Hi John, I've experienced this issue recently; it's likely caused either by:
- the size of the producer record batch, it can be reduced by configuring lower linger.ms and batch.size values - the size of an individual record On Fri, Aug 23, 2024 at 7:20 AM Ahmed Hamdy <hamdy10...@gmail.com> wrote: > Why do you believe it is an SSL issue? > The error trace seems like a memory issue. you could refer to > taskmanager memory setup guide[1]. > > 1- > https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/memory/mem_setup_tm/ > > Best Regards > Ahmed Hamdy > > > On Fri, 23 Aug 2024 at 13:47, John Smith <java.dev....@gmail.com> wrote: > >> I'm pretty sure it's not SSL is there a way to confirm, since the take >> does work. And/or is there other settings I can try? >> >> On Thu, Aug 22, 2024, 11:06 AM John Smith <java.dev....@gmail.com> wrote: >> >>> Hi getting this exception, a lot of resources online point to an SSL >>> misconfiguration. >>> >>> We are NOT using SSL. Neither on the broker or the consumer side. Our >>> jobs work absolutely fine as in the flink task is able to consume from >>> kafka parse the json and then push it to the JDBC database sink. >>> >>> I would assume if SSL was enabled on one side or the other that the >>> records would be completely mangled and unparsable from not being able to >>> encrypt/decrypt. Also this seems to happen about once a week. >>> >>> 2024-08-22 10:17:09 >>> java.lang.RuntimeException: One or more fetchers have encountered >>> exception >>> at >>> org.apache.flink.connector.base.source.reader.fetcher.SplitFetcherManager.checkErrors(SplitFetcherManager.java:225) >>> at >>> org.apache.flink.connector.base.source.reader.SourceReaderBase.getNextFetch(SourceReaderBase.java:169) >>> at >>> org.apache.flink.connector.base.source.reader.SourceReaderBase.pollNext(SourceReaderBase.java:130) >>> at >>> org.apache.flink.streaming.api.operators.SourceOperator.emitNext(SourceOperator.java:351) >>> at >>> org.apache.flink.streaming.runtime.io.StreamTaskSourceInput.emitNext(StreamTaskSourceInput.java:68) >>> at >>> org.apache.flink.streaming.runtime.io.StreamOneInputProcessor.processInput(StreamOneInputProcessor.java:65) >>> at >>> org.apache.flink.streaming.runtime.tasks.StreamTask.processInput(StreamTask.java:496) >>> at >>> org.apache.flink.streaming.runtime.tasks.mailbox.MailboxProcessor.runMailboxLoop(MailboxProcessor.java:203) >>> at >>> org.apache.flink.streaming.runtime.tasks.StreamTask.runMailboxLoop(StreamTask.java:809) >>> at >>> org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:761) >>> at >>> org.apache.flink.runtime.taskmanager.Task.runWithSystemExitMonitoring(Task.java:958) >>> at >>> org.apache.flink.runtime.taskmanager.Task.restoreAndInvoke(Task.java:937) >>> at org.apache.flink.runtime.taskmanager.Task.doRun(Task.java:766) >>> at org.apache.flink.runtime.taskmanager.Task.run(Task.java:575) >>> at java.base/java.lang.Thread.run(Thread.java:829) >>> Caused by: java.lang.OutOfMemoryError: Direct buffer memory. The direct >>> out-of-memory error has occurred. This can mean two things: either job(s) >>> require(s) a larger size of JVM direct memory or there is a direct memory >>> leak. The direct memory can be allocated by user code or some of its >>> dependencies. In this case 'taskmanager.memory.task.off-heap.size' >>> configuration option should be increased. Flink framework and its >>> dependencies also consume the direct memory, mostly for network >>> communication. The most of network memory is managed by Flink and should >>> not result in out-of-memory error. In certain special cases, in particular >>> for jobs with high parallelism, the framework may require more direct >>> memory which is not managed by Flink. In this case >>> 'taskmanager.memory.framework.off-heap.size' configuration option should be >>> increased. If the error persists then there is probably a direct memory >>> leak in user code or some of its dependencies which has to be investigated >>> and fixed. The task executor has to be shutdown... >>> at java.base/java.nio.Bits.reserveMemory(Bits.java:175) >>> at java.base/java.nio.DirectByteBuffer.<init>(DirectByteBuffer.java:118) >>> at java.base/java.nio.ByteBuffer.allocateDirect(ByteBuffer.java:317) >>> at java.base/sun.nio.ch.Util.getTemporaryDirectBuffer(Util.java:242) >>> at java.base/sun.nio.ch.IOUtil.read(IOUtil.java:242) >>> at java.base/sun.nio.ch.IOUtil.read(IOUtil.java:223) >>> at >>> java.base/sun.nio.ch.SocketChannelImpl.read(SocketChannelImpl.java:356) >>> at >>> org.apache.kafka.common.network.PlaintextTransportLayer.read(PlaintextTransportLayer.java:103) >>> at >>> org.apache.kafka.common.network.NetworkReceive.readFrom(NetworkReceive.java:117) >>> at >>> org.apache.kafka.common.network.KafkaChannel.receive(KafkaChannel.java:424) >>> at >>> org.apache.kafka.common.network.KafkaChannel.read(KafkaChannel.java:385) >>> at >>> org.apache.kafka.common.network.Selector.attemptRead(Selector.java:651) >>> at >>> org.apache.kafka.common.network.Selector.pollSelectionKeys(Selector.java:572) >>> at org.apache.kafka.common.network.Selector.poll(Selector.java:483) >>> at org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:547) >>> at >>> org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:262) >>> at >>> org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:233) >>> at >>> org.apache.kafka.clients.consumer.KafkaConsumer.pollForFetches(KafkaConsumer.java:1300) >>> at >>> org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:1240) >>> at >>> org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:1211) >>> at >>> org.apache.flink.connector.kafka.source.reader.KafkaPartitionSplitReader.fetch(KafkaPartitionSplitReader.java:97) >>> at >>> org.apache.flink.connector.base.source.reader.fetcher.FetchTask.run(FetchTask.java:58) >>> at >>> org.apache.flink.connector.base.source.reader.fetcher.SplitFetcher.runOnce(SplitFetcher.java:142) >>> at >>> org.apache.flink.connector.base.source.reader.fetcher.SplitFetcher.run(SplitFetcher.java:105) >>> at >>> java.base/java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:515) >>> at java.base/java.util.concurrent.FutureTask.run(FutureTask.java:264) >>> at >>> java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) >>> at >>> java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) >>> ... 1 more >>> >>>
