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Denormalizer

Not available in Community Designer

Short Description

Ports

Metadata

Denormalizer Attributes

Short Description

Denormalizer creates single output record from one or more input records. Input records should be sorted.

Component	Same input metadata	Sorted inputs	Inputs	Outputs	Java	CTL	Auto-propagated metadata
Denormalizer	-		1	1

Icon

Ports

Port type	Number	Required	Description	Metadata
Input	0		for input data records	any
Output	0		for denormalized data records	any

Metadata

Denormalizer does not propagate metadata.

Denormalizer does not have metadata templates.

Denormalizer does not require any specific metadata fields.

Denormalizer Attributes

Attribute	Req	Description	Possible values
Basic
Key	^[1]	Key that creates groups of input data records according to its value. Adjacent input records with the same value of Key are considered to be members of one group. One output record is composed from members of such group. See Key for more information.
Group size	^[1]	Group may be defined by exact number of its members. E.g. each five records form a single group. The input record count MUST be a multiple of `group size` (see Allow incomplete last group). This is mutually exclusive with `key` attribute.	a number
Denormalize	^[2]	Definition of how to denormalize records, written in the graph in CTL or Java.
Denormalize URL	^[2]	Name of external file, including path, containing the definition of how to denormalize records, written in CTL or Java.
Denormalize class	^[2]	Name of external class defining the way how records should be normalized.
Equal NULL		By default, records with null values of key fields are considered to be equal. If `false`, they are considered to be different.	true (default) \| false
Denormalize source charset		Encoding of external file defining the transformation. The default encoding depends on DEFAULT_SOURCE_CODE_CHARSET in defaultProperties.	E.g. UTF-8
Advanced
Allow incomplete last group		In case input records grouping is specified by Group size attribute, number of input records must be a multiple of group size. Using this attribute this condition can be suppressed. The last group does not need to be complete.	true \| false (default)
Deprecated
Sort order		Order in which groups of input records are expected to be sorted. See Sort order	Auto (default) \| Ascending \| Descending \| Ignore
Error actions		Definition of the action that should be performed when the specified transformation returns some Error code. See Return Values of Transformations.
Error log		URL of the file to which error messages for specified Error actions should be written. If not set, they are written to Console.
^[1]`group size` has higher priority than `key`. If neither of these attributes is specified, all records will form a single group. ^[2] One of them must specified.

Details

Denormalizer receives sorted data through single input port, checks Key values, creates one output record from one or more adjacent input records with the same Key value.

Denormalizer requires transformation. The transformation can be defined in CTL (see CTL Interface) or in Java (see Java Interface) or using existing .class file (Normalize class attribute).

To define transformation use one of the three transformation attributes: Denormalize, Denormalize URL or Denormalize class.

Diagram below describes flow of function calls in Denormalizer.

Figure 50.1. Denormalizer code workflow

The function append() is called with each input record. The function transform() is called once for each group of input records.

If you do not define any of the optional functions init(), preExecute(), clean() or postExecute(), the execution flow continues with the next function according to the diagram.

If you do not specify appendOnError() or transformOnError() functions and error occurs, the execution of graph fails.

The transformation uses a CTL template for Denormalizer, implements a RecordDenormalize interface or inherits from a DataRecordDenormalize superclass. The interface methods are listed in CTL Interface and Java Interface.

Key

Key is expressed as a sequence of field names separated from each other by semicolon, colon, or pipe.

Example 50.2. Key for Denormalizer

first_name;last_name

In this Key, first_name and last_name are fields of metadata on input port.

Sort order

If the records are denormalized by the Key, i.e., not by the Group size, the input records must be grouped according to the Key field value. Then, depending on the sorting order of the groups, select the proper Sort order:

Auto - the sorting order of the groups of input records is guessed from the first two records with different value in the key field, i.e., from the first records of the first two groups.
Ascending - if the groups of input records with the same key field value(s) are sorted in ascending order
Descending - if the groups of input records with the same key field value(s) are sorted in descending order
Ignore - if the groups of input records with the same key field value(s) are not sorted

CTL Interface

CTL Templates

Access to input and output fields

The transformation written in CTL uses a CTL template for Denormalizer. Only the functions count() and transform() are mandatory.

