flink-1.11.2 的 内存溢出问题

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