Short Description |
Ports |
Metadata |
Rollup Attributes |
Details |
CTL interface |
Java Interface |
Examples |
Best practices |
See also |
Rollup creates one or more output records from one or more input records.
Rollup receives potentially unsorted data through single input port, transforms them and creates one or more output records from one or more input records.
Component can send different records to different output ports as specified by user.
Component | Same input metadata | Sorted inputs | Inputs | Outputs | Java | CTL | Auto-propagated metadata |
---|---|---|---|---|---|---|---|
Rollup | - | 1 | 1-n |
Port type | Number | Required | Description | Metadata |
---|---|---|---|---|
Input | 0 | For input data records | Any(In0) | |
Output | 0 | For output data records | Any(Out0) | |
1-N | For output data records | Any(Out1-N) |
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 accumulator record in rollup transformation.
Attribute | Req | Description | Possible values |
---|---|---|---|
Basic | |||
Group key | Key according to which the records are considered to be included into one group. Expressed as the sequence of individual input field names separated from each other by semicolon. See Group Key for more information. If not specified, all records are considered to be members of a single group. | e.g. first_name;last_name;salary | |
Group accumulator | ID of metadata that serve to create group accumulators. Metadata serve to store values used for transformation of individual groups of data records. | no metadata (default) | any metadata | |
Transform | [1] | Definition of the transformation written in the graph in CTL or Java. | |
Transform URL | [1] | Name of external file, including path, containing the definition of the transformation written in CTL or Java. | |
Transform class | [1] | Name of 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. |
Rollup requires transformation. You can define the transformation using CTL (see CTL interface) or Java (see Java Interface).
The flow of function calls in 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.
Figure 55.4. Rollup code workflow
If you do not define Group accumulator metadata, VoidMetadata is used in transformation functions.
CTL Templates for Rollup |
Access to input and output fields |
The transformation uses a CTL template for Rollup,
implement a RecordRollup
interface or inherit from a DataRecordRollup
superclass.
Below is the list of RecordRollup
interface methods.
See Java Interface
for detailed information this interface.
Once you have written your transformation, you can also convert it to Java language code by clicking 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 corresponding button at the upper right corner of the tab.
Table 55.6. Functions in Rollup
CTL Template Functions | |
---|---|
void init() | |
Required | No |
Description | Initialize the component, setup the environment, global variables |
Invocation | Called before processing the first record |
Returns | void |
void initGroup(<metadata name> groupAccumulator) | |
Required | yes |
Input Parameters |
If |
Returns | void |
Invocation |
Called repeatedly, once for the first input record of each group. Called before |
Description | Initializes information for specific group. |
Example | function void initGroup( companyCustomers groupAccumulator) { groupAccumulator.count = 0; groupAccumulator.totalFreight = 0; } |
boolean updateGroup(<metadata name> groupAccumulator) | |
Required | yes |
Input Parameters |
If |
Returns |
|
Invocation |
Called repeatedly (once for each input record of the group, including the first and the last record).
Called after the |
Description |
Updates information for specific group. If If any of the input records causes fail of the |
Example |
function boolean updateGroup(companyCustomers groupAccumulator) { groupAccumulator.count++; groupAccumulator.totalFreight = groupAccumulator.totalFreight + $in.0.Freight; return true; } |
boolean finishGroup(<metadata name> groupAccumulator) | |
Required | yes |
Input Parameters |
If |
Returns |
|
Invocation |
Called repeatedly, once for the last input record of each group. Called after |
Description |
Finalizes the group information. If
If any of the input records causes fail of the The |
Example |
function boolean finishGroup(companyCustomers groupAccumulator) { groupAccumulator.avgFreight = groupAccumulator.totalFreight / groupAccumulator.count; return true; } |
integer updateTransform(integer counter, <metadata name> groupAccumulator) | |
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.) |
If | |
Returns | Integer numbers. See Return Values of Transformations for detailed information. |
Invocation |
Called repeatedly as specified by user.
Called after
The function is called until |
Description |
It creates output records based on individual record information.
