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by Jim Gillespie ORAMAIN Consulting Services, LLC emailid: [email protected] website: www.oramain.com Phone: 608-848-8642 Cell : 608-217-4351. The Do’s and Don’ts of CBO. The Do’s and Don’ts of CBO. Agenda What is the Optimizer? Why Optimize? Available Optimizers

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The do s and don ts of cbo l.jpg

by Jim Gillespie

ORAMAIN Consulting Services, LLC

emailid: [email protected]

website: www.oramain.com

Phone: 608-848-8642

Cell : 608-217-4351

The Do’s and Don’ts of CBO

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The Do’s and Don’ts of CBO

Agenda

What is the Optimizer?

Why Optimize?

Available Optimizers

Why is RBO being removed?

Why move to CBO?

Initialization parameters that affect CBO

Internal Oracle parameters that affect CBO

Setup changes for migrating to CBO

Generating Statistics

DML Monitoring

Hints

Statistics for SYS schema

How to analyze execution plans in CBO?

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The Do’s and Don’ts of CBO

WHAT IS THE OPTIMIZER?

An ‘engine’ running in the database.

It is dedicated to derive a list of execution plans.

Cost Based Optimization (CBO)

Rule Based Optimization (RBO)

In CBO the plan with the lowest cost is used.

In RBO the plan with the best ranking is used.

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WHY OPTIMIZE?

To execute a SQL statement in the shortest time.

To utilized the fewest resources.

CPU

I/O

Memory

Network operations

One bad SQL statement can impact all process on the server.

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AVAILABLE OPTIMIZERS.

Oracle has two modes (pre 10g);

Rule based optimization (RBO)

Cost based optimization (CBO)

RBO

Follows a ranking methodology.

Fifteen ranking points in RBO.

Was the preferred mode.

The fifteen ranking points are;

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The Do’s and Don’ts of CBO

Single row by ROWID

Single row by cluster join

Single row by hash cluster with unique or primary key

Single row by unique or primary key

Cluster join

Hash cluster key

Indexed cluster key

Composite key

Single column indexes

Bounded range on index columns

Unbounded range on indexed columns

Sort merge join

MAX or MIN on indexed column

ORDER BY on indexed columns

Full table scan

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CBO

Follows expense calculation methodology.

All execution plans get a cost.

The lower the cost the less resources used.

Uses statistics and histograms that are in the dictionary.

Also uses user supplied hints and initora parameters.

Can build up to 80,000 permutations of execution plans.

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STATISTICS

Critical input for the Optimizer.

Generated on data storing objects.

May be exact or estimated.

The more accurate, the better CBO works.

Estimate uses a provided sample size, either number of rows

or a percent.

Block sampling is an option – usually for huge tables.

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STATISTICS (cont.)

Good execution plans depend on how close the estimate is

to the exact values.

Test using different sample sizes. More on this later.

Statistics are stored in tables owned by the SYS user.

The DBA_ views show the statistics used by the optimizer.

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DBA_TABLES

NUM_ROWS - Number of rows.

BLOCKS - Number of used blocks.

EMPTY_BLOCKS - Number of empty blocks that have never been used.

AVG_SPACE - Average free space (in bytes) in blocks allocated to the table. All empty and free blocks are considered for this.

CHAIN_CNT - Number of chained or migrated rows.

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DBA_TABLES (cont.)

AVG_ROW_LEN - Average row length in bytes.

LAST_ANALYZED - Date when the table was last analyzed.

SAMPLE_SIZE - Sample size provided for ESTIMATE statistics. Equal to NUM_ROWS if COMPUTE.

Statistics for individual partitions of a table can be seen from DBA_TAB_PARTITIONS.

Cluster statistics are available from DBA_CLUSTERS.

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DBA_TAB_COLUMNS

NUM_DISTINCT - Number of distinct values.

LOW_VALUE - Lowest value

HIGH_VALUE - Highest value

DENSITY - Density of the column

NUM_NULLS - Number of records with null value for the concerned column.

LAST_ANALYZED - Date when the table was last analyzed.

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DBA_INDEXES

BLEVEL - Depth of the index, from root to leaf.

LEAF_BLOCKS - Number of leaf blocks.

DISTINCT KEYS - Number of distinct keys.

AVG_LEAF_BLOCKS_PER_KEY - Average number of leaf blocks in which each distinct key appears, should be 1 for unique indexes.

AVG_DATA_BLOCKS_PER_KEY - Average number of blocks in the table that are pointed to by a distinct key.

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DBA_INDEXES (cont.)

NUM_ROWS - Number of rows indexed.

SAMPLE_SIZE - Sample size provided for ESTIMATE statistics. Equal to NUM_ROWS if COMPUTE.

LAST_ANALYZED - Date when the table was last analyzed.

GLOBAL_STATS - For partitioned indexes, YES - statistics collected as a whole, NO - statistics are estimated from statistics.

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AVAILABLE CBO MODES

CBO has two available modes in which to run;

ALL_ROWS

FIRST_ROWS

FIRST_ROWS aims at returning the first row(s) of the statement as soon as possible.

Prefers nested-loops.

Best for OLTP.

As of 9i, FIRST_ROWS_n can be used.

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AVAILABLE CBO MODES (cont.)

ALL_ROWS processes all rows for a given query before returning the output. It forces the optimizer to consider minimal use of resources and best throughput.

ALL_ROWS prefers sort-merge joins.

Good for batch type processing.

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CBO is dynamic and tunes its execution plans as the database grows in size.

Do not be taken aback if the same query that works perfectly in one database setup is behaving badly in some other database of the same application.

This would happen if the setup and statistics differ between the two databases.

