7.13.9. ORDER BY Optimization

In some cases, MySQL can use an index to satisfy an ORDER BY clause without doing any extra sorting.

The index can also be used even if the ORDER BY does not match the index exactly, as long as all of the unused portions of the index and all the extra ORDER BY columns are constants in the WHERE clause. The following queries use the index to resolve the ORDER BY part:

SELECT * FROM t1
  ORDER BY key_part1,key_part2,... ;

SELECT * FROM t1
  WHERE key_part1=constant
  ORDER BY key_part2;

SELECT * FROM t1
  ORDER BY key_part1 DESC, key_part2 DESC;

SELECT * FROM t1
  WHERE key_part1=1
  ORDER BY key_part1 DESC, key_part2 DESC;

In some cases, MySQL cannot use indexes to resolve the ORDER BY, although it still uses indexes to find the rows that match the WHERE clause. These cases include the following:

  • You use ORDER BY on different keys:

    SELECT * FROM t1 ORDER BY key1, key2;
    
  • You use ORDER BY on nonconsecutive parts of a key:

    SELECT * FROM t1 WHERE key2=constant ORDER BY key_part2;
    
  • You mix ASC and DESC:

    SELECT * FROM t1 ORDER BY key_part1 DESC, key_part2 ASC;
    
  • The key used to fetch the rows is not the same as the one used in the ORDER BY:

    SELECT * FROM t1 WHERE key2=constant ORDER BY key1;
    
  • You use ORDER BY with an expression that includes terms other than the key column name:

    SELECT * FROM t1 ORDER BY ABS(key);
    SELECT * FROM t1 ORDER BY -key;
    
  • You are joining many tables, and the columns in the ORDER BY are not all from the first nonconstant table that is used to retrieve rows. (This is the first table in the EXPLAIN output that does not have a const join type.)

  • You have different ORDER BY and GROUP BY expressions.

  • You index only a prefix of a column named in the ORDER BY clause. In this case, the index cannot be used to fully resolve the sort order. For example, if you have a CHAR(20) column, but index only the first 10 bytes, the index cannot distinguish values past the 10th byte and a filesort will be needed.

  • The type of table index used does not store rows in order. For example, this is true for a HASH index in a MEMORY table.

Availability of an index for sorting may be affected by the use of column aliases. Suppose that the column t1.a is indexed. In this statement, the name of the column in the select list is a. It refers to t1.a, so for the reference to a in the ORDER BY, the index can be used:

SELECT a FROM t1 ORDER BY a;

In this statement, the name of the column in the select list is also a, but it is the alias name. It refers to ABS(a), so for the reference to a in the ORDER BY, the index cannot be used:

SELECT ABS(a) AS a FROM t1 ORDER BY a;

In the following statement, the ORDER BY refers to a name that is not the name of a column in the select list. But there is a column in t1 named a, so the ORDER BY uses that, and the index can be used. (The resulting sort order may be completely different from the order for ABS(a), of course.)

SELECT ABS(a) AS b FROM t1 ORDER BY a;

By default, MySQL sorts all GROUP BY col1, col2, ... queries as if you specified ORDER BY col1, col2, ... in the query as well. If you include an ORDER BY clause explicitly that contains the same column list, MySQL optimizes it away without any speed penalty, although the sorting still occurs. If a query includes GROUP BY but you want to avoid the overhead of sorting the result, you can suppress sorting by specifying ORDER BY NULL. For example:

INSERT INTO foo
SELECT a, COUNT(*) FROM bar GROUP BY a ORDER BY NULL;

With EXPLAIN SELECT ... ORDER BY, you can check whether MySQL can use indexes to resolve the query. It cannot if you see Using filesort in the Extra column. See Section 7.8.1, “Optimizing Queries with EXPLAIN.

MySQL has two filesort algorithms for sorting and retrieving results. The original method uses only the ORDER BY columns. The modified method uses not just the ORDER BY columns, but all the columns used in the query.

The optimizer selects which filesort algorithm to use. It normally uses the modified algorithm except when BLOB or TEXT columns are involved, in which case it uses the original algorithm.

The original filesort algorithm works as follows:

  1. Read all rows according to key or by table scanning. Rows that do not match the WHERE clause are skipped.

  2. For each row, store a pair of values in a buffer (the sort key and the row pointer). The size of the buffer is the value of the sort_buffer_size system variable.

  3. When the buffer gets full, run a qsort (quicksort) on it and store the result in a temporary file. Save a pointer to the sorted block. (If all pairs fit into the sort buffer, no temporary file is created.)

  4. Repeat the preceding steps until all rows have been read.

  5. Do a multi-merge of up to MERGEBUFF (7) regions to one block in another temporary file. Repeat until all blocks from the first file are in the second file.

  6. Repeat the following until there are fewer than MERGEBUFF2 (15) blocks left.

  7. On the last multi-merge, only the pointer to the row (the last part of the sort key) is written to a result file.

  8. Read the rows in sorted order by using the row pointers in the result file. To optimize this, we read in a big block of row pointers, sort them, and use them to read the rows in sorted order into a row buffer. The size of the buffer is the value of the read_rnd_buffer_size system variable. The code for this step is in the sql/records.cc source file.

One problem with this approach is that it reads rows twice: One time when evaluating the WHERE clause, and again after sorting the pair values. And even if the rows were accessed successively the first time (for example, if a table scan is done), the second time they are accessed randomly. (The sort keys are ordered, but the row positions are not.)

The modified filesort algorithm incorporates an optimization such that it records not only the sort key value and row position, but also the columns required for the query. This avoids reading the rows twice. The modified filesort algorithm works like this:

  1. Read the rows that match the WHERE clause.

  2. For each row, record a tuple of values consisting of the sort key value and row position, and also the columns required for the query.

  3. Sort the tuples by sort key value

  4. Retrieve the rows in sorted order, but read the required columns directly from the sorted tuples rather than by accessing the table a second time.

Using the modified filesort algorithm, the tuples are longer than the pairs used in the original method, and fewer of them fit in the sort buffer (the size of which is given by sort_buffer_size). As a result, it is possible for the extra I/O to make the modified approach slower, not faster. To avoid a slowdown, the optimization is used only if the total size of the extra columns in the sort tuple does not exceed the value of the max_length_for_sort_data system variable. (A symptom of setting the value of this variable too high is a combination of high disk activity and low CPU activity.)

For slow queries for which filesort is not used, try lowering max_length_for_sort_data to a value that is appropriate to trigger a filesort.

If you want to increase ORDER BY speed, check whether you can get MySQL to use indexes rather than an extra sorting phase. If this is not possible, you can try the following strategies:

  • Increase the size of the sort_buffer_size variable.

  • Increase the size of the read_rnd_buffer_size variable.

  • Use less RAM per row by declaring columns only as large as they need to be to hold the values stored in them. For example, CHAR(16) is better than CHAR(200) if values never exceed 16 characters.

  • Change tmpdir to point to a dedicated file system with large amounts of free space. Also, this option accepts several paths that are used in round-robin fashion, so you can use this feature to spread the load across several directories. Paths should be separated by colon characters (“:”) on Unix and semicolon characters (“;”) on Windows. The paths should be for directories in file systems that are located on different physical disks, not different partitions on the same disk.

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