stevenzwu commented on a change in pull request #13574: URL: https://github.com/apache/flink/pull/13574#discussion_r502835270
########## File path: flink-connectors/flink-connector-kafka/src/main/java/org/apache/flink/connector/kafka/source/reader/KafkaPartitionSplitReader.java ########## @@ -0,0 +1,398 @@ +/* + 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.connector.kafka.source.reader; + +import org.apache.flink.api.java.tuple.Tuple3; +import org.apache.flink.connector.base.source.reader.RecordsWithSplitIds; +import org.apache.flink.connector.base.source.reader.splitreader.SplitReader; +import org.apache.flink.connector.base.source.reader.splitreader.SplitsAddition; +import org.apache.flink.connector.base.source.reader.splitreader.SplitsChange; +import org.apache.flink.connector.kafka.source.KafkaSourceOptions; +import org.apache.flink.connector.kafka.source.reader.deserializer.KafkaRecordDeserializer; +import org.apache.flink.connector.kafka.source.split.KafkaPartitionSplit; +import org.apache.flink.util.Collector; +import org.apache.flink.util.FlinkRuntimeException; +import org.apache.flink.util.Preconditions; + +import org.apache.kafka.clients.consumer.ConsumerConfig; +import org.apache.kafka.clients.consumer.ConsumerRecord; +import org.apache.kafka.clients.consumer.ConsumerRecords; +import org.apache.kafka.clients.consumer.KafkaConsumer; +import org.apache.kafka.common.TopicPartition; +import org.apache.kafka.common.errors.WakeupException; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import javax.annotation.Nullable; + +import java.io.IOException; +import java.time.Duration; +import java.util.ArrayList; +import java.util.Collection; +import java.util.HashMap; +import java.util.HashSet; +import java.util.Iterator; +import java.util.List; +import java.util.Map; +import java.util.Properties; +import java.util.Random; +import java.util.Set; +import java.util.StringJoiner; + +/** + * A {@link SplitReader} implementation that reads records from Kafka partitions. + * + * <p>The returned type are in the format of {@code tuple3(record, offset and timestamp}. + * + * @param <T> the type of the record to be emitted from the Source. + */ +public class KafkaPartitionSplitReader<T> implements SplitReader<Tuple3<T, Long, Long>, KafkaPartitionSplit> { + private static final Logger LOG = LoggerFactory.getLogger(KafkaPartitionSplitReader.class); + private static final long POLL_TIMEOUT = 10000L; + + private final KafkaConsumer<byte[], byte[]> consumer; + private final KafkaRecordDeserializer<T> deserializationSchema; + private final Map<TopicPartition, Long> stoppingOffsets; + private final SimpleCollector<T> collector; + private final String groupId; + + public KafkaPartitionSplitReader( + Properties props, + KafkaRecordDeserializer<T> deserializationSchema) { + Properties consumerProps = new Properties(); + consumerProps.putAll(props); + consumerProps.setProperty(ConsumerConfig.CLIENT_ID_CONFIG, createConsumerClientId(props)); + this.consumer = new KafkaConsumer<>(consumerProps); + this.stoppingOffsets = new HashMap<>(); + this.deserializationSchema = deserializationSchema; + this.collector = new SimpleCollector<>(); + this.groupId = consumerProps.getProperty(ConsumerConfig.GROUP_ID_CONFIG); + } + + @Override + public RecordsWithSplitIds<Tuple3<T, Long, Long>> fetch() throws IOException { + KafkaPartitionSplitRecords<Tuple3<T, Long, Long>> recordsBySplits = new KafkaPartitionSplitRecords<>(); + ConsumerRecords<byte[], byte[]> consumerRecords; + try { + consumerRecords = consumer.poll(Duration.ofMillis(POLL_TIMEOUT)); + } catch (WakeupException we) { + return recordsBySplits; + } + + List<TopicPartition> finishedPartitions = new ArrayList<>(); + for (TopicPartition tp : consumerRecords.partitions()) { + long stoppingOffset = getStoppingOffset(tp); + String splitId = tp.toString(); + Collection<Tuple3<T, Long, Long>> recordsForSplit = recordsBySplits.recordsForSplit(splitId); + for (ConsumerRecord<byte[], byte[]> consumerRecord : consumerRecords.records(tp)) { + // Stop consuming from this partition if the offsets has reached the stopping offset. + // Note that there are two cases, either case finishes a split: + // 1. After processing a record with offset of "stoppingOffset - 1". The split reader + // should not continue fetching because the record with stoppingOffset may not exist. + // 2. Before processing a record whose offset is greater than or equals to the stopping + // offset. This should only happens when case 1 was not met due to log compaction or + // log retention. + // Case 2 is handled here. Case 1 is handled after the record is processed. + if (consumerRecord.offset() >= stoppingOffset) { + finishSplitAtRecord(tp, stoppingOffset, consumerRecord.offset(), + finishedPartitions, recordsBySplits); + break; + } + // Add the record to the partition collector. + try { + deserializationSchema.deserialize(consumerRecord, collector); + collector.getRecords().forEach(r -> + recordsForSplit.add(new Tuple3<>(r, + consumerRecord.offset(), + consumerRecord.timestamp()))); + // Finish the split because there might not be any message after this point. Keep polling + // will just block forever. + if (consumerRecord.offset() == stoppingOffset - 1) { + finishSplitAtRecord(tp, stoppingOffset, consumerRecord.offset(), + finishedPartitions, recordsBySplits); + } + } catch (Exception e) { + throw new IOException("Failed to deserialize consumer record due to", e); + } finally { + collector.reset(); + } + } + } + // Unassign the partitions that has finished. + if (!finishedPartitions.isEmpty()) { + unassignPartitions(finishedPartitions); + } + recordsBySplits.prepareForRead(); + return recordsBySplits; + } + + @Override + public void handleSplitsChanges(SplitsChange<KafkaPartitionSplit> splitsChange) { + // Get all the partition assignments and stopping offsets. + if (!(splitsChange instanceof SplitsAddition)) { + throw new UnsupportedOperationException(String.format( + "The SplitChange type of %s is not supported.", splitsChange.getClass())); + } + + // Assignment. + List<TopicPartition> newPartitionAssignments = new ArrayList<>(); + // Starting offsets. + Map<TopicPartition, Long> partitionsStartingFromSpecifiedOffsets = new HashMap<>(); + List<TopicPartition> partitionsStartingFromEarliest = new ArrayList<>(); + List<TopicPartition> partitionsStartingFromLatest = new ArrayList<>(); + // Stopping offsets. + List<TopicPartition> partitionsStoppingAtLatest = new ArrayList<>(); + Set<TopicPartition> partitionsStoppingAtCommitted = new HashSet<>(); + + // Parse the starting and stopping offsets. + splitsChange.splits().forEach(s -> { + newPartitionAssignments.add(s.getTopicPartition()); + parseStartingOffsets(s, partitionsStartingFromEarliest, partitionsStartingFromLatest, partitionsStartingFromSpecifiedOffsets); + parseStoppingOffsets(s, partitionsStoppingAtLatest, partitionsStoppingAtCommitted); + }); + + // Assign new partitions. + newPartitionAssignments.addAll(consumer.assignment()); Review comment: I thought `splitsChange` always contains the complete assignment (not delta), as KafkaSubscriber impl puts current assignment as removed partitions. if my understanding is correct, this newPartitionAssignments list can grow forever for each partition discovery cycle. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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