文章目录

ClickHouse数据查询

ClickHouse数据查询

前言

在ClickHouse数据导入一文中介绍了导入数据到ClickHouse数据表中，本文描述如何对ClickHouse中的数据进行查询。

查询语法

参见：

https://clickhouse.tech/docs/en/sql-reference/statements/select/

[WITH expr_list|(subquery)]
SELECT [DISTINCT] expr_list
[FROM [db.]table | (subquery) | table_function] [FINAL]
[SAMPLE sample_coeff]
[ARRAY JOIN ...]
[GLOBAL] [ANY|ALL|ASOF] [INNER|LEFT|RIGHT|FULL|CROSS] [OUTER|SEMI|ANTI] JOIN (subquery)|table (ON <expr_list>)|(USING <column_list>)
[PREWHERE expr]
[WHERE expr]
[GROUP BY expr_list] [WITH TOTALS]
[HAVING expr]
[ORDER BY expr_list] [WITH FILL] [FROM expr] [TO expr] [STEP expr]
[LIMIT [offset_value, ]n BY columns]
[LIMIT [n, ]m] [WITH TIES]
[UNION ALL ...]
[INTO OUTFILE filename]
[FORMAT format]

可以看到ClickHouse的SELECT语句的语法和通用的SQL的SELECT语句非常类似，包括：

SELECT: 指定返回结果字段
DISTINCT：去重
FROM: 指定要查询的表或子查询
JOIN：表连接，支持内连接和外连接、左连接和右连接
WHERE：筛选条件
GROUP BY：分组，和聚合函数一起使用
HAVING：分组后筛选
ORDER BY：排序
LIMIT：限制返回记录数
UNION ALL：并集；ClickHouse目前只支持UNION ALL，还不支持UNION

ClickHouse的SELECT语句中也有一些特殊的用法：

WITH: 设置查询中要用到的变量
SAMPLE: 数据取样，类似Pandas库的sample()函数
PREWHERE: 预筛选，起到提升性能作用
ARRAY JOIN：数组连接，用来展开数组或嵌套字段，一行变多行
LIMIT BY: 分组，再从每组中取前n条记录
INTO OUTFILE: 到处表数据到文件，再用FORMAT指定文件格式

查询子句

下面只说明ClickHouse中特有的数据查询子句。

WITH子句

参见：

https://clickhouse.tech/docs/en/sql-reference/statements/select/with/

-- 在WITH子句中定义一个变量并赋值，然后在SELECT子句中通过别名使用该变量
with '2014-03-17' as dt \
select count(1) from hits_v1 where EventDate = dt;


-- 在WITH子句中定义一个函数，然后在SELECT子句中通过别名使用该函数
with round(Duration / 60)as duration_minutes \
select StartDate, max(duration_minutes) as max_duration_minutes from visits_v1 \
group by StartDate, Duration \
order by max_duration_minutes desc \
limit 10;


-- 在WITH子句中定义一个子查询，然后在SELECT子句中通过别名使用该子查询
-- 该子查询只能返回一行数据
with ( \
  select sum(Duration) from visits_v1 \
) as total_duration \
select StartDate, sum(Duration) / total_duration as duration_percentage from visits_v1 \
group by StartDate, Duration \
limit 10;

SAMPLE子句

参见：

https://clickhouse.tech/docs/en/sql-reference/statements/select/sample/

对使用了MergeTree表引擎的表，并且设置了SAMPLE BY的表，可以使用SAMPLE子句来对数据进行抽样。

表例子：

CREATE TABLE tutorial.hits_v1 \ 
( 
  ...
)
ENGINE = MergeTree() \ 
PARTITION BY toYYYYMM(EventDate) \ 
ORDER BY (CounterID, EventDate, intHash32(UserID)) \ 
SAMPLE BY intHash32(UserID) \ 
SETTINGS index_granularity = 8192;

hits_v1表使用MergeTree表引擎，并且SAMPLE BY为将UserID转换成32位的Hash值。

SAMPLE子句分为：

分类	语法	描述
按比例采样	`SAMPLE k`	k值为0到1，比如k为0.1时表示采样10%的表数据。
按记录数采样	`SAMPLE n`	n为一个足够大的数，一般大于索引粒度index_granularity； n较小时，采样结果数据可能为0条记录。
按比例和偏移量采样	`SAMPLE k OFFSET m`	k值为0到1，比如k为0.1时表示采样10%的表数据。 m值为0到1，比如0.3表示从从后面70%的表数据中采样。

