MySQL Count / Sum Performance

MySQL Count / Sum Performance

By : user2950943
Date : November 17 2020, 11:58 AM
will be helpful for those in need The best route will depend on the frequency of reads vs. writes of points, origins and moves. Those frequencies, in turn, will be dependent upon use cases, code style and use (or lack) of caching.
It's difficult to provide a qualified opinion without more details, but consider the fact that a dedicated table brings with it some additional complications in the way of additional writes necessary for each operation and ensuring that those data tallies must always be correct (match the underlying detail data). In light of the additional complication storing logical data elements once rather than twice in a relational database is usually the best course of action.
code :

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Mysql performance and Count(*)

Mysql performance and Count(*)

By : bzx
Date : March 29 2020, 07:55 AM
wish of those help MyISAM will return immediatelly. InnoDB will do PK scan, so time will lineary increase with number of records.
If you need to see approximately how many records InnoDB table holds, the fastest way is using
code :
EXPLAIN select * from student;
mysql count performance

mysql count performance

By : user2690690
Date : March 29 2020, 07:55 AM
This might help you As cherouvim pointed out in the comments, it depends on the storage engine.
MyISAM does keep a count of the table rows, and can keep it accurate since the only locks MyISAM supports is a table lock.
mysql order by count performance

mysql order by count performance

By : Chu Chien Hao
Date : March 29 2020, 07:55 AM
around this issue You may want to add an additional index to assist the in the counting phase.
code :
ALTER TABLE keywords ADD INDEX ckp_index (collection_id,keyword,pmid);
Mysql count performance on very big tables

Mysql count performance on very big tables

By : Andrew
Date : March 29 2020, 07:55 AM
Any of those help Finally the fastest was to query the first X rows using C# and counting the rows number.
My application is treating the data in batches. The amount of time between two batches are depending the number of rows who need to be treated
code :
why mysql count(*) has better performance than count(id)

why mysql count(*) has better performance than count(id)

By : Heni Fezzeni
Date : March 29 2020, 07:55 AM
Hope that helps Often COUNT(*) would have marginally better performance. COUNT(id) needs to check if id is not NULL for it to work. That means that it needs to read the value (as well as the small overhead for checking NULLness).
I would expect the timings to be the same in most databases when id is a clustered primary key. However, perhaps the MySQL optimizer doesn't bother avoiding the NULL check even for columns that are declared NOT NULL.
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