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260 lines
10 KiB
Markdown
260 lines
10 KiB
Markdown
# Usage Recommendations
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## CPU
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The SSE 4.2 instruction set must be supported. Modern processors (since 2008) support it.
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When choosing a processor, prefer a large number of cores and slightly slower clock rate over fewer cores and a higher clock rate.
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For example, 16 cores with 2600 MHz is better than 8 cores with 3600 MHz.
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## Hyper-threading
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Don't disable hyper-threading. It helps for some queries, but not for others.
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## Turbo Boost
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Turbo Boost is highly recommended. It significantly improves performance with a typical load.
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You can use `turbostat` to view the CPU's actual clock rate under a load.
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## CPU Scaling Governor
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Always use the `performance` scaling governor. The `on-demand` scaling governor works much worse with constantly high demand.
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```bash
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sudo echo 'performance' | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
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```
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## CPU Limitations
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Processors can overheat. Use `dmesg` to see if the CPU's clock rate was limited due to overheating.
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The restriction can also be set externally at the datacenter level. You can use `turbostat` to monitor it under a load.
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## RAM
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For small amounts of data (up to \~200 GB compressed), it is best to use as much memory as the volume of data.
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For large amounts of data and when processing interactive (online) queries, you should use a reasonable amount of RAM (128 GB or more) so the hot data subset will fit in the cache of pages.
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Even for data volumes of \~50 TB per server, using 128 GB of RAM significantly improves query performance compared to 64 GB.
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## Swap File
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Always disable the swap file. The only reason for not doing this is if you are using ClickHouse on your personal laptop.
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## Huge Pages
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Always disable transparent huge pages. It interferes with memory allocators, which leads to significant performance degradation.
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```bash
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echo 'never' | sudo tee /sys/kernel/mm/transparent_hugepage/enabled
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```
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Use `perf top` to watch the time spent in the kernel for memory management.
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Permanent huge pages also do not need to be allocated.
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## Storage Subsystem
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If your budget allows you to use SSD, use SSD.
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If not, use HDD. SATA HDDs 7200 RPM will do.
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Give preference to a lot of servers with local hard drives over a smaller number of servers with attached disk shelves.
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But for storing archives with rare queries, shelves will work.
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## RAID
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When using HDD, you can combine their RAID-10, RAID-5, RAID-6 or RAID-50.
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For Linux, software RAID is better (with `mdadm`). We don't recommend using LVM.
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When creating RAID-10, select the `far` layout.
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If your budget allows, choose RAID-10.
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If you have more than 4 disks, use RAID-6 (preferred) or RAID-50, instead of RAID-5.
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When using RAID-5, RAID-6 or RAID-50, always increase stripe_cache_size, since the default value is usually not the best choice.
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```bash
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echo 4096 | sudo tee /sys/block/md2/md/stripe_cache_size
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```
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Calculate the exact number from the number of devices and the block size, using the formula: `2 * num_devices * chunk_size_in_bytes / 4096`.
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A block size of 1025 KB is sufficient for all RAID configurations.
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Never set the block size too small or too large.
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You can use RAID-0 on SSD.
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Regardless of RAID use, always use replication for data security.
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Enable NCQ with a long queue. For HDD, choose the CFQ scheduler, and for SSD, choose noop. Don't reduce the 'readahead' setting.
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For HDD, enable the write cache.
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## File System
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Ext4 is the most reliable option. Set the mount options `noatime, nobarrier`.
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XFS is also suitable, but it hasn't been as thoroughly tested with ClickHouse.
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Most other file systems should also work fine. File systems with delayed allocation work better.
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## Linux Kernel
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Don't use an outdated Linux kernel.
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## Network
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If you are using IPv6, increase the size of the route cache.
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The Linux kernel prior to 3.2 had a multitude of problems with IPv6 implementation.
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Use at least a 10 GB network, if possible. 1 Gb will also work, but it will be much worse for patching replicas with tens of terabytes of data, or for processing distributed queries with a large amount of intermediate data.
