You write:
Each customer can have multiple sites, but only one should be
displayed in this list.
Yet, your query retrieves all rows. That would be a point to optimize. But you also do not define which site
is to be picked.
Either way, it does not matter much here. Your EXPLAIN
shows only 5026 rows for the site
scan (5018 for the customer
scan). So hardly any customer actually has more than one site. Did you ANALYZE
your tables before running EXPLAIN
?
From the numbers I see in your EXPLAIN
, indexes will give you nothing for this query. Sequential table scans will be the fastest possible way. Half a second is rather slow for 5000 rows, though. Maybe your database needs some general performance tuning?
Maybe the query itself is faster, but "half a second" includes network transfer? EXPLAIN ANALYZE would tell us more.
If this query is your bottleneck, I would suggest you implement a materialized view.
After you provided more information I find that my diagnosis pretty much holds.
The query itself needs 27 ms. Not much of a problem there. "Half a second" was the kind of misunderstanding I had suspected. The slow part is the network transfer (plus ssh encoding / decoding, possibly rendering). You should only retrieve 100 rows, that would solve most of it, even if it means to execute the whole query every time.
If you go the route with a materialized view like I proposed you could add a serial number without gaps to the table plus index on it - by adding a column row_number() OVER (<your sort citeria here>) AS mv_id
.
Then you can query:
SELECT *
FROM materialized_view
WHERE mv_id >= 2700
AND mv_id < 2800;
This will perform very fast. LIMIT
/ OFFSET
cannot compete, that needs to compute the whole table before it can sort and pick 100 rows.
pgAdmin timing
When you execute a query from the query tool, the message pane shows something like:
Total query runtime: 62 ms.
And the status line shows the same time. I quote pgAdmin help about that:
The status line will show how long the last query took to complete. If
a dataset was returned, not only the elapsed time for server execution
is displayed, but also the time to retrieve the data from the server
to the Data Output page.
If you want to see the time on the server you need to use SQL EXPLAIN ANALYZE
or the built in Shift + F7
keyboard shortcut or Query -> Explain analyze
. Then, at the bottom of the explain output you get something like this:
Total runtime: 0.269 ms
I was thinking the NATURAL JOIN
example you just used
SELECT * FROM my_table NATURAL JOIN (
SELECT group_col, MAX(sort_col) sort_col
FROM my_table
GROUP BY group_col
) t
If you shift to another type of JOIN
and impose WHERE
, ordering can come and go without warning in spite of the ill-advised reliance on undocumented behavior of the GROUP BY
.
For this example, I will
- use Windows 7
- use MySQL 5.5.12-log for Windows
- create some sample data
- impose a
LEFT JOIN
without a WHERE
clause
- impose a
LEFT JOIN
with a WHERE clause
For the DB Environment
mysql> select version();
+------------+
| version() |
+------------+
| 5.5.12-log |
+------------+
1 row in set (0.00 sec)
mysql> show variables like '%version_co%';
+-------------------------+------------------------------+
| Variable_name | Value |
+-------------------------+------------------------------+
| version_comment | MySQL Community Server (GPL) |
| version_compile_machine | x86 |
| version_compile_os | Win64 |
+-------------------------+------------------------------+
3 rows in set (0.00 sec)
mysql>
Using this script to generate sample data
DROP DATABASE IF EXISTS eggyal;
CREATE DATABASE eggyal;
USE eggyal
CREATE TABLE groupby
(
id int not null auto_increment,
num int,
primary key (id)
);
INSERT INTO groupby (num) VALUES
(floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
(floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
(floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
(floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp()));
INSERT INTO groupby (num) SELECT num FROM groupby;
SELECT * FROM groupby;
and these two queries for testing the GROUP BY
subsequent use;
SELECT * FROM groupby A LEFT JOIN
(
SELECT num, MAX(id) id
FROM groupby
GROUP BY num
) B USING (id);
SELECT * FROM groupby A LEFT JOIN
(
SELECT num, MAX(id) id
FROM groupby
GROUP BY num
) B USING (id) WHERE B.num IS NOT NULL;
