planner: make var_samp can be used as a window function

[hi-rustin]

What problem does this PR solve?

Issue Number: close #52933

Problem Summary:

What changed and how does it work?

From the MySQL plan:

mysql> explain analyze select var_samp(c1) over (partition by c1) from t1;
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| EXPLAIN                                                                                                                                                                                                                                                                                                                |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| -> Window aggregate with buffering: var_samp(t1.c1) OVER (PARTITION BY t1.c1 )   (cost=0 rows=1) (actual time=0.139..0.139 rows=0 loops=1)
    -> Sort: t1.c1  (cost=0.35 rows=1) (actual time=0.133..0.133 rows=0 loops=1)
        -> Table scan on t1  (cost=0.35 rows=1) (actual time=0.116..0.116 rows=0 loops=1)
 |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.01 sec)

• Made var_samp can be used as a window function.
• Added a test case for use var_samp as window function cause unexpected error #52933.

Check List

Tests

• Unit test
• Integration test
• Manual test (add detailed scripts or steps below)
• No need to test

  • I checked and no code files have been changed.

Side effects

• Performance regression: Consumes more CPU
• Performance regression: Consumes more Memory
• Breaking backward compatibility

Documentation

• Affects user behaviors
• Contains syntax changes
• Contains variable changes
• Contains experimental features
• Changes MySQL compatibility

Release note

Please refer to Release Notes Language Style Guide to write a quality release note.

Make `var_samp` can be used as a window function.
使 `var_samp` 可以用作窗口函数。

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 74.7449%. Comparing base (4b91fee) to head (06146bb).
Report is 10 commits behind head on master.

Additional details and impacted files

@@               Coverage Diff                @@
##             master     #53130        +/-   ##
================================================
+ Coverage   74.4490%   74.7449%   +0.2959%     
================================================
  Files          1493       1493                
  Lines        356315     430968     +74653     
================================================
+ Hits         265273     322127     +56854     
- Misses        71770      89017     +17247     
- Partials      19272      19824       +552     

Flag	Coverage Δ
integration	49.4982% <0.0000%> (?)
unit	71.4551% <100.0000%> (-1.7617%)	⬇️

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Components	Coverage Δ
dumpling	53.9957% <ø> (-2.3014%)	⬇️
parser	∅ <ø> (∅)
br	50.4651% <ø> (+7.4738%)	⬆️

[hi-rustin]

/retest

[hi-rustin]

Tested locally:

1. Start the cluster: tiup playground v8.0.0 --db.binpath /Users/hi-rustin/vsc/tidb/bin/tidb-server
2. Create the table and run the query:

mysql> use test;
msqll> create table t1 (c1 int)
mysql> select c1, var_samp(c1) over (partition by c1) from t1;
Empty set (0.00 sec)

mysql> explain select c1, var_samp(c1) over (partition by c1) from t1;
+-------------------------------+----------+-----------+---------------+-----------------------------------------------------------------------------------+
| id                            | estRows  | task      | access object | operator info                                                                     |
+-------------------------------+----------+-----------+---------------+-----------------------------------------------------------------------------------+
| Shuffle_11                    | 10000.00 | root      |               | execution info: concurrency:5, data sources:[TableReader_9]                       |
| └─Window_7                    | 10000.00 | root      |               | var_samp(cast(test.t1.c1, double BINARY))->Column#4 over(partition by test.t1.c1) |
|   └─Sort_10                   | 10000.00 | root      |               | test.t1.c1                                                                        |
|     └─ShuffleReceiver_12      | 10000.00 | root      |               |                                                                                   |
|       └─TableReader_9         | 10000.00 | root      |               | data:TableFullScan_8                                                              |
|         └─TableFullScan_8     | 10000.00 | cop[tikv] | table:t1      | keep order:false, stats:pseudo                                                    |
+-------------------------------+----------+-----------+---------------+-----------------------------------------------------------------------------------+
6 rows in set (0.00 sec)

mysql> explain select c1, sum(c1) over (partition by c1) from t1;
+-------------------------------+----------+-----------+---------------+-------------------------------------------------------------------------------------+
| id                            | estRows  | task      | access object | operator info                                                                       |
+-------------------------------+----------+-----------+---------------+-------------------------------------------------------------------------------------+
| Shuffle_11                    | 10000.00 | root      |               | execution info: concurrency:5, data sources:[TableReader_9]                         |
| └─Window_7                    | 10000.00 | root      |               | sum(cast(test.t1.c1, decimal(10,0) BINARY))->Column#4 over(partition by test.t1.c1) |
|   └─Sort_10                   | 10000.00 | root      |               | test.t1.c1                                                                          |
|     └─ShuffleReceiver_12      | 10000.00 | root      |               |                                                                                     |
|       └─TableReader_9         | 10000.00 | root      |               | data:TableFullScan_8                                                                |
|         └─TableFullScan_8     | 10000.00 | cop[tikv] | table:t1      | keep order:false, stats:pseudo                                                      |
+-------------------------------+----------+-----------+---------------+-------------------------------------------------------------------------------------+
6 rows in set (0.01 sec)

[hi-rustin]

🔢 Self-check (PR reviewed by myself and ready for feedback.)

[ti-chi-bot]

[LGTM Timeline notifier]

Timeline:

• 2024-05-14 09:40:23.923885188 +0000 UTC m=+1559777.681020761: ☑️ agreed by qw4990.
• 2024-05-14 12:25:15.552696005 +0000 UTC m=+1569669.309831580: ☑️ agreed by winoros.

[easonn7]

/approve

[ti-chi-bot]

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: easonn7, qw4990, tangenta, winoros

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[ti-chi-bot]

In response to a cherrypick label: new pull request created to branch release-6.5: #53285.

[ti-chi-bot]

In response to a cherrypick label: new pull request created to branch release-7.1: #53286.

[ti-chi-bot]

In response to a cherrypick label: new pull request created to branch release-7.5: #53287.

[ti-chi-bot]

In response to a cherrypick label: new pull request created to branch release-8.1: #53288.