Pre-General Availability Draft: 2017-11-16
This section provides a conceptual overview of partitioning in MySQL 8.0.
For information on partitioning restrictions and feature limitations, see Section 23.6, “Restrictions and Limitations on Partitioning”.
The SQL standard does not provide much in the way of guidance
regarding the physical aspects of data storage. The SQL language
itself is intended to work independently of any data structures or
media underlying the schemas, tables, rows, or columns with which
it works. Nonetheless, most advanced database management systems
have evolved some means of determining the physical location to be
used for storing specific pieces of data in terms of the file
system, hardware or even both. In MySQL, the
InnoDB storage engine has long supported the
notion of a tablespace (see Section 15.7, “InnoDB Tablespaces”),
and the MySQL Server, even prior to the introduction of
partitioning, could be configured to employ different physical
directories for storing different databases (see
Section 8.12.2, “Using Symbolic Links”, for an explanation of how this
Partitioning takes this notion a step further, by enabling you to distribute portions of individual tables across a file system according to rules which you can set largely as needed. In effect, different portions of a table are stored as separate tables in different locations. The user-selected rule by which the division of data is accomplished is known as a partitioning function, which in MySQL can be the modulus, simple matching against a set of ranges or value lists, an internal hashing function, or a linear hashing function. The function is selected according to the partitioning type specified by the user, and takes as its parameter the value of a user-supplied expression. This expression can be a column value, a function acting on one or more column values, or a set of one or more column values, depending on the type of partitioning that is used.
In the case of
partitioning, the value of the partitioning column is passed to
the partitioning function, which returns an integer value
representing the number of the partition in which that particular
record should be stored. This function must be nonconstant and
nonrandom. It may not contain any queries, but may use an SQL
expression that is valid in MySQL, as long as that expression
NULL or an integer
intval such that
-MAXVALUE <= intval <= MAXVALUE
MAXVALUE is used to represent the least upper
bound for the type of integer in question.
-MAXVALUE represents the greatest lower bound.)
RANGE COLUMNS, and
COLUMNS partitioning, the partitioning expression
consists of a list of one or more columns.
partitioning, the partitioning function is supplied by MySQL.
For more information about permitted partitioning column types and partitioning functions, see Section 23.2, “Partitioning Types”, as well as Section 13.1.17, “CREATE TABLE Syntax”, which provides partitioning syntax descriptions and additional examples. For information about restrictions on partitioning functions, see Section 23.6.3, “Partitioning Limitations Relating to Functions”.
This is known as horizontal partitioning—that is, different rows of a table may be assigned to different physical partitions. MySQL 8.0 does not support vertical partitioning, in which different columns of a table are assigned to different physical partitions. There are no plans at this time to introduce vertical partitioning into MySQL.
For creating partitioned tables, you must use a storage engine that supports them. In MySQL 8.0, all partitions of the same partitioned table must use the same storage engine. However, there is nothing preventing you from using different storage engines for different partitioned tables on the same MySQL server or even in the same database.
In MySQL 8.0, the only storage engine that supports
InnoDB. Partitioning cannot be
used with storage engines that do not support it; these include
When creating a partitioned table, the default storage engine is
used just as when creating any other table; to override this
behavior, it is necessary only to use the
ENGINE option just as you would for a table that is not
partitioned. The target storage engine must provide native
partitioning support, or the statement fails. You should keep in
[STORAGE] ENGINE (and other table
options) need to be listed before any
partitioning options are used in a
TABLE statement. This example shows how to create a
table that is partitioned by hash into 6 partitions and which uses
InnoDB storage engine (regardless of the
CREATE TABLE ti (id INT, amount DECIMAL(7,2), tr_date DATE) ENGINE=INNODB PARTITION BY HASH( MONTH(tr_date) ) PARTITIONS 6;
PARTITION clause can include a
[STORAGE] ENGINE option, but in MySQL
8.0 this has no effect.
Unless otherwise specified, the remaining examples in this
discussion assume that
Partitioning applies to all data and indexes of a table; you cannot partition only the data and not the indexes, or vice versa, nor can you partition only a portion of the table.
Data and indexes for each partition can be assigned to a specific
directory using the
DATA DIRECTORY and
INDEX DIRECTORY options for the
PARTITION clause of the
CREATE TABLE statement used to
create the partitioned table.
InnoDB supports the
DATA DIRECTORY and
INDEX DIRECTORY options for individual
partitions and subpartitions.
All columns used in the table's partitioning expression must be part of every unique key that the table may have, including any primary key. This means that a table such as this one, created by the following SQL statement, cannot be partitioned:
CREATE TABLE tnp ( id INT NOT NULL AUTO_INCREMENT, ref BIGINT NOT NULL, name VARCHAR(255), PRIMARY KEY pk (id), UNIQUE KEY uk (name) );
Because the keys
have no columns in common, there are no columns available for use
in a partitioning expression. Possible workarounds in this
situation include adding the
name column to the
table's primary key, adding the
uk, or simply removing the unique key
Section 23.6.1, “Partitioning Keys, Primary Keys, and Unique Keys”,
for more information.
MIN_ROWS can be used to determine the maximum
and minimum numbers of rows, respectively, that can be stored in
each partition. See Section 23.3, “Partition Management”, for
more information on these options.
Some advantages of partitioning are listed here:
Partitioning makes it possible to store more data in one table than can be held on a single disk or file system partition.
Data that loses its usefulness can often be easily removed from a partitioned table by dropping the partition (or partitions) containing only that data. Conversely, the process of adding new data can in some cases be greatly facilitated by adding one or more new partitions for storing specifically that data.
Some queries can be greatly optimized in virtue of the fact that data satisfying a given
WHEREclause can be stored only on one or more partitions, which automatically excludes any remaining partitions from the search. Because partitions can be altered after a partitioned table has been created, you can reorganize your data to enhance frequent queries that may not have been often used when the partitioning scheme was first set up. This ability to exclude non-matching partitions (and thus any rows they contain) is often referred to as partition pruning. For more information, see Section 23.4, “Partition Pruning”.
In addition, MySQL 8.0 supports explicit partition selection for queries. For example,
SELECT * FROM t PARTITION (p0,p1) WHERE c < 5selects only those rows in partitions
p1that match the
WHEREcondition. In this case, MySQL does not check any other partitions of table
t; this can greatly speed up queries when you already know which partition or partitions you wish to examine. Partition selection is also supported for the data modification statements
LOAD XML. See the descriptions of these statements for more information and examples.
Other benefits usually associated with partitioning include those in the following list. These features are not currently implemented in MySQL Partitioning, but are high on our list of priorities.
Queries involving aggregate functions such as
COUNT()can easily be parallelized. A simple example of such a query might be
SELECT salesperson_id, COUNT(orders) as order_total FROM sales GROUP BY salesperson_id;. By “parallelized,” we mean that the query can be run simultaneously on each partition, and the final result obtained merely by summing the results obtained for all partitions.
Achieving greater query throughput in virtue of spreading data seeks over multiple disks.