If
If any part of the The |
Example |
function integer updateTransform(integer counter, companyCustomers groupAccumulator) { if (counter >= Length) { clear(customers); return SKIP; } $out.0.customers = customers[counter]; $out.0.EmployeeID = $in.0.EmployeeID; return ALL; } |
integer transform(integer counter, <metadata name> groupAccumulator) | |
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.) |
If | |
Returns | Integer numbers. See Return Values of Transformations for detailed information. |
Invocation |
Called repeatedly as specified by user. Called after The function is called until |
Description |
It creates output records based on all of the records of the whole group. If If any part of the The |
Example |
function integer transform(integer counter, companyCustomers groupAccumulator) { if (counter > 0) return SKIP; $out.0.ShipCountry = $in.0.ShipCountry; $out.0.Count = groupAccumulator.count; $out.0.AvgFreight = groupAccumulator.avgFreight; return ALL; } |
void initGroupOnError(string errorMessage, string stackTrace, <metadata name> groupAccumulator) | |
Required | no |
Input Parameters | string errorMessage |
string stackTrace | |
If | |
Returns | void |
Invocation | Called if initGroup() throws an exception. |
Description | Initializes information for specific group. |
Example | function void initGroupOnError( string errorMessage, string stackTrace, companyCustomers groupAccumulator) printErr(errorMessage); } |
boolean updateGroupOnError(string errorMessage, string stackTrace, <metadata name> groupAccumulator) | |
Required | no |
Input Parameters | string errorMessage |
string stackTrace | |
If | |
Returns |
|
Invocation | Called if updateGroup() throws an exception for a record of the group.
|
Description | Updates information for specific group. |
Example |
function boolean updateGroupOnError(string errorMessage, string stackTrace, companyCustomers groupAccumulator) { printErr(errorMessage); return true; } |
boolean finishGroupOnError(string errorMessage, string stackTrace, <metadata name> groupAccumulator) | |
Required | no |
Input Parameters | string errorMessage |
string stackTrace | |
If | |
Returns |
|
Invocation | Called if finishGroup() throws an exception. |
Description | Finalizes the group information. |
Example |
function boolean finishGroupOnError(string errorMessage, string stackTrace, <metadata name> groupAccumulator) { printErr(errorMessage); return true; } |
integer updateTransformOnError(string errorMessage, string stackTrace, integer counter, <metadata name> groupAccumulator) | |
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 example below. Function calls end when SKIP is returned.) | |
If | |
Returns | Integer numbers. See Return Values of Transformations for detailed information. |
Invocation | Called if updateTransform() throws an exception. |
Description | It creates output records based on individual record information |
Example |
function integer updateTransformOnError(string errorMessage, string stackTrace, integer counter, companyCustomers groupAccumulator) { if (counter >= 0) { return SKIP; } printErr(errorMessage); return ALL; } |
integer transformOnError(string errorMessage, string stackTrace, integer counter, <metadata name> 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 example below.
Function calls end when SKIP is returned.) | |
If | |
Returns | Integer numbers. See Return Values of Transformations for detailed information. |
Invocation | Called if transform() throws an exception. |
Description | It creates output records based on all of the records of the whole group. |
Example |
function integer transformOnError(string errorMessage, string stackTrace, integer counter, companyCustomers groupAccumulator) { if (counter >= 0) { return SKIP; } printErr(errorMessage); return ALL; } |
string getMessage() | |
Required | No |
Description | Prints error message specified and invoked by user |
Invocation | Called in any time specified by user
(called only when either updateTransform() , transform() , updateTransformOnError() ,
or transformOnError() returns value less than or equal to -2). |
Returns | string |
void preExecute() | |
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 |
Invocation | Called during each graph run before the transform is executed. |
void postExecute() | |
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. |
All of the other CTL template functions allow to access neither inputs nor outputs or groupAccumulator
.
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 are accessible within the updateTransform()
,
transform()
, updateTansformOnError()
, and transformOnError()
functions.
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.
Warning | |
---|---|
Remember that if you do not hold these rules, NPE will be thrown! |
The transformation implements methods of the RecordRollup
interface
and inherits other common methods from the Transform
interface.
