influxdb0.13命令

1、数据构成

INSERT cpu_load_short,host=server01,region=us-west value=0.64,value2=0.86 1434055562000000000

 

第一部分:“cpu_load_short,host=server01,region=us-west”

第一部分称为key,key中包含了measurement name(类似表)和tags(tags又分为tag key和tag value,tags可以有多个)

注意:在tag value中的空格应以“\”加上空格表示,tags中的值必须是string类型,其实是起到索引的作用

 

第二部分:“value=0.64,value2=0.86”

第二部分称为Field,同样和tags的形式相同,都是键值对的形式,但是tags中的值必须是string类型,而Field中的值可以为Integer、float、Boolean、string类型,

若为Integer类型,则值后必须加“i”,否则该值为float类型,

比如value=23意味着这个值23是float类型,

而value=23i,意味着值23是Integer类型。

Boolean类型的值的表示方式有很多,直接写成:t, T, true, TRUE, f, F, false或 FALSE都可以。


第三部分(可选):“1434055562000000000”
第三部分称为Timestamp,是时间戳,如果该部分省略,则默认将当前时间的时间戳插入数据库,否则按照用户输入的时间戳插入。

注意:influxdb默认使用UTC时区展示数据

2、创建及使用数据库

CREATE DATABASE "testDB"  --创建数据库
show databases  --展示所有数据库
use testDB使用  --数据库

 3、增删改查命令

查询表信息
SHOW MEASUREMENTS --查询当前数据库中含有的表
SHOW FIELD KEYS --查看当前数据库所有表的字段
SHOW series from pay --查看key数据
SHOW TAG KEYS FROM "pay" --查看key中tag key值
SHOW TAG VALUES FROM "pay" WITH KEY = "merId" --查看key中tag 指定key值对应的值
SHOW TAG VALUES FROM cpu WITH KEY IN ("region", "host") WHERE service = 'redis'

DROP SERIES FROM WHERE ='' --删除key
SHOW CONTINUOUS QUERIES --查看连续执行命令
SHOW QUERIES --查看最后执行命令
KILL QUERY --结束命令
SHOW RETENTION POLICIES ON mydb --查看保留数据

查询数据
SELECT * FROM /.*/ LIMIT 1 --查询当前数据库下所有表的第一行记录
select * from pay  order by time desc limit 2
select * from db_name."POLICIES name".measurement_name --指定查询数据库下数据保留中的表数据 POLICIES name数据保留
删除数据
delete from "query" --删除表所有数据,则表就不存在了
drop MEASUREMENT "query"  --删除表(注意会把数据保留删除使用delete不会)
DELETE FROM cpu
DELETE FROM cpu WHERE time < '2000-01-01T00:00:00Z'
DELETE WHERE time < '2000-01-01T00:00:00Z'
DROP DATABASE “testDB” --删除数据库
DROP RETENTION POLICY "dbbak" ON mydb --删除保留数据为dbbak数据
DROP SERIES from pay where tag_key='' --删除key中的tag

SHOW SHARDS --查看数据存储文件
DROP SHARD 1
SHOW SHARD GROUPS
SHOW SUBSCRIPTIONS

 

4、函数使用

mean-平均值
sum-总和
min-最小值
max-最大值
count-总个数
select * from pay   order by time desc limit 2
select mean(allTime) from pay where time >= today() group by time(10m) time_zone(+8)
select * from pay time_zone(+8) limit 2 
SELECT sum(allTime) FROM "pay" WHERE time > now() - 10s
select count(allTime) from pay  where time > now() - 10m  group by time(1s)

 

5、用户管理命令

SHOW USERS
CREATE USER jdoe WITH PASSWORD '1337password' -- Create a normal database user.
CREATE USER jdoe WITH PASSWORD '1337password' WITH ALL PRIVILEGES -- Create an admin user.
REVOKE ALL PRIVILEGES FROM jdoe revoke admin privileges from jdoe
REVOKE READ ON mydb FROM jdoe -- revoke read privileges from jdoe on mydb
SHOW GRANTS FOR jdoe -- show grants for jdoe
GRANT ALL TO jdoe -- grant admin privileges
GRANT READ ON mydb TO jdoe -- grant read access to a database
DROP USER jdoe

 

6、数据保留命令

查看保留期 SHOW RETENTION POLICIES ON mydb
修改保留期 ALTER RETENTION POLICY default    ON online   DEFAULT
删除保留期 DROP RETENTION POLICY  ON 
创建保留期 CREATE RETENTION POLICY "rp_name" ON "db_name" DURATION 30d REPLICATION 1 DEFAULT
    1. rp_name:策略名
    2. db_name:具体的数据库名
    3. 30d:保存30天,30天之前的数据将被删除
      它具有各种时间参数,比如:h(小时),w(星期)m minutes h hours d days w weeks INF infinite
    4. REPLICATION 1:副本个数,这里填1就可以了
    5. DEFAULT 设为默认的策略

 

7、创建持续性数据处理结果 提供后续查询

-- selects from default retention policy and writes into 6_months retention policy
CREATE CONTINUOUS QUERY "10m_event_count"
ON db_name
BEGIN
  SELECT count(value)
  INTO "6_months".events
  FROM events
  GROUP BY time(10m)
END;

-- this selects from the output of one continuous query in one retention policy and outputs to another series in another retention policy
CREATE CONTINUOUS QUERY "1h_event_count"
ON db_name
BEGIN
  SELECT sum(count) as count
  INTO "2_years".events
  FROM "6_months".events
  GROUP BY time(1h)
END;

