MySQL can create composite indexes (that is, indexes on multiple columns). An index may consist of up to 16 columns. For certain data types, you can index a prefix of the column (see Section 8.3.5, “Column Indexes” ). MySQL can use multiple-column indexes for queries that test all the columns in the index, or queries that test just the first column, the first two columns, the first three columns, and so on. If you specify the columns in the right order in the index definition, a single composite index can speed up several kinds of queries on the same table. A multiple-column index can be considered a sorted array, the rows of which contain values that are created by concatenating the values of the indexed columns. As an alternative to a composite index, you can introduce a column that is “ hashed ” based on information from other columns. If this column is short, reasonably unique, and indexed, it might be faster than a “ wide ” index on many columns. In MySQL, it is very easy to use this extra column:

SELECT * FROM tbl_name
  WHERE hash_col=MD5(CONCAT(val1,val2))
  AND col1=val1 AND col2=val2;

Suppose that a table has the following specification:

CREATE TABLE test (
    id         INT NOT NULL,
    last_name  CHAR(30) NOT NULL,
    first_name CHAR(30) NOT NULL,
    PRIMARY KEY (id),
    INDEX name (last_name,first_name)
        The name index is an index over the
        last_name and first_name
        columns. The index can be used for lookups in queries that
        specify values in a known range for combinations of
        last_name and first_name
        values. It can also be used for queries that specify just a
        last_name value because that column is a
        leftmost prefix of the index (as described later in this
        section). Therefore, the name index is used
        for lookups in the following queries:
      
SELECT * FROM test WHERE last_name='Widenius';
SELECT * FROM test
  WHERE last_name='Widenius' AND first_name='Michael';
SELECT * FROM test
  WHERE last_name='Widenius'
  AND (first_name='Michael' OR first_name='Monty');
SELECT * FROM test
  WHERE last_name='Widenius'
  AND first_name >='M' AND first_name < 'N';

        However, the name index is
        not used for lookups in the following
        queries:
      
SELECT * FROM test WHERE first_name='Michael';
SELECT * FROM test
  WHERE last_name='Widenius' OR first_name='Michael';

        Suppose that you issue the following
        SELECT statement:
      
SELECT * FROM tbl_name
  WHERE col1=val1 AND col2=val2;

        If a multiple-column index exists on col1 and
        col2, the appropriate rows can be fetched
        directly. If separate single-column indexes exist on
        col1 and col2, the
        optimizer attempts to use the Index Merge optimization (see
        Section 8.2.1.3, “Index Merge Optimization”), or attempts to find
        the most restrictive index by deciding which index excludes more
        rows and using that index to fetch the rows.
        If the table has a multiple-column index, any leftmost prefix of
        the index can be used by the optimizer to look up rows. For
        example, if you have a three-column index on (col1,
        col2, col3), you have indexed search capabilities on
        (col1), (col1, col2), and
        (col1, col2, col3).
        MySQL cannot use the index to perform lookups if the columns do
        not form a leftmost prefix of the index. Suppose that you have
        the SELECT statements shown here:
      
SELECT * FROM tbl_name WHERE col1=val1;
SELECT * FROM tbl_name WHERE col1=val1 AND col2=val2;
SELECT * FROM tbl_name WHERE col2=val2;
SELECT * FROM tbl_name WHERE col2=val2 AND col3=val3;

        If an index exists on (col1, col2, col3),
        only the first two queries use the index. The third and fourth
        queries do involve indexed columns, but do not use an index to
        perform lookups because (col2) and
        (col2, col3) are not leftmost prefixes of
        (col1, col2, col3).
        User comments in this section are, as the name implies, provided by MySQL users.
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        the information provided here.