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  • Centos7下安装InfluxDB教程

    1.安装

    复制代码
    (1) 创建安装目录
    mkdir /usr/local/influxdb/
    
    (2) 将 influxdb-1.7.10.x86_64.rpm复制到安装目录下
    
    (3) 安装
    cd /usr/local/influxdb/
    yum localinstall influxdb-1.7.10.x86_64.rpm
    
    (4) 环境准备
    mkdir -p /data/influxdb
    chmod -R 777 /data
    复制代码

     或者:

      # wget https://dl.influxdata.com/influxdb/releases/influxdb-1.7.8.x86_64.rpm

      # sudo yum localinstall influxdb-1.7.8.x86_64.rpm

    包文件路径

    复制代码
    /usr/bin下
    influxd    influxdb服务器
    influx      influxdb命令行客户端
    influx_inspect  查看工具
    influx_stress  压力测试工具
    influx_tsm  数据库转换工具(将数据库从b1或bz1格式转换为tsm1格式)
    
    /var/lib/influxdb/下
    data  存放最终存储的数据,文件以.tsm结尾
    meta  存放数据库元数据
    wal  存放预写日志文件
    
    /var/log/influxdb下
    influxd.log  日志文件
    
    /etc/influxdb下
    influxdb.conf  配置文件
    
    /var/run/influxdb/
    influxd.pid  PID文件
    复制代码

    修改配置文件

    复制代码
    (1)    备份配置文件
    cp /etc/influxdb/influxdb.conf /etc/influxdb/influxdb.conf.default
    
    (2)    修改配置
    vi /etc/influxdb/influxdb.conf
    找到如下配置并修改或取消注释:
    [meta]
    dir = "/data/influxdb/meta"
    [data]
    dir = "/data/influxdb/data"
    wal-dir = "/data/influxdb/wal"
    复制代码

     常用命令

    启动服务    systemctl start influxd
    停止服务    systemctl stop influxd
    重启服务    systemctl restart influxd

     检查是否已启动influxdb数据库

    ps aux | grep influx;

    2.启动
    #启动
    sudo systemctl start influxdb

    #配置开机启动
    sudo systemctl enable influxdb

    3.防火墙配置
    #开放端口
    # firewall-cmd --add-port=8086/tcp --permanent

    #重载防火墙配置
    # firewall-cmd --reload

    4.启动cli命令
    [root@localhost grafana]# influx
    Connected to http://localhost:8086 version 1.7.8
    InfluxDB shell version: 1.7.8
    >

    5.配置用户和数据库
    创建用户
    > CREATE USER dolphin WITH PASSWORD 'dolphininfluxpwd' WITH ALL PRIVILEGES

    查询用户
    > SHOW USERS
    user admin
    ---- -----
    influx true
    dolphin true
    >

    创建数据库
    > CREATE DATABASE dolphin

    查询数据库
    > SHOW DATABASES
    name: databases
    name
    ----
    _internal
    dolphin
    >

    6.插入数据与查询数据
    1.database
    数据库,和mysql的数据库相比,没有太大的歧义

    2.measurement
    对比的是mysql中的table,从实际体验来看,两个之间最明显的区别在于没有单独的创建measurement的方法,直接新增一条数据时,若measurement不存在,则直接创建并插入一条数据

    3.Point
    这个对比的是mysql中的record,在influxDB中,表示每个表中,某个时刻,满足某个条件的filed数据(简单来说就是 timestamp + tag + filed)的组成一个point

    timestamp : 时间戳,ns单位,每个记录都必然有这个属性,没有显示添加时,默认给一个。(纳秒,1s=1000ms 1ms=1000us 1us=1000ns)
    tag: 标签,kv结构,在database中, tag + measurement 一起构建索引
    参与索引创建,因此适合作为查询的过滤条件
    tag的数据量不要太多,最好能有典型的辨别性(和mysql的建立索引的原则差不多)
    value为String类型
    tag是可选的,在measurement不设置tag也是ok的
    field:存储数据,kv结构
    数据类型为: long, String, boolean, float
    4. Series
    Series: tag key 与tag value的唯一组合

    在insert执行语句中,tag与tag、field与field之间用都好进行分割,tag与field之间用空格分割
    tag的value都是,String类型,不需要加双引号
    field的String类型数据,需要放在双引号中,否则会报错
    如果需要显示添加时间戳,在filed后添加空格,再添加时间戳

    格式

    <measurement>[,<tag-key>=<tag-value>...] <field-key>=<field-value>[,<field2-key>=<field2-value>...] [unix-nano-timestamp]

    插入

    > USE dolphin
    Using database dolphin

    插入数据(host是tag,load,usage是filed)
    > INSERT cpu,host=192.168.1.1 load=0.1,usage=0.2
    > INSERT cpu,host=192.168.1.2 load=0.2,usage=0.3
    > INSERT cpu,host=192.168.1.3 load=0.6,usage=0.7

    插入相同时间数据(tagkey1,tagkey2是tag,fieldkey1,fieldkey2是filed;tag的value都是,String类型,不需要加双引号
    field的String类型数据,需要放在双引号中,否则会报错)
    > insert table2,tagkey1=1,tagkey2=a fieldkey1=11,fieldkey2="aa" 1581771014614699790
    > insert table2,tagkey1=2,tagkey2=a fieldkey1=11,fieldkey2="aa" 1581771014614699790
    > select * from table2
    name: table2
    time fieldkey1 fieldkey2 tagkey1 tagkey2
    ---- --------- --------- ------- -------
    1581771014614699790 11 aa 1 a
    1581771014614699790 11 aa 2 a

