現象：
FT走著走著，就沒了；一檢查，發現kafka沒了
排查：
1. 先復現了一次，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. 先確認了kafka的版本，安裝包，java版本，java來源，因為是按照標準檔案部署的，所以應該沒啥問題，然后順道看了下
df -lh
發現磁盤空間發現不對勁：
看了下kafka的組態檔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 就是存盤所有 kafka 接收到的資料的，現在在/tmp下面，查看下LINUX的情況（老師不離開）
lsblk
這空間分配好像應該改下，安裝FT等服務的時候應該注意下的，查看kafka資料檔案的具體占用
du -ach --max-depth=1 /tmp
3. 寄！改下組態檔，以前的都是測驗資料，刪掉就好了，然后找到
log.dirs=/tmp/kafka-logs
改到家境優渥的home下
log.dirs=/home/kafka-logs
順帶著把另一個100%的解決了吧，直接卸載就行，一看修改時間已經是18年了，是安裝時候遺留下來的，直接把/run/media/xxh/CentOS 7 x86_64刪了，
rm -rf xxh/
寄！刪了半天刪不了，提示只讀檔案系統，查了下好像解決起來需要點時間，算了先這樣吧，反正也不關鍵2333，
重啟kafka，FT管道任務成功運行！
后記:
已經有人走在了前面
https://my.oschina.net/u/4405061/blog/3326953
參考:
https://www.cnblogs.com/superlsj/p/11610517.html --LINUX磁盤掛載的邏輯
https://blog.csdn.net/qq_43427482/article/details/103552588 --超詳細的LINUX使用基礎
https://blog.csdn.net/gjalj10/article/details/95961456 --只讀檔案怎么洗掉
https://blog.csdn.net/whatday/article/details/100136236/ --解決100%爆滿的問題
彩蛋：
*** 你發現了嗎 ***
第一張圖中,有一句話“您在/var/spoot/mail/root 中有新的郵件”，我后來查看這個郵件的時候，內容是：
你沒有發現，因為你只關心你自己！
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