The post How to use ProxySQL to work on ClickHouse like MySQL ? appeared first on The WebScale Database Infrastructure Operations Experts.
]]>We have several customers on ClickHouse now for both columnar database analytics and archiving MySQL data, You can access data from ClickHouse with clickhouse-client but this involves some learning and also limitations technically. Our customers are very comfortable using MySQL so they always preferred a MySQL client for ClickHouse query analysis and reporting, Thankfully ProxySQL works as a optimal bridge between ClickHouse and MySQL client, This indeed was a great news for us and our customers worldwide. This blog post is about how we can use MySQL client with ClickHouse.
# The default configuration file is this: /etc/proxysql.cnf # There is no such data directory by default: mkdir / var / lib / proxysql # start up proxysql --clickhouse-server # ProxySQL will default to daemon mode in the background
Create a user for ClickHouse in the ProxySQL with password, The password is not configured for ClickHouse but for accessing ProxySQL:
# ProxySQL port is 6032, the default username and password are written in the configuration file
root@10.xxxx: / root # mysql -h 127.0.0.1 -P 6032 -uadmin -padmin
Welcome to the MariaDB monitor. Commands end with; or \ g.
Your MySQL connection id is 3
Server version: 5.6.81 (ProxySQL Admin Module)
Copyright (c) 2000, 2018, Oracle, MariaDB Corporation Ab and others.
Type 'help;' or '\ h' for help. Type '\ c' to clear the current input statement.
MySQL [(none)]> INSERT INTO clickhouse_users VALUES ('chuser', 'chpasswd', 1,100);
Query OK, 1 row affected (0.00 sec)
MySQL [(none)] > select * from clickhouse_users;
+ ---------- + ---------- + -------- + ----------------- +
| username | password | active | max_connections |
+ ---------- + ---------- + -------- + ----------------- +
| chuser | chpasswd | 1 | 100 |
+ ---------- + ---------- + -------- + ----------------- +
1 row in set (0.00 sec)
MySQL [(none)]> LOAD CLICKHOUSE USERS TO RUNTIME;
Query OK, 0 rows affected (0.00 sec)
MySQL [(none)]> SAVE CLICKHOUSE USERS TO DISK;
Query OK, 0 rows affected (0.00 sec)
By default ProxySQL opens the port 6090 to receive user access to ClickHouse:
# Use username and password above # If it is a different machine, remember to change the IP root@10.xxxx: / root # mysql -h 127.0.0.1 -P 6090 -uclicku -pclickp --prompt "ProxySQL-To-ClickHouse>" Welcome to the MariaDB monitor. Commands end with; or \ g. Your MySQL connection id is 64 Server version: 5.6.81 (ProxySQL ClickHouse Module) Copyright (c) 2000, 2018, Oracle, MariaDB Corporation Ab and others. Type 'help;' or '\ h' for help. Type '\ c' to clear the current input statement. ProxySQL-To-ClickHouse >
MySQL [(none)] > select version (); + ------------------- + | version | + ------------------- + | 5.6.81-clickhouse | + ------------------- + 1 row in set (0.00 sec) MySQL [(none)] > select now (); + --------------------- + | now () | + --------------------- + | 2019-12-25 20:17:14 | + --------------------- + 1 row in set (0.00 sec) MySQL [(none)] > select today (); + ------------ + | today () | + ------------ + | 2019-12-25 | + ------------ + 1 row in set (0.00 sec) # Our table is over 55 billion ProxySQL-To-ClickHouse > select count (*) from mysql_audit_log_data; + ------------- + | count () | + ------------- + | 539124837571 | + ------------- + 1 row in set (8.31 sec)
References:
The post How to use ProxySQL to work on ClickHouse like MySQL ? appeared first on The WebScale Database Infrastructure Operations Experts.
]]>The post Database Replication from MySQL to ClickHouse for High Performance WebScale Analytics appeared first on The WebScale Database Infrastructure Operations Experts.
]]>MySQL works great for Online Transaction Processing (OLTP) systems, MySQL performance degrades with analytical queries on very large database infrastructure, I agree you can optimize MySQL query performance with InnoDB compressions but why then combine OLTP and OLAP (Online Analytics Processing Systems) when you have columnar stores which can deliver high performance analytical queries more efficiently? I have seen several companies building dedicated MySQL servers for Analytics but over the period of time they end spending more money in fine tuning MySQL for Analytics with no significant improvements, There is no point in blaming MySQL for what it is not built for, MySQL / MariaDB is any day a bad choice for columnar analytics / big data solutions. Columnar database systems are best suited for handling large quantities of data: data stored in columns typically is easier to compress, it is also easier to access on per column basis – typically you ask for some data stored in a couple of columns – an ability to retrieve just those columns instead of reading all of the rows and filter out unneeded data makes the data accessed faster. So how can you combine the best of both ? Using MySQL purely for Transaction Processing Systems and Archiving MySQL Transactional Data for Data Analytics on a columnar store like ClickHouse, This post is about archiving and replicating data from MySQL to ClickHouse, you can continue reading from here.
Recommended Reading for ClickHouse:
The post Database Replication from MySQL to ClickHouse for High Performance WebScale Analytics appeared first on The WebScale Database Infrastructure Operations Experts.
]]>The post Why we recommend ClickHouse over many other columnar database systems ? appeared first on The WebScale Database Infrastructure Operations Experts.
]]>The post Why we recommend ClickHouse over many other columnar database systems ? appeared first on The WebScale Database Infrastructure Operations Experts.
]]>The post Join ClickHouse India Users Group appeared first on The WebScale Database Infrastructure Operations Experts.
]]>Github:
Server Packages:
Client Packages:
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