转自:https://docs.timescale.com/v1.3/tutorials/telegraf-output-plugin 文章演示了如何使用pg output 插件
以及Telegraf agent 获取系统信息到timescaledb,一篇不错的实践类文章
一张参考图:

Telegraf can collect metrics from a wide array of inputs and write them to a wide array of outputs. It is plugin-driven for both collection and output of data so it is easily extendable. It is written in Go, which means that it is compiled and standalone binary that can be executed on any system with no need for external dependencies, or package management tools required.

Telegraf is an open-source tool. It contains over 200 plugins for gathering and writing different types of data written by people who work with that data.

We wrote the PostgreSQL output plugin which also has the ability to send data to a TimescaleDB hypertable. The pull request is open and currently under review by the Telegraf developers, waiting to be merged. To give developers the opportunity to try this functionality, we built downloadable binaries of Telegraf with our plugin already included.

This tutorial will run through a couple of examples on how to use the PostgreSQL/TimescaleDB output plugin for Telegraf.

Installation

Before we start

Before we start, you will need TimescaleDB installed and a means to connect to it.

Setting up Telegraf

Telegraf is written in Go, and the current build process of the tool is configured to produce one standalone binary. Because of this all the code for the different plugins must be part of that binary. We have an unofficial build of Telegraf version 1.10.4 with our plugin added.

Once you download the binary and extract it to a suitable location (or install the packages) we can test out the build. You may have to make the file executable by running chmod +x telegraf. We can check the version of the installed Telegraf with

$ telegraf --version

If the installation was successful it should print out Telegraf 1.10.4-with-pg.

Telegraf Configuration

When Telegraf is started, a config file needs to be specified. The config file contains the setup for the:

  • Telegraf agent

    • Collection interval
    • Jitter
    • Buffer and batch size and so on
  • Global tags added to all collected metrics from all inputs
  • Enabled outputs, processors, aggregators, inputs (and their respective configuration)

A sample config file with PostgreSQL included as a plugin can be generated by executing

$ telegraf --input-filter=cpu --output-filter=postgresql config > telegraf.conf

The above command generates a config file that enables the CPU input plugin (which samples various metrics about CPU usage) and the PostgreSQL output plugin.
The config file also includes all available input, output, processor, and aggregator plugins, but commented out. So, it's easy to see how a plugin should be configured.

Testing out the config file

To test our configuration, we can output a single collection to STDOUT. By running

$ telegraf --config telegraf.conf --test

we select the generated config file that enables only the CPU input plugin. And the output should look something like:

> cpu,cpu=cpu0,host=local usage_guest=0,usage_idle=78.431372,usage_iowait=0,usage_irq=0,usage_softirq=0,usage_steal=0,usage_system=11.764705,usage_user=9.803921 1558613882000000000
> cpu,cpu=cpu1,host=local usage_guest=0,usage_idle=92.156862,usage_iowait=0,usage_irq=0,usage_softirq=0,usage_steal=0,usage_system=3.921568,usage_user=3.921568 1558613882000000000
> cpu,cpu=cpu-total,host=local usage_guest=0,usage_idle=87.623762,usage_iowait=0,usage_irq=0,usage_softirq=0,usage_steal=0,usage_system=6.435643,usage_user=5.940594 1558613882000000000

A line is outputted for each core of the CPU and the total. Values are presented in key=valuepairs with the timestamp last in the row. When writing to STDOUT you can distinguish between tags, which are indexed fields (cpuhost) and value fields (usage_questusage_user ...) by a blank space (in our example the space after host=local). The distinction exists because different configuration options are available for the different fields.

Configuring the PostgreSQL Output Plugin

The telegraf.conf file we generated has a section (around line 80) headed with

################################################
# OUTPUT PLUGINS #
################################################

And below this header, the default configuration for the PostgreSQL output plugin is laid out.

