Your indexes are fine for the two types of queries you mentioned.
This query will be satisfied by traversing the clustered index on the primary key...
[...] WHERE participant_id = x AND question_id = y AND given_answer_id = z;
...and this one is satisfied by the index on 'question_id':
[...] WHERE question_id = x;
The output of EXPLAIN SELECT
is not telling you what you think it is telling you, because the value shown in rows
is an estimate of the number of rows the server will need to consider, not the actual rows it will examine. For InnoDB
these are based on index statistics.
rows
The rows column indicates the number of rows MySQL believes it must examine to execute the query.
For InnoDB tables, this number is an estimate, and may not always be exact.
— http://dev.mysql.com/doc/refman/5.5/en/explain-output.html#explain_rows
The optimizer gathers information about different possible query plans, and chooses the one with the lowest cost. The information shown in EXPLAIN
is the information the optimizer gathered about the plan it selected.
When type
is ref
and key
is not NULL
, this means that the name listed in the key
column is the name of the index that the optimizer has chosen to use to find the desired rows, so your query plan looks exactly as it should.
Note, sometimes you will see Using index
in the Extra
column and a lot of people assume that this means an index is being used, or that no index is being used when that doesn't appear, but that's not correct, either. Using index
describes a special case called a "covering index" -- it does not indicate whether an index is being used to locate the rows of interest.
It's possible that running ANALYZE [LOCAL] TABLE
would cause the numbers in rows
shown by EXPLAIN
to differ, but this is a simple query and selecting this index is an obvious choice for the optimizer to make, so ANALYZE TABLE
is unlikely to make any actual difference in performance.
It is possible, however, that your overall performance might see some marginal improvement with an occasional OPTIMIZE [LOCAL] TABLE
, because you are not inserting rows in primary key order (as would be the case with an auto_increment
primary key)... but on large tables this can be time-consuming because it rebuilds a new copy of the table... but, again, I wouldn't expect any significant change.
You want to increase the speed of your cursors? Wrap them in a transaction. If you are processing millions of records and don't want/need them all in one transaction, you can commit it on occasion to reduce resources.
I did this with a cursor that took an hour to run (this is an extreme case) and afterword it ran in 1 1/2 minutes.
I know that does not answer you question but it might help you avoid doing the conversion until your more familiar with SQL. The answer to your question is... experience. There is no magic site or book you can read, it just takes time learning to do more and more in a single statement.
Best Answer
This SQL works fine in SQL Server (with appropriate syntax modifications):
Unfortunately, the syntax hits a limitation of MySQL that an updated table cannot be referenced (again) in the
WHERE
clause of theUPDATE
. A common workaround is to rewrite with aJOIN
: