Maybe the change in direct memory allocation in java 11 did this? Java 8: By default, the amount of native memory used for Direct Byte Buffers is limited to 87.5% of the maximum heap size.
Java 11: By default, the amount of native memory used for Direct Byte Buffers is limited to the maximum heap size. On Sat, Aug 24, 2024, 3:18 PM John Smith <java.dev....@gmail.com> wrote: > The same exact task/code and exact same version of flink had no issues > before. > > The only thing that changed is deployed flink to java 11. Added more > memory to the config and increased the parallelism of the Kafka source. > > On Fri, Aug 23, 2024, 3:46 PM John Smith <java.dev....@gmail.com> wrote: > >> Online resources including my previous question to this problem said >> there was some client bug connecting to SSL broker that caused memory >> issues. As far as memory setup I have the following... >> >> Here is the link and there's a link to a JIRA... >> https://stackoverflow.com/questions/64697973/java-lang-outofmemoryerror-direct-buffer-memory-error-while-listening-kafka-top >> >> taskmanager.memory.flink.size: 16384m >> taskmanager.memory.jvm-metaspace.size: 3072m >> >> My task managers are 32GB each. >> >> >> On Fri, Aug 23, 2024 at 11:21 AM Yaroslav Tkachenko <yaros...@goldsky.com> >> wrote: >> >>> 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 >>>>>> >>>>>>
