pg_flame postgresql EXPLAIN ANALYZE 火焰图工具

pg_flame 是golang 编写的一个将pg的EXPLAIN ANALYZE 转换为火焰图，使用简单
以下是一个简单的demo

环境准备

• docker-compose 文件

version: "3"

services:

  postgres:

    image: postgres:9.6.11

    ports:

    - "5432:5432"

    environment:

    - "POSTGRES_PASSWORD:dalong"

• 源码编译
  clone 代码

git clone <a href="https://github.com/mgartner/pg_flame.git">https://github.com/mgartner/pg_flame.git</a>

goreleaser release --snapshot --skip-publish --rm-dist

简单修改.goreleaser.yml支持windows

# This is an example goreleaser.yaml file with some sane defaults.

# Make sure to check the documentation at http://goreleaser.com

builds:

- env:

  - CGO_ENABLED=0

  goos:

    - linux

    - darwin

    - windows

archives:

- replacements:

    darwin: Darwin

    linux: Linux

    windows: windows

    386: i386

    amd64: x86_64

checksum:

  name_template: ‘checksums.txt‘

snapshot:

  name_template: "{{ .Tag }}-next"

changelog:

  sort: asc

• sql 脚本

CREATE TABLE users (

    id SERIAL PRIMARY KEY,

    userename text,

    userage integer

);

?

-- Indices -------------------------------------------------------

?

CREATE UNIQUE INDEX users_pkey ON users(id int4_ops);

?

?

?

CREATE TABLE userapps (

    id SERIAL PRIMARY KEY,

    appname text,

    appversion text,

    userid integer

);

?

-- Indices -------------------------------------------------------

?

CREATE UNIQUE INDEX userapps_pkey ON userapps(id int4_ops);

?

?

INSERT INTO "public"."userapps"("id","appname","appversion","userid")

VALUES

(1,E‘login‘,E‘v1‘,1),

(2,E‘view‘,E‘v2.0‘,2);

?

?

INSERT INTO "public"."users"("id","userename","userage")

VALUES

(1,E‘dalong‘,11),

(2,E‘app‘,22);

使用

• 启动pg

docker-compose  up -d

• 生成json 格式的 EXPLAIN ANALYZE

psql -U postgres -h 127.0.0.1 postgres -qAtc ‘EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) select * from userapps a join users b on a.id=b.id‘ > plan.json

• 生成报告结果

cat plan.json | ./dist/pg_flame_darwin_amd64/pg_flame > result.html

• 效果

说明

pg_flame 多平台构建使用了goreleaser，如果需要构建跨平台的语言包，需要安装，而且上边数据比较少，看的不是很明显

参考资料

https://github.com/mgartner/pg_flame

原文地址：https://www.cnblogs.com/rongfengliang/p/11752896.html