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 <measurement_name[,measurement_name]> WHERE <tag_key>='<tag_value>' --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 <qid> --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 <retentionpolicy> ON <database> 创建保留期 CREATE RETENTION POLICY "rp_name" ON "db_name" DURATION 30d REPLICATION 1 DEFAULT
- rp_name：策略名
- db_name：具体的数据库名
- 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）mminuteshhoursddayswweeksINFinfinite - REPLICATION 1：副本个数，这里填1就可以了
- 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 <cq_name> ON <database_name>--删除
SHOW CONTINUOUS QUERIES --查看连续执行命令
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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
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1. 普通保存<br>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'<strong>2.Write points from a file by passing @filename to curl.</strong>cpu_data.txt内容如下：cpu_load_short,host=server02 value=0.67cpu_load_short,host=server02,region=us-west value=0.55 1422568543702900257cpu_load_short,direction=in,host=server01,region=us-west value=2.0 1422568543702900257Write 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<strong>3.单查询</strong><br>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'"<strong>4.多查询</strong>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'"<strong>5.格式化time</strong>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