ClickHouse-尚硅谷（10. 高级-语法优化规则）学习笔记
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文章目录
- 1 准备测试用表
- 2 COUNT 优化
- 3 消除子查询重复字段
- 4 谓词下推
- 5 聚合计算外推
- 6 聚合函数消除
- 7 删除重复的 order by key
- 8 删除重复的 limit by key
- 9 删除重复的 USING Key
- 10 标量替换
- 11 三元运算优化
ClickHouse 的 SQL 优化规则是基于 RBO(Rule Based Optimization)，下面是一些优化规则
1 准备测试用表
-
上传官方的数据集
将 visits_v1.tar 和 hits_v1.tar 上传到虚拟机，解压到 clickhouse 数据路径下// 解压到 clickhouse 数据路径 sudo tar -xvf hits_v1.tar -C /var/lib/clickhouse sudo tar -xvf visits_v1.tar -C /var/lib/clickhouse //修改所属用户 sudo chown -R clickhouse:clickhouse /var/lib/clickhouse/data/datasets sudo chown -R clickhouse:clickhouse /var/lib/clickhouse/metadata/datasets -
重启 clickhouse-server
sudo clickhouse restart -
执行查询
clickhouse-client --query "SELECT COUNT(*) FROM datasets.hits_v1" clickhouse-client --query "SELECT COUNT(*) FROM datasets.visits_v1"注意：官方的 tar 包，包含了建库、建表语句、数据内容，这种方式不需要手动建库、建表，最方便。
hits_v1 表有 130 多个字段，880 多万条数据
visits_v1 表有 180 多个字段，160 多万条数据
2 COUNT 优化
在调用 count 函数时，如果使用的是 count() 或者 count(*)，且没有 where 条件，则会直接使用 system.tables 的 total_rows，例如:
EXPLAIN SELECT count()FROM datasets.hits_v1;
Union
Expression (Projection)
Expression (Before ORDER BY and SELECT)
MergingAggregated
ReadNothing (Optimized trivial count)
注意 Optimized trivial count ，这是对 count 的优化, 只要括号中不写具体的字段就会进行优化。
如果 count 具体的列字段，则不会使用此项优化：
EXPLAIN SELECT count(CounterID) FROM datasets.hits_v1;
Union
Expression (Projection)
Expression (Before ORDER BY and SELECT)
Aggregating
Expression (Before GROUP BY)
ReadFromStorage (Read from MergeTree)
3 消除子查询重复字段
-
下面语句子查询中有两个重复的 id 字段，会被去重:
EXPLAIN SYNTAX SELECT a.UserID, b.VisitID, a.URL, b.UserID FROM hits_v1 AS a LEFT JOIN ( SELECT UserID, UserID as HaHa, VisitID FROM visits_v1) AS b USING (UserID) limit 3; -
返回优化语句：
SELECT UserID, VisitID, URL, b.UserID FROM hits_v1 AS a ALL LEFT JOIN ( SELECT UserID, VisitID FROM visits_v1 ) AS b USING (UserID) LIMIT 3
4 谓词下推
当 group by 有 having 子句，但是没有 with cube、with rollup 或者 with totals 修饰的时候，having 过滤会下推到 where 提前过滤。例如下面的查询，HAVING name 变成了 WHERE name，在 group by 之前过滤：
EXPLAIN SYNTAX
SELECT UserID
FROM hits_v1
GROUP BY UserID
HAVING UserID = '8585742290196126178';
//返回优化语句
SELECT UserID
FROM hits_v1
WHERE UserID = \'8585742290196126178\'
GROUP BY UserID
子查询也支持谓词下推：
EXPLAIN SYNTAX
SELECT *
FROM
(
SELECT UserID
FROM visits_v1
)
WHERE UserID = '8585742290196126178'
//返回优化后的语句
SELECT UserID
FROM
(
SELECT UserID
FROM visits_v1
WHERE UserID = \'8585742290196126178\'
)
WHERE UserID = \'8585742290196126178\'
