com.pervasive.datarush.operators.source

Class GenerateRandom

java.lang.Object

com.pervasive.datarush.operators.AbstractLogicalOperator

com.pervasive.datarush.operators.StreamingOperator

com.pervasive.datarush.operators.ExecutableOperator

com.pervasive.datarush.operators.source.GenerateRandom

All Implemented Interfaces:

LogicalOperator, RecordSourceOperator, SourceOperator<RecordPort>

public final class GenerateRandom
extends ExecutableOperator
implements RecordSourceOperator

Generates rows of random data.

All field types except generic and object are supported.

The generated data for each field data type does not in general cover the full range of that type supported by the dataflow system, but does cover a range that any operator claiming to support that type should be able to handle.

• boolean: Either true or false
• binary: Between 1 and 2048 random bytes, with a uniform distribution of the number of bytes.
• char: ASCII characters 32-126 ("Valid Unicode" is not well defined)
• date: The range of days representable by a Date, +- 2^64 milliseconds from 1970-01-01, corresponding to +- about 292 million years.
• double: The range of Double excluding NaN and +-Inf. (NaN values can be generated by setting nullFraction > 0.0)
• float: The range of Float, excluding NaN and +-Inf. (NaN values can be generated by setting nullFraction > 0.0)
• int: The full range of Integer.
• long: The full range of a Java Long.
• numeric: The integer part is formed from 1 to 100 binary digits, corresponding to up to 31 decimal digits (2^100 - 1 = 1,267,650,600,228,229,401,496,703,205,375). This value is then divided by 10^scale, where the scale is 0 to 29, and made negative with a probability of 50%.
• string: Zero or more random ASCII characters (see also char data type). The string length is unlimited, but the probability decays exponentially, as 0.9^min_length: 10% are empty strings, 9% are 1 character long, 8.1% are two characters long, 7.29% are 3 characters long, etc.
• timestamp: The range of seconds is the range representable by a Timestamp, +- 2^64 milliseconds from 1970-01-01, corresponding to +- about 292 million years. The nanos range is 0 to 999999999. The time zone offset is a whole number of minute in the range -12:00 to +12:59 (the extra hour is for daylight savings).

Constructor Summary

Constructors

Constructor and Description
GenerateRandom() The default constructor.
GenerateRandom(RecordTokenType type, long rowCount) Creates a new instance of GenerateRandom, specifying the minimal set of required parameters.

Method Summary

Methods

Modifier and Type	Method and Description
protected void	computeMetadata(StreamingMetadataContext ctx) Implementations must adhere to the following contracts
protected void	execute(ExecutionContext ctx) Executes the operator.
double	getNullProbability() Gets the probability any given generated token will be null valued.
RecordPort	getOutput() Gets the record port providing the output data from the source.
RecordTokenType	getOutputType() Returns the data type of the generated values
long	getRowCount() Returns the number of values to generate
long	getSeed() Gets the seed for the random number generator.
void	setNullProbability(double nullProbability) Sets the probability any given generated token will be null valued.
void	setOutputType(RecordTokenType outputType) Sets the data type of the generated values
void	setRowCount(long rowCount) Sets the number of values to generate
void	setSeed(long seed) Sets the seed for the random number generator.

Methods inherited from class com.pervasive.datarush.operators.ExecutableOperator

cloneForExecution, getNumInputCopies, getPortSettings, handleInactiveOutput

Methods inherited from class com.pervasive.datarush.operators.AbstractLogicalOperator

disableParallelism, getInputPorts, getOutputPorts, newInput, newInput, newOutput, newRecordInput, newRecordInput, newRecordOutput, notifyError

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface com.pervasive.datarush.operators.LogicalOperator

disableParallelism, getInputPorts, getOutputPorts

Constructor Detail

GenerateRandom

public GenerateRandom()

The default constructor. Prior to graph compilation the following properties should be specified

• outputType
• rowCount

GenerateRandom

public GenerateRandom(RecordTokenType type,
              long rowCount)

Creates a new instance of GenerateRandom, specifying the minimal set of required parameters.

Parameters:

type - the output type

rowCount - the number of rows

Method Detail

getOutput

public RecordPort getOutput()

Description copied from interface: RecordSourceOperator

Gets the record port providing the output data from the source.

Specified by:

getOutput in interface RecordSourceOperator

Specified by:

getOutput in interface SourceOperator<RecordPort>

Returns:

the output port for the source

getSeed

public long getSeed()

Gets the seed for the random number generator.

Returns:

the seed for the random number generator

getNullProbability

public double getNullProbability()

Gets the probability any given generated token will be null valued.

Returns:

the probability any given generated token will be null valued

setSeed

public void setSeed(long seed)

Sets the seed for the random number generator.

