Background
I made a small table of 10 rows from a previous SELECT already ran (SavedAnimals).
I have a massive table (animals) which I would like to UPDATE using the rows with the same id as each row in my new table.
What I have tried so far
I can quickly SELECT the desired rows from the big table like this:
mysql> EXPLAIN SELECT * FROM animals WHERE ignored=0 and id IN (SELECT animal_id FROM SavedAnimals);
+------+--------------+-------------------------------+--------+---------------+---------+---------+----------------------------------------------------------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+------+--------------+-------------------------------+--------+---------------+---------+---------+----------------------------------------------------------+------+-------------+
| 1 | PRIMARY | <subquery2> | ALL | distinct_key | NULL | NULL | NULL | 10 | |
| 1 | PRIMARY | animals | eq_ref | PRIMARY | PRIMARY | 8 | db_staging.SavedAnimals.animal_id | 1 | Using where |
| 2 | MATERIALIZED | SavedAnimals | ALL | NULL | NULL | NULL | NULL | 10 | |
+------+--------------+-------------------------------+--------+---------------+---------+---------+----------------------------------------------------------+------+-------------+
But the "same" command on the UPDATE is not quick:
mysql> EXPLAIN UPDATE animals SET ignored=1, ignored_when=CURRENT_TIMESTAMP WHERE ignored=0 and id IN (SELECT animal_id FROM SavedAnimals);
+------+--------------------+-------------------------------+-------+---------------+---------+---------+------+----------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+------+--------------------+-------------------------------+-------+---------------+---------+---------+------+----------+-------------+
| 1 | PRIMARY | animals | index | NULL | PRIMARY | 8 | NULL | 34269464 | Using where |
| 2 | DEPENDENT SUBQUERY | SavedAnimals | ALL | NULL | NULL | NULL | NULL | 10 | Using where |
+------+--------------------+-------------------------------+-------+---------------+---------+---------+------+----------+-------------+
2 rows in set (0.00 sec)
The UPDATE command never finishes if I run it.
QUESTION
How do I make mariaDB run with the Materialized select_type on the UPDATE like it does on the SELECT?
OR
Is there a totally separate way that I should approach this which would be quick?
Notes
Version: 10.3.23-MariaDB-log
Use JOIN rather than WHERE...IN. MySQL tends to optimize them better.
UPDATE animals AS a
JOIN SavedAnimals AS sa ON a.id = sa.animal_id
SET a.ignored=1, a.ignored_when=CURRENT_TIMESTAMP
WHERE a.ignored = 0
You should find an EXISTS clause more efficient than an IN clause. For example:
UPDATE animals a
SET a.ignored = 1,
a.ignored_when = CURRENT_TIMESTAMP
WHERE a.ignored = 0
AND EXISTS (SELECT * FROM SavedAnimals sa WHERE sa.animal_id = a.id)
Related
There is one huge table which is having 25M records and when we try to delete the records by manually passing the value it is using the INDEX and query is executing faster.
Below are details.
MySQL [(none)]> explain DELETE FROM isca51410_octopus_prod_eai.WMSERVICE WHERE contextid in ('1121','1245','5432','12412','1212','7856','2342','1345','5312','2342','3432','5321');
+----+-------------+-----------+------------+-------+---------------+-------------+---------+-------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+-------+---------------+-------------+---------+-------+------+----------+-------------+
| 1 | DELETE | BIG_TABLE | NULL | range | IDX_BIG_CID | IDX_BIG_CID | 109 | const | 12 | 100.00 | Using where |
+----+-------------+-----------+------------+-------+---------------+-------------+---------+-------+------+----------+-------------+
But when we try to pass the values by using select query it is not using index and query is executing for more time.
Below is the explain plan.
MySQL [(none)]> explain DELETE FROM DATABASE1_1.BIG_TABLE WHERE contextid in (SELECT contextid FROM DATABASE_2.TABLE_2);
+----+--------------------+------------------+------------+------+---------------+------+---------+------+----------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+--------------------+------------------+------------+------+---------------+------+---------+------+----------+----------+-------------+
| 1 | DELETE | BIG_TABLE | NULL | ALL | NULL | NULL | NULL | NULL | 25730673 | 100.00 | Using where |
| 2 | DEPENDENT SUBQUERY | TABLE_2 | NULL | ALL | NULL | NULL | NULL | NULL | 10 | 10.00 | Using where |
+----+--------------------+------------------+------------+------+---------------+------+---------+------+----------+----------+-------------+
Here DATABASE_2.TABLE_2 is a table where the values will change everytime and row count will be less than 100.
