Answer Posted / subhash

DataSet:
1. The fundamental concept of the Orchestrate
framework is the Data Set. Data Sets are the inputs and
outputs of Orchestrate operators.
2. As a concept a Data Set is like a database table,
in so far as it is a collection of identically-defined
rows. It is the only structure on which Orchestrate
operators operate. Each operator( i.e., stage) accepts
input from one Data Set and sends its output to another
Data Set.
3. A Data Set exists on all the processing nodes
defined for the job that is currently processing it. That
subset of rows in a Data Set that are located on a single
processing node is referred to as a "partition" of the Data
Set. Technically, a partition is a subset of the rows in a
Data Set (or File Set) earmarked for processing on the same
processing node.
4. A control file is associated with each data set.
The control file contains the record schema that defines
the row structure (effectively its column definitions).
5. Within a Data Set data are stored in internal, or
machine-compatible format.

FileSet:
1. It allows you to read data from or write data to a
file set.
2. The stage can have a single input link, a single
output link and a single reject link.
3. It only executes in parallel mode.
4. The data files and the file that lists them are
called a file set. This capability is useful because some
operating systems impose a 2 GB limit on the size of a file
and you need to distribute files among nodes to prevent
overruns.
5. Only advantage of using fileset over a sequential
file is "it preserves partitioning scheme"

A dataset is a file/stage where the data can be read
directly by the DataStage, whereas a file set needs to be
converted into DataStage readable format (which happens
internally).

In simple words the data from the DataSet can be read
faster than from FileSet.

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