Chapter 11 Data Types

A summary of the numeric data types follows. For additional information about properties and storage requirements of the numeric types, see Section 11.2, “Numeric Types”, and Section 11.7, “Data Type Storage Requirements”.

M indicates the maximum display width for integer types. The maximum display width is 255. Display width is unrelated to the range of values a type can contain, as described in Section 11.2, “Numeric Types”. For floating-point and fixed-point types, M is the total number of digits that can be stored.

If you specify ZEROFILL for a numeric column, MySQL automatically adds the UNSIGNED attribute to the column.

Numeric data types that permit the UNSIGNED attribute also permit SIGNED. However, these data types are signed by default, so the SIGNED attribute has no effect.

SERIAL is an alias for BIGINT UNSIGNED NOT NULL AUTO_INCREMENT UNIQUE.

SERIAL DEFAULT VALUE in the definition of an integer column is an alias for NOT NULL AUTO_INCREMENT UNIQUE.

A summary of the temporal data types follows. For additional information about properties and storage requirements of the temporal types, see Section 11.3, “Date and Time Types”, and Section 11.7, “Data Type Storage Requirements”. For descriptions of functions that operate on temporal values, see Section 12.7, “Date and Time Functions”.

For the DATE and DATETIME range descriptions, “supported” means that although earlier values might work, there is no guarantee.

The SUM() and AVG() aggregate functions do not work with temporal values. (They convert the values to numbers, losing everything after the first nonnumeric character.) To work around this problem, convert to numeric units, perform the aggregate operation, and convert back to a temporal value. Examples:

SELECT SEC_TO_TIME(SUM(TIME_TO_SEC(time_col))) FROM tbl_name;
SELECT FROM_DAYS(SUM(TO_DAYS(date_col))) FROM tbl_name;

A summary of the string data types follows. For additional information about properties and storage requirements of the string types, see Section 11.4, “String Types”, and Section 11.7, “Data Type Storage Requirements”.

In some cases, MySQL may change a string column to a type different from that given in a CREATE TABLE or ALTER TABLE statement. See Section 13.1.17.4, “Silent Column Specification Changes”.

MySQL interprets length specifications in character column definitions in character units. This applies to CHAR, VARCHAR, and the TEXT types.

Column definitions for many string data types can include attributes that specify the character set or collation of the column. These attributes apply to the CHAR, VARCHAR, the TEXT types, ENUM, and SET data types:

Character column sorting and comparison are based on the character set assigned to the column. For the CHAR, VARCHAR, TEXT, ENUM, and SET data types, you can declare a column with a binary collation or the BINARY attribute to cause sorting and comparison to use the underlying character code values rather than a lexical ordering.

Section 10.1, “Character Set Support”, provides additional information about use of character sets in MySQL.

MySQL supports the SQL standard integer types INTEGER (or INT) and SMALLINT. As an extension to the standard, MySQL also supports the integer types TINYINT, MEDIUMINT, and BIGINT. The following table shows the required storage and range for each integer type.

The DECIMAL and NUMERIC types store exact numeric data values. These types are used when it is important to preserve exact precision, for example with monetary data. In MySQL, NUMERIC is implemented as DECIMAL, so the following remarks about DECIMAL apply equally to NUMERIC.

MySQL 5.5 stores DECIMAL values in binary format. See Section 12.18, “Precision Math”.

In a DECIMAL column declaration, the precision and scale can be (and usually is) specified; for example:

salary DECIMAL(5,2)

In this example, 5 is the precision and 2 is the scale. The precision represents the number of significant digits that are stored for values, and the scale represents the number of digits that can be stored following the decimal point.

Standard SQL requires that DECIMAL(5,2) be able to store any value with five digits and two decimals, so values that can be stored in the salary column range from -999.99 to 999.99.

In standard SQL, the syntax DECIMAL(M) is equivalent to DECIMAL(M,0). Similarly, the syntax DECIMAL is equivalent to DECIMAL(M,0), where the implementation is permitted to decide the value of M. MySQL supports both of these variant forms of DECIMAL syntax. The default value of M is 10.

If the scale is 0, DECIMAL values contain no decimal point or fractional part.

The maximum number of digits for DECIMAL is 65, but the actual range for a given DECIMAL column can be constrained by the precision or scale for a given column. When such a column is assigned a value with more digits following the decimal point than are permitted by the specified scale, the value is converted to that scale. (The precise behavior is operating system-specific, but generally the effect is truncation to the permissible number of digits.)

The FLOAT and DOUBLE types represent approximate numeric data values. MySQL uses four bytes for single-precision values and eight bytes for double-precision values.

For FLOAT, the SQL standard permits an optional specification of the precision (but not the range of the exponent) in bits following the keyword FLOAT in parentheses. MySQL also supports this optional precision specification, but the precision value is used only to determine storage size. A precision from 0 to 23 results in a 4-byte single-precision FLOAT column. A precision from 24 to 53 results in an 8-byte double-precision DOUBLE column.

MySQL permits a nonstandard syntax: FLOAT(M,D) or REAL(M,D) or DOUBLE PRECISION(M,D). Here, “(M,D)” means than values can be stored with up to M digits in total, of which D digits may be after the decimal point. For example, a column defined as FLOAT(7,4) will look like -999.9999 when displayed. MySQL performs rounding when storing values, so if you insert 999.00009 into a FLOAT(7,4) column, the approximate result is 999.0001.

Because floating-point values are approximate and not stored as exact values, attempts to treat them as exact in comparisons may lead to problems. They are also subject to platform or implementation dependencies. For more information, see Section B.5.5.8, “Problems with Floating-Point Values”

For maximum portability, code requiring storage of approximate numeric data values should use FLOAT or DOUBLE PRECISION with no specification of precision or number of digits.

The BIT data type is used to store bit-field values. A type of BIT(M) enables storage of M-bit values. M can range from 1 to 64.

To specify bit values, b'value' notation can be used. value is a binary value written using zeros and ones. For example, b'111' and b'10000000' represent 7 and 128, respectively. See Section 9.1.6, “Bit-Field Literals”.

If you assign a value to a BIT(M) column that is less than M bits long, the value is padded on the left with zeros. For example, assigning a value of b'101' to a BIT(6) column is, in effect, the same as assigning b'000101'.

MySQL supports an extension for optionally specifying the display width of integer data types in parentheses following the base keyword for the type. For example, INT(4) specifies an INT with a display width of four digits. This optional display width may be used by applications to display integer values having a width less than the width specified for the column by left-padding them with spaces. (That is, this width is present in the metadata returned with result sets. Whether it is used or not is up to the application.)

The display width does not constrain the range of values that can be stored in the column. Nor does it prevent values wider than the column display width from being displayed correctly. For example, a column specified as SMALLINT(3) has the usual SMALLINT range of -32768 to 32767, and values outside the range permitted by three digits are displayed in full using more than three digits.

