Relational optimization and consideration

8/12/2019 Relational optimization and consideration

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REL TION L OPTIMIZ TIONND CONSIDER TIONS


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Relational Optimization

The optimizer is the heart of a relational

database management system.

Optimizer is an inference engine fordetermining the best possible database

navigation strategy for any given SQL request.


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Relational optimization is very powerful because it

allows queries to adapt to a changing database

environment. It can also react to changes by formulatingnew access paths without requiring application coding

changes to be implemented.

Physical Data Independence is the separation of accesscriteria from physical storage characteristics


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To optimize SQL

The relational Optimizer must analyze each SQL

statements by parsing it to determine the tables and

columns that must be accessed.

The optimizer will access statistics stored by the RDBMS

in either system catalog or the database objects

themselves


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Every RDBMS has an embedded

relational optimizer that renders SQL

statements into executable accesspaths.


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Modern relational optimizers are cost based,

meaning that the optimizer will attempt to

formulate an access path for each query that

reduces overall cost.


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CPU and I/O Costs

The optimizer can arrive at a rough estimate of the

CPU time required to run the query using each optimized

access path at analyzes.


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Database Statistics

A relational optimizer is of little use without accurate

statistics about the data stored in the database. It provides

DBMS a utility program or command to gather statistics

about database objects and to store them for them for use

by the optimizer.


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The DBA should collect modified statistics whenever

a significant volume of date has been added or modified.

Failure to do so will result in the optimizer basing its cost

estimates on inaccurate statistics. This may be detrimental

to query performance.


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DBMS collects statistical information

Number of unique values stored in the column

Most frequently occurring values for columns

Index key density

Details on the ratio of clustering for clustered tables

Correlation pf columns to other columns

Structural state of the index or tablespace

Amount of the storage used by the database object


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Query Analysis

It scans the SQL statement to determine its overall

complexity. The formulation of the SQL statement is a

significant factor in determining the access paths chosen

by the optimizer.

The complexity of the query, the number and the

type of predicates, the presence of functions, and the

presence of ordering clauses enter into the estimated cost

that is calculated by the optimizer


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Which tables in which database are required

Whether any views are required to be broken down intounderlying tables

Whether tables joins or subselects are required

Which indexes, if any, can be used

How many predicates must be satisfied

Which functions must be executed

Whether the SQL uses OR or AND


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How the DBMS process each component of the SQLstatement

How much memory has been assigned to the data caches

used by the tables in the SQL statement

How much memory is available for sorting if the query

requires a sort.


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Joins

Joining combining information from multiple tables.

When multiple tables are accessed, the optimizer

figures out how to combine the tables in the most efficientmanner.

When determining the access path for a join, the

optimizer must determine the order in which the tables willbe joined.


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Choose the table to process first

Series of operations are performed on the outer table to

prepare it for joining.

Rows from that table are then combined with rows fromthe second table, called the INNER TABLE.


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Two common Join Method

Nested-loop join

Merge-scan join


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Merge-scan Join

The tables to be joined are ordered by the keys. This

ordering can be accomplished by a sort or by access via an

index.


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Join Order

The optimizer reviews each join in a query and

analyzes that appropriate statistics to determine the optimal

order in which the tables should be accessed to complete

the join.

To find optimal join access path, the optimizer uses

built-in algorithms containing knowledge about joins and

data volume.

It matches this intelligence against the join

predicates, databases statistics, and available indexes toestimate which order is more efficient.

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Relational optimization and consideration