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Optimization Modes and Hints


This chapter explains when to use the available optimization modes and how to use hints to enhance Oracle performance.

Topics include:

Using Cost-Based Optimization

This section discusses:

When to Use the Cost-Based Approach

Attention: In general, you should use the cost-based optimization approach. The rule-based approach is available for the benefit of existing applications, but all new optimizer functionality uses the cost-based approach.

The cost-based approach generally chooses an execution plan that is as good as or better than the plan chosen by the rule-based approach, especially for large queries with multiple joins or multiple indexes. The cost-based approach also improves productivity by eliminating the need for you to tune your SQL statements yourself. Finally, many Oracle performance features are available only through the cost-based approach.

Cost based optimization must be used to achieve efficient star query performance. Similarly, it must be used with hash joins and histograms. Cost-based optimization is always used with parallel query and with partition views. You must therefore perform ANALYZE at the partition level with partition views.

How to Use the Cost-Based Approach

To enable cost-based optimization for a statement, collect statistics for the tables accessed by the statement and be sure the OPTIMIZER_MODE initialization parameter is set to its default value of CHOOSE.

You can also enable cost-based optimization in these ways:

The plans generated by the cost-based optimizer depend on the sizes of the tables. When using the cost-based optimizer with a small amount of data to prototype an application, do not assume that the plan chosen for the full database will be the same as that chosen for the prototype.

Using Histograms for Non-uniformly Distributed Data

For non-uniformly distributed data, you should create histograms describing the data distribution of particular columns. For this type of data, histograms enable the cost based optimization approach to accurately guess the cost of executing a particular statement. For data that is uniformly distributed, the optimizer does not need histograms to accurately estimate the selectivity of a query.

How to Use Histograms

Create histograms on columns that are frequently used in WHERE clauses of queries and have a highly-skewed data distribution. You create a histogram by using the ANALYZE TABLE command. For example, if you want to create a 10-bucket histogram on the SAL column of the EMP table, issue the following statement:

ANALYZE TABLE emp COMPUTE STATISTICS FOR COLUMNS sal SIZE 10;

The SIZE keyword states the maximum number of buckets for the histogram. You would create a histogram on the SAL column if there were an unusual number of employees with the same salary and few employees with other salaries.

See Also: Oracle7 Server SQL Reference for more information about the ANALYZE command and its options.

Choosing the Number of Buckets for a Histogram

The default number of buckets is 75. This value provides an appropriate level of detail for most data distributions. However, since the number of buckets in the histogram, the sampling rate, and the data distribution all affect the usefulness of a histogram, you may need to experiment with different numbers of buckets to obtain the best results.

If the number of frequently occurring distinct values in a column is relatively small, then it is useful to set the number of buckets to be greater than the number of frequently occurring distinct values.

Viewing Histograms

You can find information about existing histograms in the database through the following data dictionary views:

USER_HISTOGRAMS
ALL_HISTOGRAMS
DBA_HISTOGRAMS

Find the number of buckets in each column's histogram in:

USER_TAB_COLUMNS
ALL_TAB_COLUMNS
DBA_TAB_COLUMNS

See Also: "Using Histograms" in Appendix A, "Optimizer Concepts"

Oracle7 Server Reference for more information and column descriptions of data dictionary views.

Oracle7 Concepts for restrictions on histograms.

Generating Statistics

Since the cost-based approach relies on statistics, you should generate statistics for all tables, clusters, and indexes accessed by your SQL statements before using the cost-based approach. If the size and data distribution of these tables changes frequently, you should generate these statistics regularly to ensure that they accurately represent the data in the tables.

Oracle can generate statistics using these techniques:

Use estimation, rather than computation, unless you think you need exact values:

To perform a computation, Oracle requires enough space to perform a scan and sort of the table. If there is not enough space in memory, temporary space may be required. For estimations, Oracle requires enough space to perform a scan and sort of all of the rows in the requested sample of the table.

Because of the time and space required for the computation of table statistics, it is usually best to perform an estimation with a 20% sample size for tables and clusters. For indexes, computation does not take up as much time or space, so it is best to perform a computation.

