ClickHouse之DBA运维宝典

ClickHouse 中有没有一些能够 “安家立命” 的运维 SQL 语句。我想对于这个问题很多朋友都会有兴趣，所以就在这里做一个简单的分享。

在 ClickHouse 默认的 system 数据库下(databse)，拥有众多的系统表。我们对 ClickHouse 运行状态的各种信息，就主要来自于这些系统表。

接下来就列举一些常用的运维 SQL 语句。

 

• 当前连接数

 

众所周知，CH 对外暴露的原生接口分为 TCP 和 HTTP 两类，通过 system.metrics 即可查询当前的 TCP、HTTP 与内部副本的连接数。

ch7.nauu.com :) SELECT * FROM system.metrics WHERE metric LIKE '%Connection';
SELECT *FROM system.metricsWHERE metric LIKE '%Connection'
┌─metric────────────────┬─value─┬─description─────────────────────────────────────────────────────────┐│ TCPConnection         │     2 │ Number of connections to TCP server (clients with native interface) ││ HTTPConnection        │     1 │ Number of connections to HTTP server                                ││ InterserverConnection │     0 │ Number of connections from other replicas to fetch parts            │└───────────────────────┴───────┴─────────────────────────────────────────────────────────────────────┘

 

• 当前正在执行的查询

 

通过 system.processes 可以查询目前正在执行的查询，例如：

ch7.nauu.com :) SELECT query_id, user, address, query  FROM system.processes ORDER BY query_id;
SELECT     query_id,     user,     address,     queryFROM system.processesORDER BY query_id ASC
┌─query_id─────────────────────────────┬─user────┬─address────────────┬─query─────────────────────────────────────────────────────────────────────────────┐│ 203f1d0e-944e-472d-8d8f-bae548ff9899 │ default │ ::ffff:10.37.129.4 │ SELECT query_id, user, address, query FROM system.processes ORDER BY query_id ASC ││ fb7fba85-b2a0-4271-87ff-22da97ae511b │ default │ ::ffff:10.37.129.4 │ INSERT INTO hits_v1 FORMAT TSV                                                    │└──────────────────────────────────────┴─────────┴────────────────────┴───────────────────────────────────────────────────────────────────────────────────┘

可以看到，CH 目前正在执行两条语句，其中第 2 条是 INSERT 查询正在写入数据。 

 

• 终止查询

 

通过 KILL QUERY 语句，可以终止正在执行的查询:

KILL QUERY WHERE query_id = 'query_id'

例如，终止刚才的 INSERT 查询 :

ch7.nauu.com :) KILL QUERY WHERE query_id='ff695827-dbf5-45ad-9858-a853946ea140';
KILL QUERY WHERE query_id = 'ff695827-dbf5-45ad-9858-a853946ea140' ASYNC
Ok.
0 rows in set. Elapsed: 0.024 sec.

 

众所周知，除了常规的 SELECT 和 INSERT 之外，在 ClickHouse 中还存在一类被称作 Mutation 的操作，也就是 ALTER DELETE 和 ALTER UPDATE。

 

对于 Mutation 操作， ClickHouse 专门提供了 system.mutations 用于查询，例如：

ch7.nauu.com :) SELECT database, table, mutation_id, command, create_time, is_done FROM system.mutations;
SELECT     database,     table,     mutation_id,     command,     create_time,     is_doneFROM system.mutations
┌─database─┬─table──────┬─mutation_id────┬─command──────────────────┬─────────create_time─┬─is_done─┐│ default  │ testcol_v9 │ mutation_2.txt │ DELETE WHERE ID = 'A003' │ 2020-06-29 01:15:04 │       1 │└──────────┴────────────┴────────────────┴──────────────────────────┴─────────────────────┴─────────┘
1 rows in set. Elapsed: 0.002 sec.