    查询数据全部数据
    > SELECT * FROM "cpu"
    name: cpu
    time host load usage
    ---- ---- ---- -----
    1581756324805070467 192.168.1.1 0.1 0.2
    1581756335749318117 192.168.1.2 0.2 0.3
    1581756346893987133 192.168.1.3 0.6 0.7

    # 筛选条件
    > SELECT "host","load","usage" FROM "cpu" WHERE "host" = '192.168.1.1'
    name: cpu
    time host load usage
    ---- ---- ---- -----
    1581756324805070467 192.168.1.1 0.1 0.2

    # 范围
    > SELECT "host","load","usage" FROM "cpu" WHERE "usage" > 0.3
    name: cpu
    time host load usage
    ---- ---- ---- -----
    1581756346893987133 192.168.1.3 0.6 0.7
    >

    其它
    # 创建数据库
    CREATE DATABASE "db_name"
    # 显示所有数据库
    SHOW DATABASES
    # 删除数据库
    DROP DATABASE "db_name"

    # 使用数据库
    USE mydb
    # 显示该数据库中的表
    SHOW MEASUREMENTS
    # 删除表
    DROP MEASUREMENT "t_name"

    7.HTTP API
    7.1 创建数据库
    [root@localhost ~]# curl -i -XPOST http://172.16.159.132:8086/query --data-urlencode "q=CREATE DATABASE cctestdb"
    HTTP/1.1 200 OK
    Content-Type: application/json
    Request-Id: 2ac0248e-4fd0-11ea-801e-000c29c94ec8
    X-Influxdb-Build: OSS
    X-Influxdb-Version: 1.7.8
    X-Request-Id: 2ac0248e-4fd0-11ea-801e-000c29c94ec8
    Date: Sat, 15 Feb 2020 08:50:07 GMT
    Transfer-Encoding: chunked

    {"results":[{"statement_id":0}]}
    [root@localhost ~]#

    7.2 插入数据
    #写入单条
    curl -i -XPOST http://172.16.159.132:8086/write?db=cctestdb --data-binary "cpu,host=192.168.1.3 load=0.1,usage=0.33"

    curl -i -XPOST http://172.16.159.132:8086/write?db=cctestdb --data-binary "cpu,host=192.168.1.3 load=0.1,usage=0.33 6666666666666666666"

    #写入多条
    curl -i -XPOST http://172.16.159.132:8086/write?db=cctestdb --data-binary "cpu,host=192.168.1.2 load=0.1,usage=0.22 1666666666666666661
    cpu,host=192.168.1.3 load=0.1,usage=0.33 1666666666666666663
    cpu,host=192.168.1.2 load=0.2,usage=0.22 1666666666666666664
    cpu,host=192.168.1.3 load=0.2,usage=0.33 1666666666666666665"

    7.3查询数据
    [root@localhost ~]# curl -G http://172.16.159.132:8086/query?db=cctestdb --data-urlencode "q=SELECT * FROM "cpu""
    {"results":[{"statement_id":0,"series":[{"name":"cpu","columns":["time","host","load","usage"],"values":[["2020-02-15T08:52:00.039671928Z","192.168.1.3",0.1,0.33],["2022-10-25T02:57:46.666666661Z","192.168.1.2",0.1,0.22],["2022-10-25T02:57:46.666666661Z","192.168.1.3",0.1,0.33],["2022-10-25T02:57:46.666666662Z","192.168.1.2",0.2,0.22],["2022-10-25T02:57:46.666666662Z","192.168.1.3",0.2,0.33],["2022-10-25T02:57:46.666666663Z","192.168.1.3",0.1,0.33],["2022-10-25T02:57:46.666666664Z","192.168.1.2",0.2,0.22],["2022-10-25T02:57:46.666666665Z","192.168.1.3",0.2,0.33],["2181-04-04T11:51:06.666666666Z","192.168.1.3",0.1,0.33]]}]}]}
    [root@localhost ~]#

    8.配置http账号密码
    1 创建账号

    创建用户
    > CREATE USER dolphin WITH PASSWORD 'dolphininfluxpwd' WITH ALL PRIVILEGES

    查询用户
    > SHOW USERS
    user admin
    ---- -----
    influx true
    dolphin true
    >

    2 配置`http密码访问。 auth-enabled = true
    vim /etc/influxdb/influxdb.conf

    [http]
    auth-enabled = true

    3.1cli终端账号密码登录

    [root@localhost grafana]# influx
    Connected to http://localhost:8086 version 1.7.8
    InfluxDB shell version: 1.7.8
    > auth
    username: dolphin
    password:
    > show databases;
    name: databases
    name
    ----
    _internal
    dolphin
    cctestdb
    itemdata
    >


    3.2http账号密码登录,-u dolphin:dolphininfluxpwd

    # curl -i -XPOST http://172.16.159.132:8086/write?db=dolphin -u dolphin:dolphininfluxpwd --data-binary "itemdatas,value=100, 1581772819000000000"

    参考文档
    《CentOS 7下InfluxDB部署与使用入门》:https://cloud.tencent.com/developer/article/1333874
    《influxDB基本概念小结》:https://www.cnblogs.com/yihuihui/p/9374561.html


    参考链接:https://blog.csdn.net/CleverCode/java/article/details/104329925

    参考网址:

    https://dl.influxdata.com/influxdb/releases/influxdb-1.7.10.x86_64.rpm

    https://s0docs0influxdata0com.icopy.site/influxdb/v1.7

    https://www.linuxdaxue.com/influxdb-study-series-manual.html

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  • 原文地址:https://www.cnblogs.com/zhukaijian/p/13204027.html
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