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SQL Optimizer for Oracle 10.0 - User Guide

Welcome to SQL Optimizer
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ALL PARTITION ALTER INDEX AND EQUAL ANTI JOIN BITMAP AND BITMAP COMPACTION BITMAP CONSTRUCTION BITMAP CONVERSION BITMAP INDEX BITMAP JOIN INDEX UPDATE BITMAP JOIN INDEX UPDATE STATEMENT BITMAP KEY ITERATION BITMAP MERGE BITMAP MINUS BITMAP OR BUFFER SORT CARTESIAN JOIN COLLECTION ITERATOR CONCATENATION CONNECT BY CONNECT BY PUMP COUNT COUNT STOPKEY CREATE AS SELECT CUBE SCAN DDL STATEMENT DELETE DOMAIN INDEX FAST FULL INDEX SCAN FILTER FIRST ROWS FIXED INDEX FIXED TABLE FOR UPDATE FULL INDEX SCAN FULL INDEX SCAN DESCENDING FULL INDEX SCAN (MIN/MAX) HASH GROUP BY HASH GROUP BY PIVOT HASH JOIN HASH JOIN BUFFERED HASH PARTITION HASH UNIQUE INDEX INDEX BUILD NON UNIQUE INDEX RANGE SCAN INDEX RANGE SCAN DESCENDING INDEX RANGE SCAN (MIN/MAX) INDEX SAMPLE FAST FULL SCAN INDEX SKIP SCAN INDEX SKIP SCAN DESCENDING INDEX UNIQUE SCAN INLIST ITERATOR INLIST PARTITION INSERT INTERSECTION INTO INVALID PARTITION ITERATOR PARTITION LOAD AS SELECT MAT_VIEW ACCESS MAT_VIEW REWRITE ACCESS MERGE JOIN MINUS MULTI-TABLE INSERT NESTED LOOPS OUTER JOIN PARTITION PARTITION HASH EMPTY PARTITION LIST PARTITION RANGE PROJECTION PX BLOCK ITERATOR PX COORDINATOR PX ITERATOR PX PARTITION PX PARTITION HASH ALL PX PARTITION LIST ALL PX PARTITION RANGE ALL PX RECEIVE PX SEND RANGE PARTITION RECURSIVE EXECUTION RECURSIVE WITH PUMP REFERENCE MODEL REMOTE SELECT SEMI JOIN SEQUENCE SINGLE PARTITION SINGLE RANGE PARTITION SORT SORT AGGREGATE SORT GROUP BY SORT GROUP BY CUBE SORT GROUP BY NOSORT SORT GROUP BY ROLLUP SORT JOIN SORT ORDER BY SORT UNIQUE SQL MODEL TABLE ACCESS TABLE ACCESS BY GLOBAL INDEX ROWID TABLE ACCESS BY INDEX ROWID TABLE ACCESS BY LOCAL INDEX ROWID TABLE ACCESS BY ROWID TABLE ACCESS BY USER ROWID TABLE ACCESS CLUSTER TABLE ACCESS FULL TABLE ACCESS HASH TABLE ACCESS SAMPLE TABLE QUEUE TEMP TABLE GENERATION TEMP TABLE TRANSFORMATION UNION UNION ALL UNION ALL (RECURSIVE WITH) UNPIVOT UPDATE VIEW VIEW PUSHED PREDICATE WINDOW
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COLLECTION ITERATOR

Execution Plan image: image\CollectionIterator.gif

Row operation.

The Collection Iterator operation returns certain values from a collection such as VARRAY and nested table.

 

Related Topics

 

CONCATENATION

Execution plan image: image\Plan_Concatenation.gif   

Row operation.

CONCATENATION performs a UNION ALL (a UNION without elimination of duplicate values) of result sets.

Example

select Name, City, State
from COMPANY
where State = 'TX'
and City in ('Houston', 'Austin', 'Dallas');

This query selects from the COMPANY Table based on two criteria in the WHERE clause. The criteria can use the COMPANY$CITY index and the COMPANY$STATE index to obtain ROWIDs for the rows to be returned. Since the NAME column is required by the query, the COMPANY table will have to be accessed; the other column values are already available via the index searches.

The query of the CITY column uses an IN clause, which is functionally equivalent to an OR clause. The query could be rewritten as:

select Name, City, State
from COMPANY
where State = 'TX'
and (City = 'Houston'
or City = 'Austin
or City = 'Dallas);

Taking this expansion one step further, the STATE portion of the query can be placed into each section of the OR clause. The revised query would now read:

select Name, City, State
from COMPANY
where (State = 'TX' and City = 'Houston')
or (State = 'TX' and City = 'Austin')
or (State = 'TX' and City = 'Dallas');

This query helps with understanding the plan that is generated.

Execution Plan

CONCATENATION
TABLE ACCESS BY ROWID COMPANY
AND-EQUAL
INDEX RANGE SCAN COMPANY$CITY
INDEX RANGE SCAN COMPANY$STATE
TABLE ACCESS BY ROWID COMPANY
AND-EQUAL
INDEX RANGE SCAN COMPANY$CITY
INDEX RANGE SCAN COMPANY$STATE
TABLE ACCESS BY ROWID COMPANY
AND-EQUAL
INDEX RANGE SCAN COMPANY$CITY
INDEX RANGE SCAN COMPANY$STATE

Interpreting the Execution Plan

The Execution Plan shows that the query is executed as if the IN clause is rewritten as an OR clause, and the other criteria are placed within the OR clauses. Within each OR clause, an AND-EQUAL operation is performed to merge the lists of ROWIDs returned from the index scans. The ROWIDs returned by the AND-EQUAL operations are then used to select the requested columns from the COMPANY table via a TABLE ACCESS BY ROWID operation. The resulting records from each part of the query are then concatenated to carry out the OR clause.

Note: When the query is very complex, the Optimizer may decide not to use the CONCATENATION operation. Instead, it will use partial index range scans. If you want to force the use of the CONCATENATION operation, you may need to use the format shown in the last example query.

 

 

CONNECT BY

Execution Plan image: image\Plan_Connect_By.gif   

Join operation.

CONNECT BY does a recursive join of a table to itself, in a hierarchical fashion.

Example

select Company_ID, Name
from COMPANY
where State = 'VA'
connect by Parent_Company_ID = prior Company_ID
start with Company_ID = 1;

The query shown in the preceding statement selects companies from the COMPANY in a hierarchical fashion; that is, it returns the rows based on each Company’s parent company. If there are multiple levels of company parentage, those levels display in the report.

Execution Plan

FILTER
CONNECT BY
INDEX UNIQUE SCAN COMPANY_PK
TABLE ACCESS BY ROWID COMPANY
TABLE ACCESS BY ROWID COMPANY
INDEX RANGE SCAN COMPANY$PARENT

Interpreting the Execution Plan

The plan shows that first the COMPANY_PK index is used to find the root node (Company_ID = 1), index on the Parent_Company_ID column is used to provide values for queries against the Company_ID column in an iterative fashion. After the hierarchy of Company_IDs is complete, the FILTER operation&emdash;the WHERE clause related to the STATE value&emdash;is applied. Notice that the query does not use the index on the STATE column, although it is available and the column is used in the WHERE clause.

 

Related Topics

 

CONNECT BY PUMP

Execution plan image:

Join operation.

PUMP is an operator which is used with "Connect by" in hierarchical self-join.

 

 

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