When used in conjunction with the optional (nonstandard) attribute ZEROFILL, the default padding of spaces is replaced with zeros. For example, for a column declared as INT(4) ZEROFILL, a value of 5 is retrieved as 0005.

All integer types can have an optional (nonstandard) attribute UNSIGNED. Unsigned type can be used to permit only nonnegative numbers in a column or when you need a larger upper numeric range for the column. For example, if an INT column is UNSIGNED, the size of the column's range is the same but its endpoints shift from -2147483648 and 2147483647 up to 0 and 4294967295.

Floating-point and fixed-point types also can be UNSIGNED. As with integer types, this attribute prevents negative values from being stored in the column. Unlike the integer types, the upper range of column values remains the same.

If you specify ZEROFILL for a numeric column, MySQL automatically adds the UNSIGNED attribute to the column.

Integer or floating-point data types can have the additional attribute AUTO_INCREMENT. When you insert a value of NULL (recommended) or 0 into an indexed AUTO_INCREMENT column, the column is set to the next sequence value. Typically this is value+1, where value is the largest value for the column currently in the table. AUTO_INCREMENT sequences begin with 1. (Inserting NULL to generate AUTO_INCREMENT values requires that the column be declared NOT NULL. If the column is declared NULL, inserting NULL stores a NULL.) When you insert any other value into a AUTO_INCREMENT column, the column is set to that value and the sequence is reset so that the next automatically generated value follows sequentially from the inserted value.

As of MySQL 5.5.29, negative values for AUTO_INCREMENT columns are not supported.

When MySQL stores a value in a numeric column that is outside the permissible range of the column data type, the result depends on the SQL mode in effect at the time:

Column-assignment conversions that occur due to clipping when MySQL is not operating in strict mode are reported as warnings for ALTER TABLE, LOAD DATA INFILE, UPDATE, and multiple-row INSERT statements. In strict mode, these statements fail, and some or all the values will not be inserted or changed, depending on whether the table is a transactional table and other factors. For details, see Section 5.1.7, “Server SQL Modes”.

As of MySQL 5.5.5, overflow during numeric expression evaluation results in an error. For example, the largest signed BIGINT value is 9223372036854775807, so the following expression produces an error:

mysql> SELECT 9223372036854775807 + 1;
ERROR 1690 (22003): BIGINT value is out of range in '(9223372036854775807 + 1)'

To enable the operation to succeed in this case, convert the value to unsigned;

mysql> SELECT CAST(9223372036854775807 AS UNSIGNED) + 1;
+-------------------------------------------+
| CAST(9223372036854775807 AS UNSIGNED) + 1 |
+-------------------------------------------+
|                       9223372036854775808 |
+-------------------------------------------+

Whether overflow occurs depends on the range of the operands, so another way to handle the preceding expression is to use exact-value arithmetic because DECIMAL values have a larger range than integers:

mysql> SELECT 9223372036854775807.0 + 1;
+---------------------------+
| 9223372036854775807.0 + 1 |
+---------------------------+
|     9223372036854775808.0 |
+---------------------------+

Before MySQL 5.5.5, overflow handling during numeric expression evaluation depends on the types of the operands:

Subtraction between integer values, where one is of type UNSIGNED, produces an unsigned result by default. Prior to MySQL 5.5.5, if the result would otherwise have been negative, it becomes the maximum integer value:

mysql> SET sql_mode = '';
mysql> SELECT CAST(0 AS UNSIGNED) - 1;
+-------------------------+
| CAST(0 AS UNSIGNED) - 1 |
+-------------------------+
|    18446744073709551615 |
+-------------------------+

As of MySQL 5.5.5, if the result would otherwise have been negative, an error results:

mysql> SET sql_mode = '';
Query OK, 0 rows affected (0.00 sec)

mysql> SELECT CAST(0 AS UNSIGNED) - 1;
ERROR 1690 (22003): BIGINT UNSIGNED value is out of range in '(cast(0 as unsigned) - 1)'

If the NO_UNSIGNED_SUBTRACTION SQL mode is enabled, the result is negative:

mysql> SET sql_mode = 'NO_UNSIGNED_SUBTRACTION';
mysql> SELECT CAST(0 AS UNSIGNED) - 1;
+-------------------------+
| CAST(0 AS UNSIGNED) - 1 |
+-------------------------+
|                      -1 |
+-------------------------+

If the result of such an operation is used to update an UNSIGNED integer column, the result is clipped to the maximum value for the column type, or clipped to 0 if NO_UNSIGNED_SUBTRACTION is enabled. If strict SQL mode is enabled, an error occurs and the column remains unchanged.

The DATE, DATETIME, and TIMESTAMP types are related. This section describes their characteristics, how they are similar, and how they differ. MySQL recognizes DATE, DATETIME, and TIMESTAMP values in several formats, described in Section 9.1.3, “Date and Time Literals”. For the DATE and DATETIME range descriptions, “supported” means that although earlier values might work, there is no guarantee.

The DATE type is used for values with a date part but no time part. MySQL retrieves and displays DATE values in 'YYYY-MM-DD' format. The supported range is '1000-01-01' to '9999-12-31'.

The DATETIME type is used for values that contain both date and time parts. MySQL retrieves and displays DATETIME values in 'YYYY-MM-DD HH:MM:SS' format. The supported range is '1000-01-01 00:00:00' to '9999-12-31 23:59:59'.

The TIMESTAMP data type is used for values that contain both date and time parts. TIMESTAMP has a range of '1970-01-01 00:00:01' UTC to '2038-01-19 03:14:07' UTC.

MySQL converts TIMESTAMP values from the current time zone to UTC for storage, and back from UTC to the current time zone for retrieval. (This does not occur for other types such as DATETIME.) By default, the current time zone for each connection is the server's time. The time zone can be set on a per-connection basis. As long as the time zone setting remains constant, you get back the same value you store. If you store a TIMESTAMP value, and then change the time zone and retrieve the value, the retrieved value is different from the value you stored. This occurs because the same time zone was not used for conversion in both directions. The current time zone is available as the value of the time_zone system variable. For more information, see Section 10.6, “MySQL Server Time Zone Support”.

The TIMESTAMP data type offers automatic initialization and updating to the current date and time. For more information, see Section 11.3.5, “Automatic Initialization and Updating for TIMESTAMP”.

A DATETIME or TIMESTAMP value can include a trailing fractional seconds part in up to microseconds (6 digits) precision. Although this fractional part is recognized, it is discarded from values stored into DATETIME or TIMESTAMP columns. For information about fractional seconds support in MySQL, see Section 11.3.6, “Fractional Seconds in Time Values”.

Invalid DATE, DATETIME, or TIMESTAMP values are converted to the “zero” value of the appropriate type ('0000-00-00' or '0000-00-00 00:00:00').

