The basic concept of influxdb learning Influxdb

Comparison with nouns in traditional database database measurement in the database

Nouns in the nfluxdb	Concepts in a traditional database
database
table
Points	A row of data inside the table

Second, the unique concept of INFLUXDB

1) database--database, this database concept with traditional database.

2) measurement--data Sheet, in Influxdb, measurement is the role of the table, and the traditional database of the table function consistent.

1) tag--tag, in Influxdb, tag is a very important part, table name +tag together as the index of the database, is the form of "Key-value".

2) field--data, field is mainly used to store the data part, is also the "Key-value" form.

3) timestamp--timestamp, as a time-series database, timestamp is the most important part of INFLUXDB, when inserting data can be specified by itself or left blank for the system to specify.

Description: When inserting new data, the tag, field, and timestamp are separated by a space.

4) series--sequence, all the data in the database need to be shown by the chart, and this series represents the data in the table, can be drawn on the chart as a few lines.

5) Retention policy--Data Retention policy, you can define the length of time that data is retained, each database can have multiple data retention policies, but only one default policy.

6) point--Point, which represents the data of a field at a certain point in each table, because it is a point on the chart, and it is referred to as points.

1) Point

A point consists of a timestamp (time), a data (field), a label (tags).

Point corresponds to a row of data in a traditional database, as shown in the following table:

point Property time fields

concepts in traditional databases
Each data record time is the primary index in the database (automatically generated)
various record values (attributes without indexes) are recorded values: temperature, humidity
Tags	Various indexed properties: area, altitude

2) Series

All the data in the database needs to be shown by a chart, and this series represents the data in the table, which can be drawn as a few lines on the chart: the tags are grouped together.

As shown below:

>show series from cpukeycpu,cpu=cpu-total,host=resourcepool-0246-billing07cpu,cpu=cpu-total, host=billing07cpu,cpu=cpu0,host=resourcepool-0246-billing07cpu,cpu=cpu0,host=billing07cpu,cpu=cpu1,host= resourcepool-0246-billing07cpu,cpu=cpu1,host=billing07cpu,cpu=cpu10,host=resourcepool-0246-billing07cpu,cpu= Cpu10,host=billing07cpu,cpu=cpu11,host=resourcepool-0246-billing07cpu,cpu=cpu11,host=billing07cpu,cpu=cpu12, HOST=RESOURCEPOOL-0246-BILLING07CPU,CPU=CPU12,HOST=BILLING07CPU,CPU=CPU13,HOST=RESOURCEPOOL-0246-BILLING07CPU, cpu=cpu13,host=billing07cpu,cpu=cpu14,host=resourcepool-0246-billing07cpu,cpu=cpu14,host=billing07cpu,cpu= cpu15,host=resourcepool-0246-billing07cpu,cpu=cpu15,host=billing07cpu,cpu=cpu16,host= resourcepool-0246-billing07cpu,cpu=cpu17,host=resourcepool-0246-billing07cpu,cpu=cpu18,host= resourcepool-0246-billing07cpu,cpu=cpu19,host=resourcepool-0246-billing07cpu,cpu=cpu2,host= resourcepool-0246-billing07cpu,cpu=cpu2,host=billing07cpu,cpu=cpu20,host=resourcepool-0246-BILLING07CPU,CPU=CPU21,HOST=RESOURCEPOOL-0246-BILLING07CPU,CPU=CPU22,HOST=RESOURCEPOOL-0246-BILLING07CPU, cpu=cpu23,host=resourcepool-0246-billing07cpu,cpu=cpu3,host=resourcepool-0246-billing07cpu,cpu=cpu3,host= billing07cpu,cpu=cpu4,host=resourcepool-0246-billing07cpu,cpu=cpu4,host=billing07cpu,cpu=cpu5,host= resourcepool-0246-billing07cpu,cpu=cpu5,host=billing07cpu,cpu=cpu6,host=resourcepool-0246-billing07cpu,cpu= cpu6,host=billing07cpu,cpu=cpu7,host=resourcepool-0246-billing07cpu,cpu=cpu7,host=billing07cpu,cpu=cpu8,host= resourcepool-0246-billing07cpu,cpu=cpu8,host=billing07cpu,cpu=cpu9,host=resourcepool-0246-billing07cpu,cpu= Cpu9,host=billing07

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The basic concept of influxdb learning Influxdb