MySQL IF() Function
The IF() function returns a value if a condition is TRUE.
Syntax:-
IF(condition, value_if_true, value_if_false)
Example:-
SELECT IF(500<1000, "YES", "");
SELECT OrderID, Quantity, IF(Quantity>10, "MORE", "")
FROM OrderDetails;
MySQL IF ELSE () Function
The IF ELSE() function returns a value if a condition is TRUE, or another value if a condition is FALSE.
Syntax:-
IF(condition, value_if_true, value_if_false)
Example:-
SELECT IF(500<1000, "YES", "NO");
SELECT OrderID, Quantity, IF(Quantity>10, "MORE", "LESS")
FROM OrderDetails;
SQL PARTITION
Database table partitioning in SQL Server
April 4, 2014 by Milica Medic
SQL server Quest banner
What is a database table partitioning?
Partitioning is the database process where very large tables are divided into multiple smaller parts. By splitting a large table into smaller, individual tables, queries that access only a fraction of the data can run faster because there is less data to scan. The main of goal of partitioning is to aid in maintenance of large tables and to reduce the overall response time to read and load data for particular SQL operations.
PARTITION TYPES
- RANGE
- LIST
- COLUMNS
- HASH
- KEY
- SUB
RANGE Partitioning
A table that is partitioned by range is partitioned in such a way that each partition contains rows for which the partitioning expression value lies within a given range. Ranges should be contiguous but not overlapping, and are defined using the VALUES LESS THAN operator. For the next few examples, suppose that you are creating a table such as the following to hold personnel records for a chain of 20 video stores, numbered 1 through 20.
Example:-
CREATE TABLE employees (
id INT NOT NULL,
fname VARCHAR(30),
lname VARCHAR(30),
hired DATE NOT NULL DEFAULT '1970-01-01',
separated DATE NOT NULL DEFAULT '9999-12-31',
job_code INT NOT NULL,
store_id INT NOT NULL
)
PARTITION BY RANGE (store_id) (
PARTITION p0 VALUES LESS THAN (6),
PARTITION p1 VALUES LESS THAN (11),
PARTITION p2 VALUES LESS THAN (16),
PARTITION p3 VALUES LESS THAN (21)
);
id INT NOT NULL,
fname VARCHAR(30),
lname VARCHAR(30),
hired DATE NOT NULL DEFAULT '1970-01-01',
separated DATE NOT NULL DEFAULT '9999-12-31',
job_code INT NOT NULL,
store_id INT NOT NULL
)
PARTITION BY RANGE (store_id) (
PARTITION p0 VALUES LESS THAN (6),
PARTITION p1 VALUES LESS THAN (11),
PARTITION p2 VALUES LESS THAN (16),
PARTITION p3 VALUES LESS THAN (21)
);
LIST Partitioning
List partitioning in MySQL is similar to range partitioning in many ways. As in partitioning by RANGE, each partition must be explicitly defined. The chief difference between the two types of partitioning is that, in list partitioning, each partition is defined and selected based on the membership of a column value in one of a set of value lists, rather than in one of a set of contiguous ranges of values. This is done by using PARTITION BY LIST(expr) where expr is a column value or an expression based on a column value and returning an integer value, and then defining each partition by means of a VALUES IN (value_list), where value_list is a comma-separated list of integers.
Example:-
CREATE TABLE employees (
id INT NOT NULL,
fname VARCHAR(30),
lname VARCHAR(30),
hired DATE NOT NULL DEFAULT '1970-01-01',
separated DATE NOT NULL DEFAULT '9999-12-31',
job_code INT,
store_id INT
)
PARTITION BY LIST(store_id) (
PARTITION pNorth VALUES IN (3,5,6,9,17),
PARTITION pEast VALUES IN (1,2,10,11,19,20),
PARTITION pWest VALUES IN (4,12,13,14,18),
PARTITION pCentral VALUES IN (7,8,15,16)
);
id INT NOT NULL,
fname VARCHAR(30),
lname VARCHAR(30),
hired DATE NOT NULL DEFAULT '1970-01-01',
separated DATE NOT NULL DEFAULT '9999-12-31',
job_code INT,
store_id INT
)
PARTITION BY LIST(store_id) (
PARTITION pNorth VALUES IN (3,5,6,9,17),
PARTITION pEast VALUES IN (1,2,10,11,19,20),
PARTITION pWest VALUES IN (4,12,13,14,18),
PARTITION pCentral VALUES IN (7,8,15,16)
);
COLUMNS Partitioning
The next two sections discuss COLUMNS partitioning, which are variants on RANGE and LIST partitioning. COLUMNS partitioning enables the use of multiple columns in partitioning keys. All of these columns are taken into account both for the purpose of placing rows in partitions and for the determination of which partitions are to be checked for matching rows in partition pruning.In addition, both RANGE COLUMNS partitioning and LIST COLUMNS partitioning support the use of non-integer columns for defining value ranges or list members.
