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Oracle Database 11gR2 Performance Tuning Cookbook

You're reading from   Oracle Database 11gR2 Performance Tuning Cookbook Shifting your Oracle Database into top gear takes a lot of know-how and fine-tuning ability. The 80+ recipes in this Cookbook will give you those skills along with the ability to troubleshoot if things starts running slowly.

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Product type Paperback
Published in Jan 2012
Publisher Packt
ISBN-13 9781849682602
Length 542 pages
Edition 1st Edition
Languages
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Author (1):
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Ciro Fiorillo Ciro Fiorillo
Author Profile Icon Ciro Fiorillo
Ciro Fiorillo
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Table of Contents (21) Chapters Close

Oracle Database 11gR2 Performance Tuning Cookbook
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface
1. Starting with Performance Tuning FREE CHAPTER 2. Optimizing Application Design 3. Optimizing Storage Structures 4. Optimizing SQL Code 5. Optimizing Sort Operations 6. Optimizing PL/SQL Code 7. Improving the Oracle Optimizer 8. Other Optimizations 9. Tuning Memory 10. Tuning I/O 11. Tuning Contention Dynamic Performance Views A Summary of Oracle Packages Used for Performance Tuning Index

Using hash clusters


In the previous recipe, we introduced index clusters and tested a particular way to load data in a cluster to optimize the storage of rows with the same cluster key value.

In this recipe, we introduce a different kind of cluster—hash clusters. The biggest difference between index clusters and hash clusters is in the waydata is accessed given a particular cluster key value.

How to do it...

The following steps will demonstrate the use of hash clusters:

  1. Connect to the HR schema of the TESTDB database:

    CONNECT hr@TESTDB/hr
    
  2. Create the cluster:

    CREATE CLUSTER EMP_DEPT_CLUSTER (deptid NUMBER(4))
    SIZE 8192 HASHKEYS 100;
    
  3. Create the first table and populate it with data:

    CREATE TABLE CL_DEPARTMENTS CLUSTER EMP_DEPT_CLUSTER
    (department_id) AS SELECT * FROM DEPARTMENTS;
    
  4. Create the second table, populate it with data, and gather statistics:

    CREATE TABLE CL_EMPLOYEES CLUSTER EMP_DEPT_CLUSTER
    (department_id) AS SELECT * FROM EMPLOYEES;
    EXEC DBMS_STATS.GATHER_TABLE_STATS(‹HR›, ‹CL_EMPLOYEES...
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