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MySQL-递归-日期

发布于 2023-03-14 | 标签: postgresql 、 mysql | 11分钟 | 1900字数

本文作为MySQL使用指南的延申讨论

  • 递归
  • 行列转换
  • 日期/时间处理相关函数

一. 递归

MySQL-Recursive-CTE.png

As mentioned previously, recursive common table expressions (CTEs) are frequently used for series generation and traversing hierarchical or tree-structured data.

递归成员不得包含以下结构:

递归公用表表达式 ( CTE) 是一个CTE 它有一个子查询 它引用CTE名称本身. 以下说明了递归CTE的语法

WITH RECURSIVE cte_name AS (
initial_query -- anchor member
UNION ALL
recursive_query -- 引用CTE名称的递归成员
SELECT * FROM cte_name;

递归CTE由三个主要部分组成:

  • 初始查询 形成CTE结构的基本结果集. 初始查询部分称为锚成员.
  • 递归查询部分是引用CTE名称的查询 因此 它被称为递归成员. 递归成员由UNION ALL或UNION DISTINCT运算符与锚成员连接.
  • 终止条件 确保递归成员不返回任何行时停止递归.

递归CTE的执行顺序如下:

  1. 首先 将成员分为两部分: 锚点和递归成员.
  2. 接下来 执行锚成员以形成基本结果集( R0) 并将此基本结果集用于下一次迭代.
  3. 然后 执行带有Ri结果集作为输入的递归成员并将其Ri+1作为输出.
  4. 之后 重复第三步 直到递归成员返回空结果集 换句话说 满足终止条件.
  5. 最后 使用UNION ALL运算符将结果集从R0到Rn组合.
# 生成斐波那契数列
WITH RECURSIVE fibonacci (n, fib_n, next_fib_n) AS
(
  SELECT 1, 0, 1
  UNION ALL
  SELECT n + 1, next_fib_n, fib_n + next_fib_n
    FROM fibonacci WHERE n < 10
)
SELECT * FROM fibonacci;

+------+-------+------------+
| n    | fib_n | next_fib_n |
+------+-------+------------+
|    1 |     0 |          1 |
|    2 |     1 |          1 |
|    3 |     1 |          2 |
|    4 |     2 |          3 |
|    5 |     3 |          5 |
|    6 |     5 |          8 |
|    7 |     8 |         13 |
|    8 |    13 |         21 |
|    9 |    21 |         34 |
|   10 |    34 |         55 |
+------+-------+------------+
10 rows in set (0.00 sec)

二. 日历

+--------+--------+--------+--------+--------+--------+--------+
| 星期一  | 星期二 | 星期三  | 星期四 | 星期五  | 星期六  | 星期日 |
+--------+--------+--------+--------+--------+--------+--------+
|   NULL |   NULL |      1 |      2 |      3 |      4 |      5 |
|      6 |      7 |      8 |      9 |     10 |     11 |     12 |
|     13 |     14 |     15 |     16 |     17 |     18 |     19 |
|     20 |     21 |     22 |     23 |     24 |     25 |     26 |
|     27 |     28 |     29 |     30 |     31 |   NULL |   NULL |
+--------+--------+--------+--------+--------+--------+--------+
5 rows in set (0.00 sec)

MySQL root@localhost:(none)> select current_date();
+----------------+
| current_date() |
+----------------+
| 2023-03-13     |
+----------------+
1 row in set
Time: 0.004s

WITH RECURSIVE calendar ( init_date ) AS (
    # 生成第一天的数据, 可以使用其他方式来生成
	SELECT
		subdate( adddate( CURRENT_DATE, INTERVAL 1 DAY ), INTERVAL dayofmonth( CURRENT_DATE ) DAY ) UNION ALL
	SELECT
		adddate( init_date, INTERVAL 1 DAY )
	FROM
		calendar
	WHERE
    	# 循环到最后一天
		init_date < last_day( CURRENT_DATE )
	) SELECT
	*
FROM
	calendar;

+------------+
| int_date   |
+------------+
| 2023-03-01 |
| 2023-03-02 |
| 2023-03-03 |
| 2023-03-04 |
| 2023-03-05 |
| 2023-03-06 |
| 2023-03-07 |
| 2023-03-08 |
| 2023-03-09 |
| 2023-03-10 |
| 2023-03-11 |
| 2023-03-12 |
| 2023-03-13 |
| 2023-03-14 |
| 2023-03-15 |
| 2023-03-16 |
| 2023-03-17 |
| 2023-03-18 |
| 2023-03-19 |
| 2023-03-20 |
| 2023-03-21 |
| 2023-03-22 |
| 2023-03-23 |
| 2023-03-24 |
| 2023-03-25 |
| 2023-03-26 |
| 2023-03-27 |
| 2023-03-28 |
| 2023-03-29 |
| 2023-03-30 |
| 2023-03-31 |
+------------+
31 rows in set (0.00 sec)