SAMPLE子句示例：

-- 按比例采样
-- 采样结果记录数
select count(1) from hits_v1 sample 0.1
-- 采样数据，默认限制返回10000条
select CounterID, UserID, EventDate, EventTime  from hits_v1 sample 0.1
-- 采样数据，限制返回10条
select CounterID, UserID, EventDate, EventTime  from hits_v1 sample 0.1 limit 10


-- 按记录数采样
-- 采样记录数较小时，采样结果数据为0条
select count(1) from hits_v1 sample 100
-- 采样记录数大过索引粒度时，采样结果数据记录数接近采样记录数
elect count(1) from hits_v1 sample 10000
-- 采样数据，默认限制返回10000条
select CounterID, UserID, EventDate, EventTime  from hits_v1 sample 20000
-- 采样数据，限制返回10条
select CounterID, UserID, EventDate, EventTime  from hits_v1 sample 20000 limit 10


-- 按比例和偏移量采样，类似于按比例采样
select CounterID, UserID, EventDate, EventTime  from hits_v1 sample 0.1 offset 0.3 limit 10

SAMPLE子句数据采样具有幂等性和近似性的特点：

幂等性：采样条件不变时，两次采样的结果可能一样
近似性：采样范围和采样结果不保证精确

PREWHERE子句

参见：

https://clickhouse.tech/docs/en/sql-reference/statements/select/prewhere/

只有MergeTree表引擎的表才能使用PREWHERE子句，可以将PREWHERE看作是ClickHouse对WHERE子句的优化。

ClickHouse默认将WHERE自动优化为PREWHERE:

-- optimize_move_to_prewhere为1时，表示开始PREWHERE自动优化
select name, value from system.settings where name like '%prewhere%'

ARRAY JOIN子句

参见：

https://clickhouse.tech/docs/en/sql-reference/statements/select/array-join/

可以用ARRAY JOIN子句来对数组（Array）或嵌套（Nested）类型做链接查询，可以将一行数组展成多行。

ARRAY JOIN数组示例：

-- 不使用ARRAY JOIN
select WatchID, RefererCategories from hits_v1 where WatchID = 4944118417295196513

-- 结果：
┌─────────────WatchID─┬─RefererCategories─┐
│ 4944118417295196513 │ [6,98,456,8586]   │
└─────────────────────┴───────────────────┘


-- 使用ARRAY JOIN
select WatchID, RefererCategories \
from hits_v1 \
array join RefererCategories \
where WatchID = 4944118417295196513;

-- 结果：
─────────────WatchID─┬─RefererCategories─┐
│ 4944118417295196513 │                 6 │
│ 4944118417295196513 │                98 │
│ 4944118417295196513 │               456 │
│ 4944118417295196513 │              8586 │
└─────────────────────┴───────────────────┘

ARRAY JOIN嵌套类型示例：

-- 不使用ARRAY JOIN
select WatchID, ParsedParams.Key1, ParsedParams.Key2 from hits_v1 where WatchID = 5024825574842900819

-- 结果：
┌─────────────WatchID─┬─ParsedParams.Key1───────────┬─ParsedParams.Key2───┐
│ 5024825574842900819 │ ['gen_timestamp','Toolbar'] │ ['group','true" /'] │
└─────────────────────┴─────────────────────────────┴─────────────────────┘


-- 使用ARRAY JOIN
select WatchID, ParsedParams.Key1, ParsedParams.Key2 \
from hits_v1 \
array join ParsedParams \
where WatchID = 5024825574842900819;

-- 结果：
┌─────────────WatchID─┬─ParsedParams.Key1─┬─ParsedParams.Key2─┐
│ 5024825574842900819 │ gen_timestamp     │ group             │
│ 5024825574842900819 │ Toolbar           │ true" /           │
└─────────────────────┴───────────────────┴───────────────────┘

