Introduction to Databases Chapter 8: Improving Data Access.

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Transcript of Introduction to Databases Chapter 8: Improving Data Access.

Introduction to Databases

Chapter 8: Improving Data Access

Performance Roadblocks

• Improving database access:– Goals:

• Easier access of data• Improve performance during data access

• Performance bottlenecks:– Hardware platform

• Because DBMSs are resource-intensive, hardware issues are common source of performance problems

• Database server issues• Network issues

Performance Roadblocks

• Performance bottlenecks (cont.):– Database

• Performance during data reads and writes directly impacts application performance

• Normalization can impair read performance

• Indexes can impair write performance

– Application• Poorly written, inefficient application can

result in poor performance even if hardware and database server are working at optimum levels

Hardware Performance: Disk Drive Issues

• Disk access– How quickly hard disk can process read

and write requests – Time required to locate and transfer data

• Disk queue• Disk read and write statistics

Hardware Performance: Disk Drive Issues

• Solutions:– Upgrade hardware

• More drives• Faster drives• RAID

– Reduce load • Split load between multiple drives• Increase memory and cache• Use dedicated server

Hardware Performance: Memory Issues

• Most DBMSs set aside memory to cache data; some may cache queries and executables

• To solve memory issues:– Reduce load on system memory– Increase system memory

• Virtual memory paging file:– Used by modern operating systems to increase

available memory – Paging increases with insufficient system memory and

may interfere with other disk operations

Cache Memory

Virtual Memory

Hardware Performance: Processor Issues

• Programs, queries, modules all put loads on processor

• To determine if processor is issue, check processor free and busy time

• Solutions:– Reduce processor load– Install faster processor– Install multiple processors

• Processor affinity: – Configurable option for many DBMSs (e.g. SQL Server)– Controls how, or if, database server makes use of

multiple processors

Performance Monitoring Tools

• DBMS specific utilities include:– SQL Server Profiler:

• Captures database activity for analysis

– SQL Server Database Tuning Engine: • Analyzes system activity and reports on index

use

– Execution plan: • Identifies how query processor resolves query,

specific steps involved and resources required; showing which indexes are used and how they are used by query

Performance Monitoring Tools

• Operating system tools:– Windows System/Performance Monitor:

• Provides real-time performance information

– Hardware Properties dialog boxes• Configure hardware devices

Windows System Monitor

• System Monitor (previously called Performance Monitor):– Used to collect and log performance data

• Performance data logs:– Used to give performance baseline– Allow detailed analysis

• Performance counters: Monitor specific system activity

• Alerts: Monitor one or more performance counters and send notification when counter reaches specified threshold value

• SQL Server: Installs large set of SQL Server-specific performance objects and counters

Windows System Monitor

Performance Counters

Working with Indexes

• Clustered indexes:– Impose physical organization on table

– Sorting table rows in index order

• DBMSs that support clustered indexes have limit of one clustered index

Working with Indexes

• Nonclustered indexes:– Provide logical organization

– Organizing data according to key columns

– Do not affect physical table order

• Number of nonclustered indexes allowed is DBMS-specific

Designing Indexes

• Considerations in designing indexes include:– Total number of indexes

– Defining key columns (columns that set index sort order)

– Unnecessary indexing• Small tables

• Columns with low selectivity (few unique values)

– Disk space and write performance

Designing Indexes• Columns that benefit from indexing

include:– Primary key columns– Foreign key columns– Columns commonly referenced in queries

• WHERE clause search logic• GROUP BY or ORDER BY clauses• SELECT column lists

Creating Indexes• CREATE INDEX syntax (SQL Server

Transact-SQL):CREATE [CLUSTERED] | [NONCLUSTERED]

[UNIQUE]

INDEX name

ON object (column_list)

INCLUDE (column_list)

• Object: Typically table, but in some DBMSs, may be view

Creating Indexes

• Additional options are available for managing free space, user access, etc.

• ALTER INDEX:– To modify index

– You cannot use ALTER INDEX to change index key and nonkey columns

• DROP INDEX:– To delete index

How Queries Use Indexes

• When SQL query optimizer is presented with new SELECT statement to evaluate, it seeks out information in database metadata about tables named in FROM clause:– Which columns are used as index keys– Which columns have unique values– How many rows each table has

How Queries Use Indexes

• Query optimizer uses information about tables, together with various components of SELECT statement itself, to find most efficient way to retrieve data required by query and satisfy any joins

• When extensive join operation can’t be avoided, query optimizer selects one of several join algorithms, such as:– Nested loop join– Merge-scan join

Working with Views• Views:

– Provide access to selected data– Used to:

• Restrict access to underlying base objects• Simplify security management• Join tables to provide easy access to

denormalized data

– Can have one or more base tables– May be based on other views– Syntax:

