注意：打开新环境需要手动同步环境变量
一 机器依赖(CentOS7)[重要]
yum -y install \
vim \
sudo \
net-tools.aarch64 \
nmap-ncat.aarch64 \
telnet \
openssh-server \
openssh-clients
初始化sshd文件，如果不初始化下边文件，sshd服务会启动报错：
ssh-keygen -t rsa -f /etc/ssh/ssh_host_rsa_key
ssh-keygen -t ecdsa -f /etc/ssh/ssh_host_ecdsa_key
ssh-keygen -t ed25519 -f /etc/ssh/ssh_host_ed25519_key
二 基础环境规划
-
软件版本
软件 版本 Hadoop hadoop-2.10.1.tar.gz Hive apache-hive-2.3.1-bin.tar.gz Kafka kafka_2.12-2.0.0.tgz Zookeeper apache-zookeeper-3.5.7-bin.tar.gz Hbase hbase-2.4.9-bin.tar.gz Java jdk-8u202-linux-arm64-vfp-hflt.tar.gz Scala scala-2.12.15.tgz Spark spark-3.3.2-bin-without-hadoop.tgz Hudi hudi-release-0.13.0.zip Doris apache-doris-1.2.6-bin-arm64.tar.xz Flink flink-1.16.0-bin-scala_2.12.tgz Clickhouse clickhouse-23.7.3.14-1 -
组件分布
节点 组件列表 hadoop-node1 namenode | dataname | resourcemanager | nodemanager | hive | spark | flink | fe be | clickhouse Hadoop-node2 datanode |nodemanager | mysql | zookeeper | hive | hive.metastore | hbase | fe be | clickhouse Hadoop-node3 datanode |nodemanager | kafka | hive | fe be |clichhouse -
端口注册
-
各节点节点启动脚本整合
-
hadoop-node1 启动脚本
## env source ~/.base_profile ## hdfs sbin/hadoop-daemon.sh start namenode sbin/hadoop-daemon.sh start datanode ## yarn sbin/yarn-daemon.sh start resourcemanager sbin/yarn-daemon.sh start nodemanager ## doris fe/bin/start_fe.sh --daemon be/bin/start_be.sh --daemo -
Hadoop-node2 启动脚本
## env source ~/.base_profile ## hdfs sbin/hadoop-daemon.sh start datanode ## yarn sbin/yarn-daemon.sh start nodemanager ## mysql systemctl start mariadb ## doris fe/bin/start_fe.sh --daemon be/bin/start_be.sh --daemo ## hbase bin/start-hbase.sh ## zookeeper bin/zkServer.sh start ## hive-metastore nohup hive --service metastore >> /opt/data/hive/hive-metastore.log & -
Hadoop-node3 启动脚本
## env source ~/.base_profile ## hdfs sbin/hadoop-daemon.sh start datanode ## yarn sbin/yarn-daemon.sh start nodemanager ## doris fe/bin/start_fe.sh --daemon be/bin/start_be.sh --daemo ## kafka kafka-server-start.sh -daemon config/server.properties &
-
-
启动3个节点docker容器[重要]
节点1：
docker run -itd \ -h hadoop-node1 \ --name=hadoop-node1 \ --privileged=true \ --network=gawyn-bridge \ -v /Users/chavinking/gawyn/hadoop-node1:/opt \ centos:centos7 \ /sbin/init节点2：
docker run -itd \ -h hadoop-node2 \ --name=hadoop-node2 \ --privileged=true \ --network=gawyn-bridge \ -v /Users/chavinking/gawyn/hadoop-node2:/opt \ centos:centos7 \ /sbin/init节点3：
docker run -itd \ -h hadoop-node3 \ --name=hadoop-node3 \ --privileged=true \ --network=gawyn-bridge \ -v /Users/chavinking/gawyn/hadoop-node3:/opt \ centos:centos7 \ /sbin/init
三 配置环境变量
文件地址：/opt/runner/docker-env.sh
## Java
export JAVA_HOME=/opt/system/jdk1.8.0_202
export PATH=$JAVA_HOME/bin:$JAVA_HOME/jre/bin:$PATH:.
export CLASSPATH=.:$JAVA_HOME/lib:$JAVA_HOME/jre/lib:$CLASSPATH
## scala
export SCALA_HOME=/opt/system/scala-2.12.15
export PATH=$SCALA_HOME/bin:$PATH:.