How to make use of index IDX_BIG_CID on table DATABASE1_1.BIG_TABLE for the below query
DELETE FROM DATABASE1_1.BIG_TABLE WHERE contextid in (SELECT contextid FROM DATABASE_2.TABLE_2);
Don't use IN ( SELECT ... ). Use a multi-table DELETE. (See the ref manual.)
I have a working, nice, indexed SQL query aggregating notes (sum of ints) for all my users and others stuffs. This is "query A".
I want to use this aggregated notes in others queries, say "query B".
If I create a View based on "query A", will the indexes of the original query will be used when needed if I join it in "query B" ?
Is that true for MySQL ? For others flavors of SQL ?
Thanks.
In MySQL, you cannot create an index on a view. MySQL uses indexes of the underlying tables when you query data against the views that use the merge algorithm. For the views that use the temptable algorithm, indexes are not utilized when you query data against the views.
https://www.percona.com/blog/2007/08/12/mysql-view-as-performance-troublemaker/
Here's a demo table. It has a userid attribute column and a note column.
mysql> create table t (id serial primary key, userid int not null, note int, key(userid,note));
If you do an aggregation to get the sum of note per userid, it does an index-scan on (userid, note).
mysql> explain select userid, sum(note) from t group by userid;
+----+-------------+-------+-------+---------------+--------+---------+------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+--------+---------+------+------+-------------+
| 1 | SIMPLE | t | index | userid | userid | 9 | NULL | 1 | Using index |
+----+-------------+-------+-------+---------------+--------+---------+------+------+-------------+
1 row in set (0.00 sec)
If we create a view for the same query, then we can see that querying the view uses the same index on the underlying table. Views in MySQL are pretty much like macros — they just query the underlying table.
mysql> create view v as select userid, sum(note) from t group by userid;
Query OK, 0 rows affected (0.03 sec)
mysql> explain select * from v;
+----+-------------+------------+-------+---------------+--------+---------+------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+-------+---------------+--------+---------+------+------+-------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 2 | NULL |
| 2 | DERIVED | t | index | userid | userid | 9 | NULL | 1 | Using index |
+----+-------------+------------+-------+---------------+--------+---------+------+------+-------------+
2 rows in set (0.00 sec)
So far so good.
Now let's create a table to join with the view, and join to it.
mysql> create table u (userid int primary key, name text);
Query OK, 0 rows affected (0.09 sec)
mysql> explain select * from v join u using (userid);
+----+-------------+------------+-------+---------------+-------------+---------+---------------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+-------+---------------+-------------+---------+---------------+------+-------------+
| 1 | PRIMARY | u | ALL | PRIMARY | NULL | NULL | NULL | 1 | NULL |
| 1 | PRIMARY | <derived2> | ref | <auto_key0> | <auto_key0> | 4 | test.u.userid | 2 | NULL |
| 2 | DERIVED | t | index | userid | userid | 9 | NULL | 1 | Using index |
+----+-------------+------------+-------+---------------+-------------+---------+---------------+------+-------------+
3 rows in set (0.01 sec)
I tried to use hints like straight_join to force it to read v then join to u.
mysql> explain select * from v straight_join u on (v.userid=u.userid);
+----+-------------+------------+-------+---------------+--------+---------+------+------+----------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+-------+---------------+--------+---------+------+------+----------------------------------------------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 7 | NULL |
| 1 | PRIMARY | u | ALL | PRIMARY | NULL | NULL | NULL | 1 | Using where; Using join buffer (Block Nested Loop) |
| 2 | DERIVED | t | index | userid | userid | 9 | NULL | 7 | Using index |
+----+-------------+------------+-------+---------------+--------+---------+------+------+----------------------------------------------------+
"Using join buffer (Block Nested Loop)" is MySQL's terminology for "no index used for the join." It's just looping over the table the hard way -- by reading batches of rows from start to finish of the table.
