becketqin commented on a change in pull request #6594: [FLINK-9311] [pubsub] Added PubSub source connector with support for checkpointing (ATLEAST_ONCE) URL: https://github.com/apache/flink/pull/6594#discussion_r300362007
########## File path: flink-connectors/flink-connector-gcp-pubsub/src/main/java/org/apache/flink/streaming/connectors/gcp/pubsub/PubSubSource.java ########## @@ -0,0 +1,292 @@ +/* + * 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.gcp.pubsub; + +import org.apache.flink.api.common.functions.RuntimeContext; +import org.apache.flink.api.common.serialization.DeserializationSchema; +import org.apache.flink.api.common.typeinfo.TypeInformation; +import org.apache.flink.api.java.typeutils.ResultTypeQueryable; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.runtime.state.CheckpointListener; +import org.apache.flink.streaming.api.checkpoint.ListCheckpointed; +import org.apache.flink.streaming.api.functions.source.ParallelSourceFunction; +import org.apache.flink.streaming.api.functions.source.RichSourceFunction; +import org.apache.flink.streaming.api.operators.StreamingRuntimeContext; +import org.apache.flink.streaming.connectors.gcp.pubsub.common.AcknowledgeIdsForCheckpoint; +import org.apache.flink.streaming.connectors.gcp.pubsub.common.AcknowledgeOnCheckpoint; +import org.apache.flink.streaming.connectors.gcp.pubsub.common.Acknowledger; +import org.apache.flink.streaming.connectors.gcp.pubsub.common.PubSubDeserializationSchema; +import org.apache.flink.streaming.connectors.gcp.pubsub.common.PubSubSubscriber; +import org.apache.flink.streaming.connectors.gcp.pubsub.common.PubSubSubscriberFactory; +import org.apache.flink.util.Preconditions; + +import com.google.auth.Credentials; +import com.google.cloud.pubsub.v1.Subscriber; +import com.google.pubsub.v1.ProjectSubscriptionName; +import com.google.pubsub.v1.PubsubMessage; +import com.google.pubsub.v1.ReceivedMessage; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.io.IOException; +import java.io.Serializable; +import java.time.Duration; +import java.util.List; +import java.util.concurrent.CancellationException; + +import static com.google.cloud.pubsub.v1.SubscriptionAdminSettings.defaultCredentialsProviderBuilder; + +/** + * PubSub Source, this Source will consume PubSub messages from a subscription and Acknowledge them on the next checkpoint. + * This ensures every message will get acknowledged at least once. + */ +public class PubSubSource<OUT> extends RichSourceFunction<OUT> + implements ResultTypeQueryable<OUT>, ParallelSourceFunction<OUT>, CheckpointListener, ListCheckpointed<AcknowledgeIdsForCheckpoint<String>> { + public static final int NO_MAX_MESSAGES_TO_ACKNOWLEDGE_LIMIT = -1; + private static final Logger LOG = LoggerFactory.getLogger(PubSubSource.class); + protected final PubSubDeserializationSchema<OUT> deserializationSchema; + protected final PubSubSubscriberFactory pubSubSubscriberFactory; + protected final Credentials credentials; + protected final int maxMessagesToAcknowledge; + protected final AcknowledgeOnCheckpointFactory acknowledgeOnCheckpointFactory; + + protected transient AcknowledgeOnCheckpoint<String> acknowledgeOnCheckpoint; + protected transient PubSubSubscriber subscriber; + + protected transient volatile boolean isRunning; + + PubSubSource(PubSubDeserializationSchema<OUT> deserializationSchema, + PubSubSubscriberFactory pubSubSubscriberFactory, + Credentials credentials, + int maxMessagesToAcknowledge, + AcknowledgeOnCheckpointFactory acknowledgeOnCheckpointFactory) { + this.deserializationSchema = deserializationSchema; + this.pubSubSubscriberFactory = pubSubSubscriberFactory; + this.credentials = credentials; + this.maxMessagesToAcknowledge = maxMessagesToAcknowledge; + this.acknowledgeOnCheckpointFactory = acknowledgeOnCheckpointFactory; + } + + @Override + public void open(Configuration configuration) throws Exception { + super.open(configuration); + if (hasNoCheckpointingEnabled(getRuntimeContext())) { + throw new IllegalArgumentException("The PubSubSource REQUIRES Checkpointing to be enabled and " + + "the checkpointing frequency must be MUCH lower than the PubSub timeout for it to retry a message."); + } + + getRuntimeContext().getMetricGroup().gauge("PubSubMessagesProcessedNotAcked", this::getOutstandingMessagesToAck); + + createAndSetPubSubSubscriber(); + this.isRunning = true; + } + + private boolean hasNoCheckpointingEnabled(RuntimeContext runtimeContext) { + return !(runtimeContext instanceof StreamingRuntimeContext && ((StreamingRuntimeContext) runtimeContext).isCheckpointingEnabled()); + } + + @Override + public void run(SourceContext<OUT> sourceContext) throws Exception { + while (isRunning) { + try { + if (maxMessagesToAcknowledgeLimitReached()) { Review comment: Sorry I forgot to mention that in the earlier comments, by explicit rate limiting I actually meant using `FlinkConnectorRateLimiter` and expose corresponding configurations to the users. In general, we would like to avoid the case that each individual connector implement their own way to do the throttling. > Without this limit, we will run into OOM exceptions. Lowering the CP interval does not matter because it is always trying to checkpoint but they just take too long to complete. Increasing the checkpoint timeout would work, but if this is increased too far the source can still fill up the memory. I am curious what is the cause of such continuous slow checkpoint. Usually a long checkpoint is caused by large state to be saved. And because the state to be saved are likely has a positive correlation with the records processed, a smaller CP interval would reduce the state to be saved in each CP and thus make the it faster. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. 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