## maven profile
export MAVEN_HOME=/opt/system/maven-3.5.0
export PATH=$MAVEN_HOME/bin:$PATH:.
## Hadoop Env
export HADOOP_HOME=/opt/system/hadoop-2.10.1
export PATH=$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH
## ZooKeeper Env
export ZOOKEEPER_HOME=/opt/system/zookeeper-3.5.7
export PATH=$PATH:$ZOOKEEPER_HOME/bin:.
## kafka Env
export KAFKA_HOME=/opt/system/kafka-2.12-2.0.0
export PATH=$PATH:$KAFKA_HOME/bin:.
## Hive Env
export HIVE_HOME=/opt/system/hive-2.3.1
export PATH=$PATH:$HIVE_HOME/bin:.
## Hbase Env
export HBASE_HOME=/opt/system/hbase-2.4.9
export PATH=$PATH:$HBASE_HOME/bin:.
## Spark Env
export SPARK_HOME=/opt/system/spark-3.3.2
export PATH=$PATH:$SPARK_HOME/bin:$SPARK_HOME/sbin:.
## Doris Env
export DORIS_HOME=/opt/system/doris-1.2.6
export PATH=$PATH:$DORIS_HOME/fe/bin:$DORIS_HOME/be/bin:.
## Init Env
sysctl -w vm.max_map_count=2000000
ulimit -n 65536
将source /opt/runner/docker-env.sh添加到~/.bash_profile 文件。
四 配置ssh授信
-
为centos7用户设置密码
passwd root -
yum安装ssh服务端和客户端依赖，见步骤1
-
启动sshd服务
/usr/sbin/sshd解决方案：
-
检查sshd是否启动
% ps -ef|grep sshd root 145 1 0 06:55 ? 00:00:00 /usr/sbin/sshd % telnet 127.0.0.1 22 Trying 127.0.0.1... Connected to 127.0.0.1. Escape character is '^]'. SSH-2.0-OpenSSH_7.4 -
节点间同步ssh授信文件，每个节点分别执行
% ssh-keygen -t rsa % ssh-copy-id hadoop-node1 % ssh hadoop-node1 date % ssh-copy-id hadoop-node2 % ssh hadoop-node2 date % ssh-copy-id hadoop-node3 % ssh hadoop-node3 date
五 部署Hadoop分布式集群
-
下载软件包并且解压软件
-
编辑hadoop配置文件，需要编辑配置文件如下：
-
编辑后的配置文件内容如下：
- etc/hadoop/core-site.xml
<?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <!-- Licensed 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 accompanying LICENSE file. --> <!-- Put site-specific property overrides in this file. --> <configuration> <property> <name>fs.defaultFS</name> <value>hdfs://hadoop-node1:8020</value> </property> <property> <name>hadoop.tmp.dir</name> <value>/opt/data/hdfs</value> </property> <property> <name>fs.trash.interval</name> <value>7000</value> </property> </configuration>- etc/hadoop/hdfs-site.xml
<?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="configuration.xsl"?> <!-- Licensed 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 accompanying LICENSE file. --> <!-- Put site-specific property overrides in this file. --> <configuration> <property> <name>dfs.namenode.secondary.http-address</name> <value>hadoop-node1:50090</value> </property> </configuration>- etc/hadoop/yarn-site.xml
<?xml version="1.0"?> <!-- Licensed 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 accompanying LICENSE file. --> <configuration> <!-- Site specific YARN configuration properties --> <property> <name>yarn.nodemanager.aux-services</name> <value>mapreduce_shuffle</value> </property> <property> <name>yarn.resourcemanager.hostname</name> <value>hadoop-node1</value> </property> <property> <name>yarn.log-aggregation-enable</name> <value>true</value> </property> <property> <name>yarn.log-aggregation.retain-seconds</name> <value>600000</value> </property> </configuration>- etc/hadoop/slaves
hadoop-node1 hadoop-node2 hadoop-node3- 配置Java环境变量
etc/hadoop/hadoop-env.sh etc/hadoop/yarn-env.sh etc/hadoop/mapred-env.sh- 创建数据目录
/opt/data/hdfs- 同步hadoop-node1节点文件到其他节点
% scp -r * hadoop-node2:/opt/ % scp -r * hadoop-node3:/opt/ -
格式化HDFS
% hdfs namenode -format -
启动Hadoop服务
hdfs： sbin/hadoop-daemon.sh start|stop namenode sbin/hadoop-daemon.sh start|stop datanode yarn: sbin/yarn-daemon.sh start|stop resourcemanager sbin/yarn-daemon.sh start|stop nodemanager