To prevent such behavior, you may consider using optimizer plan stability, which is covered later.

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BASIC CBO TERMS

The following terms will be used quite often when analyzing statements in CBO.

CostThe COST computed in CBO is a unit of expense involved with each operation. The logic as to how the cost is actually derived is not documented or made external. Moreover, this may change across releases.

CardinalityThe number of rows in the table or number of distinct row links in the index. The cardinality of a query is the number of rows that is expected to be returned by it.

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BASIC CBO TERMS (cont.)

StatisticsMuch required information gathered for various data holding objects. This information is vital for the CBO to decide on execution plans.

Join MethodsOracle uses joins like Hash, sort-merge and nested loops. A query may run faster using one type of join as compared to other methods. This should be evaluated for individual queries.

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BASIC CBO TERMS (cont.)

FTSFTS or Full Table Scan relates to a query sequentially scanning a table from the first block to the last allocated block. This could be very expensive for big tables and should be avoided.

Index scanRelates to random access of a table by use of one or more indexes on the table..

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WHY IS RBO BEING REMOVED?

The existence of RBO prevents Oracle from making key enhancements to its query-processing engine. Its removal will permit Oracle to improve performance and reliability of the query-processing components of the database engine.

Oracle 9i release 2 is the last version that supports RBO.

Switch to CBO before this version is no longer supported.

RBO will be available in Oracle 10g, but not supported.

Presently, Oracle support for RBO is limited to bug fixesonly and no new functionality will be added to RBO.

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WHY MOVE TO CBO?

Oracle stopped developing for RBO environment.

RBO will be removed from the Oracle database.

RBO has a limited number of access methods compared to CBO.

All new features require CBO. CBO is enabled to identify these features, and how to evaluate their cost. These features will be of importance for any setup; e.g. IOTs, bitmap indexes, Function-based indexes, reverse-key indexes, Partitioning, Hash joins, Materialized views, parallel query, star joins, etc.

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WHY MOVE TO CBO? (cont.)

Once RBO is no longer supported, Oracle support will not be available.

CBO has matured.

Distributed and remote queries are more reliable.

RBO performed poorly joining tables across links.

CBO is aware of statistics on the remote tables.

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INITORA PARMS THAT AFFECT THE OPTIMIZER

OPTIMIZER_MODE

Valid values are RULE, CHOOSE, ALL_ROWS, FIRST_ROWS (_n). Default: choose. Dynamic

If set to CHOOSE. The optimizer tries to run the query in either CBO or RBO depending on the availability or unavailability of statistics. Therefore, if the tables present in the query have statistics generated on them, CBO (ALL_ROWS only) is preferred else RBO is used.

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INITORA PARMS THAT AFFECT THE OPTIMIZER

OPTIMIZER_FEATURES_ENABLE

Set to a version number such as- 8.1.5, 8.1.7, 9.0.0.

Setting it to a lower version will prevent the use of new features that have come in later versions.

Default is current release. Static.

e.g.: optimizer_features_enable = 8.1.7

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INITORA PARMS THAT AFFECT THE OPTIMIZER

OPTIMIZER_MAX_PERMUTATIONS

Specifies the maximum number of permutations that should be considered for queries with joins, to choose an execution plan.

Influences the parse time of queries.

Set to a lower value.

Default is 80000 in Oracle 8, in Oracle 9i it is defaulted to 2000. Dynamic.

e.g.: optimizer_max_permutations = 3000

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INITORA PARMS THAT AFFECT THE OPTIMIZER

COMPATIBLE

Used to provide backward compatibility with earlier releases.

May restrict the use of some new features.

Only three digits are required to be specified, however, you can specify more for documentation purposes.

Default is current release. Static.

e.g.: compatible = 8.1.7

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INITORA PARMS THAT AFFECT THE OPTIMIZER

HASH_JOIN_ENABLED

Values, true or false.

If set to false, hash joins will not be considered by the Optimizer.

Default is true. Dynamic

e.g.: hash_join_enabled = false

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INITORA PARMS THAT AFFECT THE OPTIMIZER

HASH_AREA_SIZE

This specifies the maximum amount of memory in bytes to be used for a hash join per process.

Oracle recommends the use of PGA_AGGREGATE_TARGET instead of this parameter from Oracle 9i.

Default is 2 times SORT_AREA_SIZE. Dynamic.

e.g.: hash_area_size = 2097152

Setting this to a very low number may sometimes result in the following error.

ORA-6580: Hash Join ran out of memory while keeping large rows in memory.

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INITORA PARMS THAT AFFECT THE OPTIMIZER

OPTIMIZER_DYNAMIC_SAMPLING

Is used in situations where tables are not analyzed. As CBO depends heavily on statistics, the parameter tells the optimizer to sample the unanalyzed tables that are being used in a query. A level of 0 to 10 can be specified, the higher the value the more time optimizer spends in sampling.

Default is 1 in 9.2 and above, 0 if below. Dynamic.

e.g.: optimizer_dynamic_sampling = 4

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INITORA PARMS THAT AFFECT THE OPTIMIZER

CURSOR_SHARING

Determines what kind of SQL statements can share the same cursor. It can be set to FORCE, SIMILAR or EXACT. FORCE will try to squeeze statements that may differ in some literals to share the same cursor. SIMILAR is somewhat the same but will try to maintain the plan optimization for identical statements. EXACT allows statements with exact identical text to share a cursor.

Using FORCE may sometimes result in unexpected results.

