DataGenerator

Short Description

DataGenerator generates data records using transformation.

Ports

The component can send different records to different output ports using Return Values of Transformations.

Metadata

DataGenerator does not propagate metadata.
Datagenerator has no metadata template.
Output metadata fields can have any data types.
Metadata on output ports can differ.
Metadata on all output ports can use Autofilling Functions.

DataGenerator Attributes

[1] One of these transformation attributes should be specified instead of the deprecated attributes marked by number 2. However, these new attributes are optional.
[2] These attributes are deprecated now. Define one of the transformation attributes marked by number 1 instead.

Details

DataGenerator generates data according to a pattern instead of reading data from a file, database, or any other data source. To generate data, a generate transformation may be defined.
It uses a CTL template for DataGenerator or implements a RecordGenerate interface.

DataGenerator Deprecated Attributes

If you do not define any of these three attributes, you can instead define the fields which should be generated at random (Random fields) and by sequence (Sequence fields) and fields that are constant (Record pattern).

Record Pattern

Record pattern is a string containing all constant fields (all except random and sequential fields) of the generated records in the form of a delimited (with delimiters defined in metadata on the output port) or fixed length (with sizes defined in metadata on the output port) record.

Sequence Fields

Sequence fields can be defined in the dialog that opens after clicking the Sequence fields attribute. The Sequences dialog looks like this:

This dialog consists of two panes with all graph sequences on the left and all Clover fields (names of the fields in metadata) on the right. Choose the desired sequence on the left and drag and drop it to the right pane to the desired field.
The dialog contains two buttons on its right side. For canceling the selected assigned mapping or all assigned mappings.

Remember that it is not necessary (although possible) to assign the same sequence to different Data Shaper fields.

Random Fields

This attribute defines the values of all fields whose values are generated at random. For each of the fields you can define its range (i.e. minimum and maximum values). These values are of the corresponding data types according to metadata. You can assign random fields in the Edit key dialog that opens after clicking the Random fields attribute.

There are the Fields pane on the left, the Random fields on the right and the Random ranges pane at the bottom. In the last pane, you can specify the ranges of the selected random field. There you can type specific values. You can move fields between the Fields and Random fields panes as was described above - by clicking the Left arrow and Right arrow buttons.

CTL Interface

You can specify a transformation using CTL in Generator or Generator URL attributes.
This can be done using the Transformations tab of the Transform Editor. However, you may find that you are unable to specify more advanced transformations using the easiest approach. In such a case, use CTL scripting.

CTL Templates for DataGenerator

This transformation template is used only in DataGenerator.
Once you have written your transformation in CTL, you can also convert it to the Java language code by using a corresponding button at the upper right corner of the tab.

function integer generate() {
   myTestString = iif(randomBool(),"1","abc");
   $in.0.name = randomString(3,5) + " " randomString(5,7);
   $in.0.salary = randomInteger(20000,40000);
   $in.0.testValue = str2integer(myTestString);
   return ALL;
}

function integer generateOnError(
                      string errorMessage,
                      string stackTrace) {
   $out.0.name = randomString(3,5) + " " randomString(5,7);
   $out.0.salary = randomInteger(20000,40000);
   $out.0.stringTestValue = "myTestString is abc";
   return ALL;
}

Output records or fields

Output records or fields are accessible within the generate() and generateOnError() functions only.

Capt. Eddie to ground control:

All of the other CTL template functions do not allow to access outputs. Remember that if you do not hold these rules, NullPointerException will be thrown.

Java Interface

The transformation implements methods of the RecordGenerate interface and inherits other common methods from the Transform interface. See Common Java Interfaces.
Following are the methods of RecordGenerate interface:

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

• int generate(DataRecord[] target)
  Performs generator of target records. This method is called as one step in generate flow of records.

  

  
  This method allows to distribute different records to different connected output ports according to the value returned for them. For more information about return values and their meaning, see Return Values of Transformations.

• int generateOnError(Exception exception, DataRecord[] target)
  Performs generator of target records. This method is called as one step in generate flow of records. Called only if generate(DataRecord[]) throws an exception.

• void signal(Object signalObject)
  Method which can be used for signaling into generator that something outside has happened.

• Object getSemiResult()
  Method which can be used for getting intermediate results out of generation. May or may not be implemented.

Examples

Generating Variable Number of Records

Sometimes the number of records to be generated is not known at design time. In such a case, set the value of the Number of records to generate attribute to a negative number. The component will then generate records until the generate() function returns STOP (in this case, it is not considered an error). This works for transformations defined both in Java and CTL.

Capt. Eddie to ground control:

Note that in the last iteration when STOP is returned, no records will be sent to any of the output ports.

Example 17. Generating Variable Number of Records in CTL

integer total = randomInteger(1, 100);
integer counter = 0;

// Generates output record.
function integer generate() {
    counter++;

    if (counter > total) {
        printLog(info, "Terminating");
        return STOP;
    }

    if ((counter % 10) == 0) {
        printLog(info, "Skipping record # " + counter);
        return SKIP;
    }

    $out.0.value = "Record # " + counter;

    return OK;
}

Generating Random Values with Fixed Random Seed

Sometimes you need to generate random values in a graph and it should be possible to rerun it again returning the same values. This might be useful, for example, for tests.
The solution is to set the random seed for random number generator to some fixed value.
Example 18. Generating Random Values with Fixed Random Seed

function boolean init() {
    setRandomSeed(1231056256);
    return true;
}

function integer generate() {
    $out.0.value = randomInteger(0,199);

    return OK;
}

Best Practices

If Generator URL is used, we recommend users to explicitly specify Generator source charset.

See also

Trash
Common Properties of Components
Specific Attribute Types
Common Properties of Readers