ClickHouse 运维DBA实用场景

在 ClickHouse 中有没有一些能够 “安家立命” 的运维 SQL 语句，为此做一次简单的分享。
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。

当前连接数

CK 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。

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

┌─metric────────────────┬─value─┬─description────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│ TCPConnection	        │     9 │ Number of connections to TCP server (clients with native interface), also included server-server distributed query connections │
│ MySQLConnection	    │     0 │ Number of client connections using MySQL protocol                                                                              │
│ HTTPConnection	    │     1 │ Number of connections to HTTP server                                                                                           │
│ InterserverConnection	│     0 │ Number of connections from other replicas to fetch parts                                                                       │
│ PostgreSQLConnection	│     0 │ Number of client connections using PostgreSQL protocol                                                                         │
└───────────────────────┴───────┴────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
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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

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

┌─query_id─────────────────────────────┬─user────┬─address────────────┬─query─────────────────────────────────────────────────────────────────────────────┐
│ 203f1d0e-944e-472d-8d8f-bae548ff9899 │ default │ ::ffff:10.37.119.4 │ SELECT query_id, user, address, query FROM system.processes ORDER BY query_id ASC │
│ fb7fba85-b2a0-4271-87ff-22da97ae511b │ default │ ::ffff:10.37.119.4 │ INSERT INTO hits_v1 FORMAT TSV                                                    │
└──────────────────────────────────────┴─────────┴────────────────────┴───────────────────────────────────────────────────────────────────────────────────┘
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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'
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例如，终止刚才的 INSERT 查询：

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.
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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：

SELECT 
    database, 
    table, 
    mutation_id, 
    command, 
    create_time, 
    is_done
FROM 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.
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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';
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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;

┌─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   │
└───────────┴───────────────────┴───────────┴───────────┴──────────┘

4 rows in set. Elapsed: 0.001 sec.
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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;

┌─database─┬─on_disk──┐
│ system   │ 1.59 MiB │
│ default  │ 3.60 GiB │
└──────────┴──────────┘
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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;

┌─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 │
...
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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;

┌─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.) 
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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 │
└──────────┴─────────────────────────────┴───────────┴────────────────┴─────────────────┘
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