Contents

1. 1. Cluster-setup
   1. 1.1. BIOS config for Disk
   2. 1.2. OS
      1. 1.2.1. update root password
      2. 1.2.2. sudo免密
      3. 1.2.3. ssh
      4. 1.2.4. partition
         1. 1.2.4.1. fdisk - 数据盘<2T，MBR
         2. 1.2.4.2. parted - 数据盘>2T，GPT
      5. 1.2.5. firewall
      6. 1.2.6. network
      7. 1.2.7. repo
   3. 1.3. soft
      1. 1.3.1. download
      2. 1.3.2. [[mysql#安装|MySQL]]
      3. 1.3.3. zookeeper
         1. 1.3.3.1. zk多节点配置
      4. 1.3.4. script
         1. 1.3.4.1. profile
      5. 1.3.5. hadoop
         1. 1.3.5.1. core-site.xml
         2. 1.3.5.2. hdfs-site.xml
         3. 1.3.5.3. mapred-site.xml
         4. 1.3.5.4. yarn-site.xml
         5. 1.3.5.5. hadoop-env.sh
         6. 1.3.5.6. capacity-scheduler.xml
         7. 1.3.5.7. slave
         8. 1.3.5.8. start-stop-script
         9. 1.3.5.9. simple/kerberos跨集群客户端配置
      6. 1.3.6. spark
         1. 1.3.6.1. spark-defaults.conf
      7. 1.3.7. flink
      8. 1.3.8. dolphinscheduler
      9. 1.3.9. hbase
         1. 1.3.9.1. hbase-site.xml
      10. 1.3.10. zeppelin
      11. 1.3.11. setting
          1. 1.3.11.1. hadoop
          2. 1.3.11.2. spark
          3. 1.3.11.3. hive
          4. 1.3.11.4. dolphinscheduler
2. 2. frequent usage
   1. 2.1. start
   2. 2.2. stop

Cluster-setup

BIOS config for Disk

• SystemDisk Raid 1
• DataDisk JBOD

OS

on demand, ubuntu\fedora\centos\suse\redhat

update root password

sudo passwd root

sudo免密

su 
chmod u+w /etc/sudoers
vi /etc/sudoers   # username  ALL=(ALL:ALL) NOPASSWD: ALL
chmod u-w /etc/sudoers  

ssh

yum install openssh-server
echo "PermitRootLogin yes" >> /etc/ssh/sshd_config
service sshd restart
systemctl enable sshd

ssh-keygen -t rsa -P '' -f ~/.ssh/id_rsa
cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys
chmod 0600 ~/.ssh/authorized_keys

ssh localhost

partition

fdisk - 数据盘<2T，MBR

partprobe
fdisk -l
fdisk /dev/sdb

新建分区np1w

mkfs -t ext4 /dev/sdb1
# mount /dev/sdb1 /mnt/
vi /etc/fstab 
/dev/sdb1 /opt ext4 defaults 0 0
mount -a

parted - 数据盘>2T，GPT

dev="/dev/sdb"
targetdir="/data"

sudo mkdir $targetdir
sudo chmod 755 $targetdir

parted $dev
mklabel gpt
mkpart
sdb1
ext4
0
50%
p
q

# 不分区 或 分区完成后
mkfs.ext4 /dev/sdb

lsblk # 确定数据盘设备
blkid # 如果没有目标设备返回值，先分区再sudo执行一次。或partprobe刷新
bid=`sudo blkid $dev |awk -F'"' '{print $2}'`
sudo sh -c "echo ${bid}"
sudo sh -c "echo 'UUID='${bid}  ${targetdir} 'ext4 defaults 0 2' >> /etc/fstab"
tail -2 /etc/fstab
sudo mount -a
df -h

# 挂载后
sudo mkdir -p /data/tmp
sudo chmod 757 /data/tmp

sudo mkdir -p /data/soft
sudo chmod 755 /data/soft
sudo chown hadoop /data/soft

firewall

[CentOS7开始使用firewall替代iptables]

-时间同步
sudo systemctl enable chronyd
sudo systemctl start chronyd
sudo vi /etc/chrony.conf
chronyc sources
server 10.153.1.248 iburst
server 10.153.1.249 iburst
-防火墙
systemctl stop firewalld
systemctl disable firewalld

firewalld

sudo systemctl start  firewalld
sudo systemctl status  firewalld
sudo systemctl stop firewalld

firewalld开放端口-CSDN博客

# 信任服务器
firewall-cmd --permanent --add-rich-rule="rule family="ipv4" source address="10.x.x.x" accept"

## **允许**
firewall-cmd --permanent --add-rich-rule='rule family="ipv4" source address="192.168.1.1" port protocol="tcp" port="80" accept'
## **禁止**
firewall-cmd --permanent --add-rich-rule='rule family="ipv4" source address="192.168.1.1" port protocol="tcp" port="80" reject'
## **移除**
firewall-cmd --permanent --remove-rich-rule='rule family="ipv4" source address="192.168.1.1" port protocol="tcp" port="80" accept'

firewall-cmd --permanent --add-source=192.168.1.1
firewall-cmd --permanent --add-source=192.168.1.0/24
firewall-cmd --permanent --remove-source=192.168.1.1

