com.pervasive.datarush.operators.scripting

Class RunJavaScript

java.lang.Object

com.pervasive.datarush.operators.AbstractLogicalOperator

com.pervasive.datarush.operators.StreamingOperator

com.pervasive.datarush.operators.ExecutableOperator

com.pervasive.datarush.operators.AbstractExecutableRecordPipeline

com.pervasive.datarush.operators.scripting.RunJavaScript

All Implemented Interfaces:

LogicalOperator, PipelineOperator<RecordPort>, RecordPipelineOperator

public class RunJavaScript
extends AbstractExecutableRecordPipeline

Processes rows using user-defined scripts written in JavaScript. The Rhino JavaScript engine is used to compile and execute the scripts.

The execution of the operator is as follows:

1. Compile all scripts
2. Bind input fields into the script's context. Input field names may have to be transformed to valid script variable names.
3. Run the beforeFirstRecordScript
4. For every row of input:
   1. Move data from input ports to script context
   2. Run the onEveryRecordScript
   3. Move data from script context to output ports
5. Run the afterLastRecordScript

Binding and retrieval are done using the names given to the input and output fields via their associated types. Native JavaScript types are supported where possible.

Note that this operator supports running in a distributed context, whether that be locally partitioned or within a cluster. Each instance of the operator executes the above operation sequence. This implies that the before and after scripts only affect the scripting environment within which they are run. The environments are not shared across operator instances.

By default, the highest level of optimization is used for compiling the scripts. This will provide the most efficient and highest performing script execution. Setting the optimization level to -1 turns on interpreted mode, disabling the performance gains of compiled scripts. There should never be a need to lower the optimization level. However, compiled scripts can type variables differently at times. If this causes an issues, use interpreted mode by setting the optimization level to -1.

By default, the JavaScript language version is set to version 1.8. As of this writing, this was the highest language version supported by the Rhino engine. Set the language version lower to disable newer language features as desired.

Field Summary

Fields inherited from class com.pervasive.datarush.operators.AbstractExecutableRecordPipeline

input, output

Constructor Summary

Constructors

Constructor and Description
RunJavaScript()

Method Summary

Modifier and Type	Method and Description
static String[]	compile(Map<String,Object> variables, String... scriptSources) Compile the given snippets of JavaScript code and capture any errors or warnings that occur.
static String	compile(String scriptSource) Compile the given snippet of JavaScript and capture any warnings or errors.
protected void	computeMetadata(StreamingMetadataContext ctx) Implementations must adhere to the following contracts
protected void	execute(ExecutionContext ctx) Executes the operator.
String	getAfterLastRecordScript()
String	getBeforeFirstRecordScript()
boolean	getEnforceType()
static String	getIdentifierRegex() Function to return a Regular Expression string that can be used to identify a valid JS identifier.
int	getLanguageVersion()
String	getOnEveryRecordScript()
int	getOptimizationLevel()
RecordTokenType	getOutputType()
Map<String,Object>	getVariables()
void	setAfterLastRecordScript(String afterLastRecordScript)
void	setBeforeFirstRecordScript(String beforeFirstRecordScript)
void	setEnforceType(boolean enforceType)
void	setLanguageVersion(int languageVersion)
void	setOnEveryRecordScript(String scriptText)
void	setOptimizationLevel(int optimizationLevel)
void	setOutputType(RecordTokenType outputType)
void	setVariables(Map<String,Object> variables)
static String	validateFieldName(int position, String fldName) Function to ensure an input/output field name conforms to JS variable identifier requirements.

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

getInput, getOutput

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

RunJavaScript

public RunJavaScript()

Method Detail

getOnEveryRecordScript

public String getOnEveryRecordScript()

setOnEveryRecordScript

public void setOnEveryRecordScript(String scriptText)

getOptimizationLevel

public int getOptimizationLevel()

setOptimizationLevel

public void setOptimizationLevel(int optimizationLevel)

getLanguageVersion

public int getLanguageVersion()

setLanguageVersion

public void setLanguageVersion(int languageVersion)

getOutputType

public RecordTokenType getOutputType()

setOutputType

public void setOutputType(RecordTokenType outputType)

getBeforeFirstRecordScript

public String getBeforeFirstRecordScript()

setBeforeFirstRecordScript

public void setBeforeFirstRecordScript(String beforeFirstRecordScript)

getAfterLastRecordScript

public String getAfterLastRecordScript()

setAfterLastRecordScript

public void setAfterLastRecordScript(String afterLastRecordScript)

setVariables

public void setVariables(Map<String,Object> variables)

getVariables

public Map<String,Object> getVariables()

getEnforceType

public boolean getEnforceType()

setEnforceType

public void setEnforceType(boolean enforceType)

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, 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, 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 and RecordPort#getSourceDataOrdering. 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.

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
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

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.

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

validateFieldName

public static String validateFieldName(int position,
                                       String fldName)

Function to ensure an input/output field name conforms to JS variable identifier requirements. If the field name is not valid, performs the following standardization on the field to produce a valid identifier. This is provided as a convenience for proper identifier formatting within scripts. Input and output schemas set on this operator undergo name validation so this is a mechanism that can be used to ensure identifier referencing is consistent.

Parameters:

position - the ordinal position of the field in the source/target schema - may be needed to disambiguate field names after character substitution takes place.

fldName - the name of the field being validated

Returns:

a JS compliant identifier

getIdentifierRegex

public static String getIdentifierRegex()

Function to return a Regular Expression string that can be used to identify a valid JS identifier. The string returned here is used internally for the validateFieldName function.

Returns:

the Regular Expression string used to identