MySQL query very slow. Count(*) on indexed column - mysql

The table is in InnoDB table. Here is some information that might be helpful.
EXPLAIN SELECT COUNT(*) AS y0_ FROM db.table this_ WHERE this_.id IS NOT NULL;
+----+-------------+-------+-------+---------------+---------+---------+------+---------+--------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+---------+---------+------+---------+--------------------------+
| 1 | SIMPLE | this_ | index | PRIMARY | PRIMARY | 8 | NULL | 4711235 | Using where; Using index |
+----+-------------+-------+-------+---------------+---------+---------+------+---------+--------------------------+
1 row in set (0.00 sec)
mysql> DESCRIBE db.table;
+--------------+--------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+--------------+--------------+------+-----+---------+-------+
| id | bigint(20) | NO | PRI | NULL | |
| id2 | varchar(28) | YES | | NULL | |
| photo | longblob | YES | | NULL | |
| source | varchar(10) | YES | | NULL | |
| file_name | varchar(120) | YES | | NULL | |
| file_type | char(1) | YES | | NULL | |
| created_date | datetime | YES | | NULL | |
| updated_date | datetime | YES | | NULL | |
| createdby | varchar(50) | YES | | NULL | |
| updatedby | varchar(50) | YES | | NULL | |
+--------------+--------------+------+-----+---------+-------+
10 rows in set (0.05 sec)
The explain query gives me the result right there. But the actual query has been running for quite a while. How can I fix this? What am I doing wrong?
I basically need to figure out how many photos there are in this table. Initially the original coder had a query which checked WHERE photo IS NOT NULL (which took 3hours+) but I changed this query to check the id column as it is a primary key. I expected a huge performance gain there and was expecting an answer in under a second but that seems to not be the case.
What sort of optimizations on the database do I need to do? I think the query is fine but feel free to correct me if I am wrong.
Edit: mysql Ver 14.14 Distrib 5.1.52, for redhat-linux-gnu (x86_64) using readline 5.1
P.S: I renamed the tables for some crazy reason. I don't actually have the database named db and the table in question named table.

How long is 'long'? How many rows are there in this table?
A MyISAM table keeps track of how many rows it has, so a simple COUNT(*) will always return almost instantly.
InnoDB, on the other hand works differently: an InnoDB table doesn't keep track of how many rows it has, and so when you COUNT(*), it literally has to go and count each row. If you have a large table, this can take a number of seconds.
EDIT: Try COUNT(ID) instead of COUNT(*), where ID is an indexed column that has no NULLs in it. That may run faster.
EDIT2: If you're storing the binary data of the files in the longblob, your table will be massive, which will slow things down.
Possible solutions:
Use MyISAM instead of InnoDB.
Maintain your own count, perhaps using triggers on inserts and deletes.
Strip out the binary data into another table, or preferably regular files.

Related

How can I make this UPDATE query faster?

I need to make this update query more efficient.
UPDATE #table_name# SET #column_name2# = 1 WHERE #column_name1# in (A list of data)
Right now it takes more than 2 minute to finish the job when my list of data is quite large. Here is the result of explain of this query:
+----+-------------+--------------+-------+---------------+---------+---------+------+--------+------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+--------------+-------+---------------+---------+---------+------+--------+------------------------------+
| 1 | SIMPLE | #table_name# | index | NULL | PRIMARY | 38 | NULL | 763719 | Using where; Using temporary |
+----+-------------+--------------+-------+---------------+---------+---------+------+--------+------------------------------+
In class, I was told that an OK query should at least have a type of range and is better to reach ref. Right now mine is index, which is the second slowest I think. I'm wondering if there's a way to optimize that.
Here is the table format:
+--------------------+-------------+------+-----+-------------------+-------+
| Field | Type | Null | Key | Default | Extra |
+--------------------+-------------+------+-----+-------------------+-------+
| #column_name1# | varchar(12) | NO | PRI | | |
| #column_name2# | tinyint(4) | NO | | 0 | |
| #column_name3# | tinyint(4) | NO | | 0 | |
| ENTRY_TIME | datetime | NO | | CURRENT_TIMESTAMP | |
+--------------------+-------------+------+-----+-------------------+-------+
My friend suggested me that using exists rather than in clause may help. However, it looks like I cannot use exists like exists (A list of data)
For this query:
UPDATE #table_name#
SET #column_name2# = 1
WHERE #column_name1# in (A list of data);
You want an index on #table_name#(#column_name1#).
Do note that the number of records being updated has a very big impact on performance. If the "list of data" is really a subquery, then other methods are likely to be more helpful for improving performance.

