Optimizing SQL Processing Performance


Joins are a common and resource-intensive part of SAS Data Integration Studio. SAS SQL implements several well-known join algorithms: sort-merge, index, and hash. You can use common techniques to aid join performance, irrespective of the algorithm that you choose. Conditions often cause the SAS SQL optimizer to choose the sort-merge algorithm; techniques that improve sort performance also improve sort-merge join performance. However, understanding and leveraging index and hash joins enhance performance.
You might often perform lookups between tables in SAS Data Integration Studio. Based on key values in one table, you look up matching keys in a second table and retrieve associated data in the second table. SQL joins can perform lookups. However, SAS and SAS Data Integration Studio provide special lookup mechanisms that typically outperform a join. The problems associated with joins are similar to the problems with sorting:
  • Join performance seems slow.
  • You have trouble influencing the join algorithm that SAS SQL chooses.
  • You experience higher than expected disk space consumption.
  • You have trouble operating SAS SQL joins with RDBMS data.