Be aware of certain properties of date value interpretation in MySQL:

MySQL retrieves and displays TIME values in 'HH:MM:SS' format (or 'HHH:MM:SS' format for large hours values). TIME values may range from '-838:59:59' to '838:59:59'. The hours part may be so large because the TIME type can be used not only to represent a time of day (which must be less than 24 hours), but also elapsed time or a time interval between two events (which may be much greater than 24 hours, or even negative).

MySQL recognizes TIME values in several formats, described in Section 9.1.3, “Date and Time Literals”. Some of these formats can include a trailing fractional seconds part in up to microseconds (6 digits) precision. Although this fractional part is recognized, it is discarded from values stored into TIME columns. For information about fractional seconds support in MySQL, see Section 11.3.6, “Fractional Seconds in Time Values”.

Be careful about assigning abbreviated values to a TIME column. MySQL interprets abbreviated TIME values with colons as time of the day. That is, '11:12' means '11:12:00', not '00:11:12'. MySQL interprets abbreviated values without colons using the assumption that the two rightmost digits represent seconds (that is, as elapsed time rather than as time of day). For example, you might think of '1112' and 1112 as meaning '11:12:00' (12 minutes after 11 o'clock), but MySQL interprets them as '00:11:12' (11 minutes, 12 seconds). Similarly, '12' and 12 are interpreted as '00:00:12'.

By default, values that lie outside the TIME range but are otherwise valid are clipped to the closest endpoint of the range. For example, '-850:00:00' and '850:00:00' are converted to '-838:59:59' and '838:59:59'. Invalid TIME values are converted to '00:00:00'. Note that because '00:00:00' is itself a valid TIME value, there is no way to tell, from a value of '00:00:00' stored in a table, whether the original value was specified as '00:00:00' or whether it was invalid.

For more restrictive treatment of invalid TIME values, enable strict SQL mode to cause errors to occur. See Section 5.1.7, “Server SQL Modes”.

The YEAR type is a 1-byte type used to represent year values. It can be declared as YEAR(4) or YEAR(2) to specify a display width of four or two characters. The default is four characters if no width is given.

YEAR(4) and YEAR(2) differ in display format, but have the same range of values. For 4-digit format, MySQL displays YEAR values in YYYY format, with a range of 1901 to 2155, or 0000. For 2-digit format, MySQL displays only the last two (least significant) digits; for example, 70 (1970 or 2070) or 69 (2069).

You can specify input YEAR values in a variety of formats:

MySQL converts invalid YEAR values to 0000.

See also Section 11.3.8, “Two-Digit Years in Dates”.

This section describes problems that can occur when using YEAR(2) and provides information about converting existing YEAR(2) columns to YEAR(4).

Although the internal range of values for YEAR(4) and YEAR(2) is the same (1901 to 2155, and 0000), the display width for YEAR(2) makes that type inherently ambiguous because displayed values indicate only the last two digits of the internal values and omit the century digits. The result can be a loss of information under certain circumstances. For this reason, consider avoiding YEAR(2) throughout your applications and using YEAR(4) wherever you need a YEAR data type. Note that conversion will become necessary at some point because support for YEAR data types with display values other than 4, most notably YEAR(2), is reduced as of MySQL 5.6.6 and will be removed entirely in a future release.

YEAR(2) Limitations

Issues with the YEAR(2) data type include ambiguity of displayed values, and possible loss of information when values are dumped and reloaded or converted to strings.

To avoid these problems, use YEAR(4) rather than YEAR(2). Suggestions regarding migration strategies appear later in this section.

Migrating from YEAR(2) to YEAR(4)

To convert YEAR(2) columns to YEAR(4), use ALTER TABLE. Suppose that a table t1 has this definition:

CREATE TABLE t1 (ycol YEAR(2) NOT NULL DEFAULT '70');

Modify the column using ALTER TABLE as follows. Remember to include any column attributes such as NOT NULL or DEFAULT:

ALTER TABLE t1 MODIFY ycol YEAR(4) NOT NULL DEFAULT '1970';

The ALTER TABLE statement converts the table without changing YEAR(2) values. If the server is a replication master, the ALTER TABLE statement replicates to slaves and makes the corresponding table change on each one.

One migration method should be avoided: Do not dump your data with mysqldump and reload the dump file after upgrading. This has the potential to change YEAR(2) values, as described previously.

A migration from YEAR(2) to YEAR(4) should also involve examining application code for the possibility of changed behavior under conditions such as these:

The TIMESTAMP data type offers automatic initialization and updating to the current date and time (that is, the current timestamp). You can choose whether to use these properties and which column should have them:

In addition, you can initialize or update any TIMESTAMP column to the current date and time by assigning it a NULL value, unless it has been defined with the NULL attribute to permit NULL values.

To specify automatic properties, use the DEFAULT CURRENT_TIMESTAMP and ON UPDATE CURRENT_TIMESTAMP clauses. The order of the clauses does not matter. If both are present in a column definition, either can occur first. Any of the synonyms for CURRENT_TIMESTAMP have the same meaning as CURRENT_TIMESTAMP. These are CURRENT_TIMESTAMP(), NOW(), LOCALTIME, LOCALTIME(), LOCALTIMESTAMP, and LOCALTIMESTAMP().

Use of DEFAULT CURRENT_TIMESTAMP and ON UPDATE CURRENT_TIMESTAMP is specific to TIMESTAMP. The DEFAULT clause also can be used to specify a constant (nonautomatic) default value; for example, DEFAULT 0 or DEFAULT '2000-01-01 00:00:00'.

The following rules describe the possibilities for defining the first TIMESTAMP column in a table with the current timestamp for both the default and auto-update values, for one but not the other, or for neither:

It need not be the first TIMESTAMP column in a table that is automatically initialized or updated to the current timestamp. However, to specify automatic initialization or updating for a different TIMESTAMP column, you must suppress the automatic properties for the first one. Then, for the other TIMESTAMP column, the rules for the DEFAULT and ON UPDATE clauses are the same as for the first TIMESTAMP column, except that if you omit both clauses, no automatic initialization or updating occurs.

To suppress automatic properties for the first TIMESTAMP column, do either of the following:

Consider these table definitions:

CREATE TABLE t1 (
  ts1 TIMESTAMP DEFAULT 0,
  ts2 TIMESTAMP DEFAULT CURRENT_TIMESTAMP
                ON UPDATE CURRENT_TIMESTAMP);
CREATE TABLE t2 (
  ts1 TIMESTAMP NULL,
  ts2 TIMESTAMP DEFAULT CURRENT_TIMESTAMP
                ON UPDATE CURRENT_TIMESTAMP);
CREATE TABLE t3 (
  ts1 TIMESTAMP NULL DEFAULT 0,
  ts2 TIMESTAMP DEFAULT CURRENT_TIMESTAMP
                ON UPDATE CURRENT_TIMESTAMP);

The tables have these properties:

TIMESTAMP Initialization and the NULL Attribute

By default, TIMESTAMP columns are NOT NULL, cannot contain NULL values, and assigning NULL assigns the current timestamp. To permit a TIMESTAMP column to contain NULL, explicitly declare it with the NULL attribute. In this case, the default value also becomes NULL unless overridden with a DEFAULT clause that specifies a different default value. DEFAULT NULL can be used to explicitly specify NULL as the default value. (For a TIMESTAMP column not declared with the NULL attribute, DEFAULT NULL is invalid.) If a TIMESTAMP column permits NULL values, assigning NULL sets it to NULL, not to the current timestamp.