# 配置端口
sudo firewall-cmd --permanent --add-port=16010/tcp
sudo firewall-cmd --permanent --remove-port=8485/tcp

# 刷新配置使其生效
sudo firewall-cmd --reload
sudo firewall-cmd --list-all

network

tcpdump -nn -s 0 -i any host 10.33.21.191 and host 10.33.21.194

traceroute -nT 10.27.5.201 -p 3306

repo

/etc/yum.repos.d/
sed -i 's/mirrors.bclinux.org/mirrors-internal.cmecloud.cn/'   BCLinux-*.repo 
sed -i 's/mirrors.bclinux.org\/bclinux\/el8.2/mirrors-internal.cmecloud.cn\/bc82/'   BCLinux-*.repo 

/etc/hosts
100.127.128.193 mirrors-internal.cmecloud.cn
10.153.1.213 mirrors-internal.cmecloud.cn

soft

download

Fedora-Workstation-Live-x86_64-34-1.2.iso

https://repo.huaweicloud.com/java/jdk/8u202-b08/

[[mysql#安装|MySQL]]

zookeeper

cp conf/zoo_sample.cfg conf/zoo.cfg
bin/zkServer.sh start
bin/zkServer.sh status
echo stat |nc localhost 2181

bin/zkCli.sh -server 127.0.0.1:2181

zk ip白名单，修改需全量覆盖
setAcl / ip:192.168.1.112:cdrwa,ip:192.168.1.113:cdrwa,ip:127.0.0.1:cdrwa

getAcl /
setAcl / ip:10.27.48.0/24:cdrwa,ip:127.0.0.1:cdrwa
getAcl /

zk多节点配置

zookeeper/conf/zoo.cfg

dataDir=/opt/soft/zookeeper/data

server.0=localhost:2888:3888
server.1=north-191:2888:3888

4lw.commands.whitelist=*

echo 0 > /opt/soft/zookeeper/data/myid

script

https://www.oracle.com/java/technologies/javase/javase8-archive-downloads.html
https://dlcdn.apache.org/

RES_PATH=/data/tmp/pkg
INSTALL_PATH=/data/soft


binJDK=jdk-8u202-linux-x64.tar.gz
binHadoop=hadoop-3.3.2.tar.gz
binSpark=spark-3.3.1-bin-hadoop3.2.tgz
binFlink=flink-1.15.0-bin-scala_2.12.tgz
binHive=apache-hive-3.1.2-bin.tar.gz
binZk=apache-zookeeper-3.7.1-bin.tar.gz
binDS=apache-dolphinscheduler-2.0.5-bin.tar.gz

mkdir -p $INSTALL_PATH
sudo tar -xzf ${RES_PATH}/${binJDK}  -C ${INSTALL_PATH}
sudo tar -xzf ${RES_PATH}/${binHadoop}  -C ${INSTALL_PATH}
sudo tar -xzf ${RES_PATH}/${binSpark}  -C ${INSTALL_PATH}
sudo tar -xzf ${RES_PATH}/${binFlink}  -C ${INSTALL_PATH}
sudo tar -xzf ${RES_PATH}/${binZk} -C ${INSTALL_PATH}
sudo tar -xzf ${RES_PATH}/${binHive} -C ${INSTALL_PATH}
sudo tar -xzf ${RES_PATH}/datax-202210.tar.gz  -C ${INSTALL_PATH}

cd $INSTALL_PATH
folder=`tar -tf ${RES_PATH}/${binJDK} |head -1`
ln -s $folder jdk
folder=`tar -tf ${RES_PATH}/${binHadoop} |head -1`
ln -s $folder hadoop
folder=`tar -tf ${RES_PATH}/${binSpark} |head -1`
ln -s $folder spark
folder=`tar -tf ${RES_PATH}/${binFlink} |head -1`
ln -s $folder flink
folder=`tar -tf ${RES_PATH}/${binZk} |head -1 | awk -F/ '{print $1}'`
ln -s $folder zookeeper
folder=`tar -tf ${RES_PATH}/${binHive} |head -1 | awk -F/ '{print $1}'`
ln -s $folder hive

ll $INSTALL_PATH
sudo chown hadoop:hadoop -R $INSTALL_PATH
sudo chmod 755 -R $INSTALL_PATH

profile

echo -e '\n\n#Java' >> /etc/profile
echo 'export JAVA_HOME='${INSTALL_PATH}'/jdk' >> /etc/profile
echo 'export PATH=$JAVA_HOME/bin:$JAVA_HOME/jre/bin:$PATH' >> /etc/profile
echo 'export CLASSPATH=$CLASSPATH:.:$JAVA_HOME/lib:$JAVA_HOME/jre/lib' >> /etc/profile

echo -e '\n#Hadoop' >> /etc/profile
echo 'export HADOOP_HOME='${INSTALL_PATH}'/hadoop' >> /etc/profile
echo 'export PATH=$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH' >> /etc/profile
echo 'export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop' >> /etc/profile

echo -e '\n#Spark' >> /etc/profile
echo 'export SPARK_HOME='${INSTALL_PATH}'/spark' >> /etc/profile
echo 'export PATH=$SPARK_HOME/bin:$SPARK_HOME/sbin:$PATH' >> /etc/profile

echo -e '\n#Flink' >> /etc/profile
echo 'export FLINK_HOME='${INSTALL_PATH}'/flink' >> /etc/profile
echo 'export PATH=$FLINK_HOME/bin:$FLINK_HOME/sbin:$PATH' >> /etc/profile

echo -e '\n#zookeeper' >> /etc/profile
echo 'export ZK_HOME='${INSTALL_PATH}'/zookeeper' >> /etc/profile
echo 'export PATH=$ZK_HOME/bin:$PATH' >> /etc/profile

echo -e '\n#Hive' >> /etc/profile
echo 'export HIVE_HOME='${INSTALL_PATH}'/hive' >> /etc/profile
echo 'export PATH=$HIVE_HOME/bin:$PATH' >> /etc/profile

