使用的是rocksdb, 并行度是5,1个tm, 5个slot,tm 内存给 10G,启动任务报下面的错误。之前有启动成功过,运行一段时间后,也是报内存溢出,然后接成原来的offset启动任务,直接启动不起来了。
2020-11-16 17:44:52 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:658) at java.nio.DirectByteBuffer. (DirectByteBuffer.java:123) at java.nio.ByteBuffer.allocateDirect(ByteBuffer.java:311) at sun.nio.ch.Util.getTemporaryDirectBuffer(Util.java:174) at sun.nio.ch.IOUtil.read(IOUtil.java:195) at sun.nio.ch.SocketChannelImpl.read(SocketChannelImpl.java:380) at org.apache.flink.kafka011.shaded.org.apache.kafka.common.network.PlaintextTransportLayer.read(PlaintextTransportLayer.java:109) at org.apache.flink.kafka011.shaded.org.apache.kafka.common.network.NetworkReceive.readFromReadableChannel(NetworkReceive.java:101) at org.apache.flink.kafka011.shaded.org.apache.kafka.common.network.NetworkReceive.readFrom(NetworkReceive.java:75) at org.apache.flink.kafka011.shaded.org.apache.kafka.common.network.KafkaChannel.receive(KafkaChannel.java:203) at org.apache.flink.kafka011.shaded.org.apache.kafka.common.network.KafkaChannel.read(KafkaChannel.java:167) at org.apache.flink.kafka011.shaded.org.apache.kafka.common.network.Selector.pollSelectionKeys(Selector.java:381) at org.apache.flink.kafka011.shaded.org.apache.kafka.common.network.Selector.poll(Selector.java:326) at org.apache.flink.kafka011.shaded.org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:433) at org.apache.flink.kafka011.shaded.org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:232) at org.apache.flink.kafka011.shaded.org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:208) at org.apache.flink.kafka011.shaded.org.apache.kafka.clients.consumer.KafkaConsumer.pollOnce(KafkaConsumer.java:1096) at org.apache.flink.kafka011.shaded.org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:1043) at org.apache.flink.streaming.connectors.kafka.internal.KafkaConsumerThread.getRecordsFromKafka(KafkaConsumerThread.java:535) at org.apache.flink.streaming.connectors.kafka.internal.KafkaConsumerThread.run(KafkaConsumerThread.java:264) *来自志愿者整理的flink邮件归档
是什么部署模式呢?standalone? 之前任务运行一段时间报错之后,重新运行的时候是所有 TM 都重启了吗?还是有复用之前的 TM?
*来自志愿者整理的flink邮件归档
版权声明:本文内容由阿里云实名注册用户自发贡献,版权归原作者所有,阿里云开发者社区不拥有其著作权,亦不承担相应法律责任。具体规则请查看《阿里云开发者社区用户服务协议》和《阿里云开发者社区知识产权保护指引》。如果您发现本社区中有涉嫌抄袭的内容,填写侵权投诉表单进行举报,一经查实,本社区将立刻删除涉嫌侵权内容。