https://hub.docker.com/r/clickhouse/clickhouse-server
https://github.com/tetafro/clickhouse-cluster
https://hub.docker.com/r/yandex/clickhouse-server
https://github.com/ClickHouse/ClickHouse/releases
https://clickhouse.tech/
https://github.com/Vertamedia/clickhouse-grafana
https://grafana.net/plugins/vertamedia-clickhouse-datasource
https://github.com/jneo8/clickhouse-setup
https://abc.htmltoo.com/thread-45886.htm # clickhouse 单机部署 - 大数据分析
https://abc.htmltoo.com/thread-45902.htm # MySQL-to-ClickHouse
https://abc.htmltoo.com/thread-45933.htm # mysql2clickhouse
https://abc.htmltoo.com/thread-45940.htm # maxwell 部署 - mysql-to-json kafka
https://abc.htmltoo.com/thread-45941.htm # hangout 部署 - kafka2clickhouse
https://abc.htmltoo.com/thread-45952.htm # ClickHouse之访问权限控制
https://abc.htmltoo.com/thread-45956.htm # WaterDrop将Kafka中的数据写入Clickhouse
https://abc.htmltoo.com/thread-45951.htm # mysql2clickhouse + proxysql-clickhouse 部署
# 单机部署
https://abc.htmltoo.com/thread-45886.htm
# zookeeper 集群部署
https://abc.htmltoo.com/thread-45885.htm
# kafka 安装指南
https://abc.htmltoo.com/thread-44967.htm
# 安装DBeaver
https://github.com/dbeaver/dbeaver/releases
# 进入服务端服务
clickhouse-client # 用clickhouse-client连接本机clickhouse-server服务器：
show databases; # 显示数据库
select now();
# 进入交互式客户端,
---用clickhouse-client连接本机clickhouse-server服务器：
clickhouse-client
---用本机clickhouse-client连接远程clickhouse-server服务器：
---clickhouse-client –host clickhouse-server –port 9000 –database default–user default –password
-client 验证
clickhouse-client --host=server1 --port=9000
# 登陆clickhouse进行建表
ck-server-01 :) use yayun;
USE yayun
Ok.
0 rows in set. Elapsed: 0.001 sec.
ck-server-01 :) CREATE TABLE tb1
:-] ENGINE = MergeTree
:-] PARTITION BY toYYYYMM(pay_time)
:-] ORDER BY (pay_time) AS
:-] SELECT *
:-] FROM mysql('127.0.0.1:3306', 'yayun', 'tb1', 'ch_repl', '123') ;
CREATE TABLE tb1
ENGINE = MergeTree
PARTITION BY toYYYYMM(pay_time)
ORDER BY pay_time AS
SELECT *
FROM mysql('127.0.0.1:3306', 'yayun', 'tb1', 'ch_repl', '123')
Ok.
0 rows in set. Elapsed: 0.031 sec.这里使用MergeTree引擎，MergeTree是clickhouse里面最牛逼的引擎，支持海量数据，支持索引，支持分区，支持更新删除。toYYYYMM(pay_time)的意思是根据pay_time分区，粒度是按月。ORDER BY (pay_time)的意思是根据pay_time排序存储，同时也是索引。上面的create table命令如果mysql表里面以后数据那么数据也会一并进入clickhouse里面。通常会limit 1，然后更改一下表结构。
---看看clickhouse里面的表结构
show create table tb1;
# ClickHouse 集群和副本设置
https://abc.htmltoo.com/thread-45953.htm
==========================
ClickHouse有几核心的配置文件：
config.xml 端口配置、本地机器名配置、内存设置等
metrika.xml 集群配置、ZK配置、分片配置等
users.xml 权限、配额设置
日志的目录默认为: /var/log/clickhouse-server/
==========================
# 创建库
CREATE DATABASE test_db ENGINE = Ordinary;
# 创建本地表
CREATE TABLE test_tables( id UInt16,name String,age String,create_date date) ENGINE = MergeTree(create_date, (id), 8192);
ENGINE：是表的引擎类型，
MergeTree：最常用的，MergeTree要求有一个日期字段，还有主键。
Log引擎没有这个限制，也是比较常用。
ReplicatedMergeTree：MergeTree的分支，表复制引擎。
Distributed：分布式引擎。
create_date：是表的日期字段，一个表必须要有一个日期字段。
id：是表的主键，主键可以有多个字段，每个字段用逗号分隔。
8192：是索引粒度，用默认值8192即可。
# Tabix 部署 - ClickHouse Web 界面
https://abc.htmltoo.com/thread-45950.htm
==========================
https://blog.csdn.net/bluetjs/article/details/83011794
https://blog.csdn.net/weixin_34067102/article/details/91421749
https://blog.csdn.net/m0_37739193/article/details/79611560
https://www.cnblogs.com/grapelet520/p/11280972.html
https://www.cnblogs.com/gomysql/p/11199856.html