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.

CTL Templates

Table 50.3. Functions in Denormalizer

CTL Template Functions
boolean init()
Required	No
Description	Initializes the component, sets up the environment and global variables.
Invocation	Called before processing the first record
Returns	`true` \| `false` (in case of `false` graph fails)
integer append()
Required	yes
Input Parameters	none
Returns	Integer numbers. Negative value lower than -1 aborts processing. Any non-negative value means successful pass.
Invocation	Called repeatedly, once for each input record
Description	For the group of adjacent input records with the same Key values it appends the information from which composes the resulting output record. If `append()` fails and user has not defined any `appendOnError()`, the whole graph will fail. If any of the input records causes fail of the `append()` function, and if user has defined `appendOnError()` function, processing continues in this `appendOnError()` at the place where `append()` failed. The `append()` passes to `appendOnError()` error message and stack trace as arguments.
Example	function integer append() { CustomersInGroup++; myLength = length(errorCustomers); if(!isInteger($in.0.OneCustomer)) { errorCustomers = errorCustomers + iif(myLength > 0 ," - ","") + $in.0.OneCustomer; } customers = customers + iif(length(customers) > 0 ," - ","") + $in.0.OneCustomer; groupNo = $in.0.GroupNo; return OK; }
integer transform()
Required	yes
Input Parameters	none
Returns	Integer numbers. See Return Values of Transformations for detailed information.
Invocation	Called repeatedly, once for each output record.
Description	It creates output records. If `transform()` fails and user has not defined any `transformOnError()`, the whole graph will fail. If any part of the `transform()` function for some output record causes fail of the `transform()` function, and if user has defined `transformOnError()` function, 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 error message and stack trace are passed to `transformOnError()`.
Example	function integer transform() { $out.0.CustomersInGroup = CustomersInGroup; $out.0.CustomersOnError = errorCustomers; $out.0.Customers = customers; $out.0.GroupNo = groupNo; return OK; }
void clean()
Required	no
Input Parameters	none
Returns	void
Invocation	Called repeatedly, once for each output record. The `clean()` function is called after the `transform()` function.
Description	Returns the component to the initial settings
Example	function void clean(){ customers = ""; errorCustomers = ""; groupNo = 0; CustomersInGroup = 0; }
integer appendOnError(string errorMessage, string stackTrace)
Required	no
Input Parameters	`string errorMessage`
Input Parameters	`string stackTrace`
Returns	Integer numbers. Positive integer numbers are ignored, meaning of 0 and negative values is described in Return Values of Transformations
Invocation	Called if `append()` throws an exception.
Description	The function handles error which occurred in `append()` function. If any of the input records causes fail of the `append()` function, and if user has defined `appendOnError()` function, processing continues in this `appendOnError()` at the place where `append()` failed. The `appendOnError()` function gets the information gathered by `append()` that was get from previously successfully processed input records. Also error message and stack trace are passed to `appendOnError()`.
Example	function integer appendOnError(string errorMessage, string stackTrace) { printErr(errorMessage); return CustomersInGroup; }
integer transformOnError(Exception exception, stackTrace)
Required	no
Input Parameters	`string errorMessage`
Input Parameters	`string stackTrace`
Returns	Integer numbers. See Return Values of Transformations for detailed information.
Invocation	Called if `transform()` throws an exception.
Description	The function handles error which occurred in `transform()` function. If any part of the `transform()` function fails, and if user has defined `transformOnError()` function, 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 error message and stack trace are passed to `transformOnError()`. the function `transformOnError()` creates output records.
Example	function integer transformOnError( string errorMessage, string stackTrace) { $out.0.CustomersInGroup = CustomersInGroup; $out.0.ErrorFieldForTransform = errorCustomers; $out.0.CustomersOnError = errorCustomers; $out.0.Customers = customers; $out.0.GroupNo = groupNo; return OK; }
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 `append()`, `transform()`, `appendOnError()`, 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

Input records or fields

Input records or fields are accessible within the append() and appendOnError() functions only.

Output records or fields

Output records or fields are accessible within the transform() and transformOnError() functions only.

	Warning
All of the other CTL template functions allow to access neither inputs nor outputs. Remember that if you do not hold these rules, NPE will be thrown!

Warning

All of the other CTL template functions allow to access neither inputs nor outputs.

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

Java Interface

The transformation implements methods of the RecordDenormalize interface and inherits other common methods from the Transform interface. See Common Java Interfaces. See Public Clover API.

Following are the methods of the RecordDenormalize interface:

boolean init(Properties parameters, DataRecordMetadata sourceMetadata, DataRecordMetadata targetMetadata)
Initializes denormalize class/function. This method is called only once at the beginning of denormalization process. Any object allocation/initialization should happen here.

int append(DataRecord inRecord)
Passes one input record to the composing class.

int appendOnError(Exception exception, DataRecord inRecord)
Passes one input record to the composing class. Called only if append(DataRecord) throws an exception.

int transform(DataRecord outRecord)
Retrieves composed output record. See Return Values of Transformations for detailed information about return values and their meaning. In Denormalizer, only ALL, 0, SKIP, and Error codes have some meaning.

int transformOnError(Exception exception, DataRecord outRecord)
Retrieves composed output record. Called only if transform(DataRecord) throws an exception.

void clean()
Finalizes current round/clean after current round - called after the transform method was called for the input record.

Examples

Converting multiple having same key records to one

Converting fixed number of records to one records

Converting multiple having same key records to one

Input records acquired from relational database contain fields companyName and product.

Denormalizer Limited |chocolate
Denormalizer Limited |coffee
Denormalizer Limited |pizza
ZXCV International   |coffee

Convert the records to following form: companyName is followed by list of products separated by comma.

Solution

Use Key and Normalize attributes.

Attribute	Value
Key	companyName
Normalize	See the code below

//#CTL2

string[] products;
string companyName;

function integer append() {
 	append(products, $in.0.product);
 	companyName = $in.0.companyName;
 	return OK;
}

function integer transform() {
 	$out.0.companyName = companyName;
 	$out.0.products = join(",", products);
 	return OK;
}

function void clean() {
 	clear(products);
}

Denormalizer returns following records:

Denormalizer Limited |chocolate,coffee,pizza
ZXCV International   |coffee

	Important
Records having the same Key have to be available in input data all at once. Otherwise you will get a new output record for each several subsequent records having the same key. The best solution is to have input records sorted by Key.

Important

Records having the same Key have to be available in input data all at once. Otherwise you will get a new output record for each several subsequent records having the same key.

The best solution is to have input records sorted by Key.

Converting fixed number of records to one records

Given a list of students.

Charlie
Daniel
Agatha
Henry
Oscar
Kate
Romeo
Jane

Convert the list to groups of 3. Each group (one output record) has a number and names of it's members. The names are separated by comma.

Each output record contains groupNumber and members.

Solution

Use attributes Group size and Normalize. The be able to process number of record not being divisible by 3 you need Allow incomplete last group attribute.

Attribute	Value
Group size	3
Normalize	See the code below
Allow incomplete last group	true

//#CTL2

integer groupNumber;
string[] names;

function integer append() {
 	append(names, $in.0.name);
 	return OK;
}

function integer transform() {
 	$out.0.groupNo = groupNumber;
 	$out.0.members = join(",", names);
 	groupNumber++;

 	return OK;
}

function boolean init() {
 	groupNumber = 1;
 	return true;
}

function void clean() {
 	clear(names);
}

Denormalizer returns following records:

1|Charlie,Daniel,Agatha
2|Henry,Oscar,Kate
3|Romeo,Jane

Best Practices

If the transformation is specified in an external file (with Denormalize URL), we recommend users to explicitly specify Denormalize source charset.

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Denormalizer

Not available in Community Designer

Short Description

Icon

Ports

Metadata

Denormalizer Attributes

Details

Key

Sort order

CTL Interface

CTL Templates

Access to input and output fields

Input records or fields

Output records or fields

Java Interface

Examples

Converting multiple having same key records to one

Solution

Converting fixed number of records to one records

Solution

Best Practices

See also