[[outputs.postgresql]]
## specify address via a url matching:
## postgres://[pqgotest[:password]]@localhost[/dbname]\
## ?sslmode=[disable|verify-ca|verify-full]
## or a simple string:
## host=localhost user=pqotest password=... sslmode=... dbname=app_production
##
## All connection parameters are optional.
##
## Without the dbname parameter, the driver will default to a database
## with the same name as the user. This dbname is just for instantiating a
## connection with the server and doesn't restrict the databases we are trying
## to grab metrics for.
##
address = "host=localhost user=postgres sslmode=verify-full" ## Store tags as foreign keys in the metrics table. Default is false.
# tags_as_foreignkeys = false ## Template to use for generating tables
## Available Variables:
## {TABLE} - tablename as identifier
## {TABLELITERAL} - tablename as string literal
## {COLUMNS} - column definitions
## {KEY_COLUMNS} - comma-separated list of key columns (time + tags)
## Default template
# table_template = "CREATE TABLE IF NOT EXISTS {TABLE}({COLUMNS})"
## Example for timescaledb
# table_template = "CREATE TABLE {TABLE}({COLUMNS}); SELECT create_hypertable({TABLELITERAL},'time');" ## Schema to create the tables into
# schema = "public" ## Use jsonb datatype for tags
# tags_as_jsonb = false
## Use jsonb datatype for fields
# fields_as_jsonb = false

From the config we can notice several things:

  1. The top line enables the plugin, the plugin specific config is indented after this line
  2. There is currently only one parameter configured, address. The others are commented out
  3. Possible parameters are commented out with a single #. (tags_as_foreignkeystable_templateschematags_as_jsonbfields_as_jsonb)
  4. Explanations of the parameters are commented out with a single ##

The commented out parameters also show their default values.

For the first example we'll set the address parameter to a proper connection string to establish a connection to an instance of TimescaleDB or PostgreSQL. All the other parameters will have their default values.

Creating hypertables

The plugin we developed allows the user to configure several parameters. The table_templateparameter defines the SQL to be executed when a new measurement is recorded by Telegraf and the required table doesn't exist in the output database. By default the table_template used is CREATE TABLE IF NOT EXISTS {TABLE}({COLUMNS}) where {TABLE} and {COLUMNS} are placeholders for the name of the table and the column definitions.

Let's update table_template in the config for TimescaleDB:

  table_template=`CREATE TABLE IF NOT EXISTS {TABLE}({COLUMNS}); SELECT create_hypertable({TABLELITERAL},'time',chunk_time_interval := '1 week'::interval,if_not_exists := true);`

This way when a new table is created it is converted into a hypertable, with each chunk holding 1 week intervals. Nothing else is needed to use the plugin with TimescaleDB.

Running Telegraf

When we run Telegraf we only need to specify the config file to be used. If we execute

$  telegraf --config telegraf.conf
2019-05-23T13:48:09Z I! Starting Telegraf 1.10.4-with-pg
2019-05-23T13:48:09Z I! Loaded inputs: cpu
2019-05-23T13:48:09Z I! Loaded outputs: postgresql
2019-05-23T13:48:09Z I! Tags enabled: host=local
2019-05-23T13:48:09Z I! [agent] Config: Interval:10s, Quiet:false, Hostname:"local", Flush Interval:10s

In the output you can notice the loaded inputs (cpu) and outputs (postgresql) along with the global tags and the intervals with which the agent will collect the data from the inputs, and flush to the outputs. We can stop the execution of Telegraf after ~10-15 seconds.

Let us now connect to our PostgreSQL instance and inspect the data

$ psql -U postgres -h localhost

The cpu input plugin has one measurement, called cpu, and it's stored in a table of the same name (by default in the public schema). So with the SQL query SELECT * FROM cpu, depending on how long you left Telegraf running you will see the table populated with some values. We can find the average usage per cpu core with SELECT cpu, avg(usage_user) FROM cpu GROUP BY cpu. The output should look like

    cpu    |       avg
-----------+------------------
cpu-total | 8.46385703620795
cpu0 | 12.4343351351033
cpu1 | 4.88380203380203
cpu2 | 12.2718724052057
cpu3 | 4.26716970050303

