University of Sunderland COM 220 Lecture Ten Slide 1 Database Performance

University of Sunderland COM 220 Lecture Ten Slide 2 Database Performance Perfomance can be improved through: Denormalisation Optimisation of SQL Indexes Clusters

University of Sunderland COM 220 Lecture Ten Slide 3 Database Performance 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

University of Sunderland COM 220 Lecture Ten Slide 4 Database Performance Select * from...; DBMS DATA FILES SQL OPTIMISATION

University of Sunderland COM 220 Lecture Ten Slide 5 Database Performance INDEXES An 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.

University of Sunderland COM 220 Lecture Ten Slide 6 Database Performance 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.

University of Sunderland COM 220 Lecture Ten Slide 7 Database Performance WHEN TO CREATE AN INDEX Before any input of data for Unique index After data input for Non-unique index

University of Sunderland COM 220 Lecture Ten Slide 8 Database Performance HOW DO YOU CREATE AN INDEX ? EXAMPLE :- (a) CREATE INDEX TENIDX ON TENANT(SURNAME); (b) CREATE UNIQUE INDEX TENIDX ON TENANT(SURNAME);

University of Sunderland COM 220 Lecture Ten Slide 9 Database Performance 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

University of Sunderland COM 220 Lecture Ten Slide 10 Database Performance 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

University of Sunderland COM 220 Lecture Ten Slide 11 Database Performance 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

University of Sunderland COM 220 Lecture Ten Slide 12 Database Performance 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.

University of Sunderland COM 220 Lecture Ten Slide 13 Database Performance 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

University of Sunderland COM 220 Lecture Ten Slide 14 Database Performance 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

University of Sunderland COM 220 Lecture Ten Slide 15 Database Performance HOW TO CREATE A CLUSTER Step 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

University of Sunderland COM 220 Lecture Ten Slide 16 Database Performance CLUSTERING EXERCISE STOCK WAREHOUSE PRODUCT

University of Sunderland COM 220 Lecture Ten Slide 17 Database Performance 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.

University of Sunderland COM 220 Lecture Ten Slide 18 Database Performance If STOCK is clustered around PRODUCT No of products = 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.

University of Sunderland COM 220 Lecture Ten Slide 19 Database Performance 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.

University of Sunderland COM 220 Lecture Ten Slide 20 Database Performance OPTIMIZING PERFORMANCE Performance can be regarded as a balancing act between:- –access performance –update performance –ease of use/modification

University of Sunderland COM 220 Lecture Ten Slide 21 Further Reading Query Optimisation –Connolly & Begg, 3 rd edition, chapter 20 –Connolly & Begg, 4 th edition, chapter 21 Performance Tuning (including denormalisation) –Connolly & Begg, 3 rd edition, chapter 17 –Connolly & Begg, 4 th edition, chapter 18 Next Week –HCI