#ZK
export ZK_HOME=/data/soft/zookeeper
export PATH=$ZK_HOME/bin:$PATH

#Hadoop
export HADOOP_HOME=/data/soft/hadoop
export PATH=$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH
export HADOOP_CLASSPATH=`$HADOOP_HOME/bin/hadoop classpath`
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop

#Spark
export SPARK_HOME=/data/soft/spark
export PATH=$SPARK_HOME/bin:$SPARK_HOME/sbin:$PATH

#Flink
export FLINK_HOME=/data/soft/flink
export PATH=$FLINK_HOME/bin:$PATH

#HBase
export HBASE_HOME=/data/soft/hbase
export PATH=$HBASE_HOME/bin:$PATH

hadoop

hadoop checknative -a

core-site.xml

hadoop/etc/hadoop/core-site.xml

<configuration>
    <property>
        <name>fs.defaultFS</name>
        <value>hdfs://cluster</value>
    </property>
    <property>
        <name>hadoop.tmp.dir</name>
        <value>/data/data/hdfs/tmp</value>
    </property>
    <property>
        <name>ha.zookeeper.quorum</name>
        <value>north-190:2181,north-191:2181,north-192:2181,north-193:2181,north-194:2181</value>
    </property>  
    <!-- 配置hive server2权限和beeline无密码链接hive数据仓库-->
    <property>
        <name>hadoop.proxyuser.hadoop.hosts</name>
        <value>*</value>
    </property>
    <property>
        <name>hadoop.proxyuser.hadoop.groups</name>
        <value>*</value>
    </property>
    <property>
        <name>fs.trash.interval</name>
        <value>1440</value>
    </property>
    <property>
        <name>io.file.buffer.size</name>
        <value>65536</value>
    </property>
</configuration>

hdfs-site.xml

<configuration>
    <property>
        <name>dfs.replication</name>
        <value>2</value>
    </property>
    <property>
        <name>dfs.namenode.name.dir</name>
        <value>/data/data/hdfs/name</value>
    </property>
    <property>
        <name>dfs.datanode.data.dir</name>
        <value>/data/data/hdfs/data</value>
    </property>
    <property>
        <name>dfs.journalnode.edits.dir</name>
        <value>/data/data/hdfs/jn</value>
    </property>
    <property>
        <name>dfs.namenode.handler.count</name>
        <value>80</value>
    </property>
    <property>
        <name>dfs.datanode.handler.count</name>
        <value>80</value>
    </property>
    <!-- 指定NameNode元数据在JournalNode上的存放位置 -->
    <property>
        <name>dfs.namenode.shared.edits.dir</name>
        <value>qjournal://north-190:8485;north-191:8485;north-192:8485;north-193:8485;north-194:8485/cluster</value>
    </property>
    <property>
        <name>dfs.nameservices</name>
        <value>cluster</value>
    </property>
    <property>
        <name>dfs.ha.namenodes.cluster</name>
        <value>nn1,nn2</value>
    </property>
    <!-- nn1的RPC通信地址 -->
    <property>
        <name>dfs.namenode.rpc-address.cluster.nn1</name>
        <value>north-190:9000</value>
    </property>
    <!-- nn2的RPC通信地址 -->
    <property>
        <name>dfs.namenode.rpc-address.cluster.nn2</name>
        <value>north-192:9000</value>
    </property>
    <!-- nn1的http通信地址 -->
    <property>
        <name>dfs.namenode.http-address.cluster.nn1</name>
        <value>north-190:50070</value>
    </property>
    <!-- nn2的http通信地址 -->
    <property>
        <name>dfs.namenode.http-address.cluster.nn2</name>
        <value>north-192:50070</value>
    </property>
    <property>
        <name>dfs.namenode.lifeline.rpc-address.cluster.nn1</name>
        <value>north-190:8050</value>
    </property>
    <property>
        <name>dfs.namenode.lifeline.rpc-address.cluster.nn2</name>
        <value>north-192:8050</value>
    </property>
<!--  设置为dataNode数量  -->
    <property>
        <name>dfs.namenode.lifeline.handler.count</name>
        <value>10</value>
    </property>
    <!-- 启用异步审核日志记录开启异步日志：如果为 true，则启用异步审核日志 -->
    <property>
        <name>dfs.namenode.audit.log.async</name>
        <value>true</value>
    </property>
    <property>
        <name>dfs.permissions.enable</name>
        <value>true</value>
    </property>
    <property>
        <name>dfs.ha.fencing.methods</name>
        <value>shell(/bin/true)</value>
    </property>
    <!-- 访问代理类：client，mycluster，active配置失败自动切换实现方式-->
    <property>
        <name>dfs.client.failover.proxy.provider.cluster</name>
        <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
    </property>
    <property>
        <name>dfs.ha.automatic-failover.enabled</name>
        <value>true</value>
    </property>
    <property>
        <name>dfs.blocksize</name>
        <value>256m</value>
    </property>
    <property>
        <name>dfs.datanode.fsdataset.volume.choosing.policy</name>
        <value>org.apache.hadoop.hdfs.server.datanode.fsdataset.AvailableSpaceVolumeChoosingPolicy</value>
    </property>
    <!-- 100G -->
    <property>
        <name>dfs.datanode.du.reserved</name>
        <value>107374182400</value>
    </property>
    <property>
        <name>dfs.checksum.type</name>
        <value>CRC32</value>
    </property>
    <!-- 设置为600秒 即10分钟。默认60000 ms 即60秒 Holder DFSClient_NONMAPREDUCE_ does not have any open files-->
    <property>
        <name>dfs.client.socket-timeout</name>
        <value>600000</value>
    </property>
    <!-- 设置为1200000毫秒即20分钟。默认值480秒 即 8分钟 -->
    <property>
        <name>dfs.datanode.socket.write.timeout</name>
        <value>1200000</value>
    </property>
    <!-- 指定用于将数据传入和传出DN的最大线程数。默认值为4096 -->
    <property>
        <name>dfs.datanode.max.transfer.threads</name>
        <value>16384</value>
    </property>
</configuration>

