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https://issues.apache.org/jira/browse/FLINK-9697?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16649174#comment-16649174
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ASF GitHub Bot commented on FLINK-9697:
---------------------------------------
eliaslevy 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_r224975802
##########
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:
Probably don't want to be updating this version every time there is a new
Kafka release.
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> Provide connector for Kafka 2.0.0
> ---------------------------------
>
> Key: FLINK-9697
> URL: https://issues.apache.org/jira/browse/FLINK-9697
> Project: Flink
> Issue Type: Improvement
> Reporter: Ted Yu
> Assignee: vinoyang
> Priority: Major
> Labels: pull-request-available
>
> Kafka 2.0.0 would be released soon.
> Here is vote thread:
> [http://search-hadoop.com/m/Kafka/uyzND1vxnEd23QLxb?subj=+VOTE+2+0+0+RC1]
> We should provide connector for Kafka 2.0.0 once it is released.
> Upgrade to 2.0 documentation :
> http://kafka.apache.org/20/documentation.html#upgrade_2_0_0
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