MySQL: low cardinality/selectivity columns = how to index?

The index that you describe is pretty much pointless. An index is best used when you need to select a small number of rows in comparison to the total rows.

The reason for this is related to how a database accesses a table. Tables can be assessed either by a full table scan, where each block is read and processed in turn. Or by a rowid or key lookup, where the database has a key/rowid and reads the exact row it requires.

In the case where you use a where clause based on the primary key or another unique index, eg. where id = 1, the database can use the index to get an exact reference to where the row's data is stored. This is clearly more efficient than doing a full table scan and processing every block.

Now back to your example, you have a where clause of where status = 'enabled', the index will return 150m rows and the database will have to read each row in turn using separate small reads. Whereas accessing the table with a full table scan allows the database to make use of more efficient larger reads.

There is a point at which it is better to just do a full table scan rather than use the index. With mysql you can use FORCE INDEX (idx_name) as part of your query to allow comparisons between each table access method.

Reference: http://dev.mysql.com/doc/refman/5.5/en/how-to-avoid-table-scan.html

I'm sorry to say that I do not agree with Mike. Adding an index is meant to limit the amount of full records searches for MySQL, thereby limiting IO which usually is the bottleneck.

This indexing is not free; you pay for it on inserts/updates when the index has to be updated and in the search itself, as it now needs to load the index file (full text index for 300M records is probably not in memory). So it might well be that you get extra IO in stead of limitting it.

I do agree with the statement that a binary variable is best stored as one, a bool or tinyint, as that decreases the length of a row and can thereby limit disk IO, also comparisons on numbers are faster.

If you need speed and you seldom use the disabled records, you may wish to have 2 tables, one for enabled and one for disabled records and move the records when the status changes. As it increases complexity and risk this would be my very last choice of course. Definitely do the move in 1 transaction if you happen to go for it.

It just popped into my head that you can check wether an index is actually used by using the explain statement. That should show you how MySQL is optimizing the query. I don't really know hoe MySQL optimizes queries, but from postgresql I do know that you should explain a query on a database approximately the same (in size and data) as the real database. So if you have a copy on the database, create an index on the table and see wether it's actually used. As I said, I doubt it, but I most definitely don't know everything:)

If the data is distributed like 50:50 then query like where status="enabled" will avoid half scanning of the table.

Having index on such tables is completely depends on distribution of data, i,e : if entries having status enabled is 90% and other is 10%. and for query where status="disabled" it scans only 10% of the table.

so having index on such columns depends on distribution of data.

@a'r answer is correct, however it needs to be pointed out that the usefulness of an index is given not only by its cardinality but also by the distribution of data and the queries run on the database.

In OP's case, with 150M records having status='enabled' and 150M having status='disabled', the index is unnecessary and a waste of resource.

In case of 299M records having status='enabled' and 1M having status='disabled', the index is useful (and will be used) in queries of type SELECT ... where status='disabled'.
Queries of type SELECT ... where status='enabled' will still run with a full table scan.

You will hardly need all 150 mln records at once, so I guess "status" will always be used in conjunction with other columns. Perhaps it'd make more sense to use a compound index like (status, fullname)