Rollup
Short Description
Rollup creates one or more output records from one or more input records.
Rollup receives potentially unsorted data through the single input port, transforms it and creates one or more output records from one or more input records.
The component can send different records to different output ports as specified by the user.
Rollup
-
x
1
1-n
✓
✓
x
Ports
Input
0
✓
For input data records
Any(In0)
Output
0
✓
For output data records
Any(Out0)
1-N
x
For output data records
Any(Out1-N)
Metadata
Rollup does not propagate metadata. Rollup has no metadata template. Input and output metadata fields can have any data types. Metadata on output ports can differ. You may need a metadata for the accumulator record in rollup transformation.
Rollup Attributes
BASIC
Group Key
e.g.
Group accumulator
The ID of metadata that serves to create group accumulators. Metadata serves to store values used for transformation of individual groups of data records.
no metadata (default) | any metadata
Transform
[bl
Definition of the transformation written in the graph in CTL or Java.
Transform URL
[bl
The name of an external file, including the path, containing the definition of the transformation written in CTL or Java.
Transform class
[bl
The name of an external class defining the transformation.
Transform source charset
Encoding of external file defining the transformation. The default encoding depends on DEFAULT_SOURCE_CODE_CHARSET in defaultProperties.
E.g. UTF-8
Sorted input
By default, records are considered to be sorted. Either in ascending or descending order. Different fields may even have different sort order. If your records are not sorted, switch this attribute to false
.
true (default) | false
Equal NULL
By default, records with null values of key fields are considered to be equal. If set to false
, they are considered to be different from each other.
true (default) | false
[1] One of these must specified.
Details
Rollup requires transformation. You can define the transformation using CTL (see CTL interface below) or Java (see Java Interface below).
The flow of function calls in a rollup transformation is depicted below. If any optional function (except functions for error handling) is not used, the position of unimplemented function from diagram is skipped.
If you do not define Group accumulator metadata, VoidMetadata is used in transformation functions.
CTL Interface
The transformation uses a CTL template for Rollup, implement a RecordRollup
interface or inherit from a DataRecordRollup
superclass. Below is a list of RecordRollup
interface methods. For detailed information about this interface, see Java Interface below.
Once you have written your transformation, you can also convert it to Java language code by clicking a corresponding button at the upper right corner of the tab.
You can open the transformation definition as another tab of the graph (in addition to the Graph and Source tabs of Graph Editor) by clicking a corresponding button at the upper right corner of the tab.
CTL Templates for Rollup
CTL TEMPLATE FUNCTIONS
void init()
Required
No
Description
Initializes the component, setup the environment and global variables
Invocation
Called before processing the first record
Returns
void
Required
Yes
Input Parameters
groupAccumulator
(metadata specified by the user)
Returns
void
Invocation
Called repeatedly, once for the first input record of each group.
Called before updateGroup(groupAccumulator)
.
Description
Initializes information for specific group
Example
See here below
Required
Yes
Input Parameters
groupAccumulator
(metadata specified by user)
If groupAccumulator
is not defined, VoidMetadata Accumulator
is used in the function signature.
Returns
false (updateTransform(counter,groupAccumulator)
is not called)
true (updateTransform(counter,groupAccumulator)
is called)
Invocation
Called repeatedly (once for each input record of the group, including the first and the last record).
Called after the initGroup(groupAccumulator)
function has already been called for the whole group.
Description
Updates information for specific group.
If updateGroup()
fails and user has not defined any updateGroupOnError()
, the whole graph will fail.
If any of the input records causes a failure of the updateGroup()
function and if user has defined another function (updateGroupOnError()
), processing continues in this updateGroupOnError()
at the place where updateGroup()
failed. The updateGroup()
passes to the updateGroupOnError()
error message and stack trace as arguments.
Example
See here below
Required
Yes
Input Parameters
groupAccumulator
(metadata specified by user)
If groupAccumulator
is not defined, VoidMetadata Accumulator
is used in the function signature.
Returns
true(transform(counter,groupAccumulator)
is called)
false (transform(counter,groupAccumulator)
is not called)
Invocation
Called repeatedly, once for the last input record of each group.
Called after updateGroup(groupAccumulator)
has already been called for all input records of the group.
Description
Finalizes the group information.
If finishGroup()
fails and no finishGroupOn Error()
is defined, the whole graph will fail.
If any of the input records causes fail of the finishGroup()
function, and the finishGroupOn Error()
function is defined, processing continues in the finishGroupOn Error()
at the place where finishGroup()
failed.
The finishGroup()
passes to the finishGroupOn Error()
error message and stack trace as arguments.