The following table contains several TIMESTAMP columns that permit NULL values:

CREATE TABLE t
(
  ts1 TIMESTAMP NULL DEFAULT NULL,
  ts2 TIMESTAMP NULL DEFAULT 0,
  ts3 TIMESTAMP NULL DEFAULT CURRENT_TIMESTAMP
);

A TIMESTAMP column that permits NULL values does not take on the current timestamp at insert time except under one of the following conditions:

In other words, a TIMESTAMP column defined to permit NULL values auto-initializes only if its definition includes DEFAULT CURRENT_TIMESTAMP:

CREATE TABLE t (ts TIMESTAMP NULL DEFAULT CURRENT_TIMESTAMP);

If the TIMESTAMP column permits NULL values but its definition does not include DEFAULT CURRENT_TIMESTAMP, you must explicitly insert a value corresponding to the current date and time. Suppose that tables t1 and t2 have these definitions:

CREATE TABLE t1 (ts TIMESTAMP NULL DEFAULT '0000-00-00 00:00:00');
CREATE TABLE t2 (ts TIMESTAMP NULL DEFAULT NULL);

To set the TIMESTAMP column in either table to the current timestamp at insert time, explicitly assign it that value. For example:

INSERT INTO t1 VALUES (NOW());
INSERT INTO t2 VALUES (CURRENT_TIMESTAMP);

A trailing fractional seconds part is permissible for temporal values in contexts such as literal values, and in the arguments to or return values from some temporal functions. Example:

mysql> SELECT MICROSECOND('2010-12-10 14:12:09.019473');
+-------------------------------------------+
| MICROSECOND('2010-12-10 14:12:09.019473') |
+-------------------------------------------+
|                                     19473 |
+-------------------------------------------+

However, when MySQL stores a value into a column of any temporal data type, it discards any fractional part and does not store it.

To some extent, you can convert a value from one temporal type to another. However, there may be some alteration of the value or loss of information. In all cases, conversion between temporal types is subject to the range of valid values for the resulting type. For example, although DATE, DATETIME, and TIMESTAMP values all can be specified using the same set of formats, the types do not all have the same range of values. TIMESTAMP values cannot be earlier than 1970 UTC or later than '2038-01-19 03:14:07' UTC. This means that a date such as '1968-01-01', while valid as a DATE or DATETIME value, is not valid as a TIMESTAMP value and is converted to 0.

Conversion of DATE values:

Conversion of DATETIME and TIMESTAMP values:

Conversion of TIME values:

MySQL converts a time value to a date or date-and-time value by parsing the string value of the time as a date or date-and-time. This is unlikely to be useful. For example, '23:12:31' interpreted as a date becomes '2023-12-31'. Time values not valid as dates become '0000-00-00' or NULL.

Explicit conversion can be used to override implicit conversion. For example, in comparison of DATE and DATETIME values, the DATE value is coerced to the DATETIME type by adding a time part of '00:00:00'. To perform the comparison by ignoring the time part of the DATETIME value instead, use the CAST() function in the following way:

date_col = CAST(datetime_col AS DATE)

Conversion of TIME or DATETIME values to numeric form (for example, by adding +0) results in a double-precision value with a microseconds part of .000000:

mysql> SELECT CURTIME(), CURTIME()+0;
+-----------+---------------+
| CURTIME() | CURTIME()+0   |
+-----------+---------------+
| 10:41:36  | 104136.000000 |
+-----------+---------------+
mysql> SELECT NOW(), NOW()+0;
+---------------------+-----------------------+
| NOW()               | NOW()+0               |
+---------------------+-----------------------+
| 2007-11-30 10:41:47 | 20071130104147.000000 |
+---------------------+-----------------------+

Date values with two-digit years are ambiguous because the century is unknown. Such values must be interpreted into four-digit form because MySQL stores years internally using four digits.

For DATETIME, DATE, and TIMESTAMP types, MySQL interprets dates specified with ambiguous year values using these rules:

For YEAR, the rules are the same, with this exception: A numeric 00 inserted into YEAR(4) results in 0000 rather than 2000. To specify zero for YEAR(4) and have it be interpreted as 2000, specify it as a string '0' or '00'.

Remember that these rules are only heuristics that provide reasonable guesses as to what your data values mean. If the rules used by MySQL do not produce the values you require, you must provide unambiguous input containing four-digit year values.

ORDER BY properly sorts YEAR values that have two-digit years.

Some functions like MIN() and MAX() convert a YEAR to a number. This means that a value with a two-digit year does not work properly with these functions. The fix in this case is to convert the YEAR to four-digit year format.

The CHAR and VARCHAR types are similar, but differ in the way they are stored and retrieved. They also differ in maximum length and in whether trailing spaces are retained.

The CHAR and VARCHAR types are declared with a length that indicates the maximum number of characters you want to store. For example, CHAR(30) can hold up to 30 characters.

The length of a CHAR column is fixed to the length that you declare when you create the table. The length can be any value from 0 to 255. When CHAR values are stored, they are right-padded with spaces to the specified length. When CHAR values are retrieved, trailing spaces are removed unless the PAD_CHAR_TO_FULL_LENGTH SQL mode is enabled.

Values in VARCHAR columns are variable-length strings. The length can be specified as a value from 0 to 65,535. The effective maximum length of a VARCHAR is subject to the maximum row size (65,535 bytes, which is shared among all columns) and the character set used. See Section D.10.4, “Limits on Table Column Count and Row Size”.

In contrast to CHAR, VARCHAR values are stored as a 1-byte or 2-byte length prefix plus data. The length prefix indicates the number of bytes in the value. A column uses one length byte if values require no more than 255 bytes, two length bytes if values may require more than 255 bytes.

If strict SQL mode is not enabled and you assign a value to a CHAR or VARCHAR column that exceeds the column's maximum length, the value is truncated to fit and a warning is generated. For truncation of nonspace characters, you can cause an error to occur (rather than a warning) and suppress insertion of the value by using strict SQL mode. See Section 5.1.7, “Server SQL Modes”.

For VARCHAR columns, trailing spaces in excess of the column length are truncated prior to insertion and a warning is generated, regardless of the SQL mode in use. For CHAR columns, truncation of excess trailing spaces from inserted values is performed silently regardless of the SQL mode.

VARCHAR values are not padded when they are stored. Trailing spaces are retained when values are stored and retrieved, in conformance with standard SQL.

The following table illustrates the differences between CHAR and VARCHAR by showing the result of storing various string values into CHAR(4) and VARCHAR(4) columns (assuming that the column uses a single-byte character set such as latin1).