composite index on large table, optimizing aggregate query

We are having a large table (Having arround 160 million records) in MySql 5.5.
The machine having 4GB RAM where we installed our mysql
table schema
+---------------+---------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+---------------+---------------+------+-----+---------+-------+
| domain | varchar(50) | YES | MUL | NULL | |
| uid | varchar(100) | YES | | NULL | |
| sid | varchar(100) | YES | MUL | NULL | |
| vurl | varchar(2500) | YES | | NULL | |
| ip | varchar(20) | YES | | NULL | |
| ref | varchar(2500) | YES | | NULL | |
| stats_time | datetime | YES | MUL | NULL | |
| country | varchar(50) | YES | | NULL | |
| region | varchar(50) | YES | | NULL | |
| place | varchar(50) | YES | | NULL | |
| email | varchar(100) | YES | MUL | NULL | |
+---------------+---------------+------+-----+---------+-------+
Indexes
+------------+------------+------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+------------+------------+------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| visit_views | 1 | sid_index | 1 | sid | A | 157531031 | NULL | NULL | YES | BTREE | | |
| visit_views | 1 | domain_index | 1 | domain | A | 17 | NULL | NULL | YES | BTREE | | |
| visit_views | 1 | email_index | 1 | email | A | 392845 | NULL | NULL | YES | BTREE | | |
| visit_views | 1 | stats_time_index | 1 | stats_time | A | 78765515 | NULL | NULL | YES | BTREE | | |
+------------+------------+------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
Example query
SELECT count(*)
FROM visit_views
WHERE domain ='our'
AND email!=''
AND stats_time BETWEEN '2010-06-21 00:00:00' AND '2015-08-21 00:00:00';
We are having very slow performance on queries like above, So I want to add composite index on this table
I ran following command
ALTER TABLE visit_views ADD INDEX domain_statstime_email (domain,stats_time,email);
after running this command , our table got locked, it has reached connection limit (connect limit is 1000). Now table is not responding for any INSERTS and SELECTS.
Here are my few questions
1.Why table got locked and why table is not releasing existing connections
2.How much time it will take to complete the index. I applied 3 hours back still index not created.
3.How to see index creation progress.
4.Why connection limit suddenly increasing to max while adding index to table.
5.Is it safe to add composite indexes for this kind of large table
6.If I add partitions for this table, will it any better performance.
I don't know much about indexes
some stats
+---------------------------+
| ##innodb_buffer_pool_size |
+---------------------------+
| 3221225472 |
+---------------------------+
Your query has three conditions: an inequality, an equality, and a range.
WHERE domain ='our'
AND email!=''
AND stats_time BETWEEN '2010-06-21 00:00:00' AND '2015-08-21 00:00:00';
To make this work, you should try the following indexes to see which one works better.
(email, domain, stats_time)
(domain, email, stats_time)
Why these? MySQL indexes are BTREE. That is, they're sorted in order. So to satisfy the query MySQL finds the first element in the index matching your query. That's based on domain, email, and the starting stats_time value. It then scans the index sequentially looking for the last matching value. Along the way it counts the records, and that satisfies your query. In other words it does a range scan on stats_time.
Why the choice? I don't know what MySQL will do with the inequality in your email matching predicate. That's why I suggest trying both.
If you have not simplified the query you showed us, you also might try a compound covering index on
(domain, stats_time, email)
This will random-access immediately to the first matching domain/stats_time combination, and then scan to the last one. As it scans, it will look at the email values from the index (that's why this is called a covering index) and pick out the rows matching. Along the way it counts the rows.
You should consider declaring your email column NOT NULL to help your inequality test use its index more efficiently. Read http://use-the-index-luke.com/ for good background information.
As to your questions:
Why table got locked and why table is not releasing existing connections
Why connection limit suddenly increasing to max while adding index to table.
It can take a long time to add an index to a large table. Yours, at 160 megarows, is large. While that indexing operation us going on, other users of the table must wait. So, if you're accessing this from a web app, the connections pile up waiting for it to become available.
How much time it will take to complete the index. I applied 3 hours back still index not created.
It will be much faster on a quiet system. It is also possible you have some redundant single-column indexes you could drop. You may wish to copy the table and index the copy, then, when it's ready, rename it.
How to see index creation progress.
SHOW FULL PROCESSLIST will display all the action in your MySQL server. You'll need a command line interface to give this command.
Is it safe to add composite indexes for this kind of large table
Yes, of course, but it takes time on a production system.
If I add partitions for this table, will it any better performance.
Probably not. What WILL help is DELETEing rows that are old, if you don't need them.