Default is exact. Dynamic

e.g.: cursor_sharing = force

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INITORA PARMS THAT AFFECT THE OPTIMIZER

PGA_AGGREGATE_TARGET

Introduced in Oracle 9i, this parameter specifies the aggregate PGA memory available to all server processes attached to an instance. This parameter can be set for automatic sizing of SQL working areas. It replaces other existing parameters like SORT_AREA_SIZE, BITMAP_MERGE_AREA_SIZE and HASH_AREA_SIZE.

Default is 0, automatic memory management is off. Dynamic.

It can be set to a value between 10 MB to 4096 GB-1, depending on the setup requirement.

Determine how much memory you have, subtract the SGA and give the rest to PGA, if possible.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER.

Undocumented, set by Oracle.

Should not change unless recommended by Oracle Support.

Begin with underscore (_). e.g.: ALTER SESSION SET “_COMPLEX_VIEW_MERGING” = TRUE;

The following parameters changed the default from false to true when upgrading from 8i to 9i. They may have impact on response time. Negative or positive.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER. Changed default (cont.).

_COMPLEX_VIEW_MERGING

This parameter is related to improving the SQL performance on complex views (including inline views). Oracle tries to merge the query criteria with the existing view criteria that would result in a faster single query. For example, if a view is created with a GROUP BY clause in it and a query is executed on the view having a where clause, Oracle tries to merge the two and create a single query that would run the where clause prior to grouping it, thus giving better performance.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER. Changed default (cont.).

_PUSH_JOIN_PREDICATE

This enables the push join predicate feature that allows the optimizer to push join predicates inside a non-mergeable view(s). This would achieve something similar to a complex view merging feature, but in this case the join conditions provided in the query are pushed into the view. The view in this case cannot be merged with the query.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER. Changed default (cont.).

_PUSH_JOIN_UNION_VIEW

Same as above, but this parameter allows optimizer to push join predicates inside non-merge able views that contain UNION ALL set operators.

_TABLE_SCAN_COST_PLUS_ONE

This parameter increases the cost of a full table scan by one, in order to eliminate ties between a full table scan on a small lookup table and unique or range scan on the lookup table.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER. Changed default (cont.).

_OR_EXPAND_NVL_PREDICATE

This feature expands the NVL function predicates to evaluate the use of an index that may be present on the column used in the function. For example, if the expression is of the type "column1 = nvl(:b1, column1)" and column1 has an index on it, then optimizer may transform it to a new expression that uses the OR operator. This new expression will again be further transformed to make use of the UNION operator.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER. Changed default (cont.).

_USE_COLUMN_STATS_FOR_FUNCTION

Allows the use of column statistics for columns that are involved in non-operative expressions in query, such as:

numcol + 0

charcol || ''

Such expressions were mainly used in RBO to prevent the use of indexes.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER. Changed default (cont.).

_ORDERED_NESTED_LOOP

This reduces the cost of a nested loop join when the left side of the join is using an index or sort row source.

_NEW_INITIAL_JOIN_ORDERS

This parameter enables join permutation optimization. New ordering directives have been added to CBO for better processing of joins, setting this parameter will allow use of these directives.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER. Changed default (cont.).

_B_TREE_BITMAP_PLANS

Enables creation of interim bitmap representation for tables in a query with only binary index(es).

_UNNEST_SUBQUERY

This enables un-nesting of correlated sub-queries. Such queries may undergo MERGE join operations.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER. Changed default (cont.).

_INDEX_JOIN_ENABLED

Enables the use of index joins wherever feasible, rather than at table level.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER. Response time implications.

_SQLEXEC_PROGRESSION_COST

This controls the population of V$SESSION_LONGOPS view by long running queries. This view is used to monitor the progress of queries that are running for long duration. Queries that cost more than the value that has been set are identified for monitoring. Progression monitoring involves overhead and may affect the performance.

Default is 1000, which may prevent SQL statements from being shared! Setting it to 0 will turn off the monitoring.

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INTERNAL INITORA PARMS THAT AFFECT THE OPTIMIZER. Response time implications (cont.).

_OPTIMIZER_MODE_FORCE

This parameter decides the optimizer mode for users recursive SQL, for example, queries running from the PL/SQL block. In CBO, recursive SQL is executed in CHOOSE mode if this parameter is set to FALSE. If this parameter is set to TRUE, then recursive SQL inherits the session's optimizer mode. Hence, if the session is running in FIRST_ROWS, then all SQL processing carried out will be done in the same optimizer mode.

Default is false.

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Setup changes for migrating to CBO

Here we highlight a number of key points to consider when moving to CBO. In addition, we highlight a number of good maintenance practices. Tuning in CBO is an ongoing process and proper analysis should be done. You may encounter scenarios specific to your environment that are not mentioned here. Make it a point to refer to the documentation and check with Oracle support for any kind of anomalies.

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Setup changes for migrating to CBO (cont.)

OPTIMIZER_MODE

FIRST_ROWS(_n) for OLTP.

ALL_ROWS for DSS, batch, wharehous.

CHOOSE for mixed modes, i.e., Some applications

or modules are in RBO mode and some in CBO mode.

In CHOOSE mode CBO defaults to ALL_ROWS. Use alter session to force FIRST_ROWS(_n).

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Generate adequate statistics at proper intervals.

Use DBMS_STATS to generate periodic statistics.

ESTIMATE using 5 to 10% is usually adequate.

Use COMPUTE for indexes and indexed-organized tables.

Statistics are not incremental.

Frequency of change determines frequency of analyzing.

Global Temporary Tables can not be analyzed. Use DBMS_STATS.SET_TABLE_STATS.

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Generate adequate statistics at proper intervals (cont.).

SQL> exec dbms_stats.set_table_stats(ownname => 'SYS', tabname => ‘EMP', numrows => 3000, numblks => 300, avgrlen => 50);

PL/SQL procedure successfully completed.