Example
See here below
Required
Yes
Input Parameters
integer counter
(starts from 0, specifies the number of created records. should be terminated as shown in the example below. Function calls end when SKIP is returned.)
<metadata name> groupAccumulator
(metadata specified by the user)
If groupAccumulator
is not defined, VoidMetadata Accumulator
is used in the function signature.
Returns
Invocation
Called repeatedly as specified by user.
Called after updateGroup(groupAccumulator)
returns true
.
The function is called until SKIP
is returned.
Description
It creates output records based on individual record information.
If updateTransform()
fails and no updateTransformOnError()
is defined, the whole graph will fail.
If any part of the transform()
function for some output record causes fail of the updateTransform()
function, and if another (updateTransformOnError()
) is defined, processing continues in this updateTransformOnError()
at the place where updateTransform()
failed.
The updateTransformOnError()
function gets the information gathered by updateTransform()
that was get from previously successfully processed code. The error message and stack trace are passed to updateTransformOnError()
, as well.
Example
See here below
Required
Yes
Input Parameters
integer counter
(starts from 0, specifies the number of created records. should be terminated as shown in example below. Function calls end when SKIP
is returned.)
<metadata name> groupAccumulator
(metadata specified by the user)
If groupAccumulator
is not defined, VoidMetadata Accumulator
is used in the function signature.
Returns
Invocation
Called repeatedly as specified by the user.
Called after finishGroup(groupAccumulator)
returns true
.
The function is called until SKIP
is returned.
Description
It creates output records based on all of the records of the whole group.
If transform
fails and no transformOnError()
is defined, the whole graph will fail.
If any part of the transform()
function for some output record causes fail of the transform()
function, and if another (TransformOnError()
) is defined, processing continues in this TransformOnError()
at the place where transform()
failed.
The transformOnError()
function gets the information gathered by transform()
that was get from previously successfully processed code. The error message and stack trace are passed to transformOnError()
, as well.
Example
See here below
Required
No
Input parameters
string errorMessage
string stackTrace
groupAccumulator
(metadata specified by user)
If groupAccumulator
is not defined, VoidMetadata Accumulator
is used in the function signature.
Returns
Void
Invocation
Called if initGroup()
throws an exception.
Description
Initializes information for specific group.
Example
See here below.
Required
No
Input Parameters
string errorMessage
string stackTrace
groupAccumulator
(metadata specified by user)
If groupAccumulator
is not defined, VoidMetadata Accumulator
is used in the function signature.
Returns
false (updateTransform(counter,groupAccumulator)
is not called)
true (updateTransform(counter,groupAccumulator)
is called)
Invocation
Called if updateGroup()
throws an exception for a record of the group.
Description
Updates information for specific group.
Example
See here below.
Required
No
Input Parameters
string errorMessage
string stackTrace
groupAccumulator
(metadata specified by user)
If groupAccumulator
is not defined, VoidMetadata Accumulator
is used in the function signature.
Returns
true (transform(counter,groupAccumulator)
is called)
false (transform(counter,groupAccumulator)
is not called)
Invocation
Called if finishGroup()
throws an exception.
Description
Finalizes the group information.
Example
See here below.
Required
Yes
Input Parameters
string errorMessage
string stackTrace
integer counter
(starts from 0, specifies the number of created records. should be terminated as shown in the example below. The function calls end when SKIP
is returned.)
groupAccumulator
(metadata specified by user)
If groupAccumulator
is not defined, VoidMetadata Accumulator
is used in the function signature.
Returns
Invocation
Called if updateTransform()
throws an exception.
Description
It creates output records based on individual record information.
Example
See here below.
CTL TEMPLATE FUNCTIONS
integer transformOnError(string errorMessage, string stackTrace, integer counter, groupAccumulator)
Required
No
Input Parameters
string errorMessage
string stackTrace
integer counter
(starts from 0, specifies the number of created records. should be terminated as shown in the example below. The function calls end when SKIP
is returned.)
groupAccumulator
(metadata specified by user)
If groupAccumulator
is not defined, VoidMetadata Accumulator
is used in the function signature.
Returns
Invocation
Called if transform()
throws an exception.
Description
It creates output records based on all of the records of the whole group.
Example
See here below.
Required
No
Description
Prints an error message specified and invoked by the user.
Invocation
Called in any time specified by the user (called only when either updateTransform()
, transform()
, updateTransformOnError()
or TransformOnError()
returns value less than or equal to -2).
Returns
string
Required
No
Input parameters
None
Returns
void
Description
May be used to allocate and initialize resources required by the transform.