mapred-site.xml

<configuration>
    <!-- 指定MR运行在Yarn上 -->
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
    <property>
        <name>mapreduce.map.output.compress</name>
        <value>true</value>
    </property>
    <property>
        <name>mapreduce.client.submit.file.replication</name>
        <value>3</value>
    </property>    
</configuration>

yarn-site.xml

<configuration>
    <property>
        <name>yarn.nodemanager.local-dirs</name>
        <value>/data/data/yarn/nm-local-dir</value>
    </property>
    <property>
        <name>yarn.nodemanager.log-dirs</name>
        <value>/data/data/yarn/logs</value>
    </property>
    <property>
        <name>yarn.resourcemanager.ha.enabled</name>
        <value>true</value>
    </property>
    <property>
        <name>yarn.resourcemanager.cluster-id</name>
        <value>cluster1</value>
    </property>
    <property>
        <name>yarn.resourcemanager.ha.rm-ids</name>
        <value>rm1,rm2</value>
    </property>
    <property>
        <name>yarn.resourcemanager.hostname.rm1</name>
        <value>north-190</value>
    </property>
    <property>
        <name>yarn.resourcemanager.hostname.rm2</name>
        <value>north-193</value>
    </property>
<!-- webapp.address 不配置会导致sparkUI 500   -->
    <property>
        <name>yarn.resourcemanager.webapp.address.rm1</name>
        <value>north-190:8088</value>
    </property>
    <property>
        <name>yarn.resourcemanager.webapp.address.rm2</name>
        <value>north-193:8088</value>
    </property>
    <property>
        <name>yarn.resourcemanager.zk-address</name>
        <value>north-190:2181,north-191:2181,north-192:2181,north-193:2181,north-194:2181</value>
    </property>
    <property>
        <name>yarn.resourcemanager.store.class</name>
        <value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>
    </property>
    <property>
        <name>yarn.resourcemanager.recovery.enabled</name>
        <value>true</value>
    </property>
    <property>
        <name>yarn.resourcemanager.recovery.enabled</name>
        <value>true</value>
    </property>
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
    <property>
        <name>yarn.nodemanager.resource.memory-mb</name>
        <value>225280</value>
    </property>
    <property>
        <name>yarn.nodemanager.resource.cpu-vcores</name>
        <value>40</value>
    </property>

<property>
    <name>yarn.log-aggregation-enable</name>
    <value>true</value>
    <description>开启application 日志聚合功能</description>
</property>
<property>
    <name>yarn.log-aggregation.retain-seconds</name>
    <value>259200</value>
    <description>设置聚合日志保存时间3天</description>
</property>
<property>
    <name>yarn.log-aggregation.retain-check-interval-seconds</name>
    <value>86400</value>
    <description>清理过期聚合日志程序的执行间隔时间</description>
</property>
<property>
    <name>yarn.nodemanager.remote-app-log-dir</name>
    <value>/yarn/logs</value>
    <description>聚合日志在hdfs上的目录</description>
</property>
<property>
    <name>yarn.log.server.url</name>
    <value>http://cluster/yarn/jobhistory/logs</value>
    <description>历史日志对应路径</description>
</property>
<property>
    <name>yarn.nodemanager.vmem-check-enabled</name>
    <value>false</value>
</property>
<property>
    <name>yarn.nodemanager.pmem-check-enabled</name>
    <value>false</value>
</property>
<property>
    <name>yarn.node-labels.fs-store.root-dir</name>
    <value>hdfs://cluster/yarn/node-labels/</value>
</property>
<property>
    <name>yarn.node-labels.enabled</name>
    <value>true</value>
</property>
<!-- [可选] NM中容器管理器的地址 IP:port
必须显式指定每个机器的Node Address。
如果不显式配置该属性值的话，则默认使用主机名(机器名)作为Node Address的IP，并且每次启动时端口都会随机变化。-->
<property>
    <name>yarn.nodemanager.address</name>
    <value>ip:45454</value>
</property>
</configuration>

hadoop-env.sh

# 避免pid在tmp目录被清除
export HADOOP_PID_DIR=/data/soft/hadoop/pid
export HADOOP_SECURE_DN_PID_DIR=${HADOOP_PID_DIR}
export HADOOP_HEAPSIZE=4096
export HADOOP_NAMENODE_INIT_HEAPSIZE=2048

capacity-scheduler.xml

yarn.scheduler.capacity.resource-calculator改成 DominantResourceCalculator

slave

start-stop-script

$ZK_HOME/bin/zkServer.sh start

$HADOOP_HOME/sbin/hadoop-daemon.sh start namenode
$HADOOP_HOME/sbin/hadoop-daemon.sh start datanode
$HADOOP_HOME/sbin/hadoop-daemon.sh start journalnode
$HADOOP_HOME/sbin/hadoop-daemon.sh start zkfc