Order by and pagination

I have a thousand of records in my database mysql and I use pagination to retrieve just 10 results.
When i add a order by in my query it slow down but when i omit it the query run very fast.
I know that the problem come from that the query load whole results, sort them and after that it get the 10 records.
I don't use index because the column use for order is a PK and i think if i'm not wrong in mysql a index is created automatically on every primary key
Why the index on my PK which is the column I'm ordering.
not used ?
Is there any alternative solution to perform sorting without load all the data ?
How to add new inserted data at the first row of tables and not at the end of the table ?
My sql query
select distinct ...... order by appeloffre0_.ID_APPEL_OFFRE desc limit 10
and my indexes
mysql> show index from appel_offre;
+-------------+------------+--------------------+--------------+---------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+-------------+------------+--------------------+--------------+---------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| appel_offre | 0 | PRIMARY | 1 | ID_APPEL_OFFRE | A | 13691 | NULL | NULL | | BTREE | | |
| appel_offre | 1 | appel_offre_ibfk_1 | 1 | ID_APPEL_OFFRE_MERE | A | 2 | NULL | NULL | YES | BTREE | | |
| appel_offre | 1 | appel_offre_ibfk_2 | 1 | ID_ACHETEUR | A | 2 | NULL | NULL | | BTREE | | |
| appel_offre | 1 | appel_offre_ibfk_3 | 1 | USER_SAISIE | A | 2 | NULL | NULL | YES | BTREE | | |
| appel_offre | 1 | appel_offre_ibfk_4 | 1 | USER_VALIDATION | A | 4 | NULL | NULL | YES | BTREE | | |
| appel_offre | 1 | ao_fk_3 | 1 | TYPE_MARCHE | A | 2 | NULL | NULL | YES | BTREE | | |
| appel_offre | 1 | ao_fk_5 | 1 | USER_CONTROLE | A | 2 | NULL | NULL | YES | BTREE | | |
+-------------+------------+--------------------+--------------+---------------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
7 rows in set (0.03 sec)
no index was chosen in explain cmd:
+----+-------------+---------------+--------+-------------------------------------+--------------------+---------+----------------
| id | select_type | table | type | possible_keys | key | key_len | ref
+----+-------------+---------------+--------+-------------------------------------+--------------------+---------+----------------
| 1 | SIMPLE | appeloffre0_ | ALL | NULL | NULL | NULL | NULL
UPDATE SOLUTION
the problem was from distinct when i delete it the query finnaly use the index.
Because you already use an index on "USER_VALIDATION", MySQL won't use the ID index instead.
Try rebuilding the USER_VALIDATION index to include the ID too:
CREATE UNIQUE INDEX appel_offre_ibfk_4 ON appel_offre (USER_VALIDATION, ID);
Update
Log all Hibernate queries, extract the slow query and use EXPLAIN in a db console to understand what execution plan MySQL selects for this query. It may be possible for the db to use a FULL TABLE SCAN even when you have an index, because the index is too large to fit into memory. Try giving it a HINT as explained in this post.
According to MySQL ORDER BY optimization documentation you should:
To increase ORDER BY speed, check whether you can get MySQL to use indexes rather than an extra sorting phase. If this is not possible, you can try the following strategies:
• Increase the sort_buffer_size variable value.
• Increase the read_rnd_buffer_size variable value.
• Use less RAM per row by declaring columns only as large as they need
to be to hold the values stored in them. For example, CHAR(16) is
better than CHAR(200) if values never exceed 16 characters.
• Change the tmpdir system variable to point to a dedicated file
system with large amounts of free space. The variable value can list
several paths that are used in round-robin fashion; you can use this
feature to spread the load across several directories. Paths should be
separated by colon characters (“:”) on Unix and semicolon characters
(“;”) on Windows, NetWare, and OS/2. The paths should name directories
in file systems located on different physical disks, not different
partitions on the same disk.
Also make sure DISTINCT doesn't overrule your index. Try removing it and see if it helps.
Add an index to the column by which you are ordering.
You can't add rows to the beginning of the table, just like you can't add rows to the end of the table. Database tables are multisets. Multisets are by definition unordered collections. The notion of a first element or a last element makes no sense for multisets.

