Exadata offloading is to offload processing to
the storage tier. Offloading and Smart Scan are two terms that are used
somewhat interchangeably. Offloading is a more generic term that means
doing work at the storage tier that would otherwise have to be done on
the database tier (this can include work that is not related to
executing queries such as optimization of incremental backups). Smart
Scans on the other hand are the access mechanism used to offload query
processing tasks. For example, storage servers can apply predicate
filters at the storage layer, instead of shipping every possible block
back to the database server(s). Another thing that happens with Smart
Scans is that the volume of data returned can be further reduced by
column projection (i.e. if you only select 1 column from a 100 column
table, there is no need to return the other 99 columns). Offloading is
geared to long running queries that access a large amount of data.
Offloading only works if Oracle decides to use its direct path read
mechanism.
There three primary goals to use the smart scan/Offloading.
• Reduce the volume of data transferred from disk systems to the database servers.
• Reduce CPU usage on database servers.
• Reduce disk access times at the storage layer.
There three primary goals to use the smart scan/Offloading.
• Reduce the volume of data transferred from disk systems to the database servers.
• Reduce CPU usage on database servers.
• Reduce disk access times at the storage layer.
Reducing the volume was the main focus and primary goal. The majority of the optimizations introduced by Offloading contribute to this goal. Reducing CPU load is important as well, but is not the primary benefit provided by Exadata and therefore takes a back seat to reducing the volume of data transferred. (As you’ll see, however, decompression is a notable exception to that generalization, as it is performed on the storage servers.) Several optimizations to reduce disk access time were also introduced, and while some of the results can be quite stunning, we don’t consider them to be the bread-and-butter optimizations of Exadata.
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