SQL Performance Explained 1st edition by Markus Winand ISBN 3950307826 978-3950307825

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Product details: 

ISBN 10: 3950307826 

ISBN 13: 978-3950307825

Author: Markus Winand

SQL Performance Explained helps developers to improve database performance. The focus is on SQL—it covers all major SQL databases without getting lost in the details of any one specific product.

Starting with the basics of indexing and the WHERE clause, SQL Performance Explained guides developers through all parts of an SQL statement and explains the pitfalls of object-relational mapping (ORM) tools like Hibernate.

Topics covered include:
• Using multi-column indexes
• Correctly applying SQL functions
• Efficient use of LIKE queries
• Optimizing join operations
• Clustering data to improve performance
• Pipelined execution of ORDER BY and GROUP BY
• Getting the best performance for pagination queries
• Understanding the scalability of databases

Its systematic structure makes SQL Performance Explained both a textbook and a reference manual that should be on every developer’s bookshelf.

Covers all major databases: Oracle® Database, SQL Server®, PostgreSQL, MySQL

What readers say:
“This book is definitively worth having in the company library.” — Joe Celko

Table of contents: 

1. Anatomy of an Index
   The Index Leaf Nodes
   The Search Tree (B-Tree)
   Slow Indexes, Part I

2. The Where Clause
   The Equality Operator
   Primary Keys
   Concatenated Indexes
   Slow Indexes, Part II
   Functions
   Case-Insensitive Search Using UPPER or LOWER
   User-Defined Functions
   Over-Indexing
   Parameterized Queries
   Searching for Ranges
   Greater, Less and BETWEEN
   Indexing LIKE Filters
   Index Merge
   Partial Indexes
   NULL in the Oracle Database
   Indexing NULL
   NOT NULL Constraints
   Emulating Partial Indexes
   Obfuscated Conditions
   Date Types
   Numeric Strings
   Combining Columns
   Smart Logic
   Math

3. Performance and Scalability
   Performance Impacts of Data Volume
   Performance Impacts of System Load
   Response Time and Throughput

4. The Join Operation
   Nested Loops
   Hash Join
   Sort Merge

5. Clustering Data
   Index Filter Predicates Used Intentionally
   Index-Only Scan
   Index-Organized Tables

6. Sorting and Grouping
   Indexing Order By
   Indexing ASC, DESC and NULLS FIRST/LAST
   Indexing Group By

7. Partial Results
   Querying Top-N Rows
   Paging Through Results
   Using Window Functions for Pagination

8. Modifying Data
   Insert
   Delete
   Update

A. Execution Plans
Oracle Database
PostgreSQL
SQL Server
MySQL

Index

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Tags: Markus Winand, SQL Performance, Explained 1st