 

同样的，可以使用 KILL MUTATION 终止正在执行的 Mutation 操作:

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:

ch5.nauu.com :) SELECT name,path,formatReadableSize(free_space) AS free,formatReadableSize(total_space) AS total,formatReadableSize(keep_free_space) AS reserved FROM system.disks
SELECT     name,     path,     formatReadableSize(free_space) AS free,     formatReadableSize(total_space) AS total,     formatReadableSize(keep_free_space) AS reservedFROM system.disks
┌─name──────┬─path──────────────┬─free──────┬─total─────┬─reserved─┐│ default   │ /chbase/data/     │ 36.35 GiB │ 49.09 GiB │ 0.00 B   ││ disk_cold │ /chbase/cloddata/ │ 35.35 GiB │ 48.09 GiB │ 1.00 GiB ││ disk_hot1 │ /chbase/data/     │ 36.35 GiB │ 49.09 GiB │ 0.00 B   ││ disk_hot2 │ /chbase/hotdata1/ │ 36.35 GiB │ 49.09 GiB │ 0.00 B   │└───────────┴───────────────────┴───────────┴───────────┴──────────┘
4 rows in set. Elapsed: 0.001 sec.

 

• 各数据库占用空间统计

ch7.nauu.com :) SELECT database, formatReadableSize(sum(bytes_on_disk)) on_disk FROM system.parts GROUP BY database;
SELECT     database,     formatReadableSize(sum(bytes_on_disk)) AS on_diskFROM system.partsGROUP BY database
┌─database─┬─on_disk──┐│ system   │ 1.59 MiB ││ default  │ 3.60 GiB │└──────────┴──────────┘

 

• 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_columnsWHERE active AND database != 'system'GROUP BY     database,     table,     columnORDER BY     database ASC,     table ASC,     column ASC
┌─database─┬─table────────┬─column─────────────────────┬─any(type)──────────────────────────────┬─compressed─┬─uncompressed─┬──ratio─┬───────────────────bpr─┬─sum(rows)─┐│ default  │ hits_v1      │ AdvEngineID                │ UInt8                                  │     351534 │     26621706 │  75.73 │  0.013204788603705563 │  26621706 ││ default  │ hits_v1      │ Age                        │ UInt8                                  │    7543552 │     26621706 │   3.53 │    0.2833609536518809 │  26621706 ││ default  │ hits_v1      │ BrowserCountry             │ FixedString(2)                         │    6549379 │     53243412 │   8.13 │   0.24601650247358303 │  26621706 ││ default  │ hits_v1      │ BrowserLanguage            │ FixedString(2)                         │    2819085 │     53243412 │  18.89 │   0.10589422781545255 │  26621706 ││ default  │ hits_v1      │ CLID                       │ UInt32                                 │    2311006 │    106486824 │  46.08 │   0.08680908729140048 │  26621706 ││ default  │ hits_v1      │ ClientEventTime            │ DateTime                               │   98518704 │    106486824 │   1.08 │    3.7006908573026838 │  26621706 ││ default  │ hits_v1      │ ClientIP                   │ UInt32                                 │   25120766 │    106486824 │   4.24 │    0.9436196913901761 │  26621706 ││ default  │ hits_v1      │ ClientIP6                  │ FixedString(16)                        │   25088558 │    425947296 │  16.98 │    0.9424098515699934 │  26621706 ││ default  │ hits_v1      │ ClientTimeZone             │ Int16                                  │    8487148 │     53243412 │   6.27 │    0.3188055641512982 │  26621706 ││ default  │ hits_v1      │ CodeVersion                │ UInt32                                 │   11976952 │    106486824 │   8.89 │    0.4498942329240658 │  26621706 ││ default  │ hits_v1      │ ConnectTiming              │ Int32                                  │   27937373 │    106486824 │   3.81 │    1.0494208372671534 │  26621706 ││ default  │ hits_v1      │ CookieEnable               │ UInt8                                  │     202718 │     26621706 │ 131.32 │  0.007614763681936838 │  26621706 ││ default  │ hits_v1      │ CounterClass               │ Int8                                   │     425492 │     26621706 │  62.57 │  0.015982897564866805 │  26621706 │...