I tried to use force index to tell MySQL that type=ALL is to be avoided.
mysql> explain select * from v straight_join u force index(PRIMARY) on (v.userid=u.userid);
+----+-------------+------------+--------+---------------+---------+---------+----------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+--------+---------------+---------+---------+----------+------+-------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 7 | NULL |
| 1 | PRIMARY | u | eq_ref | PRIMARY | PRIMARY | 4 | v.userid | 1 | NULL |
| 2 | DERIVED | t | index | userid | userid | 9 | NULL | 7 | Using index |
+----+-------------+------------+--------+---------------+---------+---------+----------+------+-------------+
Maybe this is using an index for the join? But it's weird that table u is before table t in the EXPLAIN. I'm frankly not sure how to understand what it's doing, given the order of rows in this EXPLAIN report. I would expect the joined table should come after the primary table of the query.
I only put a few rows of data into each table. One might get some different EXPLAIN results with a larger representative sample of test data. I'll leave that to you to try.
SELECT id, name, detail FROM student WHERE id NOT IN (1,788,103,100) ORDER BY id DESC LIMIT 1000,10
The table is tiny (10,000 rows). I have to consider two point, "IN query" and "LIMIT query".
Here are the DDLs and the EXPLAIN. I'm using MySQL 5.6.4.
CREATE TABLE student
( id int(11) NOT NULL AUTO_INCREMENT
, name varchar(45) NOT NULL
, detail varchar(255) NOT NULL
, PRIMARY KEY (id)
) ENGINE = MyISAM;
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
| 1 | SIMPLE | student| ALL | Primary,id | NULL | NULL | NULL | 13 | |
The LIMIT and ORDER BY clauses mean that the query has to build the whole table and then order it and then go the record 1000 and then extract the next 10 records.
Why are you looking for 10 records starting at record 1000?
Removing the ORDER BY clause would make it faster as the query would only need to extract 1010 records.
I cannot replicate this finding...
SELECT VERSION();
+-----------+
| VERSION() |
+-----------+
| 5.5.16 |
+-----------+
SELECT COUNT(*) FROM student;
+----------+
| COUNT(*) |
+----------+
| 131072 |
+----------+
SELECT id
FROM student
WHERE id
NOT IN (1,788,103,100)
ORDER
BY id DESC
LIMIT 1000,10;
+--------+
| id |
+--------+
| 195591 |
| 195590 |
| 195589 |
| 195588 |
| 195587 |
| 195586 |
| 195585 |
| 195584 |
| 195583 |
| 195582 |
+--------+
10 rows in set (0.00 sec)
+----+-------------+---------+-------+---------------+---------+---------+------+--------+--------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+---------+-------+---------------+---------+---------+------+--------+--------------------------+
| 1 | SIMPLE | student | range | PRIMARY | PRIMARY | 4 | NULL | 131069 | Using where; Using index |
+----+-------------+---------+-------+---------------+---------+---------+------+--------+--------------------------+
When I add a second level of abstraction to a join, ie joining on a table that was join in the first place, the query time is be multiplied by 1000x
mysql> SELECT xxx.content.id, columns.stories.title, columns.stories.date
-> FROM xxx.content
-> LEFT JOIN columns.stories on xxx.content.contentable_id = columns.stories.id
-> WHERE columns.stories.title IS NOT NULL
-> AND xxx.content.contentable_type = 'PublisherStory';
yields results in 0.01 seconds
mysql> SELECT xxx.content.id, columns.photos.id as pid, columns.stories.title, columns.stories.date
-> FROM xxx.content
-> LEFT JOIN columns.stories on xxx.content.contentable_id = columns.stories.id
-> LEFT JOIN columns.photos on columns.stories.id = columns.photos.story_id
-> WHERE columns.stories.title IS NOT NULL
-> AND xxx.content.contentable_type = 'PublisherStory';
yields results in 14 seconds
this is being performed on tables with records in the 10ks to low 100ks of records
Is this normal or what could be causing such a slowdown?
