Real-Time Analytical Processing with InfoSphere Streams - Harness the Power of Big Data - page 150

• count

The number of tuples to include in the window

• delta Wait until a given attribute of an element in the stream has
changed by a specified delta amount

• time

The amount of time, in seconds, to allow the window to fill up

• punctuation The punctuation that is used to delimit the window,
as defined by the punctor operator
In addition to specifying the window, you must also specify an expression
that defines how you want the data to be sorted (for example, sort by a given
attribute in the stream). After the window fills up, the sort operator will sort
the tuples based on the element that you specified, and then send those tuples
to the output port in sorted order. Then the window fills up again. By default,
Streams sorts in ascending order, but you can specify a sort in descending
order.

Join
As you've likely guessed, the join operator takes two streams, matches the
tuples on a specified condition, and then sends the matches to an output
stream. When a row arrives on one input stream, the matching attribute is
compared to the tuples that already exist in the operating window of the
second input stream to try to find a match. Just as in a relational database,
several types of joins can be used, including inner joins (in which only
matches are passed on) and outer joins (which can pass on one of the
stream tuples even without a match, in addition to matching tuples from
both streams). As with the sort operator, you must specify a window of
tuples to store in each stream.

Aggregate
The aggregate operator can be used to sum up the values of a given attri-
bute or set of attributes for the tuples in the window; this operator also relies
on a windowing option to group together a set of tuples. An aggregate
operator enables groupBy and partitionBy parameters to divide up the
tuples in a window and perform aggregation on those subsets of tuples. You
can use the aggregate operator to perform count , sum , average , max ,
min , first , last , count distinct , and other forms of aggregation.