WITH RECURSIVE calendar ( init_date ) AS (
	SELECT
		subdate( adddate( CURRENT_DATE, INTERVAL 1 DAY ), INTERVAL dayofmonth( CURRENT_DATE ) DAY ) UNION ALL
	SELECT
		adddate( init_date, INTERVAL 1 DAY )
	FROM
		calendar
	WHERE
		init_date < last_day( CURRENT_DATE )
	) SELECT
	init_date,
	# 返回日期对应的周
	WEEK ( init_date, 1 ) AS wk,
	dayofmonth( init_date ) AS dm,
	dayofweek( init_date ) AS dw
FROM
	calendar;

+------------+------+------+------+
| init_date  | wk   | dm   | dw   |
+------------+------+------+------+
| 2023-03-01 |    9 |    1 |    4 |
| 2023-03-02 |    9 |    2 |    5 |
| 2023-03-03 |    9 |    3 |    6 |
| 2023-03-04 |    9 |    4 |    7 |
| 2023-03-05 |    9 |    5 |    1 |
| 2023-03-06 |   10 |    6 |    2 |
| 2023-03-07 |   10 |    7 |    3 |
| 2023-03-08 |   10 |    8 |    4 |
| 2023-03-09 |   10 |    9 |    5 |
| 2023-03-10 |   10 |   10 |    6 |
| 2023-03-11 |   10 |   11 |    7 |
| 2023-03-12 |   10 |   12 |    1 |
| 2023-03-13 |   11 |   13 |    2 |
| 2023-03-14 |   11 |   14 |    3 |
| 2023-03-15 |   11 |   15 |    4 |
| 2023-03-16 |   11 |   16 |    5 |
| 2023-03-17 |   11 |   17 |    6 |
| 2023-03-18 |   11 |   18 |    7 |
| 2023-03-19 |   11 |   19 |    1 |
| 2023-03-20 |   12 |   20 |    2 |
| 2023-03-21 |   12 |   21 |    3 |
| 2023-03-22 |   12 |   22 |    4 |
| 2023-03-23 |   12 |   23 |    5 |
| 2023-03-24 |   12 |   24 |    6 |
| 2023-03-25 |   12 |   25 |    7 |
| 2023-03-26 |   12 |   26 |    1 |
| 2023-03-27 |   13 |   27 |    2 |
| 2023-03-28 |   13 |   28 |    3 |
| 2023-03-29 |   13 |   29 |    4 |
| 2023-03-30 |   13 |   30 |    5 |
| 2023-03-31 |   13 |   31 |    6 |
+------------+------+------+------+
31 rows in set (0.00 sec)

这里涉及到行列转换问题

2.1 行列转换

这里使用MySQL和PostgreSQL进行对比

create table test_b(name char(4), s_type varchar(10), s_value int);

insert into test_b values('alex','weight', 60);
insert into test_b values('alex','age', 60);
insert into test_b values('alex','heigh', 160);
insert into test_b values('tony','weight', 78);
insert into test_b values('tony','age', 35);
insert into test_b values('tony','heigh', 170);

 name | s_type | s_value
------+--------+---------
 alex | weight |      60
 alex | age    |      60
 alex | heigh  |     160
 tony | weight |      78
 tony | age    |      35
 tony | heigh  |     170
(6 rows)

2.1.1 PostgreSQL

postgresql支持extension

test_db=# select name from pg_available_extensions;
        name
---------------------
 adminpack
 amcheck
 autoinc
 bloom
 bool_plperl
 bool_plperlu
 btree_gin
 btree_gist
 citext
 cube
 dblink
 dict_int
 dict_xsyn
 dummy_index_am
 earthdistance
 file_fdw
 fuzzystrmatch
 hstore
 hstore_plperl
 hstore_plperlu
 hstore_plpython3u
 insert_username
 intagg
 intarray
 isn
 jsonb_plperl
 jsonb_plperlu
 jsonb_plpython3u
 lo
 ltree
 ltree_plpython3u
 moddatetime
 old_snapshot
 pageinspect
 pgcrypto
 pgrowlocks
 pgstattuple
 pg_buffercache
 pg_freespacemap
 pg_prewarm
 pg_stat_statements
 pg_surgery
 pg_trgm
 pg_visibility
 pg_walinspect
 pldbgapi
 plperl
 plperlu
 plpgsql
 plpython3u
 plsample
 pltcl
 pltclu
 postgres_fdw
 refint
 seg
 spgist_name_ops
 sslinfo
 system_stats
 tablefunc
 tcn
 test_bloomfilter
 test_ext1
 test_ext2
 test_ext3
 test_ext4
 test_ext5
 test_ext6
 test_ext7
 test_ext8
 test_ext_cine
 test_ext_cor
 test_ext_cyclic1
 test_ext_cyclic2
 test_ext_evttrig
 test_ginpostinglist
 test_integerset
 test_pg_dump
 test_predtest
 test_rbtree
 test_regex
 tsm_system_rows
 tsm_system_time
 unaccent
 uuid-ossp
 xml2
(86 rows)

CREATE EXTENSION loads a new extension into the current database. There must not be an extension of the same name already loaded.