SQL> select num_rows, blocks, avg_row_len, temporary,

user_stats from dba_tables where table_name = 'EMP';

NUM_ROWS BLOCKS AVG_ROW_LEN T USE

---------- ---------- ----------- - ---

3000 300 50 Y YES

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Provide sufficient time for each site to settle down

If you are supporting multiple client installations, my recommendation is to consider migrating each setup on different dates. Each site may have its own unique issues relating to individual setups, and this will give you more time to examine performance issues at each site. Make sure that testing is done on individual site test boxes before moving the production box to CBO.

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Change your scripts!!!

Most DBAs rely on scripts. These may be outdated. For example, include columns such as LAST_ANALYZED, MONITORING, GLOBAL_STATS and USER_STATS in scripts that look at the object information. Modify your tuning scripts to find out in what mode the database, session or particular queries are running.

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Coding habits and Technical Guidelines

Moving to CBO opens many new features for developing and designing.

Your Technical Documentation Guidelines (if you have one) that developers rely on for standards. Liaise with the complete team to update your conventions.

In RBO, the last table in the where clause is the driver. The first table is the driver in CBO.

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Coding habits and Technical Guidelines (cont.).

The ORDERED hint used in CBO picks up tables left-to-right for processing.

Avoid RBO style coding techniques. Techniques used to prevent the use of indexes in RBO should be avoided. CBO has advanced features such as function-based and bitmap indexes.

Control processing of queries with proper where clauses and hints.

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Plan stability using stored outlines.

Stored outlines store existing execution plans.

Using stored outlines tells optimizer to consider the execution path specified explicitly.

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Use Hints

Hints will become a favorite practice for developers.

Use hints in queries to direct optimizer to consider an alternative path than the one being chosen.

Hints will help queries that behave differently on different databases.

CBO will give more preference to hints than to the statistics present. But this doesn’t gaurantee the hints will be used.

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Provide sufficient sort space

Gathering statistics on tables requires sorting to be done.

This takes up sort-area space in memory as well as temporary tablespace.

Make sure you have enough temporary space to generate statistics (depending on ESTIMATE or COMPUTE) for the largest table.

You may consider increasing the value of SORT_AREA_SIZE to allow more operations to take place in memory and save on I/O.

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FGAC changes

Execution plan may change if you are using Fine Grained Access control (FGAC).

FGAC adds additional predicates to an existing query that may sometimes result in a change of execution plan.

Test your queries with these additional predicates.

Make use of hints to direct optimizer to do what is needed.

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Generating Statistics

COMPUTE

100% accurate.

Takes time.

Use on indexes and IOTs.

ESTIMATE

needs input, number of rows or percent

NUM_ROWS, AVG_SPACE and AVG_ROW_LEN

will have their values derived.

Thus NUM_ROWS may not reflect actual row count.

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HOW MUCH TO ESTIMATE?

No perfect number of rows or percent.

Varies by table.

Derive statistics using different percents and report on results.

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HOW MUCH TO ESTIMATE? (cont.)

Example

The table abc.emp has around 4.5 million records. Below are statistics at various sample sizes.

Commands used:

dbms_stats.gather_table_stats('abc', ‘emp'); --compute

dbms_stats.gather_table_stats('abc', 'emp ', estimate_percent => 5);

dbms_stats.gather_table_stats('abc', ' emp ', estimate_percent => 10);

dbms_stats.gather_table_stats('abc', ' emp ', estimate_percent => 51);

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HOW MUCH TO ESTIMATE? (cont.)

Final statistics:

MODE |NUM_ROWS|SAMPLE_SIZE|Time taken

--------------------------------------------------------------

compute | 4591474 | 4591474 | 2 hr

at 5% | 4582460 | 229123 | 8 mts

at 10% | 4587520 | 458752 | 17 mts

at 20% | 4591635 | 918327 | 32 mts

at 51% | 4590890.2 | 2341354 | 1 hr 56 mts

The NUM_ROWS difference between full statistics and 5% is only 9014 records. Statistics at a 5% sample size serves my purpose as the variance is less than 1% that of actual value.

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WHAT SHOULD THE TIME INTERVAL BE?

Start with a weekly generation.

DML Monitoring can be used on tables with heavy activity.

Generate statistics after bulk loading.

Generate statistics after building a work table.

Group objects by type and generate at different intervals.

e.g: transaction tables versus master tables.

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STATISTICS LOCKS?

Tables analyzed cannot undergo DDL changes.

DML activities can be carried on.

Analyzing an index puts a shared lock on the related table; hence, neither DML nor DDL can be performed.

Preferably avoid all activities during the statistics generation phase.

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UTILITIES TO GENERATE STATISTICS

DBMS_UTILITY

ANALYZE command

DBMS_DDL

DBMS_STATS

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UTILITIES TO GENERATE STATISTICS (cont.)

DBMS_STATS

The recommend package provided for gathering and maintaining statistics in a database.

The following can be done with this package:

Gathering statistics

Deleting statistics

Providing user statistics

Retrieving statistics

Exporting and importing statistics

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UTILITIES TO GENERATE STATISTICS (cont.)

GATHERING STATISTICS WITH DBMS_STATS

DBMS_STATS.GATHER_TABLE_STATS gathers statistics for a table and its columns, and optionally the associated indexes.

Call syntax

dbms_stats.gather_table_stats(ownname, tabname, partname,

estimate_percent, block_sample, method_opt, degree, granularity, cascade, stattab, statid, statown);

The first two parms are mandatory, the rest defaulted.

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DBMS_STATS.GATHER_TABLE_STATS(cont.)

