I am new to MySQL, and trying to using MySQL on the project, basically was tracking players performance.
Below is the table fields.
+-------------------+----------------------+-------------------+------+-----+---------+----------------+---------------------------------+---------+
| Field | Type | Collation | Null | Key | Default | Extra | Privileges | Comment |
+-------------------+----------------------+-------------------+------+-----+---------+----------------+---------------------------------+---------+
| unique_id | int(11) | NULL | NO | PRI | NULL | auto_increment | select,insert,update,references | |
| record_time | datetime | NULL | NO | | NULL | | select,insert,update,references | |
| game_sourceid | char(20) | latin1_swedish_ci | NO | MUL | NULL | | select,insert,update,references | |
| game_number | smallint(6) | NULL | NO | | NULL | | select,insert,update,references | |
| game_difficulty | char(12) | latin1_swedish_ci | NO | MUL | NULL | | select,insert,update,references | |
| cost_time | smallint(5) unsigned | NULL | NO | MUL | NULL | | select,insert,update,references | |
| country | char(3) | latin1_swedish_ci | NO | | NULL | | select,insert,update,references | |
| source | char(7) | latin1_swedish_ci | NO | | NULL | | select,insert,update,references | |
+-------------------+----------------------+-------------------+------+-----+---------+----------------+---------------------------------+---------+
and I have adding game_sourceid and game_difficulty as index and the engine is innodb.
I have insert about 11m rows of test data into this table, which is generated randomly but resembles the real data.
Basically the mostly query was like this, to get the average time and best time for a specific game_sourceid
SELECT avg(cost_time) AS avgtime
, min(cost_time) AS mintime
, count(*) AS count
FROM statistics_work_table
WHERE game_sourceid = 'standard_easy_1';
+-----------+---------+--------+
| avgtime | mintime | count |
+-----------+---------+--------+
| 1681.2851 | 420 | 138034 |
+-----------+---------+--------+
1 row in set (4.97 sec)
and the query took about 5s
I have googled about this and someone said that may caused by the amout of query count, so I am trying to narrow down the scope like this
SELECT avg(cost_time) AS avgtime
, min(cost_time) AS mintime
, count(*) AS count
FROM statistics_work_table
WHERE game_sourceid = 'standard_easy_1'
AND record_time > '2015-11-19 04:40:00';
+-----------+---------+-------+
| avgtime | mintime | count |
+-----------+---------+-------+
| 1275.2222 | 214 | 9 |
+-----------+---------+-------+
1 row in set (4.46 sec)
As you can see the 9 rows data also took about 5s, so i think it's not the problem about the query count.
The test data was generated randomly to simulate the real user's activity, so the data was discontinuous, so i added more continuous data(about 250k) with the same game_sourceid='standard_easy_9' but keep all others randomly, in other words the last 250k rows in this table has the same game_sourceid. And i'm trying to query like this:
SELECT avg(cost_time) AS avgtime
, min(cost_time) AS mintime
, count(*) AS count
FROM statistics_work_table
WHERE game_sourceid = 'standard_easy_9';
+-----------+---------+--------+
| avgtime | mintime | count |
+-----------+---------+--------+
| 1271.4806 | 70 | 259379 |
+-----------+---------+--------+
1 row in set (0.40 sec)
This time the query magically took only 0.4s, that's totally beyond my expectations.
So here's the question, the data was retrived from the player at real time, so it must be randomly and discontinuous.
I am thinking of separating the data into multiple tables by the game_sourceid, but it will take another 80 tables for that, maybe more in the future.
Since I am new to MySQL, I am wondering if there are any other solutions for this, or just my query was too bad.