The values shown as stored in the last row of the table apply only when not using strict mode; if MySQL is running in strict mode, values that exceed the column length are not stored, and an error results.

If a given value is stored into the CHAR(4) and VARCHAR(4) columns, the values retrieved from the columns are not always the same because trailing spaces are removed from CHAR columns upon retrieval. The following example illustrates this difference:

mysql> CREATE TABLE vc (v VARCHAR(4), c CHAR(4));
Query OK, 0 rows affected (0.01 sec)

mysql> INSERT INTO vc VALUES ('ab  ', 'ab  ');
Query OK, 1 row affected (0.00 sec)

mysql> SELECT CONCAT('(', v, ')'), CONCAT('(', c, ')') FROM vc;
+---------------------+---------------------+
| CONCAT('(', v, ')') | CONCAT('(', c, ')') |
+---------------------+---------------------+
| (ab  )              | (ab)                |
+---------------------+---------------------+
1 row in set (0.06 sec)

Values in CHAR and VARCHAR columns are sorted and compared according to the character set collation assigned to the column.

All MySQL collations are of type PADSPACE. This means that all CHAR, VARCHAR, and TEXT values in MySQL are compared without regard to any trailing spaces. “Comparison” in this context does not include the LIKE pattern-matching operator, for which trailing spaces are significant. For example:

mysql> CREATE TABLE names (myname CHAR(10));
Query OK, 0 rows affected (0.03 sec)

mysql> INSERT INTO names VALUES ('Monty');
Query OK, 1 row affected (0.00 sec)

mysql> SELECT myname = 'Monty', myname = 'Monty  ' FROM names;
+------------------+--------------------+
| myname = 'Monty' | myname = 'Monty  ' |
+------------------+--------------------+
|                1 |                  1 |
+------------------+--------------------+
1 row in set (0.00 sec)

mysql> SELECT myname LIKE 'Monty', myname LIKE 'Monty  ' FROM names;
+---------------------+-----------------------+
| myname LIKE 'Monty' | myname LIKE 'Monty  ' |
+---------------------+-----------------------+
|                   1 |                     0 |
+---------------------+-----------------------+
1 row in set (0.00 sec)

This is true for all MySQL versions, and is not affected by the server SQL mode.

For those cases where trailing pad characters are stripped or comparisons ignore them, if a column has an index that requires unique values, inserting into the column values that differ only in number of trailing pad characters will result in a duplicate-key error. For example, if a table contains 'a', an attempt to store 'a ' causes a duplicate-key error.

The BINARY and VARBINARY types are similar to CHAR and VARCHAR, except that they contain binary strings rather than nonbinary strings. That is, they contain byte strings rather than character strings. This means that they have no character set, and sorting and comparison are based on the numeric values of the bytes in the values.

The permissible maximum length is the same for BINARY and VARBINARY as it is for CHAR and VARCHAR, except that the length for BINARY and VARBINARY is a length in bytes rather than in characters.

The BINARY and VARBINARY data types are distinct from the CHAR BINARY and VARCHAR BINARY data types. For the latter types, the BINARY attribute does not cause the column to be treated as a binary string column. Instead, it causes the binary collation for the column character set to be used, and the column itself contains nonbinary character strings rather than binary byte strings. For example, CHAR(5) BINARY is treated as CHAR(5) CHARACTER SET latin1 COLLATE latin1_bin, assuming that the default character set is latin1. This differs from BINARY(5), which stores 5-bytes binary strings that have no character set or collation. For information about differences between nonbinary string binary collations and binary strings, see Section 10.1.7.6, “The _bin and binary Collations”.

If strict SQL mode is not enabled and you assign a value to a BINARY or VARBINARY column that exceeds the column's maximum length, the value is truncated to fit and a warning is generated. For cases of truncation, you can cause an error to occur (rather than a warning) and suppress insertion of the value by using strict SQL mode. See Section 5.1.7, “Server SQL Modes”.

When BINARY values are stored, they are right-padded with the pad value to the specified length. The pad value is 0x00 (the zero byte). Values are right-padded with 0x00 on insert, and no trailing bytes are removed on select. All bytes are significant in comparisons, including ORDER BY and DISTINCT operations. 0x00 bytes and spaces are different in comparisons, with 0x00 < space.

Example: For a BINARY(3) column, 'a ' becomes 'a \0' when inserted. 'a\0' becomes 'a\0\0' when inserted. Both inserted values remain unchanged when selected.

For VARBINARY, there is no padding on insert and no bytes are stripped on select. All bytes are significant in comparisons, including ORDER BY and DISTINCT operations. 0x00 bytes and spaces are different in comparisons, with 0x00 < space.

For those cases where trailing pad bytes are stripped or comparisons ignore them, if a column has an index that requires unique values, inserting into the column values that differ only in number of trailing pad bytes will result in a duplicate-key error. For example, if a table contains 'a', an attempt to store 'a\0' causes a duplicate-key error.

You should consider the preceding padding and stripping characteristics carefully if you plan to use the BINARY data type for storing binary data and you require that the value retrieved be exactly the same as the value stored. The following example illustrates how 0x00-padding of BINARY values affects column value comparisons:

mysql> CREATE TABLE t (c BINARY(3));
Query OK, 0 rows affected (0.01 sec)

mysql> INSERT INTO t SET c = 'a';
Query OK, 1 row affected (0.01 sec)

mysql> SELECT HEX(c), c = 'a', c = 'a\0\0' from t;
+--------+---------+-------------+
| HEX(c) | c = 'a' | c = 'a\0\0' |
+--------+---------+-------------+
| 610000 |       0 |           1 |
+--------+---------+-------------+
1 row in set (0.09 sec)

If the value retrieved must be the same as the value specified for storage with no padding, it might be preferable to use VARBINARY or one of the BLOB data types instead.

A BLOB is a binary large object that can hold a variable amount of data. The four BLOB types are TINYBLOB, BLOB, MEDIUMBLOB, and LONGBLOB. These differ only in the maximum length of the values they can hold. The four TEXT types are TINYTEXT, TEXT, MEDIUMTEXT, and LONGTEXT. These correspond to the four BLOB types and have the same maximum lengths and storage requirements. See Section 11.7, “Data Type Storage Requirements”.

BLOB values are treated as binary strings (byte strings). They have no character set, and sorting and comparison are based on the numeric values of the bytes in column values. TEXT values are treated as nonbinary strings (character strings). They have a character set, and values are sorted and compared based on the collation of the character set.

If strict SQL mode is not enabled and you assign a value to a BLOB or TEXT column that exceeds the column's maximum length, the value is truncated to fit and a warning is generated. For truncation of nonspace characters, you can cause an error to occur (rather than a warning) and suppress insertion of the value by using strict SQL mode. See Section 5.1.7, “Server SQL Modes”.

