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Tame Beastly Data with Summary Tables

In this 10-Minute Solution, DB2 Pro Greg Nash will examine how DB2 can keep summary tables for you and have your answers waiting before you even ask.




Building the Right Environment to Support AI, Machine Learning and Deep Learning

anagers loved Eddie; he always had the answers on-hand.

Eddie was a production supervisor in the pre-computer era. He received comprehensive hourly production reports on paper. He also received urgent queries from managers, who needed up-to-date summaries spanning the entire year's production. He always had a ready answer.

Eddie had learned that in his job, it paid to keep running totals. He could provide a range of summaries without shuffling reams of paper, and point straight to the answers that he kept pinned up on the wall.

Do you run summary queries against your database? Are they slowing down due to the sheer bulk of the raw data? Eddie may have your solution: keep summary tables. In this article, we will examine how DB2 can do it for you and have your answers waiting before you even ask.

How do you quickly obtain a summary from a massive store of live data?

Use summary tables to hold collated information and have them updated as required. Summary tables can be used explicitly or automatically to improve the speed of certain queries.

Summary tables can be:

  • Do-it-yourself: Maintained by application logic or triggers
  • Automatic: Maintained synchronously by DB2
  • Semi-automatic: Maintained asynchronously by DB2 (updates upon request)
  • Externally hosted: Take the data elsewhere for analysis and reporting. Where you have a lot of activity on your source data, it may be worth replicating to another machine. In fact, this is recommended practice for online analytical processing (OLAP), but outside the scope of this article.

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