University of Sunderland COM 220 Lecture Ten Slide 1 Database Performance

University of Sunderland COM 220 Lecture Ten Slide 1

Database PerformanceDatabase Performance


Database Database PerformancePerformance

Perfomance can be improved through:

• Denormalisation

• Optimisation of SQL

• Indexes

• Clusters



DENORMALISATION

• Normalisation improves the logical database design and prevents anomalies BUT– More tables more joins– Joining > 3 tables is likely to be slow

• Denormalisation reverses normalisation for efficiency purposes



Select *from ...; DBMS

DATA FILES

SQL OPTIMISATION



INDEXESAn index is a table or some other data structure that

is used to determine the location of a row within a table that satisfies some condition.

• Indexes may be defined on both primary and non key attributes.



INDEXES• oracle allows faster access on any named table by

using an index.• each row within a table is given a unique value or

rowid. • each rowid can be held in an index.• an index can be created at any time.• any column within a table can be indexed.



WHEN TO CREATE AN INDEX

Before any input of data for Unique index

After data input for Non-unique index



HOW DO YOU CREATE AN INDEX ?

EXAMPLE :-(a) CREATE INDEX TENIDX ON

TENANT(SURNAME);

(b) CREATE UNIQUE INDEX TENIDX ON

TENANT(SURNAME);



GUIDELINES FOR USE OF INDEXES • > 200 rows in a table

• a column is frequently used in a where clause

• specific columns are frequently used as join columns



POINTS TO WATCH • avoid if possible > 3 indexes on any one table• avoid indexing a column with too few distinct values

For example:- male/female

• avoid indexing a column with too many distinct values

• avoid if > 15% of rows will be retrieved



CLUSTERS

• A disk is arranged in blocks

• Blocks are retrieved as a whole and buffered

• Disk Access time is slow compared with Memory access

• Gains can be made if the number of block transfers can be reduced



CLUSTERING• clusters physically arrange the data on disk so that

frequently retrieved info is stored together• allows 2 or more tables to be stored in the same

physical block• can greatly reduce access time for join operations .• can also reduce storage space requirements.



CLUSTER DEFINITION• clustering is transparent to the user

no queries have to be modified

no applications need to be changed

• tables are queried in the same way whether clustered or not



DECIDING WHERE TO USE CLUSTERS• Each table can only reside in 1 cluster• At least one attribute in the cluster must be NOT

NULL• Consider the query transactions in the system

– How often is the query submitted– How time critical is the query– What’s the amount of data retrieved



HOW TO CREATE A CLUSTERStep 1 create cluster tenpay(tenid char(8));

Step 2 alter cluster tenpay

add table tenant

where tenpay.tenid =

tenant.property_id;

Step 3 alter cluster tenpay

add table payment

where tenpay.tenid = payment.payment_id



• CLUSTERING EXERCISE

STOCK WAREHOUSE

PRODUCT1000

3



• To speed up access time to data in these three tables (WAREHOUSE, PRODUCT, STOCK) it is necessary to cluster either STOCK around WAREHOUSE, or STOCK around PRODUCT.

• How do we decide which will be the most efficient?• For the purpose of this exercise we will assume

that each block can hold 100 records.



If STOCK is clustered around PRODUCT

No of products = 1000. There will be 1 record for each PRODUCT in each WAREHOUSE. Therefore each product would have 3 records

• Each block would contain 100/3 products, i.e. 33 products. There would therefore be a 1 in 3 chance of accessing a particular stock item by reading one block of data.



If STOCK is clustered around WAREHOUSE

• No of warehouses = _____. There will be ____ record for each item of STOCK in each warehouse. Therefore each warehouse would have ______ records. The records for each warehouse would have to be stored across ______ blocks.

• Access would therefore be faster if STOCK is clustered around the product.



OPTIMIZING PERFORMANCE

Performance can be regarded as a

balancing act between:-

– access performance

– update performance

– ease of use/modification


Further ReadingFurther Reading

• Query Optimisation – Connolly & Begg, 3rd edition, chapter 20– Connolly & Begg, 4th edition, chapter 21

• Performance Tuning (including denormalisation)– Connolly & Begg, 3rd edition, chapter 17– Connolly & Begg, 4th edition, chapter 18

• Next Week– HCI

Documents

University of Sunderland COM 220 Lecture Ten Slide 1 Database Performance