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From:shawn Date:May 16 2014 3:47pm
Subject:Re: Advices for work with big tables
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Hello Antonio,

On 5/16/2014 9:49 AM, Antonio Fernández Pérez wrote:
> Hi,
> I write to the list because I need your advices.
> I'm working with a database with some tables that have a lot of rows, for
> example I have a table with 8GB of data.

How you design your tables can have a huge impact on performance. If you 
are frequently doing aggregation (GROUP BY...) queries for reports, then 
you may need to have your data pre-aggregated at various levels. 
Perhaps, as an example, you want to run a weekly report of how often 
someone logs in. Every day, you have an average of 100 users each 
logging in 10 times a day. That is 1000 rows of connection information. 
  Multiply that and you have 70000 rows, multiply that by a year and you 
have 365000 rows (appx)

If you create a table or set of tables where you have already summarized 
your most frequently used data for example (login, date, total minutes 
connected for that date, total number of connections for that day, ... ) 
then you have reduced how much work your weekly report needs to do from 
70000 rows to just 7.  How much faster would that be?

Each day, you add the previous day's totals to your summary tables.

For more information on how to do this kind of pre-computation analysis 
and optimization, do some research on the topic of OLAP (online 
analytical processing)

> How can I do to have a fluid job with this table?

Stop trying to use just the one table for everything?

> My server works with disk cabin and I think that sharding and partitioning
> are technologies that not applies. Work with a lot of data produces that
> there are some slow query, even with the correct indexes created.

Partition pruning is a very good way of improving query performance. The 
trick is to design your partitions to match the majority of your query 

> So, one option is to delete data but, I use a RADIUS system to authenticate
> and authorize users to connect to Internet. For this reason I need work
> with almost all data. Another solution is increase the server resources.
> Any ideas?

See above.

> Thanks in advance.
> Regards,
> Antonio.

Shawn Green
MySQL Senior Principal Technical Support Engineer
Oracle USA, Inc. - Hardware and Software, Engineered to Work Together.
Office: Blountville, TN
Advices for work with big tablesAntonio Fernández Pérez16 May
  • Re: Advices for work with big tablesReindl Harald16 May
  • Re: Advices for work with big tablesJohan De Meersman16 May
  • Re: Advices for work with big tablesshawn l.green16 May