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Database Performance Tuning and Query Optimization

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Chapter 11 Database Performance Tuning and Query Optimization Database Systems: Design, Implementation, and Management, Seventh Edition, Rob and Coronel – PowerPoint PPT presentation

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Title: Database Performance Tuning and Query Optimization


1
Chapter 11
  • Database Performance Tuning and Query
    Optimization
  • Database Systems Design, Implementation, and
    Management, Seventh Edition, Rob and Coronel

2
In this chapter, you will learn
  • Basic database performance-tuning concepts
  • How a DBMS processes SQL queries
  • About the importance of indexes in query
    processing
  • About the types of decisions the query optimizer
    has to make

3
In this chapter, you will learn (continued)
  • Some common practices used to write efficient SQL
    code
  • How to formulate queries and tune the DBMS for
    optimal performance

4
Database Performance-Tuning Concepts
  • Goal of database performance is to execute
    queries as fast as possible
  • Database performance tuning
  • Set of activities and procedures designed to
    reduce response time of database system

5
Database Performance-Tuning Concepts (continued)
6
Database Performance-Tuning Concepts (continued)
  • All factors must be checked to ensure that each
    one operates at its optimum level and has
    sufficient resources to minimize occurrence of
    bottlenecks
  • Good database performance starts with good
    database design

7
Performance Tuning Client and Server
  • Database performance-tuning activities can be
    divided into
  • Client side
  • Objective is to generate SQL query that returns
    correct answer in least amount of time, using
    minimum amount of resources at server end
  • SQL performance tuning

8
Performance Tuning Client and Server (continued)
  • Database performance-tuning activities can be
    divided into (continued)
  • Server side
  • DBMS environment must be properly configured to
    respond to clients requests in fastest way
    possible, while making optimum use of existing
    resources
  • DBMS performance tuning

9
DBMS Architecture
  • All data in database are stored in data files
  • Data files
  • Automatically expand in predefined increments
    known as extends
  • Generally grouped in file groups of table spaces
  • Table space or file group is logical grouping of
    several data files that store data with similar
    characteristics

10
DBMS Architecture (continued)
11
DBMS Architecture (continued)
  • DBMS retrieve data from permanent storage and
    place it in RAM
  • Data cache or buffer cache is shared, reserved
    memory area that stores most recently accessed
    data blocks in RAM
  • SQL cache or procedure cache is shared, reserved
    memory area that stores most recently executed
    SQL statements or PL/SQL procedures, including
    triggers and functions

12
DBMS Architecture (continued)
  • An input/output request is low-level (read or
    write) data access operation to/from computer
    devices
  • Working with data in data cache is many times
    faster than working with data in data files
    because DBMS doesnt have to wait for hard disk
    to retrieve data
  • Majority of performance-tuning activities focus
    on minimizing number of I/O operations

13
DBMS Architecture (continued)
  • Listener
  • User
  • Scheduler
  • Lock manager
  • Optimizer

14
Database Statistics
  • Refers to number of measurements about database
    objects and available resources
  • Tables
  • Indexes
  • Number of processors used
  • Processor speed
  • Temporary space available

15
Database Statistics (continued)
  • Make critical decisions about improving query
    processing efficiency
  • Can be gathered manually by DBA or automatically
    by DBMS

16
Database Statistics (continued)
17
Query Processing
  • DBMS processes queries in three phases
  • Parsing
  • Execution
  • Fetching

18
SQL Parsing Phase
  • Breaking down (parsing) query into smaller units
    and transforming original SQL query into slightly
    different version of original SQL code
  • Fully equivalent
  • Optimized query results are always the same as
    original query
  • More efficient
  • Optimized query will almost always execute faster
    than original query

19
SQL Parsing Phase (continued)
20
SQL Parsing Phase (continued)
  • Query optimizer analyzes SQL query and finds most
    efficient way to access data
  • Access plans are DBMS-specific and translate
    clients SQL query into series of complex I/O
    operations required to read the data from the
    physical data files and generate result set

21
SQL Parsing Phase (continued)
22
SQL Execution Phase
  • All I/O operations indicated in access plan are
    executed

23
SQL Fetching Phase
  • Rows of resulting query result set are returned
    to client
  • DBMS may use temporary table space to store
    temporary data

24
Indexes and Query Optimization
  • Indexes
  • Crucial in speeding up data access
  • Facilitate searching, sorting, and using
    aggregate functions as well as join operations
  • Ordered set of values that contains index key and
    pointers
  • More efficient to use index to access table than
    to scan all rows in table sequentially