When you generate statistics for a table, column, or index, if the data dictionary already contains statistics for the analyzed object, Oracle updates the existing statistics with the new ones. Oracle invalidates any currently parsed SQL statements that access any of the analyzed objects. When such a statement is next executed, the optimizer automatically chooses a new execution plan based on the new statistics. Distributed statements issued on remote databases that access the analyzed objects use the new statistics when they are next parsed.

Some statistics are always computed, regardless of whether you specify computation or estimation. If you choose estimation and the time saved by estimating a statistic is negligible, Oracle computes the statistic.

You can generate statistics with the ANALYZE command.

Example: This example generates statistics for the EMP table and its indexes:

ANALYZE TABLE emp
ESTIMATE STATISTICS;

Choosing a Goal for the Cost-Based Approach

The execution plan produced by the optimizer can vary depending upon the optimizer's goal. Optimizing for best throughput is more likely to result in a full table scan rather than an indexed scan, or a sort-merge join rather than a nested loops join. Optimizing for best response time is more likely to result in an index scan or a nested loops join.

For example, consider a join statement that can be executed with either a nested loops operation or a sort-merge operation. The sort-merge operation may return the entire query result faster, while the nested loops operation may return the first row faster. If the goal is best throughput, the optimizer is more likely to choose a sort-merge join. If the goal is best response time, the optimizer is more likely to choose a nested loops join.

Choose a goal for the optimizer based on the needs of your application:

By default, the cost-based approach optimizes for best throughput. You can change the goal of the cost-based approach in these ways:

Example: This statement changes the goal of the cost-based approach for your session to best response time:

ALTER SESSION SET OPTIMIZER_GOAL = FIRST_ROWS;

Parameters Which Affect CBO Plans

The following initialization parameters affect cost-based optimization plans:

Table 7-1: Parameters Affecting Cost-Based Optimization Plans

OPTIMIZER_SEARCH_LIMIT

 

the maximum number of tables in the FROM clause for which all possible join permutations will be considered

 

OPTIMIZER_GOAL

 

dynamically changeable parameter you can use to modify the goal of the cost-based optimization approach for your session. Used only in the session; not used in initialization file.

 

OPTIMIZER_MODE

 

sets the mode of the optimizer at instance startup: rule-based, cost based optimized for throughput or response time, or a choice based on presence of statistics. Used in initialization file only; use OPTIMIZER_MODE to change the value during a session.

 

OPTIMIZER_PERCENT_PARALLEL

 

defines the amount of parallelism that the optimizer uses in its cost functions

 

HASH_JOIN_ENABLED

 

enables or disables the hash join feature

 

HASH_AREA_SIZE

 

larger value causes hash join costs to be cheaper, giving more hash joins

 

HASH_MULTIBLOCK_IO_COUNT

 

larger value causes hash join costs to be cheaper, giving more hash joins

 

SORT_AREA_SIZE

 

large value causes sort costs to be cheaper, giving more sort merge joins

 

SORT_DIRECT_WRITES

 

gives lower sort costs and more sort merge joins

 

SORT_WRITE_BUFFER_SIZE

 

large value causes sort costs to be cheaper, giving more sort merge joins

 

DB_FILE_MULTIBLOCK_READ_COUNT

 

large value gives cheaper table scan cost and favors table scans over indexes

 

ALWAYS_ANTI_JOIN

 

sets the type of antijoin that Oracle uses: NESTED_LOOPS/MERGE/HASH

 

PARTITION_VIEW_ENABLED

 

enables partition views

 

V733_PLANS_ENABLED

 

enables a set of special optimizations: GROUP BY No Sort, Index Fast Full Scans, and using B-tree indexes in bitmap access paths provided bitmap indexes exist on the table

 

BITMAP_MERGE_AREA_SIZE

 

is the size of the area used to merge the different bitmaps that match a range predicate. Larger size will favor use of bitmap indexes for range predicates.

