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic, + SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated, + ProcessingTimeService processingTimeProvider, + long autoWatermarkInterval, + ClassLoader userCodeClassLoader, + String taskNameWithSubtasks, + KeyedDeserializationSchema<T> deserializer, + Properties kafkaProperties, + long pollTimeout, + MetricGroup subtaskMetricGroup, + MetricGroup consumerMetricGroup, + boolean useMetrics) throws Exception { + super( + sourceContext, + assignedPartitionsWithInitialOffsets, + watermarksPeriodic, + watermarksPunctuated, + processingTimeProvider, + autoWatermarkInterval, + userCodeClassLoader, + consumerMetricGroup, + useMetrics); + + this.deserializer = deserializer; + this.handover = new Handover(); + + this.consumerThread = new KafkaConsumerThread( + LOG, + handover, + kafkaProperties, + unassignedPartitionsQueue, + createCallBridge(), + getFetcherName() + " for " + taskNameWithSubtasks, + pollTimeout, + useMetrics, + consumerMetricGroup, + subtaskMetricGroup); + } + + // ------------------------------------------------------------------------ + // Fetcher work methods + // ------------------------------------------------------------------------ + + @Override + public void runFetchLoop() throws Exception { + try { + final Handover handover = this.handover; + + // kick off the actual Kafka consumer + consumerThread.start(); + + while (running) { + // this blocks until we get the next records + // it automatically re-throws exceptions encountered in the consumer thread + final ConsumerRecords<byte[], byte[]> records = handover.pollNext(); + + // get the records for each topic partition + for (KafkaTopicPartitionState<TopicPartition> partition : subscribedPartitionStates()) { + + List<ConsumerRecord<byte[], byte[]>> partitionRecords = + records.records(partition.getKafkaPartitionHandle()); + + for (ConsumerRecord<byte[], byte[]> record : partitionRecords) { + final T value = deserializer.deserialize( + record.key(), record.value(), + record.topic(), record.partition(), record.offset()); + + if (deserializer.isEndOfStream(value)) { + // end of stream signaled + running = false; + break; + } + + // emit the actual record. this also updates offset state atomically + // and deals with timestamps and watermark generation + emitRecord(value, partition, record.offset(), record); + } + } + } + } + finally { + // this signals the consumer thread that no more work is to be done + consumerThread.shutdown(); + } + + // on a clean exit, wait for the runner thread + try { + consumerThread.join(); + } + catch (InterruptedException e) { + // may be the result of a wake-up interruption after an exception. + // we ignore this here and only restore the interruption state + Thread.currentThread().interrupt(); + } + } + + @Override + public void cancel() { + // flag the main thread to exit. A thread interrupt will come anyways. + running = false; + handover.close(); + consumerThread.shutdown(); + } + + protected void emitRecord( + T record, + KafkaTopicPartitionState<TopicPartition> partition, + long offset, + ConsumerRecord<?, ?> consumerRecord) throws Exception { + + emitRecordWithTimestamp(record, partition, offset, consumerRecord.timestamp()); + } + + /** + * Gets the name of this fetcher, for thread naming and logging purposes. + */ + protected String getFetcherName() { + return "Kafka 2.0 Fetcher"; Review comment: Can we give it a unified name? What about `Kafka Fetcher`? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