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## ZooKeeper
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You are probably already using ZooKeeper for other purposes. You can use the same installation of ZooKeeper, if it isn't already overloaded.
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It's best to use a fresh version of ZooKeeper – 3.4.9 or later. The version in stable Linux distributions may be outdated.
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You should never use manually written scripts to transfer data between different ZooKeeper clusters, because the result will be incorrect for sequential nodes. Never use the "zkcopy" utility for the same reason: https://github.com/ksprojects/zkcopy/issues/15
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If you want to divide an existing ZooKeeper cluster into two, the correct way is to increase the number of its replicas and then reconfigure it as two independent clusters.
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Do not run ZooKeeper on the same servers as ClickHouse. Because ZooKeeper is very sensitive for latency and ClickHouse may utilize all available system resources.
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With the default settings, ZooKeeper is a time bomb:
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> The ZooKeeper server won't delete files from old snapshots and logs when using the default configuration (see autopurge), and this is the responsibility of the operator.
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This bomb must be defused.
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The ZooKeeper (3.5.1) configuration below is used in the Yandex.Metrica production environment as of May 20, 2017:
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zoo.cfg:
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```bash
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# http://hadoop.apache.org/zookeeper/docs/current/zookeeperAdmin.html
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# The number of milliseconds of each tick
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tickTime=2000
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# The number of ticks that the initial
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# synchronization phase can take
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initLimit=30000
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# The number of ticks that can pass between
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# sending a request and getting an acknowledgement
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syncLimit=10
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maxClientCnxns=2000
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maxSessionTimeout=60000000
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# the directory where the snapshot is stored.
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dataDir=/opt/zookeeper/{{ cluster['name'] }}/data
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# Place the dataLogDir to a separate physical disc for better performance
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dataLogDir=/opt/zookeeper/{{ cluster['name'] }}/logs
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autopurge.snapRetainCount=10
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autopurge.purgeInterval=1
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# To avoid seeks ZooKeeper allocates space in the transaction log file in
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# blocks of preAllocSize kilobytes. The default block size is 64M. One reason
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# for changing the size of the blocks is to reduce the block size if snapshots
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# are taken more often. (Also, see snapCount).
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preAllocSize=131072
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# Clients can submit requests faster than ZooKeeper can process them,
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# especially if there are a lot of clients. To prevent ZooKeeper from running
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# out of memory due to queued requests, ZooKeeper will throttle clients so that
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# there is no more than globalOutstandingLimit outstanding requests in the
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# system. The default limit is 1,000.ZooKeeper logs transactions to a
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# transaction log. After snapCount transactions are written to a log file a
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# snapshot is started and a new transaction log file is started. The default
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# snapCount is 10,000.
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snapCount=3000000
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# If this option is defined, requests will be will logged to a trace file named
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# traceFile.year.month.day.
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#traceFile=
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# Leader accepts client connections. Default value is "yes". The leader machine
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# coordinates updates. For higher update throughput at thes slight expense of
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# read throughput the leader can be configured to not accept clients and focus
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# on coordination.
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leaderServes=yes
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standaloneEnabled=false
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dynamicConfigFile=/etc/zookeeper-{{ cluster['name'] }}/conf/zoo.cfg.dynamic
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```
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Java version:
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```
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Java(TM) SE Runtime Environment (build 1.8.0_25-b17)
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Java HotSpot(TM) 64-Bit Server VM (build 25.25-b02, mixed mode)
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```
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JVM parameters:
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```bash
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NAME=zookeeper-{{ cluster['name'] }}
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ZOOCFGDIR=/etc/$NAME/conf
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# TODO this is really ugly
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# How to find out, which jars are needed?