Adding new Tags or Fields

Your Telegraf configuration can change at any moment. An input plugin can be reconfigured to produce different data, or you may decide to index your data with different tags. Our SQL plugin can dynamically update the created tables with new columns as they appear. The previous configuration we used had no global tags specified other than the host tag. We will now add a new global tag in the configuration. Open the file in any text editor and update the [global_tags] section (around line 18) with:

[global_tags]
location="New York"

This way all metrics collected with the instance of Telegraf running with this config will be tagged with location="New York". If we run Telegraf again, collecting the metrics in TimescaleDB

$ telegraf --config telegraf.conf

And after a while we check on the cpu table in the database

psql> \dS cpu
\dS cpu;
Table "public.cpu"
Column | Type
------------------+--------------------------
time | timestamp with time zone
cpu | text
host | text
usage_steal | double precision
usage_iowait | double precision
usage_guest | double precision
usage_idle | double precision
usage_softirq | double precision
usage_system | double precision
usage_user | double precision
usage_irq | double precision
location | text

The location column was added and it contains "New York" for all rows.

Creating a separate metadata table for tags

The plugin we developed allows the user to select to have the tag sets inserted in a separate table and then referenced via foreign keys in the measurement table. Having the tags in a separate table saves space for high cardinality tag sets, and allows certain queries to be written more efficiently. To enable this change, you need to uncomment the tags_as_foreignkeys parameter in the plugin config (around line 103 in telegraf.conf) and set it to true

 ## Store tags as foreign keys in the metrics table. Default is false.
tags_as_foreignkeys = true

To better visualize the result we'll drop the existing cpu table from our database.

psql> DROP TABLE cpu;

Now we'll fire Telegraf up again, this time with the config changed to write the tags in a separate table.

$ telegraf --config telegraf.conf

We can turn it off after 20-30 seconds. If we check on the cpu table in the database:

psql> \dS cpu
\dS cpu
Table "public.cpu"
Column | Type
------------------+--------------------------
time | timestamp with time zone
tag_id | integer
usage_irq | double precision
usage_softirq | double precision
usage_system | double precision
usage_iowait | double precision
usage_guest | double precision
usage_user | double precision
usage_idle | double precision
usage_steal | double precision

Notice that the cpuhost and location columns are not there, instead there's a tag_idcolumn. The tag sets are stored in a separate table called cpu_tag:

 psql> SELECT * FROM cpu_tag;
tag_id | host | cpu | location
--------+-------+-----------+----------
1 | local | cpu-total | New York
2 | local | cpu0 | New York
3 | local | cpu1 | New York

JSONB column for Tags and Fields

Additionally the tags and fields can be stored as JSONB columns in the database. All you need to do is uncomment the tags_as_jsonb or fields_as_jsonb parameters in telegraf.conf(around line 120) and set them to true. In this example we'll store the fields as separate columns, but the tags as JSON.

 ## Use jsonb datatype for tags
tags_as_jsonb = true
## Use jsonb datatype for fields
fields_as_jsonb = false

To better visualize the result we'll drop the existing cpu_tag table from our database.

psql> DROP TABLE cpu_tag;

Fire up Telegraf again, and turn it off after 20-30 seconds. Then we check the cpu_tag table:

$ telegraf --config telegraf.conf
 psql> SELECT * FROM cpu_tag;
tag_id | tags
--------+-----------------------------------------------------------------------------------
1 | {"cpu": "cpu-total", "host": "local", "location": "New York"}
2 | {"cpu": "cpu0", "host": "local", "location": "New York"}
3 | {"cpu": "cpu1", "host": "local", "location": "New York"}

And instead of having three text columns, one JSONB column is created.

Collecting metrics with the PostgreSQL and TimescaleDB output plugin for Telegraf的更多相关文章

  1. Logstash:Email output plugin 检查日志中是否还有某些错误信息并发送邮件报警

  2. PostgreSQL相关的软件,库,工具和资源集合

    PostgreSQL相关的软件,库,工具和资源集合. 备份 wal-e - Simple Continuous Archiving for Postgres to S3, Azure, or Swif ...