 

Note that the following sort parameters can now be modified using ALTER SESSION SET ... or ALTER SYSTEM SET ... DEFERRED:

SORT_AREA_SIZE
SORT_AREA_RETAINED_SIZE
SORT_DIRECT_WRITES
SORT_WRITE_BUFFERS
SORT_WRITE_BUFFER_SIZE
SORT_READ_FAC

See Also: Oracle7 Server Reference for complete information about each parameter.

Tips for Using the Cost-Based Approach

The cost-based optimization approach assumes that a query will be executed on a multiuser system with a fairly low buffer cache hit rate. Thus a plan selected by cost-based optimization may not be the best plan for a single user system with a large buffer cache. Timing a query plan on a single user system with a large cache may not be a good predictor of performance for the same query on a busy multiuser system.

Analyzing a table uses more system resources than analyzing an index. It may be helpful to analyze the indexes for a table separately, with a higher sampling rate.

Use of access path and join method hints causes the cost-based optimization to be invoked. Since cost-based optimization is dependent on statistics, it is important to analyze all tables referenced in a query which has hints, even though rule-based optimization may have been selected as the system default.

Using Rule-Based Optimization

If you have developed applications using version 6 of Oracle and have carefully tuned your SQL statements based on the rules of the optimizer, you may want to continue using rule-based optimization when you upgrade these applications to Oracle7.

If you neither collect statistics nor add hints to your SQL statements, your statements will use rule-based optimization. However, you should eventually migrate your existing applications to use the cost-based approach, because the rule-based approach will not be available in future versions of Oracle.

You can enable cost-based optimization on a trial basis simply by collecting statistics. You can then return to rule-based optimization by deleting them or by setting either the value of the OPTIMIZER_MODE initialization parameter or the OPTIMIZER_GOAL parameter of the ALTER SESSION command to RULE. You can also use this value if you want to collect and examine statistics for your data without using the cost-based approach.

Introduction to Hints

As an application designer, you may know information about your data that the optimizer cannot. For example, you may know that a certain index is more selective for certain queries than the optimizer can determine. Based on this information, you may be able to choose a more efficient execution plan than the optimizer can. In such a case, you can use hints to force the optimizer to use your chosen execution plan.

Hints are suggestions that you give the optimizer for optimizing a SQL statement. Hints allow you to make decisions usually made by the optimizer. You can use hints to specify

How to Specify Hints

Hints apply only to the optimization of the statement block in which they appear. A statement block is any one of the following statements or parts of statements:

For example, a compound query consisting of two component queries combined by the UNION operator has two statement blocks, one for each component query. For this reason, hints in this first component query apply only to its optimization, not to the optimization of the second component query.

You can send hints for a SQL statement to the optimizer by enclosing them in a Comment within the statement.

See Also: For more information on Comments, see Chapter 2, "Elements of SQL", of the Oracle7 Server SQL Reference.

A statement block can have only one Comment containing hints. This Comment can only follow the SELECT, UPDATE, or DELETE keyword. The syntax diagrams show the syntax for hints contained in both styles of Comments that Oracle supports within a statement block.

where:

DELETE SELECT UPDATE

 

Is a DELETE, SELECT, or UPDATE keyword that begins a statement block. Comments containing hints can only appear after these keywords.

 

+

 

Is a plus sign that causes Oracle to interpret the Comment as a list of hints. The plus sign must follow immediately after the Comment delimiter (no space is permitted).

 

hint

 

Is one of the hints discussed in this section. If the Comment contains multiple hints, each pair of hints must be separated by at least one space.

 

text

 

Is other Commenting text that can be interspersed with the hints.

 

If you specify hints incorrectly, Oracle ignores them but does not return an error:

Oracle also ignores hints in all SQL statements in environments which use PL/SQL Version 1, such as SQL*Forms Version 3 triggers.

The optimizer only recognizes hints when using the cost-based approach. If you include any hint (except the RULE hint) in a statement block, the optimizer automatically uses the cost-based approach.

The following sections show the syntax of each hint.

Hints for Optimization Approaches and Goals

The hints described in this section allow you to choose between the cost-based and the rule-based optimization approaches and, with the cost-based approach, between the goals of best throughput and best response time.

