SPD Server is designed
to meet the storage and performance demands that are associated with
processing large amounts of data using SAS. As the size of the data
grows, the demand to process that data increases, and storage architecture
must change to keep up with business needs.
SPD Server offers dynamic
cluster tables. Earlier releases of SPD Server provided a cluster
table called the time-based partitioning table. To optimize the benefits
of clustering, the SPD Server administrator can use dynamic clusters
to partition SPD Server data tables for speed and enhanced
I/O processing.
Clustering is performed using metadata. When that metadata is combined
with SPD Server functionality, the result is parallel processing capabilities
for loading and querying data tables. Parallel processing can accelerate
performance and increase the manageability, flexibility, and scalability
of very large data stores.
When you use dynamic
cluster tables, you can add new data or remove historical data from
very large tables by accessing only the member tables that are affected
by the change. You can access the individual member tables in parallel.
This strategy reduces the time that you need to complete the job,
and it uses simple commands. Furthermore, a complete refresh of a
dynamic cluster table uses a fraction of the disk space that is needed
to refresh a large traditional SAS or SPD Server table with the same
amount of data.