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Cel szkolenia szkolenie zdalne - dlearning

kod: CL451GPL | wersja: v11.x

The course is intended for Data Administrators that need to prepare for using the DB2 BLU Acceleration facilities of DB2 11.1 for Linux, UNIX and Windows systems.
The concepts and facilities of the BLU Acceleration feature of DB2 11 are presented including loading data into column-organized tables and monitoring the processing of SQL statements that access the tables.
The DB2 10.5 Fix Pack 4, referred to as Cancun, added support for Shadow tables, a new type of Materialized Query Table, and also Column-organized User Maintained MQT tables. One lecture unit describes these features. A demonstration allows students to implement and experiment with these functions.
With DB2 11.1, BLU Acceleration can be used in a clustered multiple database partition DB2 environment. This course includes a lecture and demonstration that allows students to create a set of column-organized tables from an existing set of row-organized tables and execute and analyze the performance of BLU Acceleration in a MPP database.
The lab demonstrations are performed using DB2 LUW 11.1 for Linux. 

Please refer to course overview

This is an advanced course for DB2 LUW experienced database administrators who support DB2 for UNIX, Windows, and Linux databases and want to learn more about the DB2 with BLU acceleration capabilities in DB2 11.1. These skills can also be utilized to support cloud based databases using DB2 on Cloud or IBM dashDB.

Plan szkolenia Rozwiń listę

Topics Covered:
• BLU Acceleration Concepts
• BLU Acceleration Implementation and Use
• Implementing Shadow Tables and BLU MQTs
• DB2 BLU MPP support

Pobierz konspekt szkolenia w formacie PDF

Dodatkowe informacje

Wymagania wstępne

Participants should have completed one of the following courses:
o DB2 11.1 Administration Workshop for Linux (CL206)
o DB2 11.1 Quickstart for Experienced Relational DBAs (CL486)
 

Poziom trudności
Czas trwania 2 dni

Pozostałe szkolenia IBM | DB2

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CENA SZKOLENIA OD 1300 EUR NETTO

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