Truncation of excess trailing spaces from values to be inserted into TEXT columns always generates a warning, regardless of the SQL mode.

For TEXT and BLOB columns, there is no padding on insert and no bytes are stripped on select.

If a TEXT column is indexed, index entry comparisons are space-padded at the end. This means that, if the index requires unique values, duplicate-key errors will occur for values that differ only in the number of trailing spaces. For example, if a table contains 'a', an attempt to store 'a ' causes a duplicate-key error. This is not true for BLOB columns.

In most respects, you can regard a BLOB column as a VARBINARY column that can be as large as you like. Similarly, you can regard a TEXT column as a VARCHAR column. BLOB and TEXT differ from VARBINARY and VARCHAR in the following ways:

If you use the BINARY attribute with a TEXT data type, the column is assigned the binary collation of the column character set.

LONG and LONG VARCHAR map to the MEDIUMTEXT data type. This is a compatibility feature.

MySQL Connector/ODBC defines BLOB values as LONGVARBINARY and TEXT values as LONGVARCHAR.

Because BLOB and TEXT values can be extremely long, you might encounter some constraints in using them:

Each BLOB or TEXT value is represented internally by a separately allocated object. This is in contrast to all other data types, for which storage is allocated once per column when the table is opened.

In some cases, it may be desirable to store binary data such as media files in BLOB or TEXT columns. You may find MySQL's string handling functions useful for working with such data. See Section 12.5, “String Functions”. For security and other reasons, it is usually preferable to do so using application code rather than giving application users the FILE privilege. You can discuss specifics for various languages and platforms in the MySQL Forums (http://forums.mysql.com/).

An ENUM is a string object with a value chosen from a list of permitted values that are enumerated explicitly in the column specification at table creation time. It has these advantages:

and these potential issues to consider:

Creating and Using ENUM Columns

An enumeration value must be a quoted string literal. For example, you can create a table with an ENUM column like this:

CREATE TABLE shirts (
    name VARCHAR(40),
    size ENUM('x-small', 'small', 'medium', 'large', 'x-large')
);
INSERT INTO shirts (name, size) VALUES ('dress shirt','large'), ('t-shirt','medium'),
  ('polo shirt','small');
SELECT name, size FROM shirts WHERE size = 'medium';
+---------+--------+
| name    | size   |
+---------+--------+
| t-shirt | medium |
+---------+--------+
UPDATE shirts SET size = 'small' WHERE size = 'large';
COMMIT;

Inserting 1 million rows into this table with a value of 'medium' would require 1 million bytes of storage, as opposed to 6 million bytes if you stored the actual string 'medium' in a VARCHAR column.

Index Values for Enumeration Literals

Each enumeration value has an index:

For example, a column specified as ENUM('Mercury', 'Venus', 'Earth') can have any of the values shown here. The index of each value is also shown.

An ENUM column can have a maximum of 65,535 distinct elements. (The practical limit is less than 3000.) A table can have no more than 255 unique element list definitions among its ENUM and SET columns considered as a group. For more information on these limits, see Section D.10.5, “Limits Imposed by .frm File Structure”.

If you retrieve an ENUM value in a numeric context, the column value's index is returned. For example, you can retrieve numeric values from an ENUM column like this:

mysql> SELECT enum_col+0 FROM tbl_name;

Functions such as SUM() or AVG() that expect a numeric argument cast the argument to a number if necessary. For ENUM values, the index number is used in the calculation.

Handling of Enumeration Literals

Trailing spaces are automatically deleted from ENUM member values in the table definition when a table is created.

When retrieved, values stored into an ENUM column are displayed using the lettercase that was used in the column definition. Note that ENUM columns can be assigned a character set and collation. For binary or case-sensitive collations, lettercase is taken into account when assigning values to the column.

If you store a number into an ENUM column, the number is treated as the index into the possible values, and the value stored is the enumeration member with that index. (However, this does not work with LOAD DATA, which treats all input as strings.) If the numeric value is quoted, it is still interpreted as an index if there is no matching string in the list of enumeration values. For these reasons, it is not advisable to define an ENUM column with enumeration values that look like numbers, because this can easily become confusing. For example, the following column has enumeration members with string values of '0', '1', and '2', but numeric index values of 1, 2, and 3:

numbers ENUM('0','1','2')

If you store 2, it is interpreted as an index value, and becomes '1' (the value with index 2). If you store '2', it matches an enumeration value, so it is stored as '2'. If you store '3', it does not match any enumeration value, so it is treated as an index and becomes '2' (the value with index 3).

mysql> INSERT INTO t (numbers) VALUES(2),('2'),('3');
mysql> SELECT * FROM t;
+---------+
| numbers |
+---------+
| 1       |
| 2       |
| 2       |
+---------+

To determine all possible values for an ENUM column, use SHOW COLUMNS FROM tbl_name LIKE 'enum_col' and parse the ENUM definition in the Type column of the output.

In the C API, ENUM values are returned as strings. For information about using result set metadata to distinguish them from other strings, see Section 23.8.5, “C API Data Structures”.

Empty or NULL Enumeration Values

An enumeration value can also be the empty string ('') or NULL under certain circumstances:

Enumeration Sorting

ENUM values are sorted based on their index numbers, which depend on the order in which the enumeration members were listed in the column specification. For example, 'b' sorts before 'a' for ENUM('b', 'a'). The empty string sorts before nonempty strings, and NULL values sort before all other enumeration values.

To prevent unexpected results when using the ORDER BY clause on an ENUM column, use one of these techniques:

Enumeration Limitations

An enumeration value cannot be an expression, even one that evaluates to a string value.

For example, this CREATE TABLE statement does not work because the CONCAT function cannot be used to construct an enumeration value:

CREATE TABLE sizes (
    size ENUM('small', CONCAT('med','ium'), 'large')
);

You also cannot employ a user variable as an enumeration value. This pair of statements do not work:

SET @mysize = 'medium';

CREATE TABLE sizes (
    size ENUM('small', @mysize, 'large')
);

We strongly recommend that you do not use numbers as enumeration values, because it does not save on storage over the appropriate TINYINT or SMALLINT type, and it is easy to mix up the strings and the underlying number values (which might not be the same) if you quote the ENUM values incorrectly. If you do use a number as an enumeration value, always enclose it in quotation marks. If the quotation marks are omitted, the number is regarded as an index. See Handling of Enumeration Literals to see how even a quoted number could be mistakenly used as a numeric index value.

Duplicate values in the definition cause a warning, or an error if strict SQL mode is enabled.

A SET is a string object that can have zero or more values, each of which must be chosen from a list of permitted values specified when the table is created. SET column values that consist of multiple set members are specified with members separated by commas (“,”). A consequence of this is that SET member values should not themselves contain commas.

For example, a column specified as SET('one', 'two') NOT NULL can have any of these values:

''
'one'
'two'
'one,two'

A SET column can have a maximum of 64 distinct members. A table can have no more than 255 unique element list definitions among its ENUM and SET columns considered as a group. For more information on this limit, see Section D.10.5, “Limits Imposed by .frm File Structure”.