All resources allocated within this function should be released by the postExecute()
function.
Invocation
Called during each graph run before the transform is executed.
Required
No
Input parameters
None
Returns
void
Description
Should be used to free any resources allocated within the preExecute()
function.
Invocation
Called during each graph run after the entire transform was executed.
Access to input and output fields
All of the other CTL template functions allow to access neither inputs nor outputs or groupAccumulator
.
Input records or fields
Input records or fields are accessible within the initGroup(), updateGroup(), finishGroup(), initGroupOnError(), updateGroupOnError()
and finishGroupOnError() functions
.
They are also accessible within the updateTransform(), transform(), updateTansformOnError()
and transformOnError()
functions.
Output records or fields
Output records or fields are accessible within the updateTransform(), transform(), updateTansformOnError()
and transformOnError()
functions.
Group accumulator
Group accumulator is accessible within the initGroup(), updateGroup(), finishGroup(), initGroupOnError(), updateGroupOnError()
and finishGroupOnError()
functions.
It is also accessible within the updateTransform(), transform(), updateTansformOnError()
and transformOnError()
functions.
Java Interface
void init(Properties parameters, DataRecordMetadata inputMetadata, DataRecordMetadata accumulatorMetadata, DataRecordMetadata[] outputMetadata)
Initializes the rollup transform. This method is called only once at the beginning of the life-cycle of the rollup transform. Any internal allocation/initialization code should be placed here.void initGroup(DataRecord inputRecord, DataRecord groupAccumulator)
This method is called for the first data record in a group. Any initialization of the group accumulator should be placed here.void initGroupOnError(Exception exception, DataRecord inputRecord, DataRecord groupAccumulator)
This method is called for the first data record in a group. Any initialization of the group "accumulator" should be placed here. Called only ifinitGroup(DataRecord, DataRecord)
throws an exception.boolean updateGroup(DataRecord inputRecord, DataRecord groupAccumulator)
This method is called for each data record (including the first one as well as the last one) in a group in order to update the group accumulator.boolean updateGroupOnError(Exception exception, DataRecord inputRecord, DataRecord groupAccumulator)
This method is called for each data record (including the first one as well as the last one) in a group in order to update the group accumulator. Called only ifupdateGroup(DataRecord, DataRecord)
throws an exception.boolean finishGroup(DataRecord inputRecord, DataRecord groupAccumulator)
This method is called for the last data record in a group in order to finish the group processing.boolean finishGroupOnError(Exception exception, DataRecord inputRecord, DataRecord groupAccumulator)
This method is called for the last data record in a group in order to finish the group processing. Called only iffinishGroup(DataRecord, DataRecord)
throws an exception.int updateTransformOnError(Exception exception, int counter, DataRecord inputRecord, DataRecord groupAccumulator, DataRecord[] outputRecords) This method is used to generate output data records based on the input data record and the contents of the group accumulator (if it was requested). Called only if
updateTransform(int, DataRecord, DataRecord)
throws an exception.int transformOnError(Exception exception, int counter, DataRecord inputRecord, DataRecord groupAccumulator, DataRecord[] outputRecords)
This method is used to generate output data records based on the input data record and the contents of the group accumulator (if it was requested). Called only iftransform(int, DataRecord, DataRecord)
throws an exception.
Examples
Merging and updating incomplete records
You have a list of records containing name, email address and phone number. Records do not have all fields filled in. Records are sorted according to the field name.
Merge together data of records with the same name. If more records with the same name have the same field filled in, use the last one.
Solution Input and output metadata (updateRecord) have fields name, email and phoneNumber.
Use the attributes Group key, Group accumulator and Transform of Rollup.
Group Key
Name
Group accumulator
updateRecord
Transform
See the code below
Result records contains merged field values:
Transforming multivalue fields to multiple records
Input records containing name, group and email have a multivalue field email. Split input stream to two data streams: one with name and group, the other one with name and email. The output records will be loaded into a database without support of multivalue fields.
The field name of an input record is unique.
Solution Input metadata users has fields name, group and email. Output metadata users2 has fields name and group, output metadata emails has fields name and email.
Use the Rollup attributes Group key, Group accumulator and Transform.
Group key
name
Group accumulator
users
Transform
See the code below
The transformation above requires the field user to be unique.
You receive 3 records on the first output port:
Six records will be send to second output port:
Best Practices
To process a large number of records, sort records first and than use Rollup instead of using Rollup with the Sorted input attribute set to false
.
If the transformation is specified in an external file (with Transform URL), we recommend users to explicitly specify Transform source charset.
See also
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