Queries with outer join would be executed by scanning the driving table first, which is ought to be the bigger table which is outer joined with the other table. This approach compromises with the performance as Larger table has to scanned and hashed first and then joined to the other tables, contrary to the very nature of Hash joins where smaller tables are hashed and stored in memory and then joined over to the bigger table.
In 10G, there is a new concept HASH JOIN (RIGHT OUTER) --could be seen in execution plan also--which scans the smaller tables first and then join them over to the bigger table. This surely is a welcome change as this plan is quite superior to the earlier execution plans in terms of performance.
But, beware, all your tables involved in joins should have statistics computed for 10g to pick up the new execution plan.
Wednesday, January 23, 2008
Monday, January 21, 2008
Informatica : Lookups Versus Outer Joins
A plain lookup over a dimension (fetching ROW_WID) can be replaced by an outer join over the dimension in the parent sql itself.
I have created a prototype to demonstrate this.
SILOS.TEST_BULK_SIL mapping is created as a copy of SILOS.SIL_PayrollFact (loads W_PAYROLL_F from W_PAYROLL_FS).
Original mapping had a mapplet mplt_SIL_PayrollFact. This mapplet has 12 lookups over various dimensions. It takes input (datasource_num_id, integration_id etc) from the parent sql, looks up the ROW_WID and loads into the fact table.
I removed this mapplet completely and incorporated all the 12 dimensions in the parent sql itself, Outer Joining them to W_PAYROLL_FS. All the expressions which were built in the mapplet were taken care in the main mapping itself (some of them may require more finishing).
Following are the results:
Results show that Outer join based mapping ran approx 2.7 times faster than the one based on lookups.
Again, lookups which involve some complex calculations may not be replaced by outer join.
I have created a prototype to demonstrate this.
SILOS.TEST_BULK_SIL mapping is created as a copy of SILOS.SIL_PayrollFact (loads W_PAYROLL_F from W_PAYROLL_FS).
Original mapping had a mapplet mplt_SIL_PayrollFact. This mapplet has 12 lookups over various dimensions. It takes input (datasource_num_id, integration_id etc) from the parent sql, looks up the ROW_WID and loads into the fact table.
I removed this mapplet completely and incorporated all the 12 dimensions in the parent sql itself, Outer Joining them to W_PAYROLL_FS. All the expressions which were built in the mapplet were taken care in the main mapping itself (some of them may require more finishing).
Following are the results:
| Mapping | Records Loaded (million) | Time Taken (hr.) | RPS (Reader) |
| SIL_PayrollFact (uses lookup) | 183.3 | 16.3 | 3132 |
| TEST_BULK_SIL (uses Outer Join) | 183.3 | 6.02 | 8429 |
Results show that Outer join based mapping ran approx 2.7 times faster than the one based on lookups.
Again, lookups which involve some complex calculations may not be replaced by outer join.
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