analyze query mysql

I have a question about, how to analyze a query to know performance of its (good or bad).
I searched a lot and got something like below:
SELECT count(*) FROM users; => Many experts said it's bad.
SELECT count(id) FROM users; => Many experts said it's good.
Please see the table:
+---------------+-------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+---------------+-------------+------+-----+---------+----------------+
| userId | int(11) | NO | PRI | NULL | auto_increment |
| f_name | varchar(50) | YES | | NULL | |
| l_name | varchar(50) | YES | | NULL | |
| user_name | varchar(50) | NO | | NULL | |
| password | varchar(50) | YES | | NULL | |
| email | varchar(50) | YES | | NULL | |
| active | char(1) | NO | | Y | |
| groupId | smallint(4) | YES | MUL | NULL | |
| created_date | datetime | YES | | NULL | |
| modified_date | datetime | YES | | NULL | |
+---------------+-------------+------+-----+---------+----------------+
But when I try to using EXPLAIN command for that, I got the results:
EXPLAIN SELECT count(*) FROM `user`;
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
| 1 | SIMPLE | user | index | NULL | groupId | 3 | NULL | 83 | Using index |
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
1 row in set (0.00 sec)
EXPLAIN SELECT count(userId) FROM user;
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
| 1 | SIMPLE | user | index | NULL | groupId | 3 | NULL | 83 | Using index |
+----+-------------+-------+-------+---------------+---------+---------+------+------+-------------+
1 row in set (0.00 sec)
So, the first thing for me:
Can I understand it's the same performance?
P/S: MySQL version is 5.5.8.
No, you cannot. Explain doesn't reflect all the work done by mysql, it just gives you a plan of how it will be performed.
What about specifically count(*) vs count(id). The first one is always not slower than the second, and in some cases it is faster.
count(col) semantic is amount of not null values, while count(*) is - amount of rows.
Probably mysql can optimize count(col) by rewriting into count(*) as well as id is a PK thus cannot be NULL (if not - it looks up for NULLS, which is not fast), but I still propose you to use COUNT(*) in such cases.
Also - the internall processes depend on used storage engine. For myisam the precalculated number of rows returned in both cases (as long as you don't use WHERE).
In the example you give the performance is identical.
The execution plan shows you that the optimiser is clever enough to know that it should use the Primary key to find the total number of records when you use count(*).
There is not significant difference when it comes on counting. The reason is that most optimizers will figure out the best way to count rows by themselves.
The performance difference comes to searching for values and lack of indexing. So if you search for a field that has no index assigned {f_name,l_name} and a field that has{userID(mysql automatically use index on primary keys),groupID(seems like foraign key)} then you will see the difference in performance.

In MySQL 5, SELECT COUNT(1) FROM table_name is very slow

I have a MySQL 5.0 database with a few tables containing over 50M rows. But how do I know this? By running "SELECT COUNT(1) FROM foo", of course. This query on one table containing 58.8M rows took 10 minutes to complete!
mysql> SELECT COUNT(1) FROM large_table;
+----------+
| count(1) |
+----------+
| 58778494 |
+----------+
1 row in set (10 min 23.88 sec)
mysql> EXPLAIN SELECT COUNT(1) FROM large_table;
+----+-------------+-------------------+-------+---------------+----------------------------------------+---------+------+-----------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------------------+-------+---------------+----------------------------------------+---------+------+-----------+-------------+
| 1 | SIMPLE | large_table | index | NULL | fk_large_table_other_table_id | 5 | NULL | 167567567 | Using index |
+----+-------------+-------------------+-------+---------------+----------------------------------------+---------+------+-----------+-------------+
1 row in set (0.00 sec)
mysql> DESC large_table;
+-------------------+---------------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-------------------+---------------------+------+-----+---------+----------------+
| id | bigint(20) unsigned | NO | PRI | NULL | auto_increment |
| created_on | datetime | YES | | NULL | |
| updated_on | datetime | YES | | NULL | |
| other_table_id | int(11) | YES | MUL | NULL | |
| parent_id | bigint(20) unsigned | YES | MUL | NULL | |
| name | varchar(255) | YES | | NULL | |
| property_type | varchar(64) | YES | | NULL | |
+-------------------+---------------------+------+-----+---------+----------------+
7 rows in set (0.00 sec)
All of the tables in question are InnoDB.
Any ideas why this is so slow, and how I can speed it up?
Counting all the rows in a table is a very slow operation; you can't really speed it up, unless you are prepared to keep a count somewhere else (and of course, that can become out of sync).
People who are used to MyISAM tend to think that they get count(*) "for free", but it's not really. MyISAM cheats by not having MVCC, which makes it fairly easy.
The query you're showing is doing a full index scan of a not-null index, which is generally the fastest way of counting the rows in an innodb table.
It is difficult to guess from the information you've given, what your application is, but in general, it's ok for users (etc) to see close approximations of the number of rows in large tables.
If you need to have the result instantly and you don't care if it's 58.8M or 51.7M, you can find out the approximate number of rows by calling
show table status like 'large_table';
See the column rows
For more information about the result take a look at the manual at http://dev.mysql.com/doc/refman/5.1/en/show-table-status.html
select count(id) from large_table will surely run faster