$HADOOP_HOME/sbin/yarn-daemon.sh start resourcemanager
$HADOOP_HOME/sbin/yarn-daemon.sh start nodemanager
$HADOOP_HOME/sbin/mr-jobhistory-daemon.sh start historyserver

yarn rmadmin -getAllServiceState

service  mariadb  start

$SPARK_HOME/sbin/start-history-server.sh

hbase-daemon.sh start master
hbase-daemon.sh start master --backup
hbase-daemon.sh start regionserver

hdfs namenode -format

hdfs dfs -mkdir  /input
hdfs dfs -put README.txt /input
hdfs dfs -ls  /input
hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.8.3.jar wordcount /input /output
hdfs dfs -ls /output
hdfs dfs -tail /output/part-r-00000

hdfs dfs -rmr /output /input

simple/kerberos跨集群客户端配置

<property>
  <name>ipc.client.fallback-to-simple-auth-allowed</name>
  <value>true</value>
</property>

<property>
  <name>fs.defaultFS</name>
  <value>hdfs://gdhlwtz</value>
</property>

<property>
  <name>hadoop.security.authentication</name>
  <value>kerberos</value>
</property>

<property>
	<name>dfs.nameservices</name>
	<value>gdhlwtz</value>
	</property>
	
	<property>
	<name>dfs.ha.namenodes.gdhlwtz</name>
	<value>nn1,nn2</value>
	</property>
	
	<property>
	  <name>dfs.namenode.rpc-address.gdhlwtz.nn1</name>
	  <value>xxx:8020</value>
	</property>
	
	<property>
	  <name>dfs.namenode.rpc-address.gdhlwtz.nn2</name>
	  <value>xxx:8020</value>
	</property>
	
	 <property>
	      <name>dfs.client.failover.proxy.provider.gdhlwtz</name>
	      <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
	</property>
	
	    <property>
	      <name>dfs.namenode.kerberos.principal</name>
	      <value>nn/_HOST@HLWKDC</value>
	    </property>

spark

snappy usage

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$HADOOP_HOME/lib/native:/usr/lib64
spark-shell --master local[1]

不配置下：使用本机资源
./sbin/start-thriftserver.sh
./bin/beeline -u jdbc:hive2://localhost:10000 -n hadoop

CREATE TABLE parquet_test (
 id int,
 str string)
STORED AS PARQUET;
  

insert into table parquet_test values(1,'a'),(2,'b');
select * from parquet_test;
drop table parquet_test;

spark-defaults.conf

cd jars/
zip spark-jar.zip ./*
mv spark-jar.zip ../
cd ..
chmod 644 spark-jar.zip

或者
hdfs dfs -mkdir /spark
hdfs dfs -put jars/ /spark

spark.master=yarn
#spark.yarn.jars=hdfs:///spark/jars/*.jar
spark.yarn.archive hdfs:///spark/spark-jar.zip
spark.serializer=org.apache.spark.serializer.KryoSerializer
spark.sql.warehouse.dir=hdfs:///hive/warehouse

spark.eventLog.enabled                 true
spark.eventLog.dir                     hdfs:///spark/spark-history
spark.eventLog.compress                true
spark.history.fs.logDirectory          hdfs:///spark/spark-history

spark.sql.hive.metastore.version=2.3.7

export SPARK_DIST_CLASSPATH=$(hadoop classpath)
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop

