MySQL Interview Questions And Answers Set - 8

MySQL Interview Questions And Answers Set - 8



How MySQL Optimizes LEFT JOIN and RIGHT JOIN ?
A LEFT JOIN B in MySQL is implemented as follows:

The table B is set to be dependent on table A and all tables that A is dependent on.
The table A is set to be dependent on all tables (except B) that are used in the LEFT JOIN condition.
All LEFT JOIN conditions are moved to the WHERE clause.
All standard join optimizations are done, with the exception that a table is always read after all tables it is dependent on. If there is a circular dependence then MySQL will issue an error.
All standard WHERE optimizations are done.
If there is a row in A that matches the WHERE clause, but there wasn't any row in B that matched the LEFT JOIN condition, then an extra B row is generated with all columns set to NULL.
If you use LEFT JOIN to find rows that don't exist in some table and you have the following test: column_name IS NULL in the WHERE part, where column_name is a column that is declared as NOT NULL, then MySQL will stop searching after more rows (for a particular key combination) after it has found one row that matches the LEFT JOIN condition.
RIGHT JOIN is implemented analogously as LEFT JOIN.

The table read order forced by LEFT JOIN and STRAIGHT JOIN will help the join optimizer (which calculates in which order tables should be joined) to do its work much more quickly, as there are fewer table permutations to check.

Note that the above means that if you do a query of type:

SELECT * FROM a,b LEFT JOIN c ON (c.key=a.key) LEFT JOIN d (d.key=a.key) WHERE b.key=d.key

MySQL will do a full scan on b as the LEFT JOIN will force it to be read before d.

The fix in this case is to change the query to:

SELECT * FROM b,a LEFT JOIN c ON (c.key=a.key) LEFT JOIN d (d.key=a.key) WHERE b.key=d.key

How MySQL Optimizes LIMIT ?
In some cases MySQL will handle the query differently when you are using LIMIT # and not using HAVING:

If you are selecting only a few rows with LIMIT, MySQL will use indexes in some cases when it normally would prefer to do a full table scan.
If you use LIMIT # with ORDER BY, MySQL will end the sorting as soon as it has found the first # lines instead of sorting the whole table.
When combining LIMIT # with DISTINCT, MySQL will stop as soon as it finds # unique rows.
In some cases a GROUP BY can be resolved by reading the key in order (or do a sort on the key) and then calculate summaries until the key value changes. In this case LIMIT # will not calculate any unnecessary GROUP BY's.
As soon as MySQL has sent the first # rows to the client, it will abort the query.
LIMIT 0 will always quickly return an empty set. This is useful to check the query and to get the column types of the result columns.
The size of temporary tables uses the LIMIT # to calculate how much space is needed to resolve the query.

MySQL - Speed of INSERT Queries ?
The time to insert a record consists approximately of:

Connect: (3)
Sending query to server: (2)
Parsing query: (2)
Inserting record: (1 x size of record)
Inserting indexes: (1 x number of indexes)
Close: (1)
where the numbers are somewhat proportional to the overall time. This does not take into consideration the initial overhead to open tables (which is done once for each concurrently running query).

The size of the table slows down the insertion of indexes by N log N (B-trees).

Some ways to speed up inserts:

If you are inserting many rows from the same client at the same time, use multiple value lists INSERT statements. This is much faster (many times in some cases) than using separate INSERT statements.
If you are inserting a lot of rows from different clients, you can get higher speed by using the INSERT DELAYED statement.

Note that with MyISAM you can insert rows at the same time SELECTs are running if there are no deleted rows in the tables. When loading a table from a text file, use LOAD DATA INFILE. This is usually 20 times faster than using a lot of INSERT statements.

It is possible with some extra work to make LOAD DATA INFILE run even faster when the table has many indexes. Use the following procedure:
Optionally create the table with CREATE TABLE. For example, using mysql or Perl-DBI.
Execute a FLUSH TABLES statement or the shell command mysqladmin flush-tables.
Use myisamchk --keys-used=0 -rq /path/to/db/tbl_name. This will remove all usage of all indexes from the table.
Insert data into the table with LOAD DATA INFILE. This will not update any indexes and will therefore be very fast.
If you are going to only read the table in the future, run myisampack on it to make it smaller.

Re-create the indexes with myisamchk -r -q /path/to/db/tbl_name. This will create the index tree in memory before writing it to disk, which is much faster because it avoids lots of disk seeks. The resulting index tree is also perfectly balanced. Execute a FLUSH TABLES statement or the shell command mysqladmin flush-tables.
This procedure will be built into LOAD DATA INFILE in some future version of MySQL.
You can speed up insertions by locking your tables:
mysql> LOCK TABLES a WRITE;
mysql> INSERT INTO a VALUES (1,23),(2,34),(4,33);
mysql> INSERT INTO a VALUES (8,26),(6,29);
mysql> UNLOCK TABLES;

The main speed difference is that the index buffer is flushed to disk only once, after all INSERT statements have completed. Normally there would be as many index buffer flushes as there are different INSERT statements. Locking is not needed if you can insert all rows with a single statement. Locking will also lower the total time of multi-connection tests, but the maximum wait time for some threads will go up (because they wait for locks). For example:
thread 1 does 1000 inserts
thread 2, 3, and 4 does 1 insert
thread 5 does 1000 inserts

If you don't use locking, 2, 3, and 4 will finish before 1 and 5. If you use locking, 2, 3, and 4 probably will not finish before 1 or 5, but the total time should be about 40% faster. As INSERT, UPDATE, and DELETE operations are very fast in MySQL, you will obtain better overall performance by adding locks around everything that does more than about 5 inserts or updates in a row. If you do very many inserts in a row, you could do a LOCK TABLES followed by an UNLOCK TABLES once in a while (about each 1000 rows) to allow other threads access to the table. This would still result in a nice performance gain. Of course, LOAD DATA INFILE is much faster for loading data.
To get some more speed for both LOAD DATA INFILE and INSERT, enlarge the key buffer.