Update: Here's the index of my table
mysql> show index from statistics_work_table;
+-----------------------+------------+-------------------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+-----------------------+------------+-------------------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| statistics_work_table | 0 | PRIMARY | 1 | unique_id | A | 11362113 | NULL | NULL | | BTREE | | |
| statistics_work_table | 1 | GameSourceId_CostTime | 1 | game_sourceid | A | 18 | NULL | NULL | | BTREE | | |
| statistics_work_table | 1 | GameSourceId_CostTime | 2 | cost_time | A | 344306 | NULL | NULL | | BTREE | | |
+-----------------------+------------+-------------------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
ALTER TABLE `statistics_work_table`
ADD INDEX `GameSourceId_CostTime` (`game_sourceid`,`cost_time`)
This index should make your queries super fast. Also, after you run the above statement, you should drop the single column index you have on game_sourceid, as the above will make the single column one redundant. (Which will hurt insert speed.)
The reason your queries are slow is because the database is using your single column index on game_sourceid, finding the rows, and then, for each row, using the primary key that is stored along with the index to find the main clustered index (aka primary key in this, and most cases), and then looking up the cost_time value. This is referred to as a double lookup, and it is something you want to avoid.
The index I provided above is called a "covering index". It allows your query to use ONLY the index, and so you only need a single lookup per row, greatly improving performance.
Related
i have a performance problem in MySQL.
I have a table with 215000 rows (InnoDB Engine) inserted in it and to execute the function SUM() on one column for only 1254 rows is taking 500ms.
The version i am using is : MySQL 5.7.32
The computer specs are the following:
Core I5 3.0 Ghz
8 Gb Ram
Solid State Drive
Here i leave information about the structure of the database:
mysql> select count(*) from cuenta_corriente;
+----------+
| count(*) |
+----------+
| 214514 |
+----------+
mysql> describe cuenta_corriente;
+-----------------------+-------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-----------------------+-------------+------+-----+---------+----------------+
| ID_CUENTA_CORRIENTE | int(11) | NO | PRI | NULL | auto_increment |
| ID_CLIENTE | int(11) | YES | MUL | NULL | |
| ID_PROVEEDOR | int(11) | YES | MUL | NULL | |
| FECHA | varchar(50) | YES | MUL | NULL | |
| FECHA_FISCAL | varchar(50) | YES | | NULL | |
| ID_OPERACION | int(11) | YES | MUL | NULL | |
| ID_TIPO_OPERACION | int(11) | YES | MUL | NULL | |
| DEBE | double | YES | | 0 | |
| HABER | double | YES | | 0 | |
| TOTAL | double | YES | | 0 | |
| SALDO_ANTERIOR | double | YES | | 0 | |
| SALDO_ACTUAL | double | YES | | 0 | |
| ID_OPERACION_ASOCIADA | int(11) | YES | | NULL | |
| ELIMINADO | int(11) | YES | | 0 | |
| ID_EMPLEADO | int(11) | NO | | 0 | |
+-----------------------+-------------+------+-----+---------+----------------+
show indexes from cuenta_corriente;
+------------+------------------------------------------------------------+
| Non_unique | Key_name Column_name |
+------------+------------------------------------------------------------+
| 0 | PRIMARY ID_CUENTA_CORRIENTE |
| 1 | IDX_CUENTA_CORRIENTE ID_CLIENTE |
| 1 | IX_cuenta_corriente_FECHA FECHA |
| 1 | IX_cuenta_corriente_ID_CLIENTE ID_CLIENTE |
| 1 | IX_cuenta_corriente_ID_PROVEEDOR ID_PROVEEDOR |
| 1 | IX_cuenta_corriente_ID_TIPO_OPERACION ID_TIPO_OPERACION |
| 1 | IX_cuenta_corriente_ID_OPERACION ID_OPERACION |
| 1 | IDX_cuenta_corriente_ID_OPERACION ID_OPERACION |
+------------+------------------------------------------------------------+
8 rows in set (0.00 sec)
The problem is with the folowing queries, in my opinion they are taking too long, considering that i have an index for the column ID_CLIENTE and that there are only 1254 rows with the ID_CLIENTE column = 19. Here are the query results:
mysql> SELECT COUNT(*) FROM CUENTA_CORRIENTE WHERE ID_CLIENTE = 19;
1254 rows
mysql> SELECT DEBE FROM CUENTA_CORRIENTE WHERE ID_CLIENTE = 19;
1254 rows - 0.513 sec
mysql> SELECT SUM(DEBE) FROM CUENTA_CORRIENTE WHERE ID_CLIENTE = 19;
0.582 sec
The strange thing is if i select all the columns instead selecting only the "DEBE" column, it takes less time:
mysql> SELECT * FROM CUENTA_CORRIENTE WHERE ID_CLIENTE = 19;
0.095 sec
Can anyone help me to improve the performance?
You can make just that query fast by creating a composite index to support it.
ie:
CREATE INDEX IDX_QUERY_FAST ON cuenta_corriente (ID_CLIENTE, DEBE)
But don't forget, each index has to be maintained, so it slows down any inserts into the table, so you don't want 200 indexes supporting every possible query.
With the existing index, the engine should be smart enough to identify the 1200 rows you care about using the index, but then it has to go read all the table records (across however many pages) that have the individual rows to get the DEBE column.
Add this index to help most of the queries you have shown:
INDEX(ID_CLIENTE, DEBE)
and drop INDEX(ID_CLIENTE) if you have such.
Are all of your secondary indexes starting with the PRIMARY KEY?? (The names imply such; please provide SHOW CREATE TABLE to definitively say what columns are in each index.) Don't start an index with the PK; it is likely to be useless.
Run EXPLAIN SELECT ... to see which index a query uses.
When timing a query, run it twice. The first run may spend extra time loading index or data rows into cache (in RAM in the buffer_pool); the second run may be significantly faster because of the caching.
I have this query:
SELECT
*
FROM
`av_cita`
JOIN `av_cita_cstm` ON (
(
`av_cita`.`id` = `av_cita_cstm`.`id_c`
)
)
WHERE
av_cita.deleted = 0
This query takes over 120 seconds to finish, yet I have added all indexes.
When I ask for the execution plan:
explain SELECT * FROM `av_cita`
JOIN `av_cita_cstm` ON ( ( `av_cita`.`id` = `av_cita_cstm`.`id_c` ) )
WHERE av_cita.deleted = 0;
I get this:
+----+-------------+--------------+--------+----------------------+---------+---------+---------------------------+--------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+--------------+--------+----------------------+---------+---------+---------------------------+--------+-------------+
| 1 | SIMPLE | av_cita | ALL | PRIMARY,delete_index | NULL | NULL | NULL | 192549 | Using where |
| 1 | SIMPLE | av_cita_cstm | eq_ref | PRIMARY | PRIMARY | 108 | rednacional_v2.av_cita.id | 1 | |
+----+-------------+--------------+--------+----------------------+---------+---------+---------------------------+--------+-------------+
delete_index is listed in the possible_keys column, but the key is null, and it doesn't use the index.