25
Indexes and Query Optimization (continued)
26
Optimizer Choices
  • Rule-based optimizer
  • Uses set of preset rules and points to determine
    best approach to execute query
  • Cost-based optimizer
  • Uses sophisticated algorithms based on statistics
    about objects being accessed to determine best
    approach to execute query

27
Optimizer Choices (continued)
28
Optimizer Choices (continued)
29
Using Hints to Affect Optimizer Choices
30
SQL Performance Tuning
  • Evaluated from client perspective
  • Most current-generation relational DBMSs perform
    automatic query optimization at the server end
  • Most SQL performance optimization techniques are
    DBMS-specific and are rarely portable

31
Index Selectivity
  • Indexes are likely used when
  • Indexed column appears by itself in search
    criteria of WHERE or HAVING clause
  • Indexed column appears by itself in GROUP BY or
    ORDER BY clause
  • MAX or MIN function is applied to indexed column
  • Data sparsity on indexed column is high
  • Measure of how likely an index will be used

32
Index Selectivity (continued)
  • General guidelines for creating and using
    indexes
  • Create indexes for each attribute in WHERE,
    HAVING, ORDER BY, or GROUP BY clause
  • Do not use in small tables or tables with low
    sparsity
  • Declare primary and foreign keys so optimizer can
    use indexes in join operations
  • Declare indexes in join columns other than PK/FK

33
Conditional Expressions
  • Normally expressed within WHERE or HAVING clauses
    of SQL statement
  • Restricts output of query to only rows matching
    conditional criteria

34
Conditional Expressions (continued)
35
Query Formulation
  • Identify what columns and computations are
    required
  • Identify source tables
  • Determine how to join tables
  • Determine what selection criteria is needed
  • Determine in what order to display output

36
DBMS Performance Tuning
  • Includes global tasks such as managing DBMS
    processes in primary memory and structures in
    physical storage
  • Includes applying several practices examined in
    previous section

37
DBMS Performance Tuning (continued)
  • DBMS performance tuning at server end focuses on
    setting parameters used for
  • Data cache
  • SQL cache
  • Sort cache
  • Optimizer mode

38
DBMS Performance Tuning (continued)
  • Some general recommendations for creation of
    databases
  • Use RAID (Redundant Array of Independent Disks)
    to provide balance between performance and fault
    tolerance
  • Minimize disk contention
  • Put high-usage tables in their own table spaces

39
DBMS Performance Tuning (continued)
  • Some general recommendations for creation of
    databases (continued)
  • Assign separate data files in separate storage
    volumes for indexes, system, and high-usage
    tables
  • Partition tables based on usage
  • Use denormalized tables where appropriate
  • Store computed and aggregate attributes in tables

40
DBMS Performance Tuning (continued)
41
DBMS Performance Tuning (continued)
42
DBMS Performance Tuning (continued)
43
DBMS Performance Tuning (continued)
44
DBMS Performance Tuning (continued)
45
DBMS Performance Tuning (continued)
46
DBMS Performance Tuning (continued)
47
DBMS Performance Tuning (continued)
48
DBMS Performance Tuning (continued)
49
DBMS Performance Tuning (continued)
50
Summary
  • Database performance tuning
  • Refers to set of activities and procedures
    designed to ensure that end-user query is
    processed by DBMS in minimum amount of time
  • SQL performance tuning
  • Refers to activities on client side designed to
    generate SQL code that returns correct answer in
    least amount of time, using minimum amount of
    resources at server end

51
Summary (continued)
  • DBMS performance tuning refers to activities on
    server side oriented to ensure that DBMS is
    properly configured to respond to clients
    requests in fastest way possible while making
    optimum use of existing resources
  • DBMS architecture is represented by many
    processes and structures (in memory and in
    permanent storage) used to manage a database

52
Summary (continued)
  • Database statistics refers to a number of
    measurements gathered by the DBMS that describe
    snapshot of database objects characteristics
  • DBMS processes queries in three phases Parsing,
    Execution and Fetching
  • Indexes are crucial in process that speeds up
    data access

53
Summary (continued)
  • During query optimization, DBMS must choose what
    indexes to use, how to perform join operations,
    what table to use first, and so on
  • Hints are used to change optimizer mode for
    current SQL statement
  • SQL performance tuning deals with writing queries
    that make good use of statistics

54
Summary (continued)
  • Query formulation deals with how to translate
    business questions into specific SQL code to
    generate required results
  • DBMS performance tuning includes tasks such as
    managing DBMS processes in primary memory and
    structures in physical storage
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