ARRAY JOIN也支持左连接接LEFT ARRAY JOIN。

LIMIT BY子句

参见：

https://clickhouse.tech/docs/en/sql-reference/statements/select/limit-by/

LIMIT BY子句不同于通用SQL的LIMIT子句。

LIMIT n BY expression 对SELECT结果先按expression分组，再在每组里选出前n个，类似分类排行榜的概念。

示例：

CREATE TABLE limit_by(id Int, val Int) ENGINE = Memory;
INSERT INTO limit_by VALUES (1, 10), (1, 11), (1, 12), (2, 20), (2, 21), (2, 22), (3, 31);

-- 排序
SELECT * FROM limit_by ORDER BY id, val

┌─id─┬─val─┐
│  1 │  10 │
│  1 │  11 │
│  1 │  12 │
│  2 │  20 │
│  2 │  21 │
│  2 │  22 │
│  3 │  31 │
└────┴─────┘

-- 分类排序，再在每个分组内取前2条记录
SELECT * FROM limit_by ORDER BY id, val LIMIT 2 BY id

┌─id─┬─val─┐
│  1 │  10 │
│  1 │  11 │
│  2 │  20 │
│  2 │  21 │
│  3 │  31 │
└────┴─────┘


-- 注意，与LIMIT 2的不同
SELECT * FROM limit_by ORDER BY id, val LIMIT 2

┌─id─┬─val─┐
│  1 │  10 │
│  1 │  11 │
└────┴─────┘

LIMIT BY子句也支持偏移量：LIMIT n OFFSET m BY exression

INTO OUTFILE子句

ClickHouse的INTO OUTFILE子句与MySQL的INTO OUTFILE子句类似。

-- 输出到当前目录
-- 默认格式为TSV
-- 注意文件名必须用单引号来括起来，且不能用双引号括起来，否则会报错：Expected string literal
-- 目录下不能存在同名文件，否则会报错
select WatchID, JavaEnable, EventDate  from hits_v1 limit 10 into outfile 'test.tsv'

-- 设置格式为CSV，CSV需要为全大小
select WatchID, JavaEnable, EventDate  from hits_v1 limit 10 into outfile 'out.csv' format CSV

执行计划

查看执行计划

可以通过以下方式查看执行计划：

直接查看执行计划：

ch --send_logs_level=trace <<< 'select * from tutorial.hits_v1' > /dev/null

可以将以下内容保持到一个脚本文件，比如chx.sh中：

#!/bin/bash

clickhouse-client --send_logs_level=trace <<< "$1" > /dev/null

再通过bash chi.sh "select * from tutorial.hits_v1" 来查看执行计划。

也可以在clickhouse-client执行sql同时，用tail -f clickhouse-server.log 查看clickhouse-server的日志。

执行计划示例

select * from tutorial.hits_v1的执行计划日志示例：

<Debug> tutorial.hits_v1 (SelectExecutor): Key condition: unknown
<Debug> tutorial.hits_v1 (SelectExecutor): MinMax index condition: unknown
<Debug> tutorial.hits_v1 (SelectExecutor): Selected 9 parts by date, 9 parts by key, 1094 marks to read from 9 ranges
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_1_6_1, approx. 1900000 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_7_12_1, approx. 1900000 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_13_18_1, approx. 1800000 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_19_24_1, approx. 1800000 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_25_25_0, approx. 303104 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_26_26_0, approx. 303104 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_27_27_0, approx. 303104 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_28_28_0, approx. 303104 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_29_29_0, approx. 278528 rows starting from 0
<Trace> InterpreterSelectQuery: FetchColumns -> Complete
<Information> executeQuery: Read 8873898 rows, 7.88 GiB in 47.964 sec., 185011 rows/sec., 168.22 MiB/sec.
<Debug> MemoryTracker: Peak memory usage (for query): 204.54 MiB.

说明：

Key condition: unknown：没有使用主键索引。
MinMax index condition: unknown：没有使用分区索引。
Selected 9 parts by date, 9 parts by key, 1094 marks to read from 9 ranges：共扫描了9个分区，共1094个mark。
Read 8873898 rows, 7.88 GiB in 47.964 sec., 185011 rows/sec., 168.22 MiB/sec.: 读取了8873898行数据，数据大小为7.88GB，用时47.964秒。
Peak memory usage (for query): 204.54 MiB.: 内存峰值（最大内存使用量）为204.54MB。