Example of RANGE COLUMNS partitioning:-
CREATE TABLE rcx (
a INT,
b INT,
c CHAR(3),
d INT
)
PARTITION BY RANGE COLUMNS(a,d,c) (
PARTITION p0 VALUES LESS THAN (5,10,'ggg'),
PARTITION p1 VALUES LESS THAN (10,20,'mmm'),
PARTITION p2 VALUES LESS THAN (15,30,'sss'),
PARTITION p3 VALUES LESS THAN (MAXVALUE,MAXVALUE,MAXVALUE)
);
a INT,
b INT,
c CHAR(3),
d INT
)
PARTITION BY RANGE COLUMNS(a,d,c) (
PARTITION p0 VALUES LESS THAN (5,10,'ggg'),
PARTITION p1 VALUES LESS THAN (10,20,'mmm'),
PARTITION p2 VALUES LESS THAN (15,30,'sss'),
PARTITION p3 VALUES LESS THAN (MAXVALUE,MAXVALUE,MAXVALUE)
);
Example of LIST COLUMNS partitioning:-
CREATE TABLE customers_1 (
first_name VARCHAR(25),
last_name VARCHAR(25),
street_1 VARCHAR(30),
street_2 VARCHAR(30),
city VARCHAR(15),
renewal DATE
)
PARTITION BY LIST COLUMNS(city) (
PARTITION pRegion_1 VALUES IN('Oskarshamn', 'Högsby', 'Mönsterås'),
PARTITION pRegion_2 VALUES IN('Vimmerby', 'Hultsfred', 'Västervik'),
PARTITION pRegion_3 VALUES IN('Nässjö', 'Eksjö', 'Vetlanda'),
PARTITION pRegion_4 VALUES IN('Uppvidinge', 'Alvesta', 'Växjo')
);
first_name VARCHAR(25),
last_name VARCHAR(25),
street_1 VARCHAR(30),
street_2 VARCHAR(30),
city VARCHAR(15),
renewal DATE
)
PARTITION BY LIST COLUMNS(city) (
PARTITION pRegion_1 VALUES IN('Oskarshamn', 'Högsby', 'Mönsterås'),
PARTITION pRegion_2 VALUES IN('Vimmerby', 'Hultsfred', 'Västervik'),
PARTITION pRegion_3 VALUES IN('Nässjö', 'Eksjö', 'Vetlanda'),
PARTITION pRegion_4 VALUES IN('Uppvidinge', 'Alvesta', 'Växjo')
);
HASH Partitioning
Partitioning by HASH is used primarily to ensure an even distribution of data among a predetermined number of partitions. With range or list partitioning, you must specify explicitly which partition a given column value or set of column values should be stored in; with hash partitioning, this decision is taken care of for you, and you need only specify a column value or expression based on a column value to be hashed and the number of partitions into which the partitioned table is to be divided.
Example:-
CREATE TABLE employees (
id INT NOT NULL,
fname VARCHAR(30),
lname VARCHAR(30),
hired DATE NOT NULL DEFAULT '1970-01-01',
separated DATE NOT NULL DEFAULT '9999-12-31',
job_code INT,
store_id INT
)
PARTITION BY HASH(store_id)
PARTITIONS 4;
id INT NOT NULL,
fname VARCHAR(30),
lname VARCHAR(30),
hired DATE NOT NULL DEFAULT '1970-01-01',
separated DATE NOT NULL DEFAULT '9999-12-31',
job_code INT,
store_id INT
)
PARTITION BY HASH(store_id)
PARTITIONS 4;
KEY Partitioning
Partitioning by key is similar to partitioning by hash, except that where hash partitioning employs a user-defined expression, the hashing function for key partitioning is supplied by the MySQL server. NDB Cluster uses MD5() for this purpose; for tables using other storage engines, the server employs its own internal hashing function.
Example:-
CREATE TABLE k1 (
id INT NOT NULL PRIMARY KEY,
name VARCHAR(20)
)
PARTITION BY KEY()
PARTITIONS 2;
id INT NOT NULL PRIMARY KEY,
name VARCHAR(20)
)
PARTITION BY KEY()
PARTITIONS 2;
Subpartitioning
Subpartitioning—also known as composite partitioning—is the further division of each partition in a partitioned table. Consider the following CREATE TABLE statement.
Example:-
CREATE TABLE ts (id INT, purchased DATE)
PARTITION BY RANGE( YEAR(purchased) )
SUBPARTITION BY HASH( TO_DAYS(purchased) )
SUBPARTITIONS 2 (
PARTITION p0 VALUES LESS THAN (1990),
PARTITION p1 VALUES LESS THAN (2000),
PARTITION p2 VALUES LESS THAN MAXVALUE
);
PARTITION BY RANGE( YEAR(purchased) )
SUBPARTITION BY HASH( TO_DAYS(purchased) )
SUBPARTITIONS 2 (
PARTITION p0 VALUES LESS THAN (1990),
PARTITION p1 VALUES LESS THAN (2000),
PARTITION p2 VALUES LESS THAN MAXVALUE
);