You can create a materialized view of a query to calculate and store results of an
expensive operation, such as particular join, that you repeatedly run. When you issue
queries specified by that materialized view, the optimizer rewrites the query based on it.
This action saves reprocessing. Query performance improves.
In this task, you create and populate example tables. You create a materialized view
of a join of the tables. Subsequently, when you run a query to join the tables, the
query plan takes advantage of the precomputed join to accelerate processing. This
task is over-simplified and is intended to show the syntax and output of a
materialized view, not to demonstrate accelerated processing that results in a
real-world task, which would process a large amount of data.
-
Create two tables:
CREATE TABLE emps (
empid INT,
deptno INT,
name VARCHAR(256),
salary FLOAT,
hire_date TIMESTAMP);
CREATE TABLE depts (
deptno INT,
deptname VARCHAR(256),
locationid INT);
-
Insert some data into the tables for example purposes:
INSERT INTO TABLE emps VALUES (10001,101,'jane doe',250000,'2018-01-10');
INSERT INTO TABLE emps VALUES (10002,100,'somporn klailee',210000,'2017-12-25');
INSERT INTO TABLE emps VALUES (10003,200,'jeiranan thongnopneua',175000,'2018-05-05');
INSERT INTO TABLE depts VALUES (100,'HR',10);
INSERT INTO TABLE depts VALUES (101,'Eng',11);
INSERT INTO TABLE depts VALUES (200,'Sup',20);
-
Create a materialized view to join the tables:
CREATE MATERIALIZED VIEW mv1
AS SELECT empid, deptname, hire_date
FROM emps JOIN depts
ON (emps.deptno = depts.deptno)
WHERE hire_date >= '2017-01-01';
-
Run a query that takes advantage of the precomputation performed by the
materialized view:
SELECT empid, deptname
FROM emps
JOIN depts
ON (emps.deptno = depts.deptno)
WHERE hire_date >= '2017-01-01'
AND hire_date <= '2019-01-01';
Output is:
+--------+-----------+
| empid | deptname |
+--------+-----------+
| 10003 | Sup |
| 10002 | HR |
| 10001 | Eng |
+--------+-----------+