Parameters:

seed - the seed for the random number generator

setNullProbability

public void setNullProbability(double nullProbability)

Sets the probability any given generated token will be null valued.

Parameters:

nullProbability - the probability any given generated token will be null valued

getOutputType

public RecordTokenType getOutputType()

Returns the data type of the generated values

Returns:

the data type of the generated values

setOutputType

public void setOutputType(RecordTokenType outputType)

Sets the data type of the generated values

Parameters:

outputType - the data type of the generated values

getRowCount

public long getRowCount()

Returns the number of values to generate

Returns:

the number of values to generate

setRowCount

public void setRowCount(long rowCount)

Sets the number of values to generate

Parameters:

rowCount - the number of values to generate

computeMetadata

protected void computeMetadata(StreamingMetadataContext ctx)

Description copied from class: StreamingOperator

Implementations must adhere to the following contracts

General

Regardless of input ports/output port types, all implementations must do the following:

1. Validation. Validation of configuration should always be performed first.
2. Declare parallelizability.. Implementations must declare parallelizability by calling StreamingMetadataContext.parallelize(ParallelismStrategy).

Input record ports

Implementations with input record ports must declare the following:

1. Required data ordering:
Implementations that have data ordering requirements must declare them by calling RecordPort.setRequiredDataOrdering(com.pervasive.datarush.operators.MetadataCalculationContext, com.pervasive.datarush.ports.record.DataOrdering), otherwise data may arrive in any order.
2. Required data distribution (only applies to parallelizable operators):
Implementations that have data distribution requirements must declare them by calling RecordPort.setRequiredDataDistribution(com.pervasive.datarush.operators.MetadataCalculationContext, com.pervasive.datarush.ports.record.DataDistribution), otherwise data will arrive in an unspecified partial distribution.

Note that if the upstream operator's output distribution/ordering is compatible with those required, we avoid a re-sort/re-distribution which is generally a very large savings from a performance standpoint. In addition, some operators may chose to query the upstream output distribution/ordering by calling RecordPort.getSourceDataDistribution(com.pervasive.datarush.operators.MetadataContext) and RecordPort.getSourceDataOrdering(com.pervasive.datarush.operators.MetadataContext). These should be viewed as a hints to help chose a more efficient algorithm. In such cases, though, operators must still declare data ordering and data distribution requirements; otherwise there is no guarantee that data will arrive sorted/distributed as required.

Output record ports

Implementations with output record ports must declare the following:

1. Type: Implementations must declare their output type by calling RecordPort.setType(com.pervasive.datarush.operators.MetadataCalculationContext, com.pervasive.datarush.types.RecordTokenType).

Implementations with output record ports may declare the following:

1. Output data ordering: Implementations that can make guarantees as to their output ordering may do so by calling RecordPort.setOutputDataOrdering(com.pervasive.datarush.operators.MetadataCalculationContext, com.pervasive.datarush.ports.record.DataOrdering)
2. Output data distribution (only applies to parallelizable operators): Implementations that can make guarantees as to their output distribution may do so by calling RecordPort.setOutputDataDistribution(com.pervasive.datarush.operators.MetadataCalculationContext, com.pervasive.datarush.ports.record.DataDistribution)

Note that both of these properties are optional; if unspecified, performance may suffer since the framework may unnecessarily re-sort/re-distributed the data.

Input model ports

In general, there is nothing special to declare for input model ports. Models are implicitly duplicated to all partitions when going from non-parallel to parallel operators. The case of a model going from a parallel to a non-parallel node is a special case of a "model reducer" operator. In the case of a model reducer, the downstream operator, must declare the following:

1. Merge handler: Model reducers must declare a merge handler by calling AbstractModelPort.setMergeHandler(com.pervasive.datarush.operators.MetadataCalculationContext, com.pervasive.datarush.ports.model.ModelMergeHandler<T>).

Note that MergeModel is a convenient, re-usable model reducer, parameterized with a merge-handler.

Output model ports

SimpleModelPort's have no associated metadata and therefore there is never any output metadata to declare. PMMLPort's, on the other hand, do have associated metadata. For all PMMLPorts, implementations must declare the following:

1. pmmlModelSpec: Implementations must declare the PMML model spec by calling PMMLPort.setPMMLModelSpec.

Specified by:

computeMetadata in class StreamingOperator

Parameters:

ctx - the context

execute

protected void execute(ExecutionContext ctx)

Description copied from class: ExecutableOperator

Executes the operator. Implementations should adhere to the following contracts:

1. Following execution, all input ports must be at end-of-data.
2. Following execution, all output ports must be at end-of-data.

Specified by:

execute in class ExecutableOperator

Parameters:

ctx - context in which to lookup physical ports bound to logical ports