Improving performance with Data Pump
There are some considerations the user should pay attention, in order to take full
advantage of this tool. When performing a data pump export operation it can
perform. faster if using parallelism, but if this is not used properly, the process may
end up serializing, which is very likely to happen if the dump fles are written to the
same disk location.
When performing a data pump import operation, we should consider the same
parallelism issue. If using an enterprise edition, the degree of parallelism can be set
and can be tuned so that there will be several parallel processes carrying out the
import process. It is advisable to ensure the number of processes does not exceed
twice the number of available CPU's.
Also, the tablespace features are important. The tablespace should be locally managed
with Automatic Segment Space Management (ASSM); this will allow the insert
process to perform. faster.
Other features that should be considered are related to database block checking. Both
db_block_ckecking and db_block_checksum impose a performance penalty. It has
been reported by some users that this penalty is meaningful when batch loading takes
place. It is advisable to either disable these parameters or reduce the emphasis. Those
instance parameters are dynamic, so they can be modifed during the operation.
Other instance parameters to consider are those related to parallelism, the
parallel_max_servers, and parallel_execution_message_size. When using
parallelism, the large_pool_size region should be properly confgured.
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