See Common Java Interfaces.
and Public Clover API.
Following is the list of the
RecordRollup
interface methods:
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 if initGroup(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 if updateGroup(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 if finishGroup(DataRecord, DataRecord)
throws an exception.
int updateTransform(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). The output data record will be sent to the
output when this method finishes. This method is called whenever
the boolean updateGroup(DataRecord, DataRecord)
method returns true
. The
counter
argument is the number of previous
calls to this method for the current group update. See Return Values of Transformations for detailed
information about return values and their meaning.
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 transform(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). The output data record will be sent to the
output when this method finishes. This method is called whenever
the boolean finishGroup(DataRecord, DataRecord)
method returns true
. The
counter
argument is the number of previous
calls to this method for the current group. See Return Values of Transformations for detailed
information about return values and their meaning.
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 if transform(int, DataRecord, DataRecord)
throws an exception.
Merging and updating incomplete records |
Transforming multivalue fields to multiple records |
You have list of records containing name, email address and phone number. Records does not have all field filled in. Records are sorted according to the field name.
Merge together data of records with same name. If more records with the same name have the same field filled in, use the last one.
Alice|[email protected]| Alice| |+420123456789 Alice|[email protected]| Bob | |+421212345678 Bob |[email protected] | Eve |[email protected] |+420720123456 Eve | |+420720123457
Input and output metadata (updateRecord) have fields name, email and phoneNumber.
Use attributes Group key, Group accumulator and Transform of Rollup.
Attribute | Value |
---|---|
Group key | name |
Group accumulator | updateRecord |
Transform | See the code below |
//#CTL2 function void initGroup(updateRecord groupAccumulator) { groupAccumulator.* = $in.0.*; return; } function boolean updateGroup(updateRecord groupAccumulator) { if (!isnull($in.0.email)) { groupAccumulator.email = $in.0.email; } if (!isnull($in.0.phoneNumber)) { groupAccumulator.phoneNumber = $in.0.phoneNumber; } return false; } function boolean finishGroup(updateRecord groupAccumulator) { return true; } function integer updateTransform(integer counter, updateRecord groupAccumulator) { raiseError("Function not implemented!"); } function integer transform(integer counter, updateRecord groupAccumulator) { if ( counter > 0 ) { return SKIP; } $out.0.* = groupAccumulator.*; return ALL; }
Result records contains merged field values:
Alice|[email protected]|+420123456789 Bob |[email protected] |+421212345678 Eve |[email protected] |+420720123457
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 database without support of multivalue fields.
Jane Green |users |[[email protected], [email protected], [email protected]] John Smith |users |[[email protected], [email protected]] Peter Green|users |[[email protected]]
Field name of input record is unique
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 Rollup attributes Group key, Group accumulator and Transform.
Attribute | Value |
---|---|
Group key | name |
Group accumulator | users |
Transform | See the code below |
//#CTL2 function void initGroup(users groupAccumulator) { return; } function boolean updateGroup(users groupAccumulator) { groupAccumulator.* = $in.0.*; return true; } function boolean finishGroup(users groupAccumulator) { return true; } function integer updateTransform(integer counter, users groupAccumulator) { if(counter >= length(groupAccumulator.email )) { return SKIP; } $out.1.name = $in.0.name; $out.1.email = groupAccumulator.email[counter]; return 1; } function integer transform(integer counter, users groupAccumulator) { if(counter > 0 ) { return SKIP; } $out.0.name = $in.0.name; $out.0.group = $in.0.group; return 0; }
The transformation above requires field user to be unique.
You receive 3 records on first output port:
Jane Green |users John Smith |users Peter Green|users
Six records will be send to second output port:
Jane Green |[email protected] Jane Green |[email protected] Jane Green |[email protected] John Smith |[email protected] John Smith |[email protected] Peter Green|[email protected]
To process a large number of records, sort records first and than use Rollup instead of
using Rollup with attribute Sorted input set to false
.
If the transformation is specified in an external file (with Transform URL), we recommend users to explicitly specify Transform source charset.