六 部署MySQL服务
-
以yum方式简易安装
% yum -y install mariadb mariadb-server -
启动mysql服务
% systemctl start mariadb容器内启动服务报错：
解决方案：
七 部署Zookeeper服务
-
下载软件并解压到安装目录，并且创建数据目录/opt/data/zkdata，配置环境变量
-
配置zookeeper配置文件
# conf/zoo.cfg dataDir=/opt/data/zkdata clientPort=2181 -
启动zookeeper
bin/zkServer.sh start
八 部署Kafka服务
-
下载软件并解压到安装目录，并且创建数据目录/opt/data/kafka-logs，配置环境变量
-
配置kafka配置文件
# config/server.properties broker.id=0 listeners=PLAINTEXT://hadoop-node3:9092 log.dirs=/opt/data/kafka-logs zookeeper.connect=hadoop-node2:2181 -
启动kafka服务
kafka-server-start.sh -daemon config/server.properties & -
kafka常用命令
创建topic： kafka-topics.sh --create --zookeeper hadoop-node2:2181 --replication-factor 1 --partitions 1 --topic test 查看所有topic: kafka-topics.sh --list --zookeeper hadoop-node2:2181 启动producer： kafka-console-producer.sh --broker-list hadoop-node3:9092 --topic test 启动consumer： kafka-console-consumer.sh --bootstrap-server hadoop-node3:9092 --from-beginning --topic test kafka-console-consumer.sh --zookeeper hadoop-node2:2181 --topic test --from-beginning
九 部署Hive服务
-
下载软件并解压到安装目录，配置环境变量
-
拷贝mysql jdbc依赖jar包到hive安装目录lib/文件夹内
-
配置Hive配置文件
- hive-env.sh
HADOOP_HOME=/opt/system/hadoop-2.10.1 export HIVE_CONF_DIR=/opt/system/hive-2.3.1/conf- hive-site.xml
<!-- hive metastore config --> <property> <name>javax.jdo.option.ConnectionURL</name> <value>jdbc:mysql://hadoop-node2:3306/hive?createDatabaseIfNotExist=true</value> <description>JDBC connect string for a JDBC metastore</description> </property> <property> <name>javax.jdo.option.ConnectionDriverName</name> <value>com.mysql.jdbc.Driver</value> <description>Driver class name for a JDBC metastore</description> </property> <property> <name>javax.jdo.option.ConnectionUserName</name> <value>root</value> <description>username to use against metastore database</description> </property> <property> <name>javax.jdo.option.ConnectionPassword</name> <value>mysql</value> <description>password to use against metastore database</description> </property> <!-- hive warehouse dir --> <property> <name>hive.metastore.warehouse.dir</name> <value>/user/root/warehouse</value> <description>location of default database for the warehouse</description> </property> <!-- java.io.tmpdir --> <property> <name>system:java.io.tmpdir</name> <value>/opt/data/hive/tmp</value> </property> <property> <name>hive.exec.local.scratchdir</name> <value>/opt/data/hive/tmp/${user.name}</value> <description>Local scratch space for Hive jobs</description> </property> <!-- hive metastore config --> <property> <name>hive.metastore.port</name> <value>9083</value> <description>Hive metastore listener port</description> </property> -
创建hive仓库hdfs目录与hive元数据库并初始化元数据库
% hdfs dfs -mkdir /user/root/warehouse % mkdir /opt/data/hive/tmpmysql> create database hive; mysql> grant all privileges on *.* to 'root'@'hadoop-node2' identified by 'mysql' with grant option; mysql> flush privileges; # bin/schematool -initSchema -dbType mysql -
启动hive metastore服务
% nohup hive --service metastore >> /opt/data/hive/hive-metastore.log &
十 部署Hbase服务
-
下载软件并解压到安装目录，配置环境变量
-
配置Hbase配置文件
- hbase-env.sh
export JAVA_HOME=/opt/system/jdk1.8.0_202 export HADOOP_HOME=/opt/system/hadoop-2.10.1 export HBASE_MANAGES_ZK=false- hbase-site.xml
