it seems that it is a common practice to divide the data of one table into many databases, many tables
to improve performance, i can understand the many datab
I think you have a few terms mixed up here.
All your data goes into one database (aka schema). In a database you can have tables.
e.g.
table employee
id integer
name varchar
address varchar
country varchar
table office
id integer
employee_id integer
address varchar
Inside tables you have fields (id, name, address)
aka columns.
And tables have one or more rows.
An example for table employee:
id name address country
----------------------------------------------------
1 John 1 Regent Street UK
2 James 24 Jump Street China
3 Darth Vader 1 Death Star Bestine, Tatooine
So much for the basics.
Why partitioning
Now suppose that we have lots and lots of people (rows) in our database.
Remember this a galactic database, so we have 100 billion records.
If we want to search trough this fast it's nice if we can do this in parallel.
So we partition the table (say by country) and then we can have x servers looking in 1 country each.
Partitioning across servers is called sharding
.
Or we can partition e.g. historical data by year, so we don't have to go through all the data just to get the recent news. We only have to go through the partition for this year. This is called partitioning
.
What's the big difference between sharding
can just partitioning
?
Sharding
In sharding
you anticipate that all your data is relevant, and equally likely to be queried. (e.g. google can expect all their data to be queried; archiving part of their data is useless for them).
In this case you want lots of machines to look though your data in parallel, where each machine does part of the work.
So you give each machine a different partition (shard) of the data and give all the machines the same query. When the results come out you UNION
them all together and output the result.
Basic partitioning
In basic partitioning
part of your data is hot
and part is not
. A typical case is historical data, the new data is hot
, the old data hardly gets touched.
For this use case it is pointless to put the old data in separate servers. Those machines will just wait and wait and do nothing because nobody cares about the old data except some auditors who look at it once a year.
So you partition that data by year and the server will automatically archive the old partitions so your queries will only look at one (maybe 2) years of data and be much faster.
Do I need partitioning?
You only do partitioning when you have lots and lots of data, because it complicates your setup.
Unless you have more than a million records you don't have to consider partitioning.*)
If you have more than a 100 million records, you should definitely consider it.*)
For more info see: http://dev.mysql.com/doc/refman/5.1/en/partitioning.html
and: http://blog.mayflower.de/archives/353-Is-MySQL-partitioning-useful-for-very-big-real-life-problems.html
See also wiki: http://en.wikipedia.org/wiki/Partition_%28database%29
*) These are just my personal heuristics YMMV.