• CREATE VIEW name AS select_statement

Working with Views• To manage views:

– ALTER VIEW: Modifies view definition

– DROP VIEW: Deletes view

• Can be specified as destination when running INSERT or UPDATE, with restrictions

• Indexed view: – View with clustered index

– View result is persisted through index structure

Working with Views

• Example: Creating view for New York customers

CREATE VIEW v_ny_cust AS SELECT * FROM CUSTOMERS WHERE HQCITY = ‘New York’

• To retrieve data from view:SELECT * FROM v_ny_cust

Programmable Objects

• Custom database objects programmed by developer

• Based on:

– SQL language commands and variables

– Control statements (if supported by DBMS)

• Procedures and functions: Most common programmable objects

Programmable Objects

• Procedure: – Set of executable statements that supports

input and output parameters

• Function: – Similar to system functions– Accepts input parameters and returns

specific type of value, either scalar or table value

• Trigger: – Specialized procedure associated with

specific objects and events

Procedures• Simplify and speed performance of

periodic or complicated activities• Ensures activities are performed

consistently• Aid system security:

– Placing level of isolation between users and database

• May be:– DBMS defined system procedures (system stored

procedures) • E.g. sp_helpdb (SQL Server) returns information

about specified database or all system databases– Custom, user stored

Procedures: sp_helpdb

Creating Procedures• Syntax:

CREATE PROC[EDURE] procedure name[parameter_list]ASSql_statements

• Defining parameters:– Must supply parameter name and data

type– Can specify default values– Must specify output parameter for

procedure to return value

Creating Procedures

• Example:

DECLARE @NUM CHAR(3)DECLARE @RETCOUNT INTSET @NUM = ‘137’EXECUTE usp_count_cust @NUM,

@RETCOUNT OUTPUTSELECT ‘The count for salesperson’

+ @NUM + ‘is’+ CAST( @RETCOUNT AS CHAR(2)

Functions• User defined functions (UDFs):

– Return value (unlike procedures)– Used instead of procedures when returned value

needed

• Three types of functions (SQL Server 2005)– Scalar function:

• Returns scalar value of specified type– In-line table-valued function:

• Returns table generated as result of single SELECT statement (similar to view)

– Multistatement table-valued function:• Returns table generated from multiple Transact-

SQL statements

Creating Functions• Transact-SQL CREATE FUNCTION

command: Slightly different syntax versions for function type

• For scalar function:CREATE FUNCTION name([parameter_list])RETURNS data_type[AS]BEGINSql_statementsRETURN scalar_valueEND

Creating Functions• Example scalar function:

CREATE FUNCTION fn_CountCust(@SPNUM CHAR(3))RETURNS INT ASBEGINDECLARE @CUST INTSET @CUST = (SELECT COUNT(*) FROM

CUSTOMER WHERESPNUM=@SPNUM)RETURN @CUSTEND

• To run:SELECT dbo.fn_CountCust(‘137’)

Creating Functions

• Syntax for in-line table-valued functionCREATE FUNCTION name([parameter_list])RETURNS TABLE[AS]RETURN (select_statement)

Creating Functions

• Example in-line table-valued function :

CREATE FUNCTION fn_GetCust ()RETURNS TABLERETURN (SELECT SPNAME, CUSTNAME, HQCITYFROM SALESPERSON JOIN CUSTOMERON (CUSTOMER.SPNUM =

SALESPERSON.SPNUM))

• To run:SELECT * FROM dbo.fn_GetCust

Creating Functions

• Syntax for multi-statement table-valued function

CREATE FUNCTION name([parameter_list])RETURNS @ret_variable TABLE (table_definition)[AS]BEGINSql_statementsRETURNEND

Summary• Performance bottlenecks may be caused by hardware

platform issues, database issues, and application issues. • Hardware issues (disk drives, memory, processors) may be

resolved by upgrading component or reducing load on component

• Performance monitoring tools include DBMS specific utilities (SQL Server Profiler and Database Tuning engine) and operating system utilities (Windows Performance Monitor, hardware Properties dialog boxes)

• Index performance considerations: Effects on disk space and write performance. Columns that benefit from indexing: Primary key columns, foreign key columns, and columns commonly referenced in queries

• Views provide restricted access to underlying base objects• Procedures and functions: Speed and simplify periodic or

complicated activities; aid system security by placing level of isolation between users and database.

Key Terms• Alert• Bottleneck• Cache• Dedicated server• Disk queue• Function• Indexed view• Input parameter• Key column• Merged scan join• Nested loop join

• Nested procedures• Output parameter• Paging file• Performance baseline• Performance counter• Performance object• Procedure• Processor affinity• Schema binding• System stored

procedures• Threshold value

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