利用clickhouse-client和linux管道命令结合，迁移数据。这个办法速度不是特别快，一下午大概迁移40亿数据的样子

clickhouse-client --host 127.0.0.1 --password default -q "SELECT * FROM sgdatabase.historysignal2 FORMAT CSVWithNames" | clickhouse-client --host 127.0.0.1 --port 9000 --password default -q "INSERT INTO sgdatabase.historysignal FORMAT CSVWithNames"

查看集群分布式信息

select * from system.clusters;

查看数据库版本信息等

select * from system.build_options

查看正在执行的sql

select * from system.processes

将TABLE1重命名为TABLE2

rename table TABLE1 to TABLE2;

删除数据

ALTER TABLE db.test DELETE WHERE condition!=3;

修改数据

ALTER TABLE db.test UPDATE name='ccc' WHERE createTime='2020/2/13';

从mysql插入数据到clickhouse

clickhouse-client --host 192.168.1.155 --password default --database=DB-q "INSERT INTO historysignal (ROOMID, ROOMNAME, SAMPLERID, SAMPLERNAME, EQUIPMENTID, EQUIPMENTNAME, SIGNALID, SIGNALNAME, RECORDTIME, FLOATVALUE, STRINGVALUE, MEANINGS, STATIONNAME, STATIONID, UNIT, UNIQUID, RECORDTIMETOMIN, RECORDTIMEINORDER, ESNAME) select * from mysql('192.168.1.61:3306', 'DB', 'TABLE', 'mysql', 'mysql')"

当前连接数(分为 TCP 和 HTTP )

SELECT *
FROM system.metrics
WHERE metric LIKE '%Connection'

当前正在执行的查询

SELECT 
    query_id, 
    user, 
    address, 
    query
FROM system.processes
ORDER BY query_id ASC

查询Mutation操作(ALTER DELETE 和 ALTER UPDATE)

SELECT 
    database, 
    table, 
    mutation_id, 
    command, 
    create_time, 
    is_done
FROM system.mutations

终止语句

KILL QUERY WHERE query_id = 'query_id';
KILL MUTATION WHERE mutation_id = 'mutation_id';

存储空间统计,查询 CH 各个存储路径的空间

SELECT 
    name, 
    path, 
    formatReadableSize(free_space) AS free, 
    formatReadableSize(total_space) AS total, 
    formatReadableSize(keep_free_space) AS reserved
FROM system.disks

各数据库占用空间统计

SELECT 
    database, 
    formatReadableSize(sum(bytes_on_disk)) AS on_disk
FROM system.parts
GROUP BY database

个列字段占用空间统计
每个列字段的压缩大小、压缩比率以及该列的每行数据大小的占比

SELECT 
    database, 
    table, 
    column, 
    any(type), 
    sum(column_data_compressed_bytes) AS compressed, 
    sum(column_data_uncompressed_bytes) AS uncompressed, 
    round(uncompressed / compressed, 2) AS ratio, 
    compressed / sum(rows) AS bpr, 
    sum(rows)
FROM system.parts_columns
WHERE active AND database != 'system'
GROUP BY 
    database, 
    table, 
    column
ORDER BY 
    database ASC, 
    table ASC, 
    column ASC

慢查询

SELECT 
    user, 
    client_hostname AS host, 
    client_name AS client, 
    formatDateTime(query_start_time, '%T') AS started, 
    query_duration_ms / 1000 AS sec, 
    round(memory_usage / 1048576) AS MEM_MB, 
    result_rows AS RES_CNT, 
    result_bytes / 1048576 AS RES_MB, 
    read_rows AS R_CNT, 
    round(read_bytes / 1048576) AS R_MB, 
    written_rows AS W_CNT, 
    round(written_bytes / 1048576) AS W_MB, 
    query
FROM system.query_log
WHERE type = 2
ORDER BY query_duration_ms DESC
LIMIT 10

副本预警监控
通过下面的 SQL 语句对副本进行预警监控，其中各个预警的变量可以根据自身情况调整。

SELECT database, table, is_leader, total_replicas, active_replicas 
  FROM system.replicas 
 WHERE is_readonly 
    OR is_session_expired 
    OR future_parts > 30 
    OR parts_to_check > 20 
    OR queue_size > 30 
    OR inserts_in_queue > 20 
    OR log_max_index - log_pointer > 20 
    OR total_replicas < 2 
    OR active_replicas < total_replicas

centos 安装clickhosue 客户端

sudo yum install yum-utils
sudo rpm --import https://repo.clickhouse.tech/CLICKHOUSE-KEY.GPG
sudo yum-config-manager --add-repo https://repo.clickhouse.tech/rpm/stable/x86_64
sudo yum install clickhouse-server clickhouse-client

ubuntu 安装clickhosue 客户端

sudo apt-get install apt-transport-https ca-certificates dirmngr
sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv E0C56BD4
echo "deb https://repo.clickhouse.tech/deb/stable/ main/" | sudo tee     /etc/apt/sources.list.d/clickhouse.list
sudo apt-get update
sudo apt-get install -y clickhouse-client