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SQL Optimizer for Oracle 9.3.3 - 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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HASH GROUP BY

 

The HASH GROUP BY operation indexes and retrieves rows using hashing, and then organizes rows into groups.

 

  

 

 

HASH GROUP BY PIVOT

 

The HASH GROUP BY PIVOT operation indexes and retrieves rows using hashing, and then organizes rows into groups in a pivot table.

 

  

 

 

HASH JOIN

Execution Plan image: image\Plan_Hash_Join.gif or image\Plan_Hash_Join_Cartesian.gif   

Join operation.

HASH JOINis one of the algorithms that Oracle can use to join two tables.

In a HASH JOIN a hash table, an on-the-fly index, is constructed for the larger of the two tables. The smaller table is then scanned, and the hash table used to find matching rows in the larger table.

HASH JOIN joins tables by creating an in-memory bitmap of one of the tables and then using a hashing function to locate the join rows in the second table.

In the following query, the COMPANY and SALES are joined based on their common COMPANY_ID column.

Example

select COMPANY.Name
from COMPANY, SALES
where COMPANY.Company_ID = SALES.Company_ID
and SALES.Period_ID =3
and SALES.Sales_Total>1000;

Execution Plan

HASH JOIN
TABLE ACCESS FULL SALES
TABLE ACCESS FULL COMPANY

Interpreting the Execution Plan

The Execution Plan shows that the SALES table is used as the first table in the hash join. SALES table will be read into memory. Oracle uses a hashing function to compare the values in COMPANY table to the records that have been read into memory.

When one of the tables is significantly smaller than the other in the join, and the smaller table fits into the available memory area, the optimizer will generally use a hash join instead of a traditional NESTED LOOPS join. Even if an index is available for the join, a hash join may be preferable to a NESTED LOOPS join.

 

Related Topics

 

HASH JOIN BUFFERED

 

The HASH JOIN BUFFERED operation joins buffered rows.

 

  

 

 

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