If a SQL statement contains a hint that specifies an optimization approach and goal, the optimizer uses the specified approach regardless of the presence or absence of statistics, the value of the OPTIMIZER_MODE initialization parameter, and the OPTIMIZER_GOAL parameter of the ALTER SESSION command.

Note: The optimizer goal applies only to queries submitted directly. Use hints to determine the access path for any SQL statements submitted from within PL/SQL. The ALTER SESSION OPTIMIZER_GOAL statement does not affect SQL that is run from within PL/SQL.

ALL_ROWS

The ALL_ROWS hint explicitly chooses the cost-based approach to optimize a statement block with a goal of best throughput (that is, minimum total resource consumption). For example, the optimizer uses the cost-based approach to optimize this statement for best throughput:

SELECT /*+ ALL_ROWS */ empno, ename, sal, job
FROM emp
WHERE empno = 7566;

FIRST_ROWS

The FIRST_ROWS hint explicitly chooses the cost-based approach to optimize a statement block with a goal of best response time (minimum resource usage to return first row).

This hint causes the optimizer to make these choices:

For example, the optimizer uses the cost-based approach to optimize this statement for best response time:

SELECT /*+ FIRST_ROWS */ empno, ename, sal, job
FROM emp
WHERE empno = 7566;

The optimizer ignores this hint in DELETE and UPDATE statement blocks and in SELECT statement blocks that contain any of the following syntax:

These statements cannot be optimized for best response time because Oracle must retrieve all rows accessed by the statement before returning the first row. If you specify this hint in any of these statements, the optimizer uses the cost-based approach and optimizes for best throughput.

If you specify either the ALL_ROWS or FIRST_ROWS hint in a SQL statement and the data dictionary contains no statistics about any of the tables accessed by the statement, the optimizer uses default statistical values (such as allocated storage for such tables) to estimate the missing statistics and subsequently to choose an execution plan. Since these estimates may not be as accurate as those generated by the ANALYZE command, you should use the ANALYZE command to generate statistics for all tables accessed by statements that use cost-based optimization. If you specify hints for access paths or join operations along with either the ALL_ROWS or FIRST_ROWS hint, the optimizer gives precedence to the access paths and join operations specified by the hints.

CHOOSE

The CHOOSE hint causes the optimizer to choose between the rule-based approach and the cost-based approach for a SQL statement based on the presence of statistics for the tables accessed by the statement. If the data dictionary contains statistics for at least one of these tables, the optimizer uses the cost-based approach and optimizes with the goal of best throughput. If the data dictionary contains no statistics for any of these tables, the optimizer uses the rule-based approach.

SELECT /*+ CHOOSE */
empno, ename, sal, job
FROM emp
WHERE empno = 7566;

RULE

The RULE hint explicitly chooses rule-based optimization for a statement block. This hint also causes the optimizer to ignore any other hints specified for the statement block. For example, the optimizer uses the rule-based approach for this statement:

SELECT                     --+ RULE
empno, ename, sal, job
FROM emp
WHERE empno = 7566;

The RULE hint, along with the rule-based approach, will not be available in future versions of Oracle.

Hints for Access Methods

Each hint described in this section suggests an access method for a table.

Specifying one of these hints causes the optimizer to choose the specified access path only if the access path is available based on the existence of an index or cluster and the syntactic constructs of the SQL statement. If a hint specifies an unavailable access path, the optimizer ignores it.

You must specify the table to be accessed exactly as it appears in the statement. If the statement uses an alias for the table, you must use the alias, rather than the table name, in the hint. The table name within the hint should not include the schema name, if the schema name is present in the statement.

FULL

The FULL hint explicitly chooses a full table scan for the specified table. The syntax of the FULL hint is

FULL(table)

where table specifies the name or alias of the table on which the full table scan is to be performed.

For example, Oracle performs a full table scan on the ACCOUNTS table to execute this statement, even if there is an index on the ACCNO column that is made available by the condition in the WHERE clause:

SELECT /*+ FULL(a) Don't use the index on ACCNO */ accno, bal
FROM accounts a
WHERE accno = 7086854;

Note: Because the ACCOUNTS table has an alias, A, the hint must refer to the table by its alias, rather than by its name. Also, do not specify schema names in the hint, even if they are specified in the FROM clause.

