Question about cardinality (lines) to explain the plan

I have two tables (names have been changed to protect the innocent):


TABLE 1:


The Null columns?    Type

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

Table1_Primary_Key NOT NULL NUMBER

more than 10 columns


TABLE2:


The Null columns?    Type

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

Table2_Primary_Key NOT NULL NUMBER

more than 8 columns


Lines of table1 has 1097172


Rows of table2 has 160960


I am analysis request and get explain below:


SELECT t1. Table1_Primary_Key

--

FROM TABLE1 t1,

From TABLE2 T2

--

WHERE t1. Table1_Primary_Key = t1. Table1_Primary_Key

AND t2. Table2_Primary_Key = 3432798

/


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

| ID | Operation | Name | Lines | Bytes | Cost (% CPU). Time |

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

|   0 | SELECT STATEMENT |                 |     1.    21.     5 (0) | 00:00:01 |

|   1.  NESTED LOOPS |                 |     1.    21.     5 (0) | 00:00:01 |

|   2.   TABLE ACCESS BY INDEX ROWID | TABLE2.     1.    12.     3 (0) | 00:00:01 |

|*  3 |    INDEX UNIQUE SCAN | TABLE2_PK |     1.       |     2 (0) | 00:00:01 |

|   4.   TABLE ACCESS BY INDEX ROWID | TABLE1.  1096K |  9634K |     2 (0) | 00:00:01 |

|*  5 |    INDEX UNIQUE SCAN | TABLE1_PK |     1.       |     1 (0) | 00:00:01 |

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


As you can see it table2 is exactly 1 row and join table1 on a correspondence of single line.


My question is this:


Why the plan of the explain command seems (at least for me) to indicate that it looked like all the rows in TABLE1?


Thank you


Thomas

the optimizer's decisions are based on the object (and maybe system) statistics: so it's a good idea to provide as much information as possible in these statistics. Basically, there is nothing wrong with statistics automatic collection job - so I would count on that if I don't have very good reason to use anything else. Of course, there are some situations in which it's a good idea to add a few adjustions for automatic collection: sometimes, there is too much created histograms, sometimes there is too little (basically you have histograms when the distribution of the data is not yet). And if there are columns with correlated values who serve together in boundary conditions then create extensive statistics may be a good idea. To make these adjustions, you can use the routines of pref dbms_stats. And sometimes, it may even be a good idea is not to collect statistics for an object and use the sample dynamic (dynamic statistics) for more detailed information on the cardinality of distribution and join.

In the book of my opinion Jonathan Lewis cost base Oracle Fundamentals still contains the best explanation of the use of optimizer statistics - and Christian Antognini Oracle performance troubleshooting also provides a lot of valuable information about statistics and their gathering. Of course the documentation also explains the basics in detail: Managing optimizer statistics - 11 g Release 2 (11.2). And if you want to get a shorter summary, then you can always take a look at the Web of Tim Hall site: https://oracle-base.com/articles/misc/cost-based-optimizer-and-database-statistics.

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