PARAMETERS

ownname - owner

tabname - table name

partname - partition name

estimate_percent - sample percent ratio

block_sample - consider random blocks sampling rather than rows sampling. TRUE/FALSE

method_opt - method options. FOR ALL COLUMNS/FOR ALL INDEXED COLUMNS. Append the phase SIZE 1 if it is required to generate statistics in parallel.

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DBMS_STATS.GATHER_TABLE_STATS(cont.)

PARAMETERS (cont.)

degree - degree of parallelism.

granularity - for partitioned tables. DEFAULT/SUBPARTITION

/PARTITION/GLOBAL/ALL.

cascade - gather statistics for indexes also. TRUE/FALSE

stattab, statid, statown - required for user statistics, covered below in this section.

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DBMS_STATS.GATHER_TABLE_STATS examples.

e.g.: Estimate statistics for a table and its columns

SQL> exec dbms_stats.gather_table_stats

(ownname => ‘SCOTT', tabname => ‘EMP', estimate_percent => 5);

e.g.: Estimate statistics for a table, its columns and indexes.

SQL> exec dbms_stats.gather_table_stats

(ownname => ‘SCOTT', tabname => 'EMP',

estimate_percent => 5, cascade => true);

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DBMS_STATS.GATHER_TABLE_STATS examples(cont.).

e.g.: Estimate statistics in parallel, the following uses 8 threads to complete the task.

SQL> exec dbms_stats.gather_table_stats

(ownname => 'SCOTT', tabname => 'EMP_TRX',

estimate_percent => 5, degree => 8);

When the above process is running;

select * from v$px_process; produces -

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DBMS_STATS.GATHER_TABLE_STATS examples(cont.).

SERV|STATUS | PID|SPID |SID| SERIAL#

P000 | IN USE | 50|9684 | 7| 50586

P001 | IN USE | 65|9686 | 60| 51561

P002 | IN USE | 66|9688 | 17| 2694

P003 | IN USE | 67|9690 | 30| 39243

P004 | IN USE | 68|9692 | 74| 11017

P005 | IN USE | 69|9694 | 48| 4253

P006 | IN USE | 70|9696 | 76| 17

P007 | IN USE | 71|9698 | 68| 1285

8 rows selected.

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DBMS_STATS.GATHER_INDEX_STATS examples.

Call syntax

dbms_stats.gather_index_stats(ownname, indname, partname, estimate_percent, stattab, statid, statown);

e.g.:

SQL> exec dbms_stats.gather_index_stats

(ownname => 'SCOTT', indname => EMP_IDX');

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DBMS_STATS.GATHER_SCHEMA_STATS examples.

Call Syntax

dbms_stats.gather_schema_stats(ownname, estimate_percent, block_sample, method_opt, degree, granularity,

cascade, stattab, statid, options, objlist, statown);

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DBMS_STATS.GATHER_SCHEMA_STATS examples (cont.).

Parameters

options - object information can be further specified here.

GATHER - gather statistics for all objects (default).

GATHER STALE - update statistics for stale objects, identified with the monitoring option.

GATHER EMPTY - gather statistics for objects without any statistics.

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DBMS_STATS.GATHER_SCHEMA_STATS examples (cont.).

Parameters

LIST STALE - return a list of stale objects, this depends on the SMON processing.

LIST EMPTY - return a list of objects with no statistics.

GATHER AUTO - same as STALE but will include objects without any statistics.

objlist - table of type DBMS_STATS.OBJECTTAB, returns an empty or stale list.

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DBMS_STATS.GATHER_SCHEMA_STATS examples (cont.).

e.g.: Gather schema statistics, for tables and indexes at 5% estimate.

SQL> exec dbms_stats.gather_schema_stats(ownname => 'SCOTT', estimate_percent => 5, cascade => true,

options => 'GATHER');

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DBMS_STATS.GATHER_SCHEMA_STATS examples (cont.).

e.g.: Gather statistics for objects with no statistics. The GATHER EMPTY options generates statistics for all objects without any statistics.

SQL> exec dbms_stats.gather_schema_stats

(ownname => 'SCOTT', estimate_percent => 5,

options => 'GATHER EMPTY');

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DBMS_STATS.GATHER_SCHEMA_STATS examples (cont.).

e.g.: To identify a list of objects without any statistics.

SQL>declare

l_owner varchar2(30) := 'SCOTT';

l_emptylst dbms_stats.objecttab;

begin dbms_stats.gather_schema_stats(ownname => l_owner options => 'LIST EMPTY', objlist => l_emptylst);

for i in nvl(l_emptylst.first, 0) .. nvl(l_emptylst.last, 0) loop dbms_output.put_line(l_emptylst(i).objtype || '/' || l_emptylst(i).objname); end loop; end; /

INDEX/EMP_N1

TABLE/EMP

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DBMS_STATS.GATHER_DATABASE_STATS examples

Call Syntax

dbms_stats.gather_database_stats(estimate_percent, block_sample, method_opt, degree, granularity,

cascade, stattab, statid, options, objlist, statown);

In 8i this will generate statistics for the SYS schema. In 9i it will not.

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DBMS_STATS.DELETE_TABLE_STATS

Call Syntax

dbms_stats.delete_table_stats

(ownname, tabname, partname,

stattab, statid, cascade_parts,

cascade_columns, cascade_indexes,

statown);

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DBMS_STATS.DELETE_TABLE_STATS examples (cont.)

Parameters

cascade_parts - delete statistics for all partitions (partname should be null).

cascade_columns - delete column statistics. Default is true.

cascade_indexes - delete index statistics. Default is true.

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DBMS_STATS.DELETE_TABLE_STATS examples (cont.)

e.g.: Delete statistics for a table and its columns and indexes.