#### hive-site.xml

手动先创建数据库 `create database hive character set latin1;`

```xml
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
    <property>
        <name>javax.jdo.option.ConnectionURL</name>
        <value>jdbc:mysql://ip:3306/hive?createDatabaseIfNotExist=true&amp;characterEncoding=UTF-8&amp;useSSL=false</value>
    </property>
    <property>
        <name>javax.jdo.option.ConnectionDriverName</name>
        <value>com.mysql.jdbc.Driver</value>
    </property>
    <property>
        <name>javax.jdo.option.ConnectionUserName</name>
        <value>root</value>
    </property>
    <property>
        <name>javax.jdo.option.ConnectionPassword</name>
        <value>xxx</value>
    </property>
    <property>
        <name>hive.metastore.schema.verification</name>
        <value>false</value>
    </property>
    <property>
        <name>datanucleus.schema.autoCreateAll</name>
        <value>true</value>
    </property>

</configuration>

flink

./bin/start-cluster.sh
./bin/flink run examples/streaming/WordCount.jar
./bin/flink run -m yarn-cluster examples/streaming/WordCount.jar
tail log/flink-*-taskexecutor-*.out
./bin/stop-cluster.sh

操作示例

dolphinscheduler

限制sudo切换用户
root ALL=(ALL) ALL
dolphinscheduler ALL=(hadoop) NOPASSWD:ALL

用户 主机=(用户:用户组) 命令

• 用户名或者用户组，表示谁有权限来使用后面的配置。%sudo代表sudo组下的所有用户
• 表示来源地，即从(远程)哪执行这条命令。ALL表示所有计算机
• 表示sudo可以切换到什么用户。ALL表示所有用户
• 表示sudo可以切换到哪些组下的用户。ALL表示所有组
• 表示sudo之后能够执行的命令。NOPASSWD:ALL表示执行任意命令都不需要密码

  yum -y install psmisc
  tar -xf ${binDS}
  folder=`tar -tf ${binDS} |head -1 | awk -F/ '{print $1}'`
  ln -s $folder dolphinscheduler

zk info to restart service

echo "ls /dolphinscheduler/nodes/master" |zkCli.sh -server <ip>:2181 |tail -2

vi ds-watcher.sh

#!/bin/bash

restart_master()
{
#pid=`pgrep -f org.apache.dolphinscheduler.server.master.MasterServer`
/usr/bin/pkill -f org.apache.dolphinscheduler.server.master.MasterServer
rm -f /data/dolphinscheduler-1.3.6/pid/dolphinscheduler-master-server.pid
sleep 3s
su dolphinscheduler -c "sh /data/dolphinscheduler-1.3.6/bin/dolphinscheduler-daemon.sh start master-server"
}

restart_worker()
{
#pid=`pgrep -f org.apache.dolphinscheduler.server.worker.WorkerServer`
/usr/bin/pkill -f org.apache.dolphinscheduler.server.worker.WorkerServer
rm -f /data/dolphinscheduler-1.3.6/pid/dolphinscheduler-worker-server.pid
sleep 3s
su dolphinscheduler -c "sh /data/dolphinscheduler-1.3.6/bin/dolphinscheduler-daemon.sh start worker-server"
}

# master
ret=`java -cp /data/dolphinscheduler-1.3.6/ds-watcher.jar  ds.ZkCheckNode master:2181,slave1:2181,slave2:2181 /dolphinscheduler/nodes/master/10.17.41.129:5678`

if [ $ret = 'false' ] ;then
restart_master
fi


# worker
ret=`java -cp /data/dolphinscheduler-1.3.6/ds-watcher.jar  ds.ZkCheckNode master:2181,slave1:2181,slave2:2181 /dolphinscheduler/nodes/worker/10.17.41.129/10.17.41.129:1234`

if [ $ret = 'false' ] ;then
restart_worker
fi


crontab -e
*/5 * * * * /bin/sh /data/dolphinscheduler-1.3.6/ds-watcher.sh

hbase

tar -xf hbase-2.4.6-bin.tar.gz
folder=`tar -tf ${binHBase} |head -1 | awk -F/ '{print $1}'`
ln -s $folder hbase


[本地测试请配置hbase-site.xml加入hbase.rootdir]
 <property>
    <name>hbase.rootdir</name>
    <value>file:///opt/soft/hbase-data</value>
  </property>



手动启动： --config "${HBASE_CONF_DIR}"
hbase-daemon.sh start master
hbase-daemon.sh start regionserver
hbase-daemon.sh start master --backup


bin/start-hbase.sh
./bin/hbase shell

create 'test', 'cf'
list 'test'
describe 'test'
put 'test', 'row1', 'cf:a', 'value1'
scan 'test'
get 'test', 'row1'
disable 'test'
drop 'test'

hbase-site.xml

<configuration>
    <property>
        <name>hbase.cluster.distributed</name>
        <value>true</value>
    </property>
    <property>
        <name>hbase.rootdir</name>
        <value>hdfs://cluster/hbase</value>
    </property>
    <property>
        <name>hbase.tmp.dir</name>
        <value>/data/data/hbase/tmp</value>
    </property>
    <property>
        <name>hbase.zookeeper.property.dataDir</name>
        <value>/data/data/hbase/zkdata</value>
    </property>
    <property>
        <name>hbase.zookeeper.quorum</name>
        <value>north-190:2181,north-191:2181,north-192:2181,north-193:2181,north-194:2181</value>
    </property>
    <property>
        <name>hbase.unsafe.stream.capability.enforce</name>
        <value>false</value>
    </property>
</configuration>

zeppelin

tar xf zeppelin-0.10.0-bin-all.tgz

cp conf/zeppelin-site.xml.template conf/zeppelin-site.xml
vi conf/zeppelin-site.xml
cp zeppelin-env.sh.template zeppelin-env.sh
vi zeppelin-env.sh
bin/zeppelin-daemon.sh start

setting

source /etc/profile

hadoop

vi etc/hadoop/core-site.xml