Table and index definitions:
+------------------+--------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+------------------+--------------+------+-----+---------+-------+
| id | char(36) | NO | PRI | NULL | |
| name | varchar(255) | YES | MUL | NULL | |
| date_entered | datetime | YES | MUL | NULL | |
| date_modified | datetime | YES | | NULL | |
| modified_user_id | char(36) | YES | | NULL | |
| created_by | char(36) | YES | MUL | NULL | |
| description | text | YES | | NULL | |
| deleted | tinyint(1) | YES | MUL | 0 | |
| assigned_user_id | char(36) | YES | MUL | NULL | |
+------------------+--------------+------+-----+---------+-------+
+---------+------------+--------------------+--------------+------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+---------+------------+--------------------+--------------+------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| av_cita | 0 | PRIMARY | 1 | id | A | 192786 | NULL | NULL | | BTREE | | |
| av_cita | 1 | delete_index | 1 | deleted | A | 2 | NULL | NULL | YES | BTREE | | |
| av_cita | 1 | name_index | 1 | name | A | 96393 | NULL | NULL | YES | BTREE | | |
| av_cita | 1 | date_entered_index | 1 | date_entered | A | 96393 | NULL | NULL | YES | BTREE | | |
| av_cita | 1 | created_by | 1 | created_by | A | 123 | NULL | NULL | YES | BTREE | | |
| av_cita | 1 | assigned_user_id | 1 | assigned_user_id | A | 1276 | NULL | NULL | YES | BTREE | | |
| av_cita | 1 | deleted_id | 1 | deleted | A | 2 | NULL | NULL | YES | BTREE | | |
| av_cita | 1 | deleted_id | 2 | id | A | 192786 | NULL | NULL | | BTREE | | |
| av_cita | 1 | id | 1 | id | A | 192786 | NULL | NULL | | BTREE | | |
+---------+------------+--------------------+--------------+------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
How can I improve the performance of this query?
The query is losing time on making the join. I would strongly suggest to create and index on av_cita_cstm.id_c. Then the plan will probably be changed to use that index for the av_cita_cstm table, which is much better than PRIMARY. As a consequence PRIMARY will be used on ac_cita.
I think that will bring a big improvement. You might still get more improvement if you make sure delete_index is defined with two fields: (deleted, id), and then move the where condition of the SQL statement into the join condition. But I am not sure MySql will see this as a possibility.
The index on deleted is not used probably because the optimizer has decided that a full table-scan is cheaper than using the index. MySQL tends to make this decision if the value you search for is found on about 20% or more of the rows in the table.
By analogy, think of the index at the back of a book. You can understand why common words like "the" aren't indexed. It would be easier to just read the book cover-to-cover than to flip back and forth to the index, which only tells you that "the" appears on a majority of pages.
If you think MySQL has made the wrong decision, you can make it pretend that a table-scan is more expensive than using a specific index:
SELECT
*
FROM
`av_cita` FORCE INDEX (deleted_index)
JOIN `av_cita_cstm` ON (
(
`av_cita`.`id` = `av_cita_cstm`.`id_c`
)
)
WHERE
av_cita.deleted = 0
Read http://dev.mysql.com/doc/refman/5.7/en/index-hints.html for more information about index hints. Don't overuse index hints, they're useful only in rare cases. Most of the time the optimizer makes the right decision.
Your EXPLAIN plan shows that your join to av_cita_cstm is already using a unique index (the clue is "type: eq_ref" and also the "rows: 1"). I don't think any new index is needed in that table.
I notice the EXPLAIN shows that the table-scan on av_cita scans about an estimated 192549 rows. I'm really surprised that this takes 120 seconds. On any reasonably powerful computer, that should run much faster.
That makes me wonder if you have something else that needs tuning or configuration on this server:
What other processes are running on the server? A lot of applications, perhaps? Are the other processes also running slowly on this server? Do you need to increase the power of the server, or move applications onto their own server?
If you're on MySQL 5.7, try querying the sys schema: this:
select * from sys.innodb_buffer_stats_by_table
where object_name like 'av_cita%';
Are there other costly SQL queries running concurrently?
Did you under-allocate MySQL's innodb_buffer_pool_size? If it's too small, it could be furiously recycling pages in RAM as it scans your table.
select ##innodb_buffer_pool_size;
Did you over-allocate innodb_buffer_pool_size? Once I helped tune a server that was running very slowly. It turned out they had a 4GB buffer pool, but only 1GB of physical RAM. The operating system was swapping like crazy, causing everything to run slowly.
Another thought: You have shown us the columns in av_cita, but not the table structure for av_cita_cstm. Why are you fetching SELECT *? Do you really need all the columns? Are there huge BLOB/TEXT columns in the latter table? If so, it could be reading a large amount of data from disk that you don't need.
