记一次kafka莫名其妙关闭问题排查

现象：

FT走着走着，就没了；一检查，发现kafka没了

排查：

1. 先复现了一次，拿到server.log

[2021-09-14 16:53:07,545] ERROR [KafkaServer id=0] Fatal error during KafkaServer startup. Prepare to shutdown (kafka.server.KafkaServer) java.lang.InternalError: a fault occurred in a recent unsafe memory access operation in compiled Java code at scala.runtime.BoxesRunTime.equals2(BoxesRunTime.java:130) at scala.runtime.BoxesRunTime.equals(BoxesRunTime.java:123) at scala.collection.mutable.HashTable.elemEquals(HashTable.scala:365) at scala.collection.mutable.HashTable.elemEquals$(HashTable.scala:365) at scala.collection.mutable.HashMap.elemEquals(HashMap.scala:44) at scala.collection.mutable.HashTable.findEntry0(HashTable.scala:140) at scala.collection.mutable.HashTable.findEntry(HashTable.scala:136) at scala.collection.mutable.HashTable.findEntry$(HashTable.scala:135) at scala.collection.mutable.HashMap.findEntry(HashMap.scala:44) at scala.collection.mutable.HashMap.get(HashMap.scala:74) at kafka.log.ProducerStateManager.lastEntry(ProducerStateManager.scala:648) at kafka.log.ProducerStateManager.prepareUpdate(ProducerStateManager.scala:614) at kafka.log.LogSegment.updateProducerState(LogSegment.scala:248) at kafka.log.LogSegment.$anonfun$recover$1(LogSegment.scala:367) at kafka.log.LogSegment.$anonfun$recover$1$adapted(LogSegment.scala:344) at scala.collection.Iterator.foreach(Iterator.scala:943) at scala.collection.Iterator.foreach$(Iterator.scala:943) at scala.collection.AbstractIterator.foreach(Iterator.scala:1431) at scala.collection.IterableLike.foreach(IterableLike.scala:74) at scala.collection.IterableLike.foreach$(IterableLike.scala:73) at scala.collection.AbstractIterable.foreach(Iterable.scala:56) at kafka.log.LogSegment.recover(LogSegment.scala:344) at kafka.log.Log.recoverSegment(Log.scala:648) at kafka.log.Log.recoverLog(Log.scala:787) at kafka.log.Log.$anonfun$loadSegments$3(Log.scala:723) at scala.runtime.java8.JFunction0$mcJ$sp.apply(JFunction0$mcJ$sp.java:23) at kafka.log.Log.retryOnOffsetOverflow(Log.scala:2351) at kafka.log.Log.loadSegments(Log.scala:723) at kafka.log.Log.<init>(Log.scala:287) at kafka.log.Log$.apply(Log.scala:2485) at kafka.log.LogManager.loadLog(LogManager.scala:274) at kafka.log.LogManager.$anonfun$loadLogs$12(LogManager.scala:353) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)

2. 先确认了kafka的版本，安装包，java版本，java来源。因为是按照标准文档部署的，所以应该没啥问题。然后顺道看了下

df -lh
发现磁盘空间发现不对劲：

看了下kafka的配置文件server.properties

# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# see kafka.server.KafkaConfig for additional details and defaults

############################# Server Basics #############################

# The id of the broker. This must be set to a unique integer for each broker.
broker.id=0

############################# Socket Server Settings #############################

# The address the socket server listens on. It will get the value returned from 
# java.net.InetAddress.getCanonicalHostName() if not configured.
#   FORMAT:
#     listeners = listener_name://host_name:port
#   EXAMPLE:
#     listeners = PLAINTEXT://your.host.name:9092
#listeners=PLAINTEXT://:9092

# Hostname and port the broker will advertise to producers and consumers. If not set, 
# it uses the value for "listeners" if configured.  Otherwise, it will use the value
# returned from java.net.InetAddress.getCanonicalHostName().
#advertised.listeners=PLAINTEXT://your.host.name:9092

# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details
#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL

# The number of threads that the server uses for receiving requests from the network and sending responses to the network
num.network.threads=3

# The number of threads that the server uses for processing requests, which may include disk I/O
num.io.threads=8

# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=102400

# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=102400

# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600


############################# Log Basics #############################

# A comma separated list of directories under which to store log files
log.dirs=/tmp/kafka-logs

# The default number of log partitions per topic. More partitions allow greater
# parallelism for consumption, but this will also result in more files across
# the brokers.
num.partitions=1

# The number of threads per data directory to be used for log recovery at startup and flushing at shutdown.
# This value is recommended to be increased for installations with data dirs located in RAID array.
num.recovery.threads.per.data.dir=1

############################# Internal Topic Settings  #############################
# The replication factor for the group metadata internal topics "__consumer_offsets" and "__transaction_state"
# For anything other than development testing, a value greater than 1 is recommended to ensure availability such as 3.
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=1

############################# Log Flush Policy #############################

# Messages are immediately written to the filesystem but by default we only fsync() to sync
# the OS cache lazily. The following configurations control the flush of data to disk.
# There are a few important trade-offs here:
#    1. Durability: Unflushed data may be lost if you are not using replication.
#    2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush.
#    3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to excessive seeks.
# The settings below allow one to configure the flush policy to flush data after a period of time or
# every N messages (or both). This can be done globally and overridden on a per-topic basis.

# The number of messages to accept before forcing a flush of data to disk
#log.flush.interval.messages=10000

# The maximum amount of time a message can sit in a log before we force a flush
#log.flush.interval.ms=1000

############################# Log Retention Policy #############################

# The following configurations control the disposal of log segments. The policy can
# be set to delete segments after a period of time, or after a given size has accumulated.
# A segment will be deleted whenever *either* of these criteria are met. Deletion always happens
# from the end of the log.

# The minimum age of a log file to be eligible for deletion due to age
log.retention.hours=168

# A size-based retention policy for logs. Segments are pruned from the log unless the remaining
# segments drop below log.retention.bytes. Functions independently of log.retention.hours.
#log.retention.bytes=1073741824

# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=1073741824

# The interval at which log segments are checked to see if they can be deleted according
# to the retention policies
log.retention.check.interval.ms=300000

############################# Zookeeper #############################

# Zookeeper connection string (see zookeeper docs for details).
# This is a comma separated host:port pairs, each corresponding to a zk
# server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002".
# You can also append an optional chroot string to the urls to specify the
# root directory for all kafka znodes.
zookeeper.connect=localhost:2181

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=18000


############################# Group Coordinator Settings #############################

# The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance.
# The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms.
# The default value for this is 3 seconds.
# We override this to 0 here as it makes for a better out-of-the-box experience for development and testing.
# However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
group.initial.rebalance.delay.ms=0

log.dirs 就是存储所有 kafka 接收到的数据的，现在在/tmp下面，查看下LINUX的情况（老师不离开）
lsblk
这空间分配好像应该改下，安装FT等服务的时候应该注意下的，查看kafka数据文件的具体占用
du -ach --max-depth=1 /tmp

3. 寄！改下配置文件，以前的都是测试数据，删掉就好了。然后找到

log.dirs=/tmp/kafka-logs
改到家境优渥的home下
log.dirs=/home/kafka-logs
顺带着把另一个100%的解决了吧，直接卸载就行，一看修改时间已经是18年了，是安装时候遗留下来的。直接把/run/media/xxh/CentOS 7 x86_64删了。
rm -rf xxh/
寄！删了半天删不了，提示只读文件系统。查了下好像解决起来需要点时间，算了先这样吧，反正也不关键2333。
重启kafka，FT管道任务成功运行！