<configuration>
    <property>
        <name>fs.defaultFS</name>
        <value>hdfs://localhost:9000</value>
    </property>
    <property>
        <name>hadoop.tmp.dir</name>
        <value>/opt/hdfs/tmp</value>
    <description>temporary directories.</description>
    </property>
</configuration>

vi etc/hadoop/hdfs-site.xml

<configuration>
    <property>
        <name>dfs.replication</name>
        <value>1</value>
    </property>
    <property>
        <name>dfs.namenode.name.dir</name>
        <value>/opt/hdfs/name</value>
    </property>
    <property>
        <name>dfs.datanode.data.dir</name>
        <value>/opt/hdfs/data</value>
    </property>
</configuration>

vi hadoop_env.sh

# limit who can execute certain subcommands. 
export JAVA_HOME=/opt/soft/jdk
export HDFS_NAMENODE_USER=root
export HDFS_DATANODE_USER=root
export HDFS_SECONDARYNAMENODE_USER=root
export YARN_RESOURCEMANAGER_USER=root
export YARN_NODEMANAGER_USER=root

分发&启动

#scp -r hadoop-3.2.1 root@hadoop1:/data1/
cd $HADOOP_HOME
mkdir -p /opt/hdfs/name
mkdir -p /opt/hdfs/data
mkdir -p /opt/hdfs/tmp

hdfs namenode -format

start-dfs.sh
http://192.168.56.101:9870/

start-yarn.sh
http://192.168.56.101:8088/

TestCase

hdfs dfs -mkdir /in
hdfs dfs -put README.txt /in
hdfs dfs -ls /in
hadoop jar ./share/hadoop/mapreduce/hadoop-mapreduce-examples-*.jar wordcount /in /out
hdfs dfs -cat /out/part-r-00000 |head
hdfs dfs -rmr /in /out

HA 启动

[主]hdfs zkfc -formatZK
[主]hdfs namenode -format
[备]hdfs namenode -bootstrapStandby

HA切换

nn1 -> nn2
hdfs haadmin -getAllServiceState
hdfs haadmin -failover nn1 nn2
hdfs haadmin -getAllServiceState

nn2 -> nn1
hdfs haadmin -failover nn2 nn1

spark

cd $SPARK_HOME

hdfs dfs -mkdir -p /spark/lib
hdfs dfs -mkdir -p /spark/spark-history
hdfs dfs -put jars/* /spark/lib

cp conf/spark-env.sh.template conf/spark-env.sh
echo -e '\nexport HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop' >> conf/spark-env.sh
cp conf/spark-defaults.conf.template conf/spark-defaults.conf

echo -e '\n\n' >> conf/spark-defaults.conf
echo 'spark.master=yarn' >> conf/spark-defaults.conf
echo 'spark.yarn.jars=hdfs:///spark/lib' >> conf/spark-defaults.conf
echo 'spark.serializer=org.apache.spark.serializer.KryoSerializer' >> conf/spark-defaults.conf
echo 'spark.sql.warehouse.dir=hdfs:///user/hive/warehouse' >> conf/spark-defaults.conf
echo 'spark.eventLog.enabled           true' >> conf/spark-defaults.conf
echo 'spark.eventLog.dir               hdfs:///spark/spark-history' >> conf/spark-defaults.conf
echo 'spark.eventLog.compress          true' >> conf/spark-defaults.conf
echo 'spark.history.fs.logDirectory    hdfs:///spark/spark-history' >> conf/spark-defaults.conf


./bin/spark-submit --master yarn --class org.apache.spark.examples.SparkPi examples/jars/spark-examples*.jar 10

./sbin/start-thriftserver.sh --driver-memory 2g --executor-memory 4g --executor-cores 5 --num-executors 5
./bin/beeline -n root -u jdbc:hive2://localhost:10000

控制访问权限方案

• thriftserver使用proxyuser （此方式可以共用sts进行有限制的读写）
• zeppelin不使用proxyuser （此方式可以支持跟踪每个用户的sql但不能写）
• hdfs设定目录权限给proxyuser

sbin/start-thriftserver.sh
–master yarn
–driver-cores 2
–driver-memory 6G
–executor-cores 5
–executor-memory 6G
–num-executors 10
–proxy-user zeppelin
–conf spark.default.parallelism=80
–conf spark.sql.shuffle.partitions=80
–conf spark.sql.adaptive.enabled=true
–conf spark.scheduler.mode=FAIR
–conf spark.network.timeout=600s
–conf spark.memory.fraction=0.8
–conf spark.dynamicAllocation.shuffleTracking.enabled=true
–conf spark.dynamicAllocation.shuffleTracking.timeout=180000
–conf spark.dynamicAllocation.enabled=true
–conf spark.dynamicAllocation.minExecutors=3
–conf spark.dynamicAllocation.maxExecutors=50
–hiveconf hive.server2.thrift.port=10199
–hiveconf hive.default.fileformat=Orc

create database t;
use t;
create table test(
id int,
name string
) stored as parquet;
desc formatted test;
insert into table test values (1,'a'),(2,'b');
select * from test;

hive

create db and user in mysql

create database hive;
grant all on hive.* to hive@'%'  identified by 'Hive!@#2023';
grant all on hive.* to hive@'localhost'  identified by 'Hive!@#2023';
flush privileges;

Hive表设置支持中文注释、中文表数据导入

alter table COLUMNS_V2 modify column COMMENT varchar(256) character set utf8;
alter table TABLE_PARAMS modify column PARAM_VALUE varchar(4000) character set utf8;
alter table PARTITION_PARAMS  modify column PARAM_VALUE varchar(4000) character set utf8;
alter table PARTITION_KEYS  modify column PKEY_COMMENT varchar(4000) character set utf8;
alter table  INDEX_PARAMS  modify column PARAM_VALUE  varchar(4000) character set utf8;

还需要在mysql的hive中执行 hive安装包中TXN schema初始化sql