When you ask SQL questions, it would help if you run
SHOW CREATE TABLE av_cita\G
SHOW TABLE STATUS LIKE 'av_cita'\G
And also run the same commands for the other table av_cita_cstm, and include the output in your question above.
This is table structure:
+--------------+--------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+--------------+--------------+------+-----+---------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| visitor_hash | varchar(40) | YES | MUL | NULL | |
| uri | varchar(255) | YES | | NULL | |
| ip_address | char(15) | YES | MUL | NULL | |
| last_visit | datetime | YES | | NULL | |
| visits | int(11) | NO | | NULL | |
| object_app | varchar(255) | YES | MUL | NULL | |
| object_model | varchar(255) | YES | | NULL | |
| object_id | varchar(255) | YES | | NULL | |
| blocked | tinyint(1) | NO | | NULL | |
+--------------+--------------+------+-----+---------+----------------+
This is request:
SELECT `object_id`
FROM `visits_visit`
WHERE `object_model` = 'News'
GROUP BY `object_id`
ORDER BY COUNT( * ) DESC
LIMIT 0, 3
Time for response is ~77,63 ms.
CREATE INDEX resource_model ON visits_visit (object_model(100));
After this request the time for response increased to ~150ms.
How to improve performance for this case? Thank you.
UPDATED:
Answering to Michal Komorowski.
This is explain before index:
+----+-------------+--------------+------+---------------+------+---------+------+--------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+--------------+------+---------------+------+---------+------+--------+----------------------------------------------+
| 1 | SIMPLE | visits_visit | ALL | NULL | NULL | NULL | NULL | 142938 | Using where; Using temporary; Using filesort |
+----+-------------+--------------+------+---------------+------+---------+------+--------+----------------------------------------------+
1 row in set (0.00 sec)
And this is after index:
+----+-------------+--------------+------+----------------+----------------+---------+-------+-------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+--------------+------+----------------+----------------+---------+-------+-------+----------------------------------------------+
| 1 | SIMPLE | visits_visit | ref | resource_model | resource_model | 303 | const | 64959 | Using where; Using temporary; Using filesort |
+----+-------------+--------------+------+----------------+----------------+---------+-------+-------+----------------------------------------------+
1 row in set (0.00 sec)
I don't know what gives me this information.
SELECT `object_id`
FROM `visits_visit`
WHERE `object_model` = 'News'
GROUP BY `object_id`
ORDER BY COUNT( * ) DESC
LIMIT 0, 3
78,85 ms before indexing and 365,59 ms after indexing.
Also i have index
CREATE INDEX resource ON visits_visit (object_app(100), object_model(100), object_id(100));
But i need this one, because in other select queries WHERE contains this three keys.
UPDATE:
I'm using django debug toolbar to test performance of requests.
UPDATE:
Query:
ANALYZE TABLE visits_visit;
Output:
+-----------------------------+---------+----------+-----------------------------+
| Table | Op | Msg_type | Msg_text |
+-----------------------------+---------+----------+-----------------------------+
| **************.visits_visit | analyze | status | Table is already up to date |
+-----------------------------+---------+----------+-----------------------------+
1 row in set (0.00 sec)
UPDATE:
SHOW INDEXES FROM visits_visit;
Output:
+--------------+------------+-----------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+--------------+------------+-----------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| visits_visit | 0 | PRIMARY | 1 | id | A | 142938 | NULL | NULL | | BTREE | | |
| visits_visit | 1 | visits_visit_0880babc | 1 | visitor_hash | A | 142938 | NULL | NULL | YES | BTREE | | |
| visits_visit | 1 | visits_visit_5325a746 | 1 | ip_address | A | 142938 | NULL | NULL | YES | BTREE | | |
| visits_visit | 1 | resource | 1 | object_app | A | 1 | 100 | NULL | YES | BTREE | | |
| visits_visit | 1 | resource | 2 | object_model | A | 3 | 100 | NULL | YES | BTREE | | |
| visits_visit | 1 | resource | 3 | object_id | A | 959 | 100 | NULL | YES | BTREE | | |
+--------------+------------+-----------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
It seems to me that although you have an index, MySQL doesn't know how to use it properly. It happens when information about data distribution (statistics) within a table are not up to date. In order to update them you should call ANALYZE TABLE visits_visit and then check results.