Loading an extension essentially amounts to running the extension's script file. The script will typically create new SQL objects such as functions, data types, operators and index support methods. CREATE EXTENSION additionally records the identities of all the created objects, so that they can be dropped again if DROP EXTENSION is issued.

The user who runs CREATE EXTENSION becomes the owner of the extension for purposes of later privilege checks, and normally also becomes the owner of any objects created by the extension's script.

Loading an extension ordinarily requires the same privileges that would be required to create its component objects. For many extensions this means superuser privileges are needed. However, if the extension is marked trusted in its control file, then it can be installed by any user who has CREATE privilege on the current database. In this case the extension object itself will be owned by the calling user, but the contained objects will be owned by the bootstrap superuser (unless the extension's script explicitly assigns them to the calling user). This configuration gives the calling user the right to drop the extension, but not to modify individual objects within it.

SELECT
	*
FROM
	crosstab ( 'select name, s_type, s_value from test_b' ) AS ct ( NAME CHAR ( 4 ), weight INT, age INT, heigh INT );

ERROR:  function crosstab(unknown) does not exist

# 需要先执行
CREATE EXTENSION IF NOT EXISTS tablefunc;

test_db=# SELECT * FROM crosstab('select name, s_type, s_value from test_b') AS ct(name char(4), weight int, age int, heigh int);
 name | weight | age | heigh
------+--------+-----+-------
 alex |     60 |  60 |   160
 tony |     78 |  35 |   170
(2 rows)

非常简单, 在 postgresql之下.

PostgreSQL: Documentation: 15: F.43. tablefunc

2.1.2 MySQL

MySQL root@localhost:test_db> select name,
                           -> sum(case when s_type='age' then s_value else 0 end) as age,
                           -> sum(case when s_type='heigh' then s_value else 0 end) as heigh,
                           -> sum(case when s_type='weight' then s_value else 0 end) as weight
                           -> from test_b group by name;
+------+-----+-------+--------+
| name | age | heigh | weight |
+------+-----+-------+--------+
| alex | 60  | 160   | 60     |
| tony | 35  | 170   | 78     |
+------+-----+-------+--------+
2 rows in set

MySQL root@localhost:test_db> select name,
                           -> max(case when s_type='age' then s_value else 0 end) as age,
                           -> max(case when s_type='heigh' then s_value else 0 end) as heigh,
                           -> max(case when s_type='weight' then s_value else 0 end) as weight
                           -> from test_b group by name;
+------+-----+-------+--------+
| name | age | heigh | weight |
+------+-----+-------+--------+
| alex | 60  | 160   | 60     |
| tony | 35  | 170   | 78     |
+------+-----+-------+--------+
2 rows in set
Time: 0.007s

WITH RECURSIVE calendar ( init_date ) AS (
	SELECT
		subdate( adddate( CURRENT_DATE, INTERVAL 1 DAY ), INTERVAL dayofmonth( CURRENT_DATE ) DAY ) UNION ALL
	SELECT
		adddate( init_date, INTERVAL 1 DAY )
	FROM
		calendar
	WHERE
		init_date < last_day( CURRENT_DATE )
	),
	a AS (
	SELECT
		init_date,
		WEEK ( init_date, 1 ) AS wk,
		dayofmonth( init_date ) AS dm,
		dayofweek( init_date ) - 1 AS dw
	FROM
		calendar
	) SELECT
	max(
	IF
	( dw = 1, dm, NULL )) AS "星期一",
	max(
	IF
	( dw = 2, dm, NULL )) AS "星期二",
	max(
	IF
	( dw = 3, dm, NULL )) AS "星期三",
	max(
	IF
	( dw = 4, dm, NULL )) AS "星期四",
	max(
	IF
	( dw = 5, dm, NULL )) AS "星期五",
	max(
	IF
	( dw = 6, dm, NULL )) AS "星期六",
	max(
	IF
	( dw = 0, dm, NULL )) AS "星期日"
FROM
	a
GROUP BY
	wk;

+--------+--------+--------+--------+--------+--------+--------+
| 星期一 | 星期二  | 星期三  | 星期四 | 星期五  | 星期六  | 星期日 |
+--------+--------+--------+--------+--------+--------+--------+
|   NULL |   NULL |      1 |      2 |      3 |      4 |      5 |
|      6 |      7 |      8 |      9 |     10 |     11 |     12 |
|     13 |     14 |     15 |     16 |     17 |     18 |     19 |
|     20 |     21 |     22 |     23 |     24 |     25 |     26 |
|     27 |     28 |     29 |     30 |     31 |   NULL |   NULL |
+--------+--------+--------+--------+--------+--------+--------+
5 rows in set (0.00 sec)

不管是max, min, sum操作, 其原理都是类似的, 但是需要注意不能使用any_value.

2.2 涉及的日期处理函数

  • current_date, 当前日期
  • subdate, 减掉间隔
  • adddate, 增加间隔
  • last_day, 返回月的最后一天
  • week, 日期所在的周(一年)
  • dayofmonth, 日所在的月
  • dayofweek, 日所在星期
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