-- this customizes the resample interval so the interval is queried every 10s and intervals are resampled until 2m after their start time
-- when resample is used, at least one of "EVERY" or "FOR" must be used
CREATE CONTINUOUS QUERY "cpu_mean"
ON db_name
RESAMPLE EVERY 10s FOR 2m
BEGIN
  SELECT mean(value)
  INTO "cpu_mean"
  FROM "cpu"
  GROUP BY time(1m)
END;
DROP CONTINUOUS QUERY ON --删除
SHOW CONTINUOUS QUERIES   --查看连续执行命令

================================================
案例:根据tags查询交易成功与失败笔数,并保存到一个表中,每分钟统计1分钟内的
CREATE CONTINUOUS QUERY fail ON online
  BEGIN SELECT count(allTime) as fail INTO online."default".sign_result FROM online."default".sign
  where orderFlag='0'
  GROUP BY time(1m)
END
CREATE CONTINUOUS QUERY success ON online
  BEGIN SELECT count(allTime) as success INTO online."default".sign_result FROM online."default".sign
  where orderFlag='1'
  GROUP BY time(1m)
END

> select * from sign_result
name: sign_result
-----------------
time            fail    success
1478053740000000000    2    2
1478053800000000000    3    3
1478053860000000000    1    1
1478053920000000000    3    1

 

8、http api

 
1. 普通保存
curl -i -X POST 'http://127.0.0.1:8086/write?db=online' --data-binary 'pay,host=1,merId=1234567890,orderFlag=1 allTime=347,ecifTime=39,icqTime=88' 2.Write points from a file by passing @filename to curl. cpu_data.txt内容如下: cpu_load_short,host=server02 value=0.67 cpu_load_short,host=server02,region=us-west value=0.55 1422568543702900257 cpu_load_short,direction=in,host=server01,region=us-west value=2.0 1422568543702900257 Write the data in cpu_data.txt to the mydb database with: curl -i -XPOST 'http://localhost:8086/write?db=mydb' --data-binary @cpu_data.txt 3.单查询
curl -GET 'http://localhost:8086/query?pretty=true' --data-urlencode "db=mydb" --data-urlencode "q=SELECT value FROM cpu_load_short WHERE region='us-west'" 4.多查询 curl -G 'http://localhost:8086/query?pretty=true' --data-urlencode "db=mydb" --data-urlencode "q=SELECT value FROM cpu_load_short WHERE region='us-west';SELECT count(value) FROM cpu_load_short WHERE region='us-west'" 5.格式化time epoch=[h,m,s,ms,u,ns] curl -G 'http://localhost:8086/query' --data-urlencode "db=mydb" --data-urlencode "epoch=s" --data-urlencode "q=SELECT value FROM cpu_load_short WHERE region='us-west'"

 注意:如果是自己程序生成时间戳,进行数据保存后,查询时使用用select count(*) from pay进行查询总条数时,需要确认一下influxdb数据库时间与程序生成数据的机器时间,因为查询不添加时间条件默认采用当前系统时间,所以就会造成数据无法做到实时入库,数据查询总是延后;

9、常用命令

9.1 转化查询结果数据time格式

precision rfc3339

> select * from sign
name: sign
----------
time            allTime    ecifTime    host        icqTime    icqTime1    merId        orderFlag
1479880151976609227    348    0        195.203.56.35    0    0        305110099990002    null
1479880301566372997    724    0        195.203.56.35    641    0        305110048163089    0
1479880846739979577    28    0        195.203.56.35    12    0        305110099990002    0
1479881595261796657    25    0        195.203.56.35    10    0        305110099990002    0
1479881617138308807    106    0        195.203.56.35    17    0        305110099990002    0

> precision rfc3339
> select * from sign
name: sign
----------
time                            allTime    ecifTime    host        icqTime  icqTime1   merId          orderFlag
2016-11-23T05:49:11.976609227Z      348    0        195.203.56.35    0        0        305110099990002    null
2016-11-23T05:51:41.566372997Z      724    0        195.203.56.35    641      0        305110048163089    0
2016-11-23T06:00:46.739979577Z       28    0        195.203.56.35    12       0        305110099990002    0
2016-11-23T06:13:15.261796657Z       25    0        195.203.56.35    10       0        305110099990002    0
2016-11-23T06:13:37.138308807Z      106    0        195.203.56.35    17       0        305110099990002    0

9.2按时间分组统计数据(分组只能用time()注意空格)

select count(allTime) from pay  where time > now() - 15h group by time(1h)

9.3按指定时间段查询数据

select count(allTime),mean(allTime) from pay  where  time>='2016-11-30T16:00:00Z'and time<='2016-12-01T16:59:59Z' and orderFlag='1'

9.4脚本执行数据格式

influx -execute "select count(allTime),mean(allTime) from pay  
where time>='2016-12-10T16:00:00Z'and time<='2016-12-11T16:59:59Z' and orderFlag='1'
" -database 'online'; 查询2016-12-11全天数据
格式: influx -execute "sql" -database 'databasename'

注意如果自己程序生成的时间戳作为time,则需要注意查询出的数据时间相差8小时,所以查某一天的数据需要减掉8小时,如上

 

 

 

 



 

 

转载于:https://www.cnblogs.com/atwanli/articles/5732022.html

你可能感兴趣的:(influxdb0.13命令)