I was confused by misunderstanding of sql mechanisms, so i decided to create model Popular and save instances in it every 24 hours. Thanks to everyone, who tried to help.
As I said in your other question, Prefix indexes are virtually useless; don't use them except in rare circumstances.
Shrink the fields to reasonable lengths and you won't be tempted to use Prefix indexes.
The optimal index for that query is INDEX(object_model, object_id). Attempting to use INDEX(object_model(##), ...) will not get past object_model to anything after it.
If object_model is things like 'News', I suspect the other possible values are short, and perhaps there is a finite number of models. For "short" change to some smaller VARCHAR. For "finite", consider using ENUM('News', 'Weather', 'Sports', ...).
As for why it took longer after indexing...
Without the index, the Optimizer had no choice but to scan the entire table. This is a simple linear scan. It would read but not count any non-News rows.
With the index, the Optimizer has the additional choice of using the index. But, perhaps most rows are News? Well, it would scan the index (nice), but for each News item in the index, it would have to look up the row to get object_id (not so nice). It seems (from the timings) that the latter is less efficient.
By shrinking the declarations and using INDEX(object_model, object_id) (in this order), the query can be performed in the index. Think of the index as a mini-table with just those two columns in it. It is smaller. It is ordered by model, so it only needs to scan the 'News' part. The explain will show this "covering" by saying "Using index".
If all cases, the GROUP BY adds some overhead -- either keeping a hash of object_id in RAM or by saving intermediate results and sorting them. Then the ORDER BY requires a sort (or a priority hash) before the LIMIT can apply.
I'm trying to calculate maximum simultaneous calls. My query, which I believe to be accurate, takes way too long given ~250,000 rows. The cdrs table looks like this:
+---------------+-----------------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+---------------+-----------------------+------+-----+---------+----------------+
| id | bigint(20) unsigned | NO | PRI | NULL | auto_increment |
| CallType | varchar(32) | NO | | NULL | |
| StartTime | datetime | NO | MUL | NULL | |
| StopTime | datetime | NO | | NULL | |
| CallDuration | float(10,5) | NO | | NULL | |
| BillDuration | mediumint(8) unsigned | NO | | NULL | |
| CallMinimum | tinyint(3) unsigned | NO | | NULL | |
| CallIncrement | tinyint(3) unsigned | NO | | NULL | |
| BasePrice | float(12,9) | NO | | NULL | |
| CallPrice | float(12,9) | NO | | NULL | |
| TransactionId | varchar(20) | NO | | NULL | |
| CustomerIP | varchar(15) | NO | | NULL | |
| ANI | varchar(20) | NO | | NULL | |
| ANIState | varchar(10) | NO | | NULL | |
| DNIS | varchar(20) | NO | | NULL | |
| LRN | varchar(20) | NO | | NULL | |
| DNISState | varchar(10) | NO | | NULL | |
| DNISLATA | varchar(10) | NO | | NULL | |
| DNISOCN | varchar(10) | NO | | NULL | |
| OrigTier | varchar(10) | NO | | NULL | |
| TermRateDeck | varchar(20) | NO | | NULL | |
+---------------+-----------------------+------+-----+---------+----------------+
I have the following indexes:
+-------+------------+-----------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+-------+------------+-----------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| cdrs | 0 | PRIMARY | 1 | id | A | 269622 | NULL | NULL | | BTREE | | |
| cdrs | 1 | id | 1 | id | A | 269622 | NULL | NULL | | BTREE | | |
| cdrs | 1 | call_time_index | 1 | StartTime | A | 269622 | NULL | NULL | | BTREE | | |
| cdrs | 1 | call_time_index | 2 | StopTime | A | 269622 | NULL | NULL | | BTREE | | |
+-------+------------+-----------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
The query I am running is this:
SELECT MAX(cnt) AS max_channels FROM
(SELECT cl1.StartTime, COUNT(*) AS cnt
FROM cdrs cl1
INNER JOIN cdrs cl2
ON cl1.StartTime
BETWEEN cl2.StartTime AND cl2.StopTime
GROUP BY cl1.id)
AS counts;
It seems like I might have to chunk this data for each day and store the results in a separate table like simultaneous_calls.