将SQL改为只返回一个字段select WatchID from tutorial.hits_v1，再来看执行计划：

<Debug> tutorial.hits_v1 (SelectExecutor): Key condition: unknown
<Debug> tutorial.hits_v1 (SelectExecutor): MinMax index condition: unknown
<Debug> tutorial.hits_v1 (SelectExecutor): Selected 9 parts by date, 9 parts by key, 1094 marks to read from 9 ranges
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_1_6_1, approx. 1900000 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_7_12_1, approx. 1900000 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_13_18_1, approx. 1800000 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_19_24_1, approx. 1800000 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_25_25_0, approx. 303104 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_26_26_0, approx. 303104 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_27_27_0, approx. 303104 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_28_28_0, approx. 303104 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 1 ranges from part 201403_29_29_0, approx. 278528 rows starting from 0
<Trace> InterpreterSelectQuery: FetchColumns -> Complete
<Information> executeQuery: Read 8873898 rows, 67.70 MiB in 0.318 sec., 27892532 rows/sec., 212.80 MiB/sec.
<Debug> MemoryTracker: Peak memory usage (for query): 12.32 MiB.

几个变化：

Read 8873898 rows, 67.70 MiB in 0.318 sec., 27892532 rows/sec., 212.80 MiB/sec.: 数据大小从7.88GB减小到67.70MB，用时从47.964秒减小到0.318秒。
Peak memory usage (for query): 12.32 MiB.: 内存峰值从204.54MB减小到12.32MB。

再将SQL改为指定分区查询：

select WatchID from tutorial.hits_v1 where EventDate = '2014-03-17'

执行计划日志：

<Debug> executeQuery: (from 127.0.0.1:48102) SELECT WatchID FROM tutorial.hits_v1 WHERE EventDate = '2014-03-17'
<Debug> InterpreterSelectQuery: MergeTreeWhereOptimizer: condition "EventDate = '2014-03-17'" moved to PREWHERE
<Trace> ContextAccess (default): Access granted: SELECT(WatchID, EventDate) ON tutorial.hits_v1
<Debug> tutorial.hits_v1 (SelectExecutor): Key condition: (column 1 in [16146, 16146])
<Debug> tutorial.hits_v1 (SelectExecutor): MinMax index condition: (column 0 in [16146, 16146])
<Debug> tutorial.hits_v1 (SelectExecutor): Selected 9 parts by date, 9 parts by key, 833 marks to read from 72 ranges
<Trace> MergeTreeSelectProcessor: Reading 14 ranges from part 201403_1_6_1, approx. 818656, up to 818656 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 14 ranges from part 201403_7_12_1, approx. 1621472, up to 1621472 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 15 ranges from part 201403_13_18_1, approx. 1349440, up to 1349440 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 14 ranges from part 201403_19_24_1, approx. 1619776, up to 1619776 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 4 ranges from part 201403_25_25_0, approx. 278528, up to 278528 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 3 ranges from part 201403_26_26_0, approx. 286720, up to 286720 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 2 ranges from part 201403_27_27_0, approx. 294912, up to 294912 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 3 ranges from part 201403_28_28_0, approx. 229376, up to 229376 rows starting from 0
<Trace> MergeTreeSelectProcessor: Reading 3 ranges from part 201403_29_29_0, approx. 253952, up to 253952 rows starting from 0
<Trace> InterpreterSelectQuery: FetchColumns -> Complete
<Information> executeQuery: Read 6735786 rows, 61.49 MiB in 0.097 sec., 69655325 rows/sec., 635.86 MiB/sec.
<Debug> MemoryTracker: Peak memory usage (for query): 16.32 MiB.

说明：

MergeTreeWhereOptimizer: condition "EventDate = '2014-03-17'" moved to PREWHERE：启动了PREWHERE优化。
Key condition: (column 1 in [16146, 16146])：用了主键索引。
MinMax index condition: (column 0 in [16146, 16146])：用了分区索引。
Selected 9 parts by date, 9 parts by key, 833 marks to read from 72 ranges：从1094 marks减少到833 marks。
Read 6735786 rows, 61.49 MiB in 0.097 sec., 69655325 rows/sec., 635.86 MiB/sec.：数据大小从67.70MB变为61.49MB，用时从0.318秒减少到0.097秒。

原文链接：https://blog.csdn.net/nklinsirui/article/details/108886972