 

• 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,     queryFROM system.query_logWHERE type = 2ORDER BY query_duration_ms DESCLIMIT 10
┌─user────┬─host─────────┬─client────────────┬─started──┬────sec─┬─MEM_MB─┬──RES_CNT─┬────────────────RES_MB─┬────R_CNT─┬─R_MB─┬───W_CNT─┬─W_MB─┬─query───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐│ default │ ch7.nauu.com │ ClickHouse client │ 01:05:03 │ 51.434 │   1031 │  8873898 │      8706.51146697998 │        0 │    0 │ 8873898 │ 8707 │ INSERT INTO hits_v1 FORMAT TSV                                                                                                                                          ││ default │ ch7.nauu.com │ ClickHouse client │ 01:01:48 │ 43.511 │   1031 │  8873898 │      8706.51146697998 │        0 │    0 │ 8873898 │ 8707 │ INSERT INTO hits_v1 FORMAT TSV                                                                                                                                          ││ default │ ch7.nauu.com │ ClickHouse client │ 17:12:04 │  11.12 │   1801 │ 18874398 │     446.8216323852539 │  6291466 │  351 │       0 │    0 │ SELECT id, arrayJoin(arrayConcat(groupArray(a), groupArray(b), groupArray(c))) AS v FROM test_y GROUP BY id ORDER BY v ASC                                              ││ default │ ch7.nauu.com │ ClickHouse client │ 17:13:28 │  3.992 │   1549 │ 18874398 │     446.8216323852539 │  6291466 │  351 │       0 │    0 │ SELECT id, arrayJoin(arrayConcat(groupArray(a), groupArray(b), groupArray(c))) AS v FROM test_y GROUP BY id                                                             ││ default │ ch7.nauu.com │ ClickHouse client │ 17:13:12 │  3.976 │   1549 │ 18874398 │     446.8216323852539 │  6291466 │  351 │       0 │    0 │ SELECT id, arrayJoin(arrayConcat(groupArray(a), groupArray(b), groupArray(c))) AS v FROM test_y GROUP BY id                                                             ││ default │ ch7.nauu.com │ ClickHouse client │ 01:25:39 │  3.962 │   1549 │ 18874398 │     446.8216323852539 │  6291466 │  351 │       0 │    0 │ SELECT id, arrayJoin(arrayConcat(groupArray(a), groupArray(b), groupArray(c))) AS v FROM test_y GROUP BY id                                                             ││ default │ ch7.nauu.com │ ClickHouse client │ 04:32:29 │  3.114 │   1542 │ 10000000 │    219.82192993164062 │ 10500000 │  231 │       0 │    0 │ SELECT user_id, argMax(score, create_time) AS score, argMax(deleted, create_time) AS deleted, max(create_time) AS ctime FROM test_a GROUP BY user_id HAVING deleted = 0 ││ default │ ch7.nauu.com │ ClickHouse client │ 02:59:56 │   3.03 │   1544 │ 10000000 │    219.75380992889404 │ 10500000 │  231 │       0 │    0 │ SELECT user_id, argMax(score, create_time) AS score, argMax(is_update, create_time) AS is_update, max(create_time) AS ctime FROM test_a GROUP BY user_id                ││ default │ ch7.nauu.com │ ClickHouse client │ 02:54:01 │  3.019 │   1543 │ 10000000 │     219.3450927734375 │ 10500000 │  230 │       0 │    0 │ SELECT user_id, argMax(score, create_time) AS score, argMax(delete, create_time) AS delete, max(create_time) AS ctime FROM test_a GROUP BY user_id                      ││ default │              │                   │ 03:03:12 │  2.857 │   1543 │       10 │ 0.0002269744873046875 │ 10500000 │  231 │       0 │    0 │ SELECT * FROM view_test_a limit 10                                                                                                                                      │└─────────┴──────────────┴───────────────────┴──────────┴────────┴────────┴──────────┴───────────────────────┴──────────┴──────┴─────────┴──────┴─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
10 rows in set. Elapsed: 0.017 sec. Processed 1.44 thousand rows, 200.81 KB (83.78 thousand rows/s., 11.68 MB/s.) 

 

• 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
┌─database─┬─table───────────────────────┬─is_leader─┬─total_replicas─┬─active_replicas─┐│ default  │ replicated_sales_12         │         0 │              0 │               0 ││ default  │ test_fetch                  │         0 │              0 │               0 ││ default  │ test_sharding_simple2_local │         0 │              0 │               0 │└──────────┴─────────────────────────────┴───────────┴────────────────┴─────────────────┘

 

好了，今天的分享就到这里。对于 CH 日常的运维 SQL 远不止这些，这里也只是抱砖引玉啦。

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