ROWID

The ROWID hint explicitly chooses a table scan by ROWID for the specified table. The syntax of the ROWID hint is

ROWID(table)

where table specifies the name or alias of the table on which the table access by ROWID is to be performed.

CLUSTER

The CLUSTER hint explicitly chooses a cluster scan to access the specified table. The syntax of the CLUSTER hint is

CLUSTER(table)

where table specifies the name or alias of the table to be accessed by a cluster scan.

The following example illustrates the use of the CLUSTER hint.

SELECT --+ CLUSTER emp
ename, deptno
FROM emp, dept
WHERE deptno = 10 AND
emp.deptno = dept.deptno;

HASH

The HASH hint explicitly chooses a hash scan to access the specified table. The syntax of the HASH hint is

HASH(table)

where table specifies the name or alias of the table to be accessed by a hash scan.

HASH_AJ

The HASH_AJ hint transforms a NOT IN subquery into a hash anti-join to access the specified table. The syntax of the HASH_AJ hint is

HASH_AJ(table)

where table specifies the name or alias of the table to be accessed.

See Also: "How to Use an Anti-Join" on page 8-5

INDEX

The INDEX hint explicitly chooses an index scan for the specified table. The syntax of the INDEX hint is

where:

table

 

Specifies the name or alias of the table associated with the index to be scanned.

 

index

 

Specifies an index on which an index scan is to be performed.

 

This hint may optionally specify one or more indexes:

For example, consider this query, which selects the name, height, and weight of all male patients in a hospital:

SELECT name, height, weight
FROM patients
WHERE sex = 'M';

Assume that there is an index on the SEX column and that this column contains the values M and F. If there are equal numbers of male and female patients in the hospital, the query returns a relatively large percentage of the table's rows and a full table scan is likely to be faster than an index scan. However, if a very small percentage of the hospital's patients are male, the query returns a relatively small percentage of the table's rows and an index scan is likely to be faster than a full table scan.

The number of occurrences of each distinct column value is not available to the optimizer. The cost-based approach assumes that each value has an equal probability of appearing in each row. For a column having only two distinct values, the optimizer assumes each value appears in 50% of the rows, so the cost-based approach is likely to choose a full table scan rather than an index scan.

If you know that the value in the WHERE clause of your query appears in a very small percentage of the rows, you can use the INDEX hint to force the optimizer to choose an index scan. In this statement, the INDEX hint explicitly chooses an index scan on the SEX_INDEX, the index on the SEX column:

SELECT /*+ INDEX(patients sex_index) Use SEX_INDEX, since there
are few male patients */
name, height, weight
FROM patients
WHERE sex = 'M';

INDEX_ASC

The INDEX_ASC hint explicitly chooses an index scan for the specified table. If the statement uses an index range scan, Oracle scans the index entries in ascending order of their indexed values. The syntax of the INDEX_ASC hint is

Each parameter serves the same purpose as in the INDEX hint.

Because Oracle's default behavior for a range scan is to scan index entries in ascending order of their indexed values, this hint does not currently specify anything more than the INDEX hint. However, since Oracle Corporation does not guarantee that the default behavior for an index range scan will remain the same in future versions of Oracle, you may want to use the INDEX_ASC hint to specify ascending range scans explicitly, should the default behavior change.

INDEX_COMBINE

If no indexes are given as arguments for the INDEX_COMBINE hint, the optimizer will use on the table whatever boolean combination of bitmap indexes has the best cost estimate. If certain indexes are given as arguments, the optimizer will try to use some boolean combination of those particular bitmap indexes. The syntax of INDEX_COMBINE is

INDEX_DESC

The INDEX_DESC hint explicitly chooses an index scan for the specified table. If the statement uses an index range scan, Oracle scans the index entries in descending order of their indexed values. Syntax of the INDEX_DESC hint is

Each parameter serves the same purpose as in the INDEX hint. This hint has no effect on SQL statements that access more than one table. Such statements always perform range scans in ascending order of the indexed values. For example, consider this table, which contains the temperature readings of a tank of water holding marine life:

CREATE TABLE tank_readings
(time DATE CONSTRAINT un_time UNIQUE,
temperature NUMBER );

Each of the table's rows stores a time and the temperature measured at that time. A UNIQUE constraint on the TIME column ensures that the table does not contain more than one reading for the same time.