SQL> exec dbms_stats.delete_table_stats

(ownname => 'SCOTT', tabname => 'EMP');

e.g.: Delete statistics for table only. Column and index statistics will be preserved.

SQL> exec dbms_stats.delete_table_stats

(ownname => 'SCOTT', tabname => 'EMP', cascade_columns => false, cascade_indexes => false);

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DBMS_STATS.DELETE_COLUMN_STATS examples

Call Syntax

dbms_stats.delete_column_stats(ownname, tabname, colname, partname, stattab, statid, cascade_parts, statown);

e.g.: Deleting statistics for one column.

SQL> exec dbms_stats.delete_column_stats

(ownname => ‘SCOTT', tabname => 'EMP',

colname => ‘ENAME');

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DBMS_STATS.DELETE_INDEX_STATS examples

Call Syntax

dbms_stats.delete_index_stats(ownname, indname, partname, stattab, statid, cascade_parts, statown);

e.g.: Deleting index statistics.

SQL> exec dbms_stats.delete_index_stats

(ownname => 'SCOTT', indname => 'EMP_N1');

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DBMS_STATS.DELETE_SCHEMA_STATS examples

Call Syntax

dbms_stats.delete_schema_stats(ownname, stattab, statid, statown);

e.g.: Deleting statistics for schema SCOTT.

SQL> exec dbms_stats.delete_schema_stats(‘SCOTT');

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DBMS_STATS.DELETE_SCHEMA_STATS examples

Call Syntax

dbms_stats.delete_schema_stats(ownname, stattab, statid, statown);

e.g.: Deleting statistics for schema SCOTT.

SQL> exec dbms_stats.delete_schema_stats(‘SCOTT');

DBMS_STATS.DELETE_DATABASE_STATS

Call Syntax

dbms_stats.delete_database_stats(stattab, statid, statown);

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DBMS_STATS.SET_TABLE_STATS examples

Call Syntax

dbms_stats.set_table_stats(ownname, tabname, partname, stattab, statid, numrows, numblks, avgrlen, flags, statown);

Parameters

numrows - number of rows.

numblks - blocks in the table.

avgrlen - average row length.

flags - currently for internal use only.

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DBMS_STATS.SET_TABLE_STATS examples

e.g.:

SQL> exec dbms_stats.set_table_stats

(ownname => 'SCOTT', tabname => ‘EMP’,

numrows => 12422, numblks => 100, avgrlen => 124);

SQL> select owner, num_rows, blocks, avg_row_len

from dba_tables

where table_name = ‘EMP’;

OWNER | NUM_ROWS| BLOCKS|AVG_ROW_LEN

SCOTT | 12422| 100| 124

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DBMS_STATS examples (cont.)

ALSO

dbms_stats.set_column_stats

dbms_stats.set_index_stats

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DBMS_STATS.GET_TABLE_STATS examples

Call syntax

dbms_stats.get_table_stats(ownname, tabname,

partname, stattab, statid, numrows,

numblks, avgrlen, statown);

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DBMS_STATS.GET_TABLE_STATS examples (cont.)

e.g.: getting table statistics data.

SQL> declare l_numrows number; l_numblks number;

l_avgrlen number;

begin

dbms_stats.get_table_stats(ownname => 'SCOTT',

tabname => 'EMP', numrows => l_numrows,

numblks => l_numblks, avgrlen => l_avgrlen);

dbms_output.put_line('No. of rows: ' || l_numrows);

dbms_output.put_line('No. of blks: ' || l_numblks);

dbms_output.put_line('Avg row length: ' || l_avgrlen);

end; /

No. of rows: 4106860

No. of blks: 6219

Avg row length: 3

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DBMS_STATS examples (cont.)

ALSO

dbms_stats.get_column_stats

dbms_stats.get_index_stats

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS has routines for gathering statistics and storing them outside the dictionary. This does not influence the optimizer. Most of the procedures in this package have three common parameters - STATID, STATTAB and STATOWN that are related to user processing of statistics.

Advantages of this feature:

1. Estimated statistics at different percentages could be stored and used for testing.

2. Statistics generated on one database could be transferred to another database.

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.CREATE_STAT_TABLE

Call syntax

dbms_stats.create_stat_table(ownname, stattab, tblspace);

Parameters

stattab - statistics table name.

tblspace - tablespace to be used.

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.CREATE_STAT_TABLE (cont.)

e.g.: creating a user statistics table.

SQL> exec dbms_stats.create_stat_table

(ownname => 'SYS', stattab => 'STAT_AT_5PC',

tblspace => 'SYSTEM');

The table looks like this.

Desc stat_at_5pc

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.CREATE_STAT_TABLE (cont.)

Name Null? Type

---------------------- -------- -----------------------

STATID VARCHAR2(30)

TYPE CHAR(1)

VERSION NUMBER

FLAGS NUMBER

C1 VARCHAR2(30)

C2 VARCHAR2(30)

C3 VARCHAR2(30)

C4 VARCHAR2(30)

C5 VARCHAR2(30)

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.CREATE_STAT_TABLE (cont.)

Name Null? Type

---------------------- -------- -----------------------

N1 NUMBER

N2 NUMBER

N3 NUMBER

N4 NUMBER

N5 NUMBER

N6 NUMBER

N7 NUMBER

N7 NUMBER

N8 NUMBER

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.CREATE_STAT_TABLE (cont.)

Name Null? Type

---------------------- -------- -----------------------

N9 NUMBER

N10 NUMBER

N11 NUMBER

N12 NUMBER

D1 DATE

R1 RAW(32)

R2 RAW(32)

CH1 VARCHAR2(1000)

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.EXPORT_TABLE_STATS

Retrieves table statistics for a particular table and puts it in the user statistics table.

