Daniel, >>Somehow oracle seems to know that a right join is the better way to go. In fact, PostgreSQL is just doing the same thing: it hashes smaller table and scans the bigger one.
Could you please clarify how do you consume 25M rows? It could be the difference of response times comes not from the PostgreSQL itself, but from the client code. Could you please add the following information? 1) Execution time of simple query that selects MAX of all the required columns "select max(test1.slsales_batch) , max(test1.slsales_checksum), ...". I mean not explain (analyze, buffers), but simple execution. The purpose of MAX is to split overhead of consuming of the resultset from the overhead of producing it. 2) explain (analyze, buffers) for the same query with maxes. That should reveal the overhead of explain analyze itself. 3) The output of the following SQLPlus script (from Oracle): set linesize 1000 pagesize 10000 trimout on trimspool on time on timing on spool slow_query.lst select /*+ gather_plan_statistics */ max(test1.slsales_batch) , max(test1.slsales_checksum), ..; select * from table(dbms_xplan.display_cursor(null, null, 'ALLSTATS LAST')); spool off That would display detailed statistics on execution time similar to the explain (analyze, buffers). 4) Could you please clarify how did you migrate test1 table? I guess the order of rows in that table might affect overall execution time. Sorted table would be more CPU cache friendly, thus giving speedup. (see [1] for similar example). As far as I understand, simple create table as select * from test1 order by slsales_date_id, slsales_prod_id should improve cache locality. [1]: http://stackoverflow.com/questions/11227809/why-is-processing-a-sorted-array-faster-than-an-unsorted-array -- Regards, Vladimir Sitnikov
