FLINK消费kafka 报错java.lang.OutOfMemoryError: Direct buffer memory

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香山上的麻雀 2022-01-07 16:09:27 博主文章分类：Flink ©著作权

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问题描述

flink 消费kafka 报错，kafka中的数据目前也不大，10个g左右

有时候几个小时报错，有时候3，5分钟报错，是不是kafka的参数没有设置好呢？目前jvm设置为16G，TM 内存也设置比较高的

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.nio.Bits.reserveMemory(Bits.java:695)
at java.nio.DirectByteBuffer.(DirectByteBuffer.java:123)
at java.nio.ByteBuffer.allocateDirect(ByteBuffer.java:311)
at sun.nio.ch.Util.getTemporaryDirectBuffer(Util.java:241)
at sun.nio.ch.IOUtil.read(IOUtil.java:195)
at sun.nio.ch.SocketChannelImpl.read(SocketChannelImpl.java:378)
at org.apache.flink.kafka.shaded.org.apache.kafka.common.network.PlaintextTransportLayer.read(PlaintextTransportLayer.java:103)
at org.apache.flink.kafka.shaded.org.apache.kafka.common.network.NetworkReceive.readFrom(NetworkReceive.java:117)
at org.apache.flink.kafka.shaded.org.apache.kafka.common.network.KafkaChannel.receive(KafkaChannel.java:424)
at org.apache.flink.kafka.shaded.org.apache.kafka.common.network.KafkaChannel.read(KafkaChannel.java:385)
at org.apache.flink.kafka.shaded.org.apache.kafka.common.network.Selector.attemptRead(Selector.java:651)
at org.apache.flink.kafka.shaded.org.apache.kafka.common.network.Selector.pollSelectionKeys(Selector.java:572)
at org.apache.flink.kafka.shaded.org.apache.kafka.common.network.Selector.poll(Selector.java:483)
at org.apache.flink.kafka.shaded.org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:547)
at org.apache.flink.kafka.shaded.org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:262)
at org.apache.flink.kafka.shaded.org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:233)
at org.apache.flink.kafka.shaded.org.apache.kafka.clients.consumer.KafkaConsumer.pollForFetches(KafkaConsumer.java:1300)
at org.apache.flink.kafka.shaded.org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:1240)
at org.apache.flink.kafka.shaded.org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:1168)
at org.apache.flink.streaming.connectors.kafka.internals.KafkaConsumerThread.run(KafkaConsumerThread.java:249)