Duplicate values in the definition cause a warning, or an error if strict SQL mode is enabled.

Trailing spaces are automatically deleted from SET member values in the table definition when a table is created.

When retrieved, values stored in a SET column are displayed using the lettercase that was used in the column definition. Note that SET columns can be assigned a character set and collation. For binary or case-sensitive collations, lettercase is taken into account when assigning values to the column.

MySQL stores SET values numerically, with the low-order bit of the stored value corresponding to the first set member. If you retrieve a SET value in a numeric context, the value retrieved has bits set corresponding to the set members that make up the column value. For example, you can retrieve numeric values from a SET column like this:

mysql> SELECT set_col+0 FROM tbl_name;

If a number is stored into a SET column, the bits that are set in the binary representation of the number determine the set members in the column value. For a column specified as SET('a','b','c','d'), the members have the following decimal and binary values.

If you assign a value of 9 to this column, that is 1001 in binary, so the first and fourth SET value members 'a' and 'd' are selected and the resulting value is 'a,d'.

For a value containing more than one SET element, it does not matter what order the elements are listed in when you insert the value. It also does not matter how many times a given element is listed in the value. When the value is retrieved later, each element in the value appears once, with elements listed according to the order in which they were specified at table creation time. For example, suppose that a column is specified as SET('a','b','c','d'):

mysql> CREATE TABLE myset (col SET('a', 'b', 'c', 'd'));

If you insert the values 'a,d', 'd,a', 'a,d,d', 'a,d,a', and 'd,a,d':

mysql> INSERT INTO myset (col) VALUES 
-> ('a,d'), ('d,a'), ('a,d,a'), ('a,d,d'), ('d,a,d');
Query OK, 5 rows affected (0.01 sec)
Records: 5  Duplicates: 0  Warnings: 0

Then all these values appear as 'a,d' when retrieved:

mysql> SELECT col FROM myset;
+------+
| col  |
+------+
| a,d  |
| a,d  |
| a,d  |
| a,d  |
| a,d  |
+------+
5 rows in set (0.04 sec)

If you set a SET column to an unsupported value, the value is ignored and a warning is issued:

mysql> INSERT INTO myset (col) VALUES ('a,d,d,s');
Query OK, 1 row affected, 1 warning (0.03 sec)

mysql> SHOW WARNINGS;
+---------+------+------------------------------------------+
| Level   | Code | Message                                  |
+---------+------+------------------------------------------+
| Warning | 1265 | Data truncated for column 'col' at row 1 |
+---------+------+------------------------------------------+
1 row in set (0.04 sec)

mysql> SELECT col FROM myset;
+------+
| col  |
+------+
| a,d  |
| a,d  |
| a,d  |
| a,d  |
| a,d  |
| a,d  |
+------+
6 rows in set (0.01 sec)

If strict SQL mode is enabled, attempts to insert invalid SET values result in an error.

SET values are sorted numerically. NULL values sort before non-NULL SET values.

Functions such as SUM() or AVG() that expect a numeric argument cast the argument to a number if necessary. For SET values, the cast operation causes the numeric value to be used.

Normally, you search for SET values using the FIND_IN_SET() function or the LIKE operator:

mysql> SELECT * FROM tbl_name WHERE FIND_IN_SET('value',set_col)>0;
mysql> SELECT * FROM tbl_name WHERE set_col LIKE '%value%';

The first statement finds rows where set_col contains the value set member. The second is similar, but not the same: It finds rows where set_col contains value anywhere, even as a substring of another set member.

The following statements also are permitted:

mysql> SELECT * FROM tbl_name WHERE set_col & 1;
mysql> SELECT * FROM tbl_name WHERE set_col = 'val1,val2';

The first of these statements looks for values containing the first set member. The second looks for an exact match. Be careful with comparisons of the second type. Comparing set values to 'val1,val2' returns different results than comparing values to 'val2,val1'. You should specify the values in the same order they are listed in the column definition.

To determine all possible values for a SET column, use SHOW COLUMNS FROM tbl_name LIKE set_col and parse the SET definition in the Type column of the output.

In the C API, SET values are returned as strings. For information about using result set metadata to distinguish them from other strings, see Section 23.8.5, “C API Data Structures”.

MySQL has data types that correspond to OpenGIS classes. Some of these types hold single geometry values:

GEOMETRY can store geometry values of any type. The other single-value types (POINT, LINESTRING, and POLYGON) restrict their values to a particular geometry type.

The other data types hold collections of values:

GEOMETRYCOLLECTION can store a collection of objects of any type. The other collection types (MULTIPOINT, MULTILINESTRING, MULTIPOLYGON, and GEOMETRYCOLLECTION) restrict collection members to those having a particular geometry type.

MySQL spatial data types have their basis in the OpenGIS geometry model, described in Section 11.5.2, “The OpenGIS Geometry Model”. For examples showing how to use spatial data types in MySQL, see Section 11.5.3, “Using Spatial Data”.

The set of geometry types proposed by OGC's SQL with Geometry Types environment is based on the OpenGIS Geometry Model. In this model, each geometric object has the following general properties:

This section describes how to create tables that include spatial data type columns, and how to manipulate spatial information.

0101000000000000000000F03F000000000000F03F

Byte order:   01
WKB type:     01000000
X coordinate: 000000000000F03F
Y coordinate: 000000000000F03F

SET @g = 'LINESTRING(0 0,1 1,2 2)';
INSERT INTO geom VALUES (GeomFromText(@g));

SET @g = 'POLYGON((0 0,10 0,10 10,0 10,0 0),(5 5,7 5,7 7,5 7, 5 5))';
INSERT INTO geom VALUES (GeomFromText(@g));

SET @g =
'GEOMETRYCOLLECTION(POINT(1 1),LINESTRING(0 0,1 1,2 2,3 3,4 4))';
INSERT INTO geom VALUES (GeomFromText(@g));

SET @g = 'POINT(1 1)';
INSERT INTO geom VALUES (PointFromText(@g));

SET @g = 'LINESTRING(0 0,1 1,2 2)';
INSERT INTO geom VALUES (LineStringFromText(@g));

SET @g = 'POLYGON((0 0,10 0,10 10,0 10,0 0),(5 5,7 5,7 7,5 7, 5 5))';
INSERT INTO geom VALUES (PolygonFromText(@g));