Oracle enforces this constraint with an index on the TIME column. Consider this complex query, which selects the most recent temperature reading taken as of a particular time T. The subquery returns either T or the latest time before T at which a temperature reading was taken. The parent query then finds the temperature taken at that time:

SELECT temperature
FROM tank_readings
WHERE time = (SELECT MAX(time)
FROM tank_readings
WHERE time <= TO_DATE(:t) );

The execution plan for this statement looks like the following figure:

Figure 7-1: Execution Plan without Hints

To execute this statement, Oracle performs these operations:

In Step 4, Oracle scans the TIME values in the index in ascending order beginning with the smallest. Oracle stops scanning at the first TIME value greater than T and then returns all the values less than or equal to T to Step 3. Note that Step 3 needs only the greatest of these values. Using the INDEX_DESC hint, you can write an equivalent query that reads only one TIME value from the index:

SELECT /*+ INDEX_DESC(tank_readings un_time) */ temperature
FROM tank_readings
WHERE time <= TO_DATE(:t)
AND ROWNUM = 1
ORDER BY time DESC;

The execution plan for this query looks like the following figure:

Figure 7-2: Execution Plan Using the INDEX_DESC Hint

To execute this statement, Oracle performs these operations:

Because of the INDEX_DESC hint, Step 3 scans the TIME values in the index in descending order beginning at T. The first TIME value scanned is either T (if the temperature was taken at T) or the greatest TIME value less than T. Since Step 1 requests only one row, Step 3 scans no more index entries after the first.Since the default behavior is an ascending index scan, issuing this query without the INDEX_DESC hint would cause Oracle to begin scanning at the earliest time in the table, rather than at the latest time less than or equal to T. Step 1 would then return the temperature at the earliest time. You must use this hint to make this query return the same temperature as the complex query described earlier in this section.

INDEX_FFS

This hint causes a fast full index scan to be performed rather than a full table scan. The syntax of INDEX_FFS is

See Also: "FAST FULL SCAN" on page 8-12

MERGE_AJ

The MERGE_AJ hint transforms a NOT IN subquery into a merge anti-join to access the specified table. The syntax of the MERGE_AJ hint is

MERGE_AJ(table)

where table specifies the name or alias of the table to be accessed.

See Also: "How to Use an Anti-Join" on page 8-5

AND_EQUAL

The AND_EQUAL hint explicitly chooses an execution plan that uses an access path that merges the scans on several single-column indexes. The syntax of the AND_EQUAL hint is:

where:

table

 

Specifies the name or alias of the table associated with the indexes to be merged.

 

index

 

Specifies an index on which an index scan is to be performed. You must specify at least two indexes. You cannot specify more than five.

 

USE_CONCAT

The USE_CONCAT hint forces combined OR conditions in the WHERE clause of a query to be transformed into a compound query using the UNION ALL set operator. Normally, this transformation occurs only if the cost of the query using the concatenations is cheaper than the cost without them.

Hints for Join Orders

The hints in this section suggest join orders:

ORDERED

The ORDERED hint causes Oracle to join tables in the order in which they appear in the FROM clause. For example, this statement joins table TAB1 to table TAB2 and then joins the result to table TAB3:

SELECT /*+ ORDERED */ tab1.col1, tab2.col2, tab3.col3
FROM tab1, tab2, tab3
WHERE tab1.col1 = tab2.col1
AND tab2.col1 = tab3.col1;

If you omit the ORDERED hint from a SQL statement performing a join, the optimizer chooses the order in which to join the tables.

You may want to use the ORDERED hint to specify a join order if you know something about the number of rows selected from each table that the optimizer does not. Such information would allow you to choose an inner and outer table better than the optimizer could.