mv mysql-connector-java-5.1.48.jar $HIVE_HOME/lib

cd $HIVE_HOME/conf
#cp hive-env.sh.template hive-env.sh
cp hive-default.xml.template hive-site.xml
cp hive-log4j2.properties.template hive-log4j2.properties
cp hive-exec-log4j2.properties.template hive-exec-log4j2.properties

vi hive-site.xml

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
    <name>javax.jdo.option.ConnectionURL</name>
    <value>jdbc:mysql://[IP]:3306/[DB]?characterEncoding=UTF-8&useSSL=false</value>
  </property>
  <property>
    <name>javax.jdo.option.ConnectionDriverName</name>
    <value>com.mysql.jdbc.Driver</value>
  </property>
  <property>
    <name>javax.jdo.option.ConnectionUserName</name>
    <value>hive</value>
  </property>
  <property>
    <name>javax.jdo.option.ConnectionPassword</name>
    <value>hive</value>
  </property>
  <property>
  <name>hive.metastore.uris</name>
  <value>thrift://[hostname]:9083</value>
  <description>Thrift uri for the remote metastore. Used by metastore client to connect to remote metastore.</description>
</property>
    <property>
        <name>hive.metastore.schema.verification</name>
        <value>false</value>
    </property>
</configuration>

in vi, update system var to absolute path
:%s#${system:java.io.tmpdir}#/tmp/javaiotmp#g
:%s#${system:user.name}#hive#g

hadoop fs -mkdir -p /user/hive/warehouse  
hadoop fs -mkdir -p /user/hive/tmp  
hadoop fs -mkdir -p /user/hive/log  
hadoop fs -chmod -R 777 /user/hive/warehouse  
hadoop fs -chmod -R 777 /user/hive/tmp  
hadoop fs -chmod -R 777 /user/hive/log  

initialize

$HIVE_HOME/bin/schematool -dbType mysql -initSchema hive hive

standalone run

nohup $HIVE_HOME/bin/hiveserver2 &

$HIVE_HOME/bin/beeline

!connect jdbc:hive2://localhost:10000 hive hive

as meta service for spark
copy hive-site.xml to $SPARK-HOME/conf

hive --service metastore &
spark-sql

CREATE TABLE emp (
empno int,
name string
)stored as PARQUET;

insert into table emp values (1,'a'),(2,'b');

CREATE TABLE info (
age int,
name string
)stored as PARQUET;

insert into table info values (11,'a'),(22,'b');

role

https://www.cnblogs.com/yszd/p/11086677.html

set role admin;
show roles;
SHOW CURRENT ROLES;    
CREATE ROLE guest;
show grant on all;
show grant user manhua on database default;

GRANT SELECT ON TABLE default.emp TO ROLE guest;
grant select on database default to user manhua;

GRANT ROLE guest TO USER hadoop;
REVOKE ALL PRIVILEGES on default.emp from user hadoop;

revoke role role_test1 from user jayliu;
revoke ALL on database default from user lisi;

revoke select on database default from user hive;
revoke select on TABLE default.emp from user hadoop;

dolphinscheduler

useradd dolphinscheduler
echo "dolphinscheduler" | passwd --stdin dolphinscheduler
sed -i '$adolphinscheduler  ALL=(ALL)  NOPASSWD: NOPASSWD: ALL' /etc/sudoers
sed -i 's/Defaults    requirett/#Defaults    requirett/g' /etc/sudoers
chown -R dolphinscheduler:dolphinscheduler $folder

su dolphinscheduler

ssh-keygen -t rsa -P '' -f ~/.ssh/id_rsa
cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys
chmod 600 ~/.ssh/authorized_keys

mysql -uroot -p

CREATE DATABASE dolphinscheduler DEFAULT CHARACTER SET utf8 DEFAULT COLLATE utf8_general_ci;
GRANT ALL PRIVILEGES ON dolphinscheduler.* TO 'dolphinscheduler'@'%' IDENTIFIED BY 'ds';
GRANT ALL PRIVILEGES ON dolphinscheduler.* TO 'dolphinscheduler'@'localhost' IDENTIFIED BY 'ds';
 flush privileges;

vi conf/datasource.properties

SPRING_DATASOURCE_URL="jdbc:mysql://10.3.16.120:3306,10.3.16.121:3306/dolphinscheduler?autoReconnect=true&useUnicode=true&characterEncoding=utf-8&failOverReadOnly=false&useSSL=false"
SPRING_DATASOURCE_DRIVER_CLASS_NAME=com.mysql.cj.jdbc.Driver

spring.datasource.driver-class-name=com.mysql.jdbc.Driver
spring.datasource.url="jdbc:mysql://localhost:3306/dolphinscheduler?useUnicode=true&characterEncoding=UTF-8&useSSL=false"
spring.datasource.username=dolphinscheduler
spring.datasource.password=ds

字段中文乱码
ALTER TABLE t_ds_project CHANGE description description VARCHAR(255) CHARACTER SET UTF8 COLLATE utf8_general_ci;

download mysql-jar 5.1.47 to lib
link

vi conf/env/dolphinscheduler_env.sh

vi install.sh

cp core-site.xml hdfs-site.xml TO conf

frequent usage

start

pushd $HADOOP_HOME
sbin/start-all.sh
popd

pushd $ZK_HOME
bin/zkServer.sh start
popd

service mariadb start

pushd /opt/soft/dolphinscheduler
sudo -u dolphinscheduler script/start-all.sh
popd

http://[ip]:12345/dolphinscheduler/#/home

stop

pushd /opt/soft/dolphinscheduler
sudo -u dolphinscheduler script/stop-all.sh
popd

pushd $ZK_HOME
bin/zkServer.sh stop
popd

pushd $HADOOP_HOME
sbin/stop-all.sh
popd