Let's test the durability of the GROUP BY
's results;
STEP 01 : Create the Sample Data
mysql> DROP DATABASE IF EXISTS eggyal;
Query OK, 1 row affected (0.09 sec)
mysql> CREATE DATABASE eggyal;
Query OK, 1 row affected (0.00 sec)
mysql> USE eggyal
Database changed
mysql> CREATE TABLE groupby
-> (
-> id int not null auto_increment,
-> num int,
-> primary key (id)
-> );
Query OK, 0 rows affected (0.07 sec)
mysql> INSERT INTO groupby (num) VALUES
-> (floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
-> (floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
-> (floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp())),
-> (floor(rand() * unix_timestamp())),(floor(rand() * unix_timestamp()));
Query OK, 8 rows affected (0.06 sec)
Records: 8 Duplicates: 0 Warnings: 0
mysql> INSERT INTO groupby (num) SELECT num FROM groupby;
Query OK, 8 rows affected (0.05 sec)
Records: 8 Duplicates: 0 Warnings: 0
mysql> SELECT * FROM groupby;
+----+------------+
| id | num |
+----+------------+
| 1 | 269529129 |
| 2 | 387090406 |
| 3 | 1126864683 |
| 4 | 411160755 |
| 5 | 29173595 |
| 6 | 266349579 |
| 7 | 1244227156 |
| 8 | 6231766 |
| 9 | 269529129 |
| 10 | 387090406 |
| 11 | 1126864683 |
| 12 | 411160755 |
| 13 | 29173595 |
| 14 | 266349579 |
| 15 | 1244227156 |
| 16 | 6231766 |
+----+------------+
16 rows in set (0.00 sec)
STEP 02 : Use LEFT JOIN
without a WHERE
clause
mysql> SELECT * FROM groupby A LEFT JOIN
-> (
-> SELECT num, MAX(id) id
-> FROM groupby
-> GROUP BY num
-> ) B USING (id);
+----+------------+------------+
| id | num | num |
+----+------------+------------+
| 1 | 269529129 | NULL |
| 2 | 387090406 | NULL |
| 3 | 1126864683 | NULL |
| 4 | 411160755 | NULL |
| 5 | 29173595 | NULL |
| 6 | 266349579 | NULL |
| 7 | 1244227156 | NULL |
| 8 | 6231766 | NULL |
| 9 | 269529129 | 269529129 |
| 10 | 387090406 | 387090406 |
| 11 | 1126864683 | 1126864683 |
| 12 | 411160755 | 411160755 |
| 13 | 29173595 | 29173595 |
| 14 | 266349579 | 266349579 |
| 15 | 1244227156 | 1244227156 |
| 16 | 6231766 | 6231766 |
+----+------------+------------+
16 rows in set (0.00 sec)
mysql>
STEP 03 : Use LEFT JOIN
with a WHERE
clause
mysql> SELECT * FROM groupby A LEFT JOIN
-> (
-> SELECT num, MAX(id) id
-> FROM groupby
-> GROUP BY num
-> ) B USING (id) WHERE B.num IS NOT NULL;
+----+------------+------------+
| id | num | num |
+----+------------+------------+
| 16 | 6231766 | 6231766 |
| 13 | 29173595 | 29173595 |
| 14 | 266349579 | 266349579 |
| 9 | 269529129 | 269529129 |
| 10 | 387090406 | 387090406 |
| 12 | 411160755 | 411160755 |
| 11 | 1126864683 | 1126864683 |
| 15 | 1244227156 | 1244227156 |
+----+------------+------------+
8 rows in set (0.00 sec)
mysql>
ANALYSIS
Looking at the aforementioned results, here are two questions:
- Why does a
LEFT JOIN
keep an ordering by id
?
- Why in the world did using a
WHERE
impose a reordering ?
- Was it during the JOIN phase ?
- Did the Query Optimizer look ahead at the ordering of the subquery or ignore it ?
No one foresaw any of these effects because the behavior of explicit clauses was relied upon by the implicit behavior of the Query Optimizer.
CONCLUSION
From my perspective, corner cases can only be of an external nature. In light of this, developers must be willing to fully evaluate the results of a GROUP BY
in conjunction with the following twelve(12) aspects:
- aggregate functions
- subquery usage
JOINs
clauses
WHERE
clauses
- sort order of results with no explicit
ORDER BY
clause
- query results using older GA releases of MySQL
- query results using newer beta releases of MySQL
- the current SQL_MODE setting in
my.cnf
- the operating system the code was compiled for
- possibly the size of join_buffer_size with respect to its effect on the Query Optimizer
- possibly the size of sort_buffer_size with respect to its effect on the Query Optimizer
- possibly the storage engine being used (MyISAM vs InnoDB)
Here is the key thing to remember : Any instance of MySQL that works for your query in a specific environment is itself a corner case. Once you change one or more of the twelve(12) evaluation aspects, the corner case is due to break, especially given the first nine(9) aspects.
Best Answer
IMHO your first query should throw the same error message.
But you can move
json_agg
to a subquery instead of joining both tables, then you can easily limit the number of returned rows.db<>fiddle here