<property> <name>hbase.rootdir</name> <value>hdfs://hadoop-node1:8020/user/root/hbase</value> </property> <property> <name>hbase.cluster.distributed</name> <value>true</value> </property> <property> <name>hbase.zookeeper.quorum</name> <value>hadoop-node2</value> </property> <property> <name>hbase.zookeeper.property.clientPort</name> <value>2181</value> </property> <property> <name>hbase.tmp.dir</name> <value>/opt/data/hbase/tmp</value> </property> <property> <name>zookeeper.znode.parent</name> <value>/hbase</value> </property> <property> <name>hbase.unsafe.stream.capability.enforce</name> <value>false</value> </property>- regionservers
hadoop-node2 -
创建目录
% hdfs dfs -mkdir /user/root/hbase % mkdir -p /opt/data/hbase/tmp -
启动hbase服务
% bin/start-hbase.sh -
测试hbase集群
% hbase shell hbase:001:0> status 1 active master, 0 backup masters, 1 servers, 0 dead, 2.0000 average load Took 1.3384 seconds hbase:002:0> create 'testtable','colfaml' Created table testtable Took 0.7568 seconds => Hbase::Table - testtable hbase:003:0> list 'testtable' TABLE testtable 1 row(s) Took 0.0390 seconds => ["testtable"] hbase:004:0> put 'testtable','myrow-1','colfaml:q1','value-1' Took 0.3415 seconds hbase:005:0> put 'testtable','myrow-2','colfaml:q2','value-2' Took 0.0067 seconds hbase:006:0> scan 'testtable' ROW COLUMN+CELL myrow-1 column=colfaml:q1, timestamp=2023-08-08T06:14:14.685, value=value-1 myrow-2 column=colfaml:q2, timestamp=2023-08-08T06:14:19.278, value=value-2 2 row(s) Took 0.0372 seconds hbase:007:0> get 'testtable','myrow-1' COLUMN CELL colfaml:q1 timestamp=2023-08-08T06:14:14.685, value=value-1 1 row(s) Took 0.0424 seconds
十一 部署Spark服务
-
下载软件并解压到安装目录，执行编译
mvn clean package -DskipTests -Pyarn -Phadoop-2 -Dhadoop.version=2.10.1 -Phive -Phive-thriftserver -
配置环境变量，配置spark-env.sh文件[without-hadoop版本配置参数]
export JAVA_HOME=/opt/system/jdk1.8.0_202 export HADOOP_CONF_DIR=/opt/system/hadoop-2.10.1/etc/hadoop export YARN_CONF_DIR=/opt/system/hadoop-2.10.1/etc/hadoop export SPARK_DIST_CLASSPATH=$(hadoop classpath) export LD_LIBRARY_PATH=$HADOOP_HOME/lib/native -
拷贝hive配置文件到spark配置目录
cp /opt/system/hive-2.3.1/conf/hive-site.xml /opt/system/spark-3.3.2/conf/hive-site.xml -
测试spark
% spark-shell% spark-sql
-
编译遇到问题
-
问题1
编译maven版本比软件pom.xml文件指定版本低，调整pom文件中maven版本，重新编译。
-
十二 部署Flink服务
-
下载软件并解压到安装目录，配置环境变量
-
配置flink配置文件
taskmanager.numberOfTaskSlots: 4 -
测试flink
十三 部署Doris服务
-
下载软件并解压到安装目录，配置环境变量
-
FE配置
-
创建元数据目录
% mkdir -p /opt/data/doris/doris-meta % mkdir -p /opt/data/doris/fe-log -
编辑配置文件[同步各个节点]
LOG_DIR = /opt/data/doris/fe-log meta_dir = /opt/data/doris/doris-meta priority_networks = hadoop-node1-ip/24 ## FE涉及端口号 http_port = 18030 edit_log_port = 19010 rpc_port = 19020 query_port = 19030 -
启动FE
% fe/bin/start_fe.sh --daemon -
FE添加BE
% mysql -hhadoop-node1 -uroot -p -P19030 mysql > ALTER SYSTEM ADD BACKEND "hadoop-node1:19050"; mysql > ALTER SYSTEM ADD BACKEND "hadoop-node2:19050"; mysql > ALTER SYSTEM ADD BACKEND "hadoop-node3:19050"; mysql > SHOW PROC '/frontends'; mysql > SHOW PROC '/backends';
-
-
BE配置
-
创建数据目录
% mkdir -p /opt/data/doris/doris-data % mkdir -p /opt/data/doris/be-log -
编辑配置文件[同步各个节点]
PPROF_TMPDIR="/opt/data/doris/be-log/" priority_networks = hadoop-node1-ip/24 storage_root_path = /opt/data/doris/doris-data ## BE涉及端口号 be_port = 19060 webserver_port = 18040 heartbeat_service_port = 19050 brpc_port = 18060 -
启动BE
- 添加环境变量
- 启动指令
% be/bin/start_be.sh --daemo
-
-
FE库容3个节点
-
注册节点
mysql > ALTER SYSTEM ADD FOLLOWER "hadoop-node2:19010"; mysql > ALTER SYSTEM ADD FOLLOWER "hadoop-node3:19010"; -
启动节点