Call syntax

dbms_stats.export_table_stats(ownname, tabname, partname, stattab, statid, cascade, statown);

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.EXPORT_TABLE_STATS (cont.)

e.g.: exporting EMP stats for testing purpose, including table and indexes.

SQL> exec dbms_stats.export_table_stats

(ownname => ‘SCOTT', tabname => ‘EMP',

stattab => 'STAT_AT_5PC', cascade => true,

statown => ‘SYS');

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.EXPORT_COLUMN_STATS

Call syntax

dbms_stats.export_table_stats(ownname, tabname, colname, partname, stattab, statid, statown);

DBMS_STATS.EXPORT_INDEX_STATS

Call syntax

dbms_stats.export_index_stats(ownname, indname, partname, stattab, statid, statown);

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.EXPORT_SCHEMA_STATS

Call syntax

dbms_stats.export_schema_stats(ownname, stattab, statid, statown);

DBMS_STATS.EXPORT_DATABASE_STATS

Call syntax

dbms_stats.export_database_stats(stattab, statid, statown);

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.IMPORT_TABLE_STATS

Retrieves statistics for a table from a user statistics table and stores it in dictionary.

Call syntax

dbms_stats.import_table_stats(ownname, tabname, partname, stattab, statid, cascade, statown);

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.IMPORT_TABLE_STATS (cont.)

e.g.: importing statistics for table emp, including column and indexes.

SQL> exec dbms_stats.import_table_stats

(ownname => 'SCOTT', tabname => ‘EMP',

stattab => 'STAT_AT_5PC', cascade => true,

statown => 'SYS');

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.IMPORT_COLUMN_STATS

Call syntax

dbms_stats.import_column_stats(ownname, tabname, colname, partname, stattab, statid, statown);

DBMS_STATS.IMPORT_INDEX_STATS

Call syntax

dbms_stats.import_index_stats(ownname, indname, partname, stattab, statid, statown);

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.IMPORT_SCHEMA_STATS

Call syntax

dbms_stats.import_schema_stats(ownname, stattab, statid, statown);

DBMS_STATS.IMPORT_DATABASE_STATS

Call syntax

dbms_stats.import_schema_stats(stattab, statid, statown);

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Exporting and importing statistics with DBMS_STATS

DBMS_STATS.DROP_STAT_TABLE

Drops a user statistics table.

Call syntax

dbms_stats.drop_stat_table(ownname, stattab);

e.g.: dropping my stat table.

SQL> exec dbms_stats.drop_stat_table(ownname => 'SCOTT', stattab => 'STAT_AT_5PC');

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DML MONITORING

Used to automate the updating of statistics as tables are updated.

When enabled for a table, Oracle monitors the DML changes (including truncates) being done on the table and maintains the details in the SGA. After time SMON wakes up and post the information in the dictionary.

In Oracle 9i, this time is 15 minutes. In 8i it is 3 hours.

Enable with Alter table, Create table or DBMS_STATS.

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DML MONITORING (cont.)

SQL> alter table EMP monitoring;

SQL> select monitoring from dba_tables where table_name = ‘EMP';

MON

---

YES

e.g.: Monitoring option for table EMP.

SQL> exec dbms_stats.gather_table_stats(‘SCOTT', ‘EMP')

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DML MONITORING (cont.)

Statistics on tables that had > 10% modifications can be seen in the DBA_TAB_MODIFICATIONS view.

SQL> select * from dba_tab_modifications;

no rows selected

--DML activities were carried on the table.

SQL> select table_owner, table_name, inserts, updates,

deletes, timestamp, truncated

from dba_tab_modifications;

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  • DML MONITORING (cont.)

  • TABLE_OWNER TABLE_NAME INSERTS UPDATES DELETES TIMESTAMP TRU

  • ----------- ---------- ------- ------- ------- --------- ---

  • SCOTT EMP 1028577 0

  • 19-SEP-03 NO

  • SQL> exec dbms_stats.gather_schema_stats

  • (ownname => ‘SCOTT',

  • options => 'GATHER STALE');

  • SQL> select * from dba_tab_modifications;

  • no rows selected

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DML MONITORING (cont.)

No known SGA issues when using montoring.

Does not result in performance issues.

Use on tables that are being changed significantly and optimizer results fluctuate significantly.

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HINTS

Clues or directives that will assist the optimizer in choosing an execution plan.

Guide the Optimizer to do things in a certain way--the way we would like a statement to run.

Not orders but directives to the optimizer.

Provided in comment form

/*+ <hint> */

--+ <hint>

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HINTS (cont.)

Multiple hints can be provided in a single comment for a statement, each separated with spaces.

Meant for DML statements.

Are not case sensitive.

If a wrong or invalid hint is provided, the optimizer ignores it and continues with the execution of the statement. The optimizer will not notify the user about such hints.

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HINTS (cont.)

Hints are CBO features. Using them in RBO setup will force the queries to run in cost mode. The exception to this is the RULE hint that invokes the RBO for executing a statement.

Hints can be used to influence the mode of the optimizer, the access path, the join order, the join method used etc..

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HINTS (cont.)

SQL statements that are executed directly may behave differently when executed from within PL/SQL. Make use of hints in such cases to achieve the required results.

Table hints can be provided with the table name. . If an alias name is provided, use it instead of the table name.

Avoid the use of schema name along with the table name in hints, even if they appear in the FROM clause. Using aliases is a safe bet.

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HINTS (cont.)

