The predicate window opens and closes the window regarding a start and optional an end condition.

Parameter

Remark: This is a blocking operator. The operator does not write elements before it sees new elements not belonging to the window anymore (similiar to ElementWindow)

Example


In the following we provide some examples and the corresponding output.

As input, we assume the following simple input:

ID	Time	isLast
A    1    false
A    2    false
A    3    false
A    4    true
B    5    false
B    6    false
B    7    false
B    8    false
B    9    false
B    10    true
C    11    false
C    12    false
C    13    false
C    14    false
C    15    false
C    16    false

Preprocessing

With some preprocessing we will get:


Using only a start predicate


#PARSER PQL
#ADDQUERY
in = CSVFILESOURCE({SCHEMA = [['ID', 'String'],['pos','STARTTIMESTAMP'],['isLast','Boolean']], DELIMITER = '\t', SOURCE = 'source', FILENAME = '${PROJECTPATH}/input.csv'})

map = STATEMAP({EXPRESSIONS = [['isNull(__last_1.ID) OR (__last_1.ID != ID)','newElem']], KEEPINPUT = true}, in)

win = PREDICATEWINDOW({start = 'newElem', SAMESTARTTIME = true}, map)

will result in:

A|1|false|true | META | 1|2
B|5|false|true | META | 5|6
C|11|false|true | META | 11|12

Here the window is opened for every true evaluation of the start condition and is closed for every evaluation of !start. All elements between these elements are discarded. They do not open a new window.

Using a start and an end predicate

#PARSER PQL
#ADDQUERY
in = CSVFILESOURCE({SCHEMA = [['ID', 'String'],['pos','STARTTIMESTAMP'],['isLast','Boolean']], DELIMITER = '\t', SOURCE = 'source', FILENAME = '${PROJECTPATH}/input.csv'})

map = STATEMAP({EXPRESSIONS = [['isNull(__last_1.ID) OR (__last_1.ID != ID)','newElem']], KEEPINPUT = true}, in)

win = PREDICATEWINDOW({start = 'newElem', end = 'newElem', SAMESTARTTIME = true}, map)
A|1|false|true | META | 1|5
A|2|false|false | META | 1|5
A|3|false|false | META | 1|5
A|4|true|false | META | 1|5
B|5|false|true | META | 5|11
B|6|false|false | META | 5|11
B|7|false|false | META | 5|11
B|8|false|false | META | 5|11
B|9|false|false | META | 5|11
B|10|true|false | META | 5|11
C|11|false|true | META | 11|17
C|12|false|false | META | 11|17
C|13|false|false | META | 11|17
C|14|false|false | META | 11|17
C|15|false|false | META | 11|17
C|16|false|false | META | 11|17

Here each time a new window opens, the old window is closed, i.e. the same input element is responsible for starting and closing a window.


Using a start and an end predicate and keeping the ending element:

#PARSER PQL
#ADDQUERY
in = CSVFILESOURCE({SCHEMA = [['ID', 'String'],['pos','STARTTIMESTAMP'],['isLast','Boolean']], DELIMITER = '\t', SOURCE = 'source', FILENAME = '${PROJECTPATH}/input.csv'})

map = STATEMAP({EXPRESSIONS = [['isNull(__last_1.ID) OR (__last_1.ID != ID)','newElem']], KEEPINPUT = true}, in)

win = PREDICATEWINDOW({start = 'newElem', end = 'isLast', KEEPENDINGELEMENT = true, SAMESTARTTIME = true}, map)

will result in:

A|1|false|true | META | 1|4
A|2|false|false | META | 1|4
A|3|false|false | META | 1|4
A|4|true|false | META | 1|4
B|5|false|true | META | 5|10
B|6|false|false | META | 5|10
B|7|false|false | META | 5|10
B|8|false|false | META | 5|10
B|9|false|false | META | 5|10
B|10|true|false | META | 5|10
C|11|false|true | META | 11|17
C|12|false|false | META | 11|17
C|13|false|false | META | 11|17
C|14|false|false | META | 11|17
C|15|false|false | META | 11|17
C|16|false|false | META | 11|17

Remark the difference: This operator blocks only until the end predicate is reached. This works only, if samestarttime is set to true, else e.g. A|4|true|false | META | 1|4 would be A|4|true|false | META | 4|4, this has no validitiy and will not be produced.