25-05-2012, 11:17 AM
Embracing the BI Appliance wave
Embracing the BI Appliance wave.pdf (Size: 4.45 MB / Downloads: 47)
What is an Appliance?
Out of the Box
Low maintenance
Performs a very
specific function
Why BI Appliance?
• Large volume data processing requirements
• Need for greater speed and throughput
• Lower development and maintenance costs
• Lower dependency on multiple H/W and S/W
vendors
Hybrid Columnar Compression
• Tables are organized into sets of a few thousand rows called
Compression Units (CUs)
• Within Compression Unit, data is Organized by Column and
then compressed
• Column organization brings similar values close
together, enhancing compression
• Useful for data that is bulk loaded and queried
• Update activity is light
Map Reduce
MapReduce is a framework for processing huge datasets on certain kinds of
distributable problems using a large number of computers (nodes), collectively referred
to as a cluster. Computational processing can occur on data stored either in a filesystem
(unstructured) or within a database (structured).
"Map" step: The master node takes the input, chops it up into smaller sub-problems,
and distributes those to worker nodes. A worker node may do this again in turn, leading
to a multi-level tree structure. The worker node processes that smaller problem, and
passes the answer back to its master node.
"Reduce" step: The master node then takes the answers to all the sub-problems and
combines them in a way to get the output - the answer to the problem it was originally
trying to solve.