STAR

The STAR hint forces the large table to be joined last using a nested loops join on the index. The optimizer will consider different permutations of the small tables.

Usually, if you analyze the tables the optimizer will choose an efficient star plan. You can also use hints to improve the plan. The most precise method is to order the tables in the FROM clause in the order of the keys in the index, with the large table last. Then use the following hints:

/*+ ORDERED USE_NL(facts) INDEX(facts fact_concat) */

A more general method is to use the STAR hint /*+ STAR */.

See Also: Appendix A, "Optimizer Concepts"

Hints for Join Operations

Each hint described in this section suggests a join operation for a table.

You must specify a table to be joined exactly as it appears in the statement. If the statement uses an alias for the table, you must use the alias rather than the table name in the hint. The table name within the hint should not include the schema name, if the schema name is present in the statement.

The USE_NL and USE_MERGE hints must be used with the ORDERED hint. Oracle uses these hints when the referenced table is forced to be the inner table of a join, and they are ignored if the referenced table is the outer table.

USE_NL

The USE_NL hint causes Oracle to join each specified table to another row source with a nested loops join using the specified table as the inner table. The syntax of the USE_NL hint is

where table is the name or alias of a table to be used as the inner table of a nested loops join.

For example, consider this statement, which joins the ACCOUNTS and CUSTOMERS tables. Assume that these tables are not stored together in a cluster:

SELECT accounts.balance, customers.last_name, customers.first_name
FROM accounts, customers
WHERE accounts.custno = customers.custno;

Since the default goal of the cost-based approach is best throughput, the optimizer will choose either a nested loops operation or a sort-merge operation to join these tables, depending on which is likely to return all the rows selected by the query more quickly.

However, you may want to optimize the statement for best response time, or the minimal elapsed time necessary to return the first row selected by the query, rather than best throughput. If so, you can force the optimizer to choose a nested loops join by using the USE_NL hint. In this statement, the USE_NL hint explicitly chooses a nested loops join with the CUSTOMERS table as the inner table:

SELECT /*+ ORDERED USE_NL(customers) Use N-L to get first row 
faster */
accounts.balance, customers.last_name, customers.first_name
FROM accounts, customers
WHERE accounts.custno = customers.custno;

In many cases, a nested loops join returns the first row faster than a sort-merge join. A nested loops join can return the first row after reading the first selected row from one table and the first matching row from the other and combining them, while a sort-merge join cannot return the first row until after reading and sorting all selected rows of both tables and then combining the first rows of each sorted row source.

USE_MERGE

The USE_MERGE hint causes Oracle to join each specified table with another row source with a sort-merge join. The syntax of the USE_MERGE hint is

where table is a table to be joined to the row source resulting from joining the previous tables in the join order using a sort-merge join.

NO_MERGE

The NO_MERGE hint causes Oracle not to merge mergeable views. The syntax of the NO_MERGE hint is:

This hint is most often used to reduce the number of possible permutations for a query and make optimization faster. This hint has no arguments. For example,

SELECT * FROM t1, (SELECT /*+ NO_MERGE */ * from t2) v ...

causes view v not to be merged.

USE_HASH

The USE_HASH hint causes Oracle to join each specified table with another row source with a hash join. The syntax of the USE_HASH hint is

where table is a table to be joined to the row source resulting from joining the previous tables in the join order using a hash join.

Hints for Parallel Query Execution

The hints described in this section determine how statements are parallelized or not parallelized when using the parallel query feature.

See Also: Chapter 18, "Parallel Query Tuning"

PARALLEL

The PARALLEL hint allows you to specify the desired number of concurrent query servers that can be used for the query. The syntax is0

The PARALLEL hint must use the table alias if an alias is specified in the query. The PARALLEL hint can then take two values separated by commas after the table name. The first value specifies the degree of parallelism for the given table, the second value specifies how the table is to be split among the instances of a parallel server. Specifying DEFAULT or no value signifies the query coordinator should examine the settings of the initialization parameters (described in a later section) to determine the default degree of parallelism.

