curcur commented on a change in pull request #11725: URL: https://github.com/apache/flink/pull/11725#discussion_r425771337
########## File path: flink-connectors/flink-connector-kafka/src/main/java/org/apache/flink/streaming/connectors/kafka/internal/KafkaShuffleFetcher.java ########## @@ -0,0 +1,380 @@ +/* + * 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.annotation.VisibleForTesting; +import org.apache.flink.api.common.typeutils.TypeSerializer; +import org.apache.flink.api.common.typeutils.base.IntSerializer; +import org.apache.flink.api.common.typeutils.base.LongSerializer; +import org.apache.flink.core.memory.DataInputDeserializer; +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.api.watermark.Watermark; +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.util.Preconditions; +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.io.Serializable; +import java.util.Comparator; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.Optional; +import java.util.Properties; + +import static org.apache.flink.streaming.connectors.kafka.shuffle.FlinkKafkaShuffleProducer.KafkaSerializer.TAG_REC_WITHOUT_TIMESTAMP; +import static org.apache.flink.streaming.connectors.kafka.shuffle.FlinkKafkaShuffleProducer.KafkaSerializer.TAG_REC_WITH_TIMESTAMP; +import static org.apache.flink.streaming.connectors.kafka.shuffle.FlinkKafkaShuffleProducer.KafkaSerializer.TAG_WATERMARK; +import static org.apache.flink.util.Preconditions.checkState; + +/** + * Fetch data from Kafka for Kafka Shuffle. + */ +@Internal +public class KafkaShuffleFetcher<T> extends AbstractFetcher<T, TopicPartition> { + private static final Logger LOG = LoggerFactory.getLogger(KafkaShuffleFetcher.class); + + private final WatermarkHandler watermarkHandler; + // ------------------------------------------------------------------------ + + /** The schema to convert between Kafka's byte messages, and Flink's objects. */ + private final KafkaShuffleElementDeserializer<T> deserializer; + + /** Serializer to serialize record. */ + private final TypeSerializer<T> serializer; + + /** 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 KafkaShuffleFetcher( + SourceFunction.SourceContext<T> sourceContext, + Map<KafkaTopicPartition, Long> assignedPartitionsWithInitialOffsets, + SerializedValue<AssignerWithPeriodicWatermarks<T>> watermarksPeriodic, + SerializedValue<AssignerWithPunctuatedWatermarks<T>> watermarksPunctuated, + ProcessingTimeService processingTimeProvider, + long autoWatermarkInterval, + ClassLoader userCodeClassLoader, + String taskNameWithSubtasks, + TypeSerializer<T> serializer, + Properties kafkaProperties, + long pollTimeout, + MetricGroup subtaskMetricGroup, + MetricGroup consumerMetricGroup, + boolean useMetrics, + int producerParallelism) throws Exception { + super( + sourceContext, + assignedPartitionsWithInitialOffsets, + watermarksPeriodic, + watermarksPunctuated, + processingTimeProvider, + autoWatermarkInterval, + userCodeClassLoader, + consumerMetricGroup, + useMetrics); + this.deserializer = new KafkaShuffleElementDeserializer<>(); + this.serializer = serializer; + this.handover = new Handover(); + this.consumerThread = new KafkaConsumerThread( + LOG, + handover, + kafkaProperties, + unassignedPartitionsQueue, + getFetcherName() + " for " + taskNameWithSubtasks, + pollTimeout, + useMetrics, + consumerMetricGroup, + subtaskMetricGroup); + this.watermarkHandler = new WatermarkHandler(producerParallelism); + } + + // ------------------------------------------------------------------------ + // 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 KafkaShuffleElement<T> element = deserializer.deserialize(serializer, record); + + // TODO: do we need to check the end of stream if reaching the end watermark? + + if (element.isRecord()) { + // timestamp is inherent from upstream + // If using ProcessTime, timestamp is going to be ignored (upstream does not include timestamp as well) + // If using IngestionTime, timestamp is going to be overwritten + // If using EventTime, timestamp is going to be used + synchronized (checkpointLock) { + KafkaShuffleRecord<T> elementAsRecord = element.asRecord(); + sourceContext.collectWithTimestamp( + elementAsRecord.value, + elementAsRecord.timestamp == null ? record.timestamp() : elementAsRecord.timestamp); + partition.setOffset(record.offset()); + } + } else if (element.isWatermark()) { + final KafkaShuffleWatermark watermark = element.asWatermark(); + Optional<Watermark> newWatermark = watermarkHandler.checkAndGetNewWatermark(watermark); + newWatermark.ifPresent(sourceContext::emitWatermark); + } Review comment: Me Answer why. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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