I'm sure you want to know not only the maximum simultaneous calls, but when that happened.
I would create a table containing the timestamp of every individual minute
CREATE TABLE times (ts DATETIME UNSIGNED AUTO_INCREMENT PRIMARY KEY);
INSERT INTO times (ts) VALUES ('2014-05-14 00:00:00');
. . . until 1440 rows, one for each minute . . .
Then join that to the calls.
SELECT ts, COUNT(*) AS count FROM times
JOIN cdrs ON times.ts BETWEEN cdrs.starttime AND cdrs.stoptime
GROUP BY ts ORDER BY count DESC LIMIT 1;
Here's the result in my test (MySQL 5.6.17 on a Linux VM running on a Macbook Pro):
+---------------------+----------+
| ts | count(*) |
+---------------------+----------+
| 2014-05-14 10:59:00 | 1001 |
+---------------------+----------+
1 row in set (1 min 3.90 sec)
This achieves several goals:
Reduces the number of rows examined by two orders of magnitude.
Reduces the execution time from 3 hours+ to about 1 minute.
Also returns the actual timestamp when the highest count was found.
Here's the EXPLAIN for my query:
explain select ts, count(*) from times join cdrs on times.ts between cdrs.starttime and cdrs.stoptime group by ts order by count(*) desc limit 1;
+----+-------------+-------+-------+---------------+---------+---------+------+--------+------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+---------+---------+------+--------+------------------------------------------------+
| 1 | SIMPLE | times | index | PRIMARY | PRIMARY | 5 | NULL | 1440 | Using index; Using temporary; Using filesort |
| 1 | SIMPLE | cdrs | ALL | starttime | NULL | NULL | NULL | 260727 | Range checked for each record (index map: 0x4) |
+----+-------------+-------+-------+---------------+---------+---------+------+--------+------------------------------------------------+
Notice the figures in the rows column, and compare to the EXPLAIN of your original query. You can estimate the total number of rows examined by multiplying these together (but that gets more complicated if your query is anything other than SIMPLE).
The inline view isn't strictly necessary. (You're right about a lot of time to run the EXPLAIN on the query with the inline view, the EXPLAIN will materialize the inline view (i.e. run the inline view query and populate the derived table), and then give an EXPLAIN on the outer query.
Note that this query will return an equivalent result:
SELECT COUNT(*) AS max_channels
FROM cdrs cl1
JOIN cdrs cl2
ON cl1.StartTime BETWEEN cl2.StartTime AND cl2.StopTime
GROUP BY cl1.id
ORDER BY max_channels DESC
LIMIT 1
Though it still has to do all the work, and probably doesn't perform any better; the EXPLAIN should run a lot faster. (We expect to see "Using temporary; Using filesort" in the Extra column.)
The number of rows in the resultset is going to be the number of rows in the table (~250,000 rows), and those are going to need to be sorted, so that's going to be some time there. The bigger issue (my gut is telling me) is that join operation.
I'm wondering if the EXPLAIN (or performance) would be any different if you swapped the cl1 and cl2 in the predicate, i.e.
ON cl2.StartTime BETWEEN cl1.StartTime AND cl1.StopTime
I'm thinking that, just because I'd be tempted to try a correlated subquery. That's ~250,000 executions, and that's not likely going to be any faster...