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# seems, that log4j requires the log4j.properties file to be in the classpath
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CLASSPATH="$ZOOCFGDIR:/usr/build/classes:/usr/build/lib/*.jar:/usr/share/zookeeper/zookeeper-3.5.1-metrika.jar:/usr/share/zookeeper/slf4j-log4j12-1.7.5.jar:/usr/share/zookeeper/slf4j-api-1.7.5.jar:/usr/share/zookeeper/servlet-api-2.5-20081211.jar:/usr/share/zookeeper/netty-3.7.0.Final.jar:/usr/share/zookeeper/log4j-1.2.16.jar:/usr/share/zookeeper/jline-2.11.jar:/usr/share/zookeeper/jetty-util-6.1.26.jar:/usr/share/zookeeper/jetty-6.1.26.jar:/usr/share/zookeeper/javacc.jar:/usr/share/zookeeper/jackson-mapper-asl-1.9.11.jar:/usr/share/zookeeper/jackson-core-asl-1.9.11.jar:/usr/share/zookeeper/commons-cli-1.2.jar:/usr/src/java/lib/*.jar:/usr/etc/zookeeper"
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ZOOCFG="$ZOOCFGDIR/zoo.cfg"
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ZOO_LOG_DIR=/var/log/$NAME
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USER=zookeeper
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GROUP=zookeeper
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PIDDIR=/var/run/$NAME
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PIDFILE=$PIDDIR/$NAME.pid
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SCRIPTNAME=/etc/init.d/$NAME
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JAVA=/usr/bin/java
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ZOOMAIN="org.apache.zookeeper.server.quorum.QuorumPeerMain"
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ZOO_LOG4J_PROP="INFO,ROLLINGFILE"
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JMXLOCALONLY=false
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JAVA_OPTS="-Xms{{ cluster.get('xms','128M') }} \
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-Xmx{{ cluster.get('xmx','1G') }} \
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-Xloggc:/var/log/$NAME/zookeeper-gc.log \
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-XX:+UseGCLogFileRotation \
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-XX:NumberOfGCLogFiles=16 \
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-XX:GCLogFileSize=16M \
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-verbose:gc \
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-XX:+PrintGCTimeStamps \
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-XX:+PrintGCDateStamps \
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-XX:+PrintGCDetails
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-XX:+PrintTenuringDistribution \
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-XX:+PrintGCApplicationStoppedTime \
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-XX:+PrintGCApplicationConcurrentTime \
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-XX:+PrintSafepointStatistics \
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-XX:+UseParNewGC \
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-XX:+UseConcMarkSweepGC \
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-XX:+CMSParallelRemarkEnabled"
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```
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Salt init:
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```
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description "zookeeper-{{ cluster['name'] }} centralized coordination service"
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start on runlevel [2345]
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stop on runlevel [!2345]
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respawn
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limit nofile 8192 8192
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pre-start script
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[ -r "/etc/zookeeper-{{ cluster['name'] }}/conf/environment" ] || exit 0
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. /etc/zookeeper-{{ cluster['name'] }}/conf/environment
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[ -d $ZOO_LOG_DIR ] || mkdir -p $ZOO_LOG_DIR
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chown $USER:$GROUP $ZOO_LOG_DIR
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end script
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script
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. /etc/zookeeper-{{ cluster['name'] }}/conf/environment
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[ -r /etc/default/zookeeper ] && . /etc/default/zookeeper
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if [ -z "$JMXDISABLE" ]; then
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JAVA_OPTS="$JAVA_OPTS -Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.local.only=$JMXLOCALONLY"
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fi
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exec start-stop-daemon --start -c $USER --exec $JAVA --name zookeeper-{{ cluster['name'] }} \
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-- -cp $CLASSPATH $JAVA_OPTS -Dzookeeper.log.dir=${ZOO_LOG_DIR} \
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-Dzookeeper.root.logger=${ZOO_LOG4J_PROP} $ZOOMAIN $ZOOCFG
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end script
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```
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[Original article](https://clickhouse.yandex/docs/en/operations/tips/) <!--hide-->
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