  3. TimescaleDB比拼InfluxDB:如何选择合适的时序数据库?

    https://www.itcodemonkey.com/article/9339.html 时序数据已用于越来越多的应用中,包括物联网.DevOps.金融.零售.物流.石油天然气.制造业.汽车.太空 ...

  4. Flink – metrics V1.2

    WebRuntimeMonitor   .GET("/jobs/:jobid/vertices/:vertexid/metrics", handler(new JobVertexM ...

  5. Application Metrics With Spring Boot Actuator

    转自:https://bartcode.co.uk/2015/01/application-metrics-with-spring-boot-actuator Update 12/2017: It w ...

  6. Debezium for PostgreSQL to Kafka

    In this article, we discuss the necessity of segregate data model for read and write and use event s ...

  7. SQL_CALC_FOUND_ROWS equivalent in PostgreSQL

    https://www.postgresql.org/message-id/1185863074.10580.91.camel%40linda.lfix.co.uk On Tue, 2007-07-3 ...

  8. JOOQ快速上手(基于springboot 和 postgresql)

    是什么 全称Java Object Oriented Querying,基于java开发出来的工具包,主要用于访问关系型数据库. 为什么用 Hibernate对SQL的操作太抽象 JDBC使用太过繁琐 ...

  9. Filebeat-1.3.1安装和设置(图文详解)(多节点的ELK集群安装在一个节点就好)(以Console Output为例)

    前期博客 Filebeat的下载(图文讲解) 前提 Elasticsearch-2.4.3的下载(图文详解) Elasticsearch-2.4.3的单节点安装(多种方式图文详解) Elasticse ...

随机推荐

  1. CentOS7 安装 Docker、最佳Docker学习文档

    目录 一.Docker支持 二.安装Docker -1.在新主机上首次安装Docker CE之前,需要设置Docker存储库.之后,就可以从存储库安装和更新Docker. 0.卸载旧版 1.正式安装 ...

  2. C#静态字段的两个用处

    静态字段的2个常用方法 (1)记录已实例化的对象的个数 (2)存储必须在所有实例化之间共享的值 (1)记录已实例化的对象的个数 现在某个培训机构啊,要开设一个学理发的班,计划招5人,只要人数够5人就开 ...

  3. 学习docker 部署nginx记录

    docker pull nginx $ docker pull nginx $ docker run --name nginx-test -p 8081:80 -d nginx docker conf ...

  4. C# vb .net实现过度曝光效果滤镜

    在.net中,如何简单快捷地实现Photoshop滤镜组中的过度曝光效果呢?答案是调用SharpImage!专业图像特效滤镜和合成类库.下面开始演示关键代码,您也可以在文末下载全部源码: 设置授权 第 ...

  5. Matlab迭代器模式

    迭代器(Iterator)模式,又叫做游标(Cursor)模式.提供一种方法访问一个容器(container)或者聚集(Aggregator)对象中各个元素,而又不需暴露该对象的内部细节.在采用不同的 ...

  6. linux入门—安装linux系统(1)

    一,linux介绍 linux是一套免费使用和自由传播的类Unix操作系统,简单的说就是不要钱,你可以随便使用,也可以分享给其他人. (剩下的详细内容,个人认为百度百科的内容比我瞎讲强的多,网址:ht ...

  7. 学习笔记之DBeaver

    DBeaver Community | Free Universal Database Tool https://dbeaver.io/ Universal Database Tool Free mu ...

  8. Linux应用与端口

    lsof -i:port --- 得到对应端口的应用pid PS -ef|grep pid --- 根据pid得到对应应用

  9. Openlayers学习开始前序

    Openlayers将抽象事物具体化为类,其核心类是Map.Layers.Source.View,几乎所有的动作都是围绕这几个核心类展开.Map的实例就是内嵌于网页的交互式地图,因此,最关键的是Map ...

  10. Linux--基本目录

    特点 系统版本:CentOS 6.5 Linux目录:一切从根开始 Linux下面的设备(磁盘)不挂载的话没有办法使用,使用设备必须有一个入口,挂载点实质就是一个目录. 目录结构及含义 目录 说明 b ...