first query plan:
+----+-------------+---------+--------+---------------+---------+---------+--------------------------------------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+---------+--------+---------------+---------+---------+--------------------------------------+------+-------------+
| 1 | SIMPLE | content | ALL | NULL | NULL | NULL | NULL | 7099 | Using where |
| 1 | SIMPLE | stories | eq_ref | PRIMARY | PRIMARY | 8 | xxx.content.contentable_id | 1 | Using where |
+----+-------------+---------+--------+---------------+---------+---------+--------------------------------------+------+-------------+
Second Query
+----+-------------+---------+--------+---------------+---------+---------+--------------------------------------+-------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+---------+--------+---------------+---------+---------+--------------------------------------+-------+-------------+
| 1 | SIMPLE | content | ALL | NULL | NULL | NULL | NULL | 7099 | Using where |
| 1 | SIMPLE | stories | eq_ref | PRIMARY | PRIMARY | 8 | xxx.content.contentable_id | 1 | Using where |
| 1 | SIMPLE | photos | ALL | NULL | NULL | NULL | NULL | 21239 | |
+----+-------------+---------+--------+---------------+---------+---------+--------------------------------------+-------+-------------+
if joining columns.photos slows down so much, it could be because :
photos.story_id is not a foreign key from stories and there is no index on that column.
Not seing your table structure, I could no tell exactly but I suggest you to
verify that photos.story_id is a foreign key and if your mysql version does not
support foreign key ( pretty old) put an index on that column.
I would check indexes on contentable_type and stories.title also as they are
part of the where close.
I am trying to optimize a query on a mysql table I've created. I expect that there will be many many rows in the table. Looking at this question the accepted answer and the top voted answer suggests two different approaches.
I wrote these two queries and want to know which one is more performant.
SELECT uv.*
FROM UserVisit uv INNER JOIN
(SELECT ID,MAX(visitDate) visitDate
FROM UserVisit GROUP BY ID) last
ON (uv.ID = last.ID AND uv.visitDate = last.visitDate);
Running this with EXPLAIN yields:
+----+-------------+------------+--------+---------------+---------+---------+--------------------------------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+--------+---------------+---------+---------+--------------------------------+------+-------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 2 | |
| 1 | PRIMARY | uv | eq_ref | PRIMARY | PRIMARY | 11 | last.playscanID,last.visitDate | 1 | |
| 2 | DERIVED | UserVisit | index | NULL | PRIMARY | 11 | NULL | 4 | Using index |
+----+-------------+------------+--------+---------------+---------+---------+--------------------------------+------+-------------+
3 rows in set (0.01 sec)
And the other query:
SELECT lastVisits.*
FROM ( SELECT * FROM UserVisit ORDER BY visitDate DESC ) lastVisits
GROUP BY lastVisits.ID
Running that with EXPLAIN yields:
+----+-------------+------------+------+---------------+------+---------+------+------+---------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+------+---------------+------+---------+------+------+---------------------------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 4 | Using temporary; Using filesort |
| 2 | DERIVED | UserVisit | ALL | NULL | NULL | NULL | NULL | 4 | Using filesort |
+----+-------------+------------+------+---------------+------+---------+------+------+---------------------------------+
2 rows in set (0.00 sec)
I am uncertain how to interpret the result of the two EXPLAINs.
Which of these queries can I expect to be faster and why?
EDIT:
This is the way UserVisit table looks:
+----------------+---------------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+----------------+---------------------+------+-----+---------+-------+
| ID | bigint(20) unsigned | NO | PRI | NULL | |
| visitDate | date | NO | PRI | NULL | |
| visitTime | time | NO | | NULL | |
| analysisResult | decimal(3,2) | NO | | NULL | |
+----------------+---------------------+------+-----+---------+-------+
4 rows in set (0.00 sec)
Firstly, you might want to read the manual on EXPLAIN. It's a dense read, but it should provide most of the information you want.
Secondly, as Strawberry says, the second query works by accident. The behaviour may change in future versions, and your query would not return an error, just different data. That's nearly always a bad thing.
Finally, the EXPLAIN suggests that version 1 will be faster. In EXTRA, it's saying it's using an index, which is much faster than filesort. Without a schema, it's hard to be sure, but I think you will also benefit from a compound key on ID and visitdate.