Despite our best efforts to achieve excellent database normalization, sometimes it's necessary or simply more efficient to create a temporary table containing some data as of a certain time. SQL satisfies this need with Materialized Query Tables (MQT). These specialized SQL objects allow a database administrator to define the data selected for inclusion and then easily refresh the query with current data from the database tables as needed.
The most powerful use of an MQT is not having users access it directly, but allowing the SQL optimizer to choose to use the MQT instead of the underlying base tables to satisfy other SQL statements. Anytime an application needs static data—such as end of year, end of month, or end of day statistics—this information, which might normally be found by accumulating data from detail tables, could instead be provided by creating an MQT that contains this static data.
Creating a Materialized Query
Creating MQTs relies upon the SQL CREATE statement, as shown below:
(WITH TEMP AS (SELECT DEC(SUM(QTY),7,0) as TOTAL,
PART FROM INVDETL
GROUP BY PART)
SELECT INVMAST.PART, DESC, PRICE, COST, TOTAL FROM INVMAST
LEFT JOIN TEMP ON INVMAST.PART = TEMP.PART)
DATA INITIALLY DEFERRED
REFRESH DEFERRED
ENABLE QUERY OPTIMIZATION
MAINTAINED BY USER
This statement creates an MQT named INVTOTALS. This query contains the part number, description, price, and cost from the inventory master file joined with the sum of the quantity column for each part. TOTAL is the name assigned to the total quantity. This statement uses WITH to define a temporary table object before resolving the main select. This temporary table, named TEMP, contains only a list of parts from the INVDETL file and the total of the QTY column for each part. Using WITH frequently simplifies the code needed later in the main select. Following the main select are four clauses that further define the MQT.
- DATA INITIALLY DEFERRED indicates that the MQT is not loaded with data at the time of creation. Use DATA INITIALLY IMMEDIATE to load it with data right away if necessary.
- REFRESH DEFERRED indicates that the user may choose to refresh the table at any time by issuing the REFRESH TABLE mqt-name statement. This clause is not optional.
- ENABLE QUERY OPTIMIZATION indicates that the SQL engine may choose to use this MQT to satisfy other SQL statements issued against the underlying table(s). To deactivate this feature, use DISBALE QUERY OPTIMIZATION instead.
- MAINTAINED BY USER indicates that the user is responsible for loading the correct data into the MQT using INSERT, UPDATE, DELETE, and REFRESH TABLE statements. This is not optional.
Managing Materialized Queries
The data within an MQT is static, meaning that once data is loaded into it, it will not change regardless of what happens to the underlying tables. Programmers may choose to manually update the MQT with INSERT, UPDATE, and DELETE statements, or more likely, they can repopulate the table with current data using the REFRESH TABLE statement such as the one shown below.
QAQQINI File
To enable the use of MQTs within the SQL optimizer, the QAQQINI file must be updated, as the default settings do not allow the use of Materialized Queries during the optimization process. These settings are needed:
MATERIALIZED_QUERY_TABLE_REFRESH_AGE = *ANY
Want to Know More?
Materialized Queries are a powerful new tool for improving SQL performance within DB2 for i5/OS. This article just touches the tip of the iceberg. For more information on MQTs, check out IBM's white paper "Creating and using materialized query tables (MQT) in IBM DB2 for i5/OS" or contact DMC Consulting about its new "SQL: Data Definition Language" class. This newly created class explores the details of creating DB2 for i5/OS databases through SQL. Contact DMC by email at
Kevin Forsythe has worked on IBM midrange systems for more than 20 years. With many years of experience in programming, analysis, consulting, and instruction, he is uniquely skilled at making difficult material more easily understood. As the lead instructor for DMC Consulting's AS/Credentials training classes, Kevin is responsible for developing up-to-date courseware as well as providing instruction on a wide range of topics. This comprehensive background includes practical application, education, and research and provides a perspective that allows him to help others steer their way through the technical maze that surrounds them.
Kevin speaks regularly at conferences and user group meetings, volunteers as a Subject Matter Expert for COMMON, has written numerous articles on a variety of iSeries topics, and authored the bestselling book SQL for eServer i5 and iSeries.
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