Advanced Database Systems

Sekolah Tinggi Ilmu Statistik (STIS)

Advanced Database Systems



Main TopicsDenormalizing and introducing controlled

redundancy Meaning of denormalization. When to denormalize to improve performance.

Monitoring the system to improve performance Importance of monitoring and tuning the operational system. How to measure efficiency. How system resources affect performance.

2Dr. Said Mirza Pahlevi, M.Eng.

Denormalizing and introducing controlled redundancy

First Topic


Sekolah Tinggi Ilmu Statistik (STIS) 4

Introduction of Controlled Redundancy To determine whether introducing redundancy in

a controlled manner by relaxing normalization rules will improve the performance of the system.

Dr. Said Mirza Pahlevi, M.Eng.


Introduction of Controlled Redundancy Sometimes a normalized database does not provide

maximum processing efficiency.

We may accept loss of some benefits of a fully normalized design in favor of performance.

To determine whether introducing redundancy in a controlled manner by relaxing normalization rules will improve the performance of the system.

Result of normalization is a design that is structurally consistent with minimal redundancy.



Effect of DenormalizationMakes implementation more complex;Often sacrifices flexibility;May speed up retrievals but it slows down

updates.



Example: Data Redundancy



What is Denormalization?Refers to a refinement to relational schema such

that the degree of normalization for a modified relation is less than the degree of at least one of the original relations.

Also use term more loosely to refer to situations where two relations are combined into one new relation, which is still normalized but contains more nulls than original relations.



Denormalization Situation Consider denormalization to speed up frequent or

critical transactions:

1. Combining 1:1 relationships2. Duplicating non-key attributes in 1:* relationships to reduce

joins3. Duplicating foreign key attributes in 1:* relationships to

reduce joins4. Duplicating attributes in *:* relationships to reduce joins 5. Introducing repeating groups6. Creating extract tables



Sample Relation Diagram



Sample Relations



1. Combining 1:1 relationships When Client and Interview tables are frequently referenced together and infrequently referenced separately



2. Duplicating non-key attributes in 1:* relationships to reduce joins

When PropertyForRent table is accessed, it is very common for the owner’s name to be accessed at the same time. SELECT p.*, o.lName FROM PropertyForRent p, PrivateOwner o WHERE

p.ownerNo=o.ownerNo AND branchNo=‘B003’

SQL after denormalization (no name will be change) SELECT p.* FROM PropertyForRent p WHERE branchNo=‘B003’



Duplicating non-key attributes in 1:* relationships: Lookup Table

• If lookup table is used frequent or critical queries, and the description is unlikely to change.



After Duplicating non-key attributes

• Note: the lookup table can still be used to validate user input



3. Duplicating FK attributes in 1:* relationship to reduce joins

• When frequent query is to list all private prop. owners at a branch

• SELECT o.lName FROM PropertyForRent p, PrivateOwner o WHERE p.ownerNo= o.OwnerNo AND branchNo=‘B003’

• After duplicating FK.

• SELECT o.lName FROM PrivateOwner o WHERE branchNo=‘B003’



4. Duplicating attributes in *:* relationships to reduce joins

Sales staff should contact clients without comment on the properties and he needs only street of the property.

SELECT p.street, c.*, v.viewDate FROM Client c, Viewing v, PropertyForRent p WHERE v.propertyNo=p.propertyNo AND c.clientNo=v.clientNo AND comment IS NULL

After duplicating the attributes.

SELECT v.street, c.*, v.viewDate FROM Client c, Viewing v WHERE c.clientNo=v.clientNo AND comment IS NULL



5. Introducing repeating groups

When access to tel. no is important and frequent.Use this when:

The absolute number of items in the group is known The number is static The number is not very large (less than 10)



6. Creating extract tables Reports can access derived data and perform

multi-relation joins on same set of base relations.

However, data the report is based on may be relatively static or may not have to be current.

Possible to create a single, highly denormalized extract table based on relations required by reports, and allow users to access extract table directly instead of base relations.



Advantages and disadvantages of denormalization


Monitoring the System to Improve Performance

Second Topic



Monitor & Tune Operational System To monitor operational system and improve

performance of system to correct inappropriate design decisions or reflect changing requirements.



Monitor & Tune Operational System Number of factors may be used to measure efficiency:

Transaction throughput: number of transactions processed in given time interval.

Response time: elapsed time for completion of a single transaction. Disk storage: amount of disk space required to store database files.

Have to trade each off against another to achieve reasonable balance.

Need to understand how the various hardware components interact and affect database performance.



Consideration PointsIt is sensible always to have a minimum of 5% of

main memory available.

It is necessary to understand the typical workload through 24 hour period to ensure sufficient resources are available

Storage should evently distributed to reduce disk contention Separate OS, main database files, index files and recovery log

files.


Advanced Database Systems

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