As stated by Oracle Documentation, the use of hints involves extra code that must be managed, checked and controlled. Use hints to tame queries that execute with sub-optimal execution plans, but take care to provide the right access paths.

Here is a list of the most widely used hints:

ALL_ROWS : for good throughput and resource utilization.

FIRST_ROWS : for good response time.

RULE : Use rule-based optimization rather than cost.

CHOOSE : Decide on rule or cost optimization based on the existence of statistics.

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HINTS (cont.)

FULL : for doing a full table scan on the table.

HASH : hash scan, applies only for clustered tables (do not confuse with HASH join).

ROWID : table scan by rowid.

CLUSTER : cluster scan, applies only for clustered tables.

INDEX : index scan, specify the table and the index name.

INDEX_ASC : for range scan, scan index in ascending order of values.

INDEX_DESC : for range scan, scan index in descending order of values.

INDEX_JOIN : use index join as an access path. Two indexes could be joined to return the required values.

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HINTS (cont.)

INDEX_FFS : perform a fast full scan on the index rather than on the table.

NO_INDEX : avoid the use of the specified index or all indexes.

INDEX_COMBINE : explicitly choose a bitmap access path, make use of bitmap indexes.

ORDERED : access and join tables in the order mentioned in the FROM clause, left to right.

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HINTS (cont.)

USE_NL : use Nested Loop for joining tables.

USE_HASH : use Hash joins.

USE_MERGE : use Sort-Merge joins.

The optimizer hints ALL_ROWS, FIRST_ROWS, RULE and CHOOSE affect the Optimizer mode for executing the query, irrespective of what is set at session level.

The RULE Hint causes the Optimizer to use rule based optimization to choose the execution path. This is an instant solution for queries that ran perfectly in RBO but have slowed down in CBO.

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HINTS examples

e.g.: improving a queries response time.

select /*+ first_rows */ trx_value

from jnc_rtl_sales_iface_hdr

where trx_no = 1211;

e.g.: Full table scan directive.

select /*+ full(a) */ a.shop_no, a.subinventory_code, b.item_code

from jnc_shop_mapping a, jnc_rtl_sales_iface_hdr b

where b.shop_no = a.shop_no;

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Statistics for SYS schema.

One issue that has always been in doubts is whether to generate statistics for SYS schema. Generating statistics for dictionary tables owned by SYS is not recommended in Oracle 8i. The dictionary views that reference the SYS tables execute efficiently with the Rule Based Optimizer.

You may generate statistics in Oracle 9i but you will have to evaluate this option for your setup. As per a note I came across, Oracle does not perform any regression testing with dictionaries analyzed and there may be a possibility of performance issues. Oracle 10 and above would require statistic generation for SYS schema as RBO will be desupported.

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  • Statistics for SYS schema (cont.)

  • Ways to deal with SYS related queries

  • Run your setup in CHOOSE mode. Generate statistics for application specific schemas. Avoid doing so for SYS schema.

  • This way, RBO will be used when accessing the dictionary and CBO when your application runs. The only catch is that CBO will resort to ALL_ROWS and that may cause issues in OLTP systems. Setting the initialization parameters appropriately and extensive use of hints for application queries will stabilize the system in due course.

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The Do’s and Don’ts of CBO

Statistics for SYS schema (cont.)

Ways to deal with SYS related queries (cont.)

Run your setup in ALL_ROWS or FIRST_ROWS mode. Generate statistics for application specific schemas. Avoid doing so for SYS schema. Make extensive use of RULE hints for dictionary queries that are slow.

This way, Dictionary related queries will still be on RBO and the application can run on CBO.

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The Do’s and Don’ts of CBO

How to get execution plans in CBO?

Same as RBO.

Use sqltrace with TKPROF.

Use Explain Plan.

Two scripts, UTLXPLS.SQL (serial) and UTLXPLP.SQL (parallel executions), are provided by oracle to show the formatted execution plans.

Use autotrace.

Set timing on.

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The Do’s and Don’ts of CBO

PLAN STABILITY

- most useful when you cannot risk

performance changes

- preserves execution plans in stored

outlines

- the optimizer generates equivalent

execution plans from the stored outlines.

- facilitates migration from rule to cost

based optimization when you upgrade.

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The Do’s and Don’ts of CBO

PLAN STABILITY

- will use hints

- needs exact text matching

- degradation can occur if datatypes

change

- contrary to CBO.

- uses system table OL$ and OL$HINTS

- outlines are retained indefinetly

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The Do’s and Don’ts of CBO

CREATING STORED OUTLINES

- INITORA parameter

CREATE_STORED_OUTLINE = TRUE

- schema needs CREATE ANY OUTLINE

privilege.

- see the CREATE OUTLINE statement in

the ORACLE9i SQL Reference.

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The Do’s and Don’ts of CBO

USING STORED OUTLINES

- set system parameter

USED_STORED_OUTLINES to TRUE or to

a category. If set to TRUE then Oracle uses

the DEFAULT category. If a category is listed

then Oracle uses that category until you set the

category to another name or set

USED_STORED_OUTLINES to FALSE.

- there is an OUTLN_PKG for managing

stored outlines and their categories, see

Oracle9i Supplied PL/SQL Packages Ref.

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The Do’s and Don’ts of CBO

VIEWING STORED OUTLINES

- select outline_category from v$sql

where sql_text like ‘your sql text%’;

- select name, sql_text

from user_outlines

where category = ‘yourcategory’;

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The Do’s and Don’ts of CBO

WHEW!!!

As you can see CBO will bring many changes.

Start now so your ready for 10g.

Use the phase approach. Set optimizer_mode to CHOOSE and convert a few modules at a time.

Lastly, if you need help, contact me.

Questions? THANK YOU!

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