SELECT ( SELECT COUNT(*)
FROM cdrs cl2
WHERE cl2.StartTime BETWEEN cl1.StartTime AND cl1.StopTime
) AS max_channels
, cl1.StartTime
FROM cdrs cl1
ORDER BY max_channels DESC
LIMIT 11
You could run an EXPLAIN on that, we're still going to see a "Using temporary; Using filesort", and it will also show the "dependent subquery"...
Obviously, adding a predicate on the cl1 table to cut down the number of rows to be returned (for example, checking only the past 15 days); that should speed things up, but it doesn't get you the answer you want.
WHERE cl1.StartTime > NOW() - INTERVAL 15 DAY
(None of my musings here are sure-fire answers to your question, or solutions to the performance issue; they're just musings.)
I have a database of 5m rows and it grows and it's getting harder and harder to do operations with it.
Is it a good idea to split the table in 10 tables (v0_table, v1_table... v9_table), where the number(v*) is the first number of the user's id?
The user's id in my case are not auto-increment so it would sort the data evenly across those 10 tables.
The problem is I have never done similar things....
Can anyone spot any disadvantages?
EDIT:
I would appreciate any help with tuning the structure or the query.
So the slowest query is the following one:
SELECT logos.user,
logos.date,
logos.level,
logos.title,
Count(guesses.id),
Sum(guesses.points)
FROM logos
LEFT JOIN guesses
ON guesses.user = '".$user['uid']."'
AND guesses.done = '1'
AND guesses.logo = logos.id
WHERE open = '1'
GROUP BY level
Where guesses table:
+--------+------------+------+-----+-------------------+----------------+
| Field | Type | Null | Key | Default | Extra |
+--------+------------+------+-----+-------------------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| logo | int(11) | NO | MUL | NULL | |
| user | int(11) | NO | MUL | NULL | |
| date | timestamp | NO | | CURRENT_TIMESTAMP | |
| points | int(4) | YES | MUL | 100 | |
| done | tinyint(1) | NO | MUL | 0 | |
+--------+------------+------+-----+-------------------+----------------+
LOGOS table:
+-------+--------------+------+-----+-------------------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-------+--------------+------+-----+-------------------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| name | varchar(100) | NO | | NULL | |
| img | varchar(222) | NO | MUL | NULL | |
| level | int(3) | NO | MUL | NULL | |
| date | timestamp | NO | MUL | CURRENT_TIMESTAMP | |
| user | int(11) | NO | MUL | NULL | |
| open | tinyint(1) | NO | MUL | 0 | |
+-------+--------------+------+-----+-------------------+----------------+
EXPLAIN:
+----+-------------+---------+------+----------------+------+---------+-------+------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+---------+------+----------------+------+---------+-------+------+----------------------------------------------+
| 1 | SIMPLE | logos | ref | open | open | 1 | const | 521 | Using where; Using temporary; Using filesort |
| 1 | SIMPLE | guesses | ref | done,user,logo | user | 4 | const | 87 | |
+----+-------------+---------+------+----------------+------+---------+-------+------+----------------------------------------------+
Your problem isn't that you have too much data, it's that this data is not properly indexed. Try adding an index:
CREATE INDEX open_level ON logos(open, level)
This should eliminate Using temporary; Using filesort on logos.
Basically, you need an index on this table for this query to cover two things: open - for WHERE open = '1' and level - for GROUP BY level in this order, as MySQL will first filter by open, then will group the results by level (implicitly sorting by it in process).
Short and sweet: No. This is never a good idea. Is your table properly indexed? Is MySQL properly tuned? Are your queries efficient? Are you using any caching?
Instead of sharding your table, you may want to examine other tables in your database to see if they can be split off into other dbs. For example tables, that are never joined to are great candidates for this type of vertical partitioning.
This allows you to optimize hardware for smaller sets of data.