SET @g =
'GEOMETRYCOLLECTION(POINT(1 1),LINESTRING(0 0,1 1,2 2,3 3,4 4))';
INSERT INTO geom VALUES (GeomCollFromText(@g));

mysql> DESCRIBE geom;
+-------+----------+------+-----+---------+----------------+
| Field | Type     | Null | Key | Default | Extra          |
+-------+----------+------+-----+---------+----------------+
| fid   | int(11)  |      | PRI | NULL    | auto_increment |
| g     | geometry |      |     |         |                |
+-------+----------+------+-----+---------+----------------+
2 rows in set (0.00 sec)

mysql> SELECT COUNT(*) FROM geom;
+----------+
| count(*) |
+----------+
|    32376 |
+----------+
1 row in set (0.00 sec)

mysql> ALTER TABLE geom ADD SPATIAL INDEX(g) ENGINE=MyISAM;
Query OK, 32376 rows affected (4.05 sec)
Records: 32376  Duplicates: 0  Warnings: 0

mysql> SET @poly =
    -> 'Polygon((30000 15000,
                 31000 15000,
                 31000 16000,
                 30000 16000,
                 30000 15000))';
mysql> SELECT fid,AsText(g) FROM geom WHERE
    -> MBRContains(GeomFromText(@poly),g);
+-----+---------------------------------------------------------------+
| fid | AsText(g)                                                     |
+-----+---------------------------------------------------------------+
|  21 | LINESTRING(30350.4 15828.8,30350.6 15845,30333.8 15845,30 ... |
|  22 | LINESTRING(30350.6 15871.4,30350.6 15887.8,30334 15887.8, ... |
|  23 | LINESTRING(30350.6 15914.2,30350.6 15930.4,30334 15930.4, ... |
|  24 | LINESTRING(30290.2 15823,30290.2 15839.4,30273.4 15839.4, ... |
|  25 | LINESTRING(30291.4 15866.2,30291.6 15882.4,30274.8 15882. ... |
|  26 | LINESTRING(30291.6 15918.2,30291.6 15934.4,30275 15934.4, ... |
| 249 | LINESTRING(30337.8 15938.6,30337.8 15946.8,30320.4 15946. ... |
|   1 | LINESTRING(30250.4 15129.2,30248.8 15138.4,30238.2 15136. ... |
|   2 | LINESTRING(30220.2 15122.8,30217.2 15137.8,30207.6 15136, ... |
|   3 | LINESTRING(30179 15114.4,30176.6 15129.4,30167 15128,3016 ... |
|   4 | LINESTRING(30155.2 15121.4,30140.4 15118.6,30142 15109,30 ... |
|   5 | LINESTRING(30192.4 15085,30177.6 15082.2,30179.2 15072.4, ... |
|   6 | LINESTRING(30244 15087,30229 15086.2,30229.4 15076.4,3024 ... |
|   7 | LINESTRING(30200.6 15059.4,30185.6 15058.6,30186 15048.8, ... |
|  10 | LINESTRING(30179.6 15017.8,30181 15002.8,30190.8 15003.6, ... |
|  11 | LINESTRING(30154.2 15000.4,30168.6 15004.8,30166 15014.2, ... |
|  13 | LINESTRING(30105 15065.8,30108.4 15050.8,30118 15053,3011 ... |
| 154 | LINESTRING(30276.2 15143.8,30261.4 15141,30263 15131.4,30 ... |
| 155 | LINESTRING(30269.8 15084,30269.4 15093.4,30258.6 15093,30 ... |
| 157 | LINESTRING(30128.2 15011,30113.2 15010.2,30113.6 15000.4, ... |
+-----+---------------------------------------------------------------+
20 rows in set (0.00 sec)

mysql> SET @poly =
    -> 'Polygon((30000 15000,
                 31000 15000,
                 31000 16000,
                 30000 16000,
                 30000 15000))';
mysql> EXPLAIN SELECT fid,AsText(g) FROM geom WHERE
    -> MBRContains(GeomFromText(@poly),g)\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: geom
         type: range
possible_keys: g
          key: g
      key_len: 32
          ref: NULL
         rows: 50
        Extra: Using where
1 row in set (0.00 sec)

mysql> SET @poly =
    -> 'Polygon((30000 15000,
                 31000 15000,
                 31000 16000,
                 30000 16000,
                 30000 15000))';
mysql> EXPLAIN SELECT fid,AsText(g) FROM g IGNORE INDEX (g) WHERE
    -> MBRContains(GeomFromText(@poly),g)\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: geom
         type: ALL
possible_keys: NULL
          key: NULL
      key_len: NULL
          ref: NULL
         rows: 32376
        Extra: Using where
1 row in set (0.00 sec)

mysql> SET @poly =
    -> 'Polygon((30000 15000,
                 31000 15000,
                 31000 16000,
                 30000 16000,
                 30000 15000))';
mysql> SELECT fid,AsText(g) FROM geom IGNORE INDEX (g) WHERE
    -> MBRContains(GeomFromText(@poly),g);
+-----+---------------------------------------------------------------+
| fid | AsText(g)                                                     |
+-----+---------------------------------------------------------------+
|   1 | LINESTRING(30250.4 15129.2,30248.8 15138.4,30238.2 15136. ... |
|   2 | LINESTRING(30220.2 15122.8,30217.2 15137.8,30207.6 15136, ... |
|   3 | LINESTRING(30179 15114.4,30176.6 15129.4,30167 15128,3016 ... |
|   4 | LINESTRING(30155.2 15121.4,30140.4 15118.6,30142 15109,30 ... |
|   5 | LINESTRING(30192.4 15085,30177.6 15082.2,30179.2 15072.4, ... |
|   6 | LINESTRING(30244 15087,30229 15086.2,30229.4 15076.4,3024 ... |
|   7 | LINESTRING(30200.6 15059.4,30185.6 15058.6,30186 15048.8, ... |
|  10 | LINESTRING(30179.6 15017.8,30181 15002.8,30190.8 15003.6, ... |
|  11 | LINESTRING(30154.2 15000.4,30168.6 15004.8,30166 15014.2, ... |
|  13 | LINESTRING(30105 15065.8,30108.4 15050.8,30118 15053,3011 ... |
|  21 | LINESTRING(30350.4 15828.8,30350.6 15845,30333.8 15845,30 ... |
|  22 | LINESTRING(30350.6 15871.4,30350.6 15887.8,30334 15887.8, ... |
|  23 | LINESTRING(30350.6 15914.2,30350.6 15930.4,30334 15930.4, ... |
|  24 | LINESTRING(30290.2 15823,30290.2 15839.4,30273.4 15839.4, ... |
|  25 | LINESTRING(30291.4 15866.2,30291.6 15882.4,30274.8 15882. ... |
|  26 | LINESTRING(30291.6 15918.2,30291.6 15934.4,30275 15934.4, ... |
| 154 | LINESTRING(30276.2 15143.8,30261.4 15141,30263 15131.4,30 ... |
| 155 | LINESTRING(30269.8 15084,30269.4 15093.4,30258.6 15093,30 ... |
| 157 | LINESTRING(30128.2 15011,30113.2 15010.2,30113.6 15000.4, ... |
| 249 | LINESTRING(30337.8 15938.6,30337.8 15946.8,30320.4 15946. ... |
+-----+---------------------------------------------------------------+
20 rows in set (0.46 sec)