再来一个复杂例子：
EXPLAIN SYNTAX
SELECT * FROM (
SELECT *
FROM
(
SELECT UserID
FROM visits_v1
)
UNION ALL
SELECT *
FROM
(
SELECT UserID
FROM visits_v1
)
)
WHERE UserID = '8585742290196126178'
//返回优化后的语句
SELECT UserID
FROM
(
SELECT UserID
FROM
(
SELECT UserID
FROM visits_v1
WHERE UserID = \'8585742290196126178\'
)
WHERE UserID = \'8585742290196126178\'
UNION ALL
SELECT UserID
FROM
(
SELECT UserID
FROM visits_v1
WHERE UserID = \'8585742290196126178\'
)
WHERE UserID = \'8585742290196126178\'
)
WHERE UserID = \'8585742290196126178\'
5 聚合计算外推
聚合函数内的计算，会外推，例如：
EXPLAIN SYNTAX
SELECT sum(UserID * 2)
FROM visits_v1
//返回优化后的语句
SELECT sum(UserID) * 2
FROM visits_v1
6 聚合函数消除
如果对聚合键，也就是 group by key 使用 min、max、any 聚合函数，则将函数消除，
例如：
EXPLAIN SYNTAX
SELECT
sum(UserID * 2),
max(VisitID),
max(UserID)
FROM visits_v1
GROUP BY UserID
//返回优化后的语句
SELECT
sum(UserID) * 2,
max(VisitID),
UserID
FROM visits_v1
GROUP BY UserID
7 删除重复的 order by key
例如下面的语句，重复的聚合键 id 字段会被去重:
EXPLAIN SYNTAX
SELECT *
FROM visits_v1
ORDER BY
UserID ASC,
UserID ASC,
VisitID ASC,
VisitID ASC
//返回优化后的语句：
select ……
FROM visits_v1
ORDER BY
UserID ASC,
VisitID ASC
8 删除重复的 limit by key
例如下面的语句，重复声明的 name 字段会被去重：
EXPLAIN SYNTAX
SELECT *
FROM visits_v1
LIMIT 3 BY
VisitID,
VisitID
LIMIT 10
//返回优化后的语句：
select ……
FROM visits_v1
LIMIT 3 BY VisitID
LIMIT 10
9 删除重复的 USING Key
例如下面的语句，重复的关联键 id 字段会被去重：
EXPLAIN SYNTAX
SELECT
a.UserID,
a.UserID,
b.VisitID,
a.URL,
b.UserID
FROM hits_v1 AS a
LEFT JOIN visits_v1 AS b USING (UserID, UserID)
//返回优化后的语句：
SELECT
UserID,
UserID,
VisitID,
URL,
b.UserID
FROM hits_v1 AS a
ALL LEFT JOIN visits_v1 AS b USING (UserID)
10 标量替换
如果子查询只返回一行数据，在被引用的时候用标量替换，例如下面语句中的 total_disk_usage 字段：
EXPLAIN SYNTAX
WITH
(
SELECT sum(bytes)
FROM system.parts
WHERE active
) AS total_disk_usage
SELECT
(sum(bytes) / total_disk_usage) * 100 AS table_disk_usage, table
FROM system.parts
GROUP BY table
ORDER BY table_disk_usage DESC
LIMIT 10;
//返回优化后的语句：
WITH CAST(0, \'UInt64\') AS total_disk_usage
SELECT
(sum(bytes) / total_disk_usage) * 100 AS table_disk_usage, table
FROM system.parts
GROUP BY table
ORDER BY table_disk_usage DESC
LIMIT 10
11 三元运算优化
如果开启了 optimize_if_chain_to_multiif 参数，三元运算符会被替换成 multiIf 函数，
例如：
EXPLAIN SYNTAX
SELECT number = 1 ? 'hello' : (number = 2 ? 'world' : 'atguigu')
FROM numbers(10)
settings optimize_if_chain_to_multiif = 1;
//返回优化后的语句：
SELECT multiIf(number = 1, \'hello\', number = 2, \'world\', \'atguigu\')
FROM numbers(10)
SETTINGS optimize_if_chain_to_multiif = 1