Rollup

Development > Component reference > Transformers > Rollup

Short description

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.

Same input metadata	Sorted inputs	Inputs	Outputs	Java	CTL	Auto-propagated metadata
-	⨯	1	1-n	✓	✓	⨯

Same input metadata

Sorted inputs

Inputs

Outputs

Java

CTL

Auto-propagated metadata

⨯

1-n

✓

⨯

Ports

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)

Port type

Number

Required

Description

Metadata

Input

✓

For input data records

Any(In0)

Output

✓

For output data records

Any(Out0)

1-N

⨯

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

Attribute Req Description Possible values

Attribute	Req	Description	Possible values
Basic
Group key		Key according to which the records are considered to be included into one group. Expressed as a sequence of individual input field names separated from each other by a semicolon. For more information, see Group key. If not specified, all records are considered to be members of a single group.	e.g. `first_name;last_name;salary`
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	^[1]	Definition of the transformation written in the graph in CTL or Java.
Transform URL	^[1]	The name of an external file, including the path, containing the definition of the transformation written in CTL or Java.
Transform class	^[1]	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

Basic

Group key

Key according to which the records are considered to be included into one group. Expressed as a sequence of individual input field names separated from each other by a semicolon. For more information, see Group key.

If not specified, all records are considered to be members of a single group.

e.g. first_name;last_name;salary

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

^[1]

Definition of the transformation written in the graph in CTL or Java.

Transform URL

^[1]

The name of an external file, including the path, containing the definition of the transformation written in CTL or Java.

Transform class

^[1]

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) or Java (see Java interface).

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.

Figure 407. Rollup code workflow

If you do not define Group accumulator metadata, VoidMetadata is used in transformation functions.

CTL interface

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 a list of RecordRollup interface methods. For detailed information about this interface, see Java interface.

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

Table 74. 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	`<metadata name> groupAccumulator` (metadata specified by the user) If `groupAccumulator` is not defined, `VoidMetadata Accumulator` is used in the function signature.
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	`function void initGroup( companyCustomers groupAccumulator) { groupAccumulator.count = 0; groupAccumulator.totalFreight = 0; }`
boolean updateGroup(<metadata name> groupAccumulator)
Required	yes
Input Parameters	`<metadata name> 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	`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	`<metadata name> 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 `finishGroupOnError()` is defined, the whole graph will fail. If any of the input records causes fail of the `finishGroup()` function, and the `finishGroupOnError()` function is defined, processing continues in the `finishGroupOnError()` at the place where `finishGroup()` failed. The `finishGroup()` passes to the `finishGroupOnError()` error message and stack trace as arguments.
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 the example below. Function calls end when `SKIP` is returned.)
Input Parameters	`<metadata name> groupAccumulator` (metadata specified by the user) If `groupAccumulator` is not defined, `VoidMetadata Accumulator` is used in the function signature.
Returns	Integer numbers. For more information, see Return values of transformations.
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	`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.)
Input Parameters	`<metadata name> groupAccumulator` (metadata specified by the user) If `groupAccumulator` is not defined, `VoidMetadata Accumulator` is used in the function signature.
Returns	Integer numbers. For more information, see Return values of transformations.
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 the `transformOnError()` function is defined, processing continues in the `transformOnError()` at the place where `transform()` failed. The `transformOnError()` function gets the information gathered by `transform()` that was get from previously successfully processed code. Also the error message and stack trace are passed to `transformOnError()`.
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`
	`<metadata name> 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	`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`
	`<metadata name> 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	`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`
	`<metadata name> 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	`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 the example below. The 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	Integer numbers. For detailed information, see Return values of transformations.
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 the example below. The function calls end when `SKIP` is returned.)
	`<metadata name> groupAccumulator` (metadata specified by user) If `groupAccumulator` is not defined, `VoidMetadata Accumulator` is used in the function signature.
Returns	Integer numbers. For detailed information, see Return values of transformations.
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 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`
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 `postExecute()` function.
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.

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.

Remember that if you do not hold these rules, NPE will be thrown.

Java interface

The transformation implements methods of the RecordRollup interface and inherits other common methods from the Transform interface. See Common Java interfaces and Public CloverDX 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.

Examples

Merging and updating incomplete records

Transforming multivalue fields to multiple records

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.

Alice|alice@example.com|
Alice|                 |+420123456789
Alice|alice@example.org|
Bob  |                 |+421212345678
Bob  |bob@example.info |
Eve  |eve@example.com  |+420720123456
Eve  |                 |+420720123457

Solution

Input and output metadata (updateRecord) have fields name, email and phoneNumber.

Use the attributes Group key, Group accumulator and Transform of Rollup.

Attribute	Value
Group key	name
Group accumulator	updateRecord
Transform	See the code below

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|alice@example.org|+420123456789
Bob  |bob@example.info |+421212345678
Eve  |eve@example.com  |+420720123457

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.

Jane Green |users |[jane.green@example.org, greenj@example.org, jane.brown@example.org]
John Smith |users |[john.smith@example.com, jsmith@example.com]
Peter Green|users |[peter.green@example.com]

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.

Attribute	Value
Group key	name
Group accumulator	users
Transform	See the code below

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 the field user to be unique.

You receive 3 records on the first output port:

Jane Green |users
John Smith |users
Peter Green|users

Six records will be send to second output port:

Jane Green |jane.green@example.org
Jane Green |greenj@example.org
Jane Green |jane.brown@example.org
John Smith |john.smith@example.com
John Smith |jsmith@example.com
Peter Green|peter.green@example.com

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.

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Rollup

Short description

Ports

Metadata

Rollup attributes

Details

CTL interface

CTL templates for Rollup

Access to input and output fields

Input records or fields

Output records or fields

Group accumulator

Java interface

Examples

Merging and updating incomplete records

Solution

Transforming multivalue fields to multiple records

Solution

Best practices

See also