% fe/bin/start_fe.sh --helper hadoop-node1:19010 --daemon
-
十四 部署Clickhouse服务
-
安装Clickhouse
yum install -y yum-utils yum-config-manager --add-repo https://packages.clickhouse.com/rpm/clickhouse.repo yum clean all yum makecache yum install -y clickhouse-server clickhouse-client -
启动单机版Clickhouse
sudo /etc/init.d/clickhouse-server start clickhouse-client # or "clickhouse-client --password" if you set up a password.sudo -u 'clickhouse' /usr/bin/clickhouse-server \ --config-file /etc/clickhouse-server/config.xml \ --pid-file /var/run/clickhouse-server/clickhouse-server.pid \ --daemon -
Clickhouse集群配置
-
3.1 集群各个机器修改配置文件config.xml
<http_port>8123</http_port> <tcp_port>9000</tcp_port> <mysql_port>9004</mysql_port> <postgresql_port>9005</postgresql_port> <interserver_http_port>9009</interserver_http_port> <listen_host>::1</listen_host> <path>/opt/data/clickhouse/</path> <tmp_path>/opt/data/clickhouse/tmp/</tmp_path> -
3.2 在每台机器的etc目录下新建metrika.xml文件，并且编辑如下内容：
<yandex> <!-- cluster config:单副本配置 --> <clickhouse_remote_servers> <gawyn_cluster> <!-- data shard one --> <shard> <internal_replication>true</internal_replication> <replica> <host>hadoop-node1</host> <port>9123</port> <user>default</user> <password>clickhouse</password> </replica> </shard> <!-- data shard two --> <shard> <replica> <internal_replication>true</internal_replication> <host>hadoop-node2</host> <port>9123</port> <user>default</user> <password>clickhouse</password> </replica> </shard> <!-- data shard three --> <shard> <internal_replication>true</internal_replication> <replica> <host>hadoop-node3</host> <port>9123</port> <user>default</user> <password>clickhouse</password> </replica> </shard> </gawyn_cluster> </clickhouse_remote_servers> <!-- zookeeper config --> <zookeeper-servers> <node index="1"> <host>hadoop-node2</host> <port>2181</port> </node> </zookeeper-servers> <!-- 本地节点副本名称 --> <macros> <layer>gawyn_cluster</layer> <!-- gawyn_cluster_node1/gawyn_cluster_node2/gawyn_cluster_node3 --> <replica>gawyn_cluster_nodeX</replica> </macros> <!-- 监听网络 允许任何地址访问 --> <networks> <ip>::/0</ip> </networks> <!-- 数据压缩算法 --> <clickhouse_compression> <case> <min_part_size>10000000000</min_part_size> <min_part_size_ratio>0.01</min_part_size_ratio> <method>lz4</method> </case> </clickhouse_compression> </yandex> -
3.3 每台机器分别配置users.xml
<clickhouse> <!-- See also the files in users.d directory where the settings can be overridden. --> <!-- Profiles of settings. --> <profiles> <!-- Default settings. --> <default> </default> <!-- Profile that allows only read queries. --> <readonly> <readonly>1</readonly> </readonly> </profiles> <!-- Users and ACL. --> <users> <!-- If user name was not specified, 'default' user is used. --> <default> <!-- See also the files in users.d directory where the password can be overridden. Password could be specified in plaintext or in SHA256 (in hex format). If you want to specify password in plaintext (not recommended), place it in 'password' element. Example: <password>qwerty</password>. Password could be empty. If you want to specify SHA256, place it in 'password_sha256_hex' element. Example: <password_sha256_hex>65e84be33532fb784c48129675f9eff3a682b27168c0ea744b2cf58ee02337c5</password_sha256_hex> Restrictions of SHA256: impossibility to connect to ClickHouse using MySQL JS client (as of July 2019). If you want to specify double SHA1, place it in 'password_double_sha1_hex' element. Example: <password_double_sha1_hex>e395796d6546b1b65db9d665cd43f0e858dd4303</password_double_sha1_hex> If you want to specify a previously defined LDAP server (see 'ldap_servers' in the main config) for authentication, place its name in 'server' element inside 'ldap' element. Example: <ldap><server>my_ldap_server</server></ldap> If you want to authenticate the user via Kerberos (assuming Kerberos is enabled, see 'kerberos' in the main config), place 'kerberos' element instead of 'password' (and similar) elements. The name part of the canonical principal name of the initiator must match the user name for authentication to succeed. You can also place 'realm' element inside 'kerberos' element to further restrict authentication to only those requests whose initiator's realm matches it. Example: <kerberos /> Example: <kerberos><realm>EXAMPLE.COM</realm></kerberos> How to generate decent password: Execute: PASSWORD=$(base64 < /dev/urandom | head -c8); echo "$PASSWORD"; echo -n "$PASSWORD" | sha256sum | tr -d '-' In first line will be password and in second - corresponding SHA256. How to generate double SHA1: Execute: PASSWORD=$(base64 < /dev/urandom | head -c8); echo "$PASSWORD"; echo -n "$PASSWORD" | sha1sum | tr -d '-' | xxd -r -p | sha1sum | tr -d '-' In first line will be password and in second - corresponding double SHA1. --> <password></password> <!-- List of networks with open access. To open access from everywhere, specify: <ip>::/0</ip> To open access only from localhost, specify: <ip>::1</ip> <ip>127.0.0.1</ip> Each element of list has one of the following forms: <ip> IP-address or network mask. Examples: 213.180.204.3 or 10.0.0.1/8 or 10.0.0.1/255.255.255.0 2a02:6b8::3 or 2a02:6b8::3/64 or 2a02:6b8::3/ffff:ffff:ffff:ffff::. <host> Hostname. Example: server01.clickhouse.com. To check access, DNS query is performed, and all received addresses compared to peer address. <host_regexp> Regular expression for host names. Example, ^server\d\d-\d\d-\d\.clickhouse\.com$ To check access, DNS PTR query is performed for peer address and then regexp is applied. Then, for result of PTR query, another DNS query is performed and all received addresses compared to peer address. Strongly recommended that regexp is ends with $ All results of DNS requests are cached till server restart. --> <networks> <ip>::/0</ip> </networks> <!-- Settings profile for user. --> <profile>default</profile> <!-- Quota for user. --> <quota>default</quota> <!-- User can create other users and grant rights to them. --> <!-- <access_management>1</access_management> --> </default> </users> <!-- Quotas. --> <quotas> <!-- Name of quota. --> <default> <!-- Limits for time interval. You could specify many intervals with different limits. --> <interval> <!-- Length of interval. --> <duration>3600</duration> <!-- No limits. Just calculate resource usage for time interval. --> <queries>0</queries> <errors>0</errors> <result_rows>0</result_rows> <read_rows>0</read_rows> <execution_time>0</execution_time> </interval> </default> </quotas> </clickhouse> -
3.4 启动clickhouse服务
创建目录：
mdkir -p /opt/data/clickhouse/tmp启动服务：
sudo /etc/init.d/clickhouse-server start -
3.5 客户端登陆
clienthouse-client
-
十五 编译Hudi
-
从github下载hudi源码
-
环境准备
-
添加下面Kafka依赖到maven仓库
-
执行Hudi编译&验证是否编译成功
mvn clean package -DskipTests \ -Dspark3.3 -Dscala-2.12 \ -Dflink1.16 -Dscala-2.12 \ -Dhadoop.version=2.10.1 \ -Pflink-bundle-shade-hive3执行以下命令验证是否编译成功：
# hudi-cli/hudi-cli.sh
