Hi, We have a Class db.t2.medium database on AWS. We use a procedure to transfer data records from the Source to the Target Schema. Transfers are identified by the log_id field in the target table. The procedure is: 1 all records are deleted from the Target table with the actual log_id value 2 a complicated SELECT (numerous tables are joined) is created on the Source system 3 a cursor is defined based on this SELECT 4 we go trough the CURSOR and insert new records into the Target table with this log_id (Actually we have about 100 tables in the Target schema and the size of the database backup file is about 1GByte. But we do the same for all the Target tables.) Our procedure is extremely slow for the first run: 3 days for the 100 tables. For the second and all subsequent run it is fast enough (15 minutes). The only difference between the first run and all the others is that in the first run there are no records in the Target schema with this log_id. It seems, that in the first step the DELETE operation makes free some “space”, and the INSET operation in the 4. step can reuse this space. But if no records are deleted in the first step, the procedure is extremely slow. To speed up the first run we found the following workaround: We inserted dummy records into the Target tables with the proper log_id, and really the first run became very fast again. Is there any “normal” way to speed up this procedure? In the production environment there will be only “first runs”, the same log_id will never be used again. thank Zoltán |
