Re: How does PostgerSQL planner decide driving table - Mailing list pgsql-general

Dear All,

 

I have read about query tuning and attempt to check the impact of

exchanging the driving table in Join condition.

 

To test Simple Join condition, I prepared Two tables.

One is the table for employees and another is the table for departments.

Employees table has the foreign key which referencing departments table.

 

The proportion of each table, filtered table and joined table is below:

(E means employees table and D means departments table.)

#rows in E                 #rows in D                #filtered rows in E                    #filtered rows in D                   #rows in E and D

10000                          490                              1000                                               245                                                 9800

 

After make the index on the filtered column, I tried the query:

EXPLAIN ANALYZE

SELECT   D.Department_Name, E.Last_Name, E.First_Name

FROM Employees E, Departments D

WHERE E.Department_Id=D.Department_Id

  AND E.Exempt_Flag='Y'

  AND D.US_Based_Flag='Y'

;

 

Result was:

Hash Join  (cost=8.85..241.59 rows=499 width=15) (actual time=0.105..2.052 rows=518 loops=1)

   Hash Cond: (e.department_id = d.department_id)

   ->  Seq Scan on employees e  (cost=0.00..209.00 rows=5000 width=17) (actual time=0.007..1.541 rows=5000 loops=1)

         Filter: (exempt_flag = 'Y'::bpchar)

         Rows Removed by Filter: 5000

   ->  Hash  (cost=8.24..8.24 rows=49 width=14) (actual time=0.087..0.087 rows=49 loops=1)

         Buckets: 1024  Batches: 1  Memory Usage: 3kB

         ->  Bitmap Heap Scan on departments d  (cost=4.63..8.24 rows=49 width=14) (actual time=0.069..0.078 rows=49 loops=1)

               Recheck Cond: (us_based_flag = 'Y'::bpchar)

               ->  Bitmap Index Scan on dept2_flg_idx  (cost=0.00..4.62 rows=49 width=0) (actual time=0.063..0.063 rows=49 loops=1)

                     Index Cond: (us_based_flag = 'Y'::bpchar)

Total runtime: 2.095 ms

 

In order to exchange the driving table, I tried the query:

EXPLAIN ANALYZE

SELECT   D.Department_Name, E.Last_Name, E.First_Name

FROM Departments D, Employees E

WHERE D.Department_Id=E.Department_Id

  AND E.Exempt_Flag='Y'

  AND D.US_Based_Flag='Y'

;

 

However, the result was same.

I think this is because the query planner can optimizer the 2^nd query based on table statistics of E and D.

E being the larger number of records and has higher filtering rate so it continues to be driving table.

 

Now, I tried another test case to confirm my assumption.

The proportion of another test case is different from above one.

The proportion of each table, filtered table and joined table is below:

(E means employees table and D means departments table.)

#rows in E                 #rows in D                #filtered rows in E                    #filtered rows in D                   #rows in E and D

10000                          490                              5000                                               49                                                  9800

The important point is the difference in the filtering rate.

In this case, departments table is higher filtering rate,

so taking departments table as driving table will be able to cut the computational cost, I think.

 

I tried same query:

EXPLAIN ANALYZE

SELECT   D.Department_Name, E.Last_Name, E.First_Name

FROM Employees E, Departments D

WHERE E.Department_Id=D.Department_Id

  AND E.Exempt_Flag='Y'

  AND D.US_Based_Flag='Y'

And

EXPLAIN ANALYZE

SELECT   D.Department_Name, E.Last_Name, E.First_Name

FROM Employees E, Departments D

WHERE E.Department_Id=D.Department_Id

  AND E.Exempt_Flag='Y'

  AND D.US_Based_Flag='Y'

 

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Emanuel Calvo                 http://www.2ndQuadrant.com/
PostgreSQL Development, 24x7 Support, Training & Services