Version

    Rollup

    Rollup 64x64

    Short Description

    Ports

    Metadata

    Rollup Attributes

    Details

    CTL interface

    Java Interface

    Examples

    Best practices

    See also

    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

    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)

    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

    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.

    Rollup diagram
    Figure 435. 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 64. 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.)

    <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.)

    <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

    //#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.

    Rollup example 020

    Use the 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 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.