In the following example, the PARALLEL hint overrides the degree of parallelism specified in the EMP table definition:

SELECT /*+ FULL(scott_emp) PARALLEL(scott_emp, 5) */ 
ename
FROM scott.emp scott_emp;

In the next example, the PARALLEL hint overrides the degree of parallelism specified in the EMP table definition and tells the optimizer to use the default degree of parallelism determined by the initialization parameters. This hint also specifies that the table should be split among all of the available instances, with the default degree of parallelism on each instance.

SELECT /*+ FULL(scott_emp) PARALLEL(scott_emp, DEFAULT,DEFAULT) */
ename
FROM scott.emp scott_emp;

NOPARALLEL

The NOPARALLEL hint allows you to disable parallel scanning of a table, even if the table was created with a PARALLEL clause. The following example illustrates the NOPARALLEL hint:

SELECT /*+ NOPARALLEL(scott_emp) */ 
ename
FROM scott.emp scott_emp;

The NOPARALLEL hint is equivalent to specifying the hint
/*+ PARALLEL(table,1,1) */

Additional Hints

Three additional hints are included in this section:

CACHE

The CACHE hint specifies that the blocks retrieved for the table in the hint are placed at the most recently used end of the LRU list in the buffer cache when a full table scan is performed. This option is useful for small lookup tables. In the following example, the CACHE hint overrides the table's default caching specification:

SELECT /*+ FULL (scott_emp) CACHE(scott_emp) */
ename
FROM scott.emp scott_emp;

NOCACHE

The NOCACHE hint specifies that the blocks retrieved for this table are placed at the least recently used end of the LRU list in the buffer cache when a full table scan is performed. This is the normal behavior of blocks in the buffer cache. The following example illustrates the NOCACHE hint:

SELECT /*+ FULL(scott_emp) NOCACHE(scott_emp) */
ename
FROM scott.emp scott_emp;

PUSH_SUBQ

The PUSH_SUBQ hint causes nonmerged subqueries to be evaluated at the earliest possible place in the execution plan. Normally, subqueries that are not merged are executed as the last step in the execution plan. If the subquery is relatively inexpensive and reduces the number of rows significantly, it will improve performance to evaluate the subquery earlier.

The hint will have no effect if the subquery is applied to a remote table or one that is joined using a merge join.

Considering Alternative SQL Syntax

Because SQL is a flexible language, more than one SQL statement may meet the needs of your application. Although two SQL statements may produce the same result, Oracle may process one faster than the other. You can use the results of the EXPLAIN PLAN statement to compare the execution plans and costs of the two statements and determine which is more efficient.

This example shows the execution plans for two SQL statements that perform the same function. Both statements return all the departments in the DEPT table that have no employees in the EMP table. Each statement searches the EMP table with a subquery. Assume there is an index, DEPTNO_INDEX, on the DEPTNO column of the EMP table.

This is the first statement and its execution plan:

SELECT dname, deptno
FROM dept
WHERE deptno NOT IN
(SELECT deptno FROM emp);

Figure 7-3: Execution Plan with Two Full Table Scans

Step 3 of the output indicates that Oracle executes this statement by performing a full table scan of the EMP table despite the index on the DEPTNO column. This full table scan can be a time-consuming operation. Oracle does not use the index because the subquery that searches the EMP table does not have a WHERE clause that makes the index available.

However, this SQL statement selects the same rows by accessing the index:

SELECT dname, deptno
FROM dept
WHERE NOT EXISTS
(SELECT deptno
FROM emp
WHERE dept.deptno = emp.deptno);

Figure 7-4: Execution Plan with a Full Table Scan and an Index Scan

The WHERE clause of the subquery refers to the DEPTNO column of the EMP table, so the index DEPTNO_INDEX is used. The use of the index is reflected in Step 3 of the execution plan. The index range scan of DEPTNO_INDEX takes less time than the full scan of the EMP table in the first statement. Furthermore, the first query performs one full scan of the EMP table for every DEPTNO in the DEPT table. For these reasons, the second SQL statement is faster than the first.

If you have statements in your applications that use the NOT IN operator, as the first query in this example does, you should consider rewriting them so that they use the NOT EXISTS operator. This would allow such statements to use an index, if one exists.




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