Funnel Stage:
Funnel stage is processing stage is
Datastage, which is used to combine more than one file into single file. It can
support n #.of Input links and one output link.But prerequisite for it is that
each and every file in source should have same Metadata. Here metadata means
Data types and Column names too.
Funnel Stage provides 3 funnel types in
combining the files.Below same has been described.
v
Sequence Funnel.
v
Continuous Funnel.
v
Sort Funnel.
Continuous Funnel:
In
this type of funneling, all the input rows sent to output as they arrived for
processing.
Below example explains in detail.
Below are 3 input files data.
File 1:
EID
|
ENAME
|
DEPT NO
|
MGR_ID
|
102
|
Joe
|
10
|
105
|
103
|
Latha
|
10
|
102
|
101
|
Leela
|
20
|
101
|
File 2:
EID
|
ENAME
|
DEPT NO
|
MGR_ID
|
110
|
Vidhya
|
30
|
109
|
134
|
Rama
|
20
|
101
|
112
|
Neethu
|
10
|
111
|
File 3:
EID
|
ENAME
|
DEPT NO
|
MGR_ID
|
456
|
Yogesh
|
10
|
324
|
345
|
Jeevan
|
20
|
101
|
909
|
Varu
|
10
|
101
|
Output:
EID
|
ENAME
|
DEPT NO
|
MGR_ID
|
102
|
Joe
|
10
|
105
|
103
|
Latha
|
10
|
102
|
101
|
Leela
|
20
|
101
|
456
|
Yogesh
|
10
|
324
|
134
|
Rama
|
20
|
101
|
112
|
Neethu
|
10
|
111
|
110
|
Vidhya
|
30
|
109
|
345
|
Jeevan
|
20
|
101
|
909
|
Varu
|
10
|
101
|
Sequence Funnel:
Sequence Funnel copies all records from the
first input data set to the output data set,
then all the records from the second input data set, and so on.
Output
would be below for above input.
EID
|
ENAME
|
DEPT NO
|
MGR_ID
|
102
|
Joe
|
10
|
105
|
103
|
Latha
|
10
|
102
|
101
|
Leela
|
20
|
101
|
110
|
Vidhya
|
30
|
109
|
134
|
Rama
|
20
|
101
|
112
|
Neethu
|
10
|
111
|
456
|
Yogesh
|
10
|
324
|
345
|
Jeevan
|
20
|
101
|
909
|
Varu
|
10
|
101
|
Sort Funnel:
Sort
Funnel combines the input records in the order defined by the Value of one or
more key columns and the order of the output records is determined by these
sorting keys.
Typically all input data sets for a sort
funnel operation are hash-partitioned before they’re sorted (choosing the auto
partitioning method will ensure that this is done). Hash partitioning
guarantees that all records with the same key column values are located in the
same partition and so are processed on the same node. If sorting and
partitioning are carried out on separate stages before the Funnel stage, this
partitioning must be
Preserved.
The sort funnel operation allows you to set
one primary key and multiple
Secondary
keys. The Funnel stage first examines the primary key in each input record. For
multiple records with the same primary key value, it then examines secondary
keys to determine the order of records it will output.
Output
would be below for above 3 input files.
101
|
Leela
|
20
|
101
|
102
|
Joe
|
10
|
105
|
103
|
Latha
|
10
|
102
|
110
|
Vidhya
|
30
|
109
|
112
|
Neethu
|
10
|
111
|
134
|
Rama
|
20
|
101
|
345
|
Jeevan
|
20
|
101
|
456
|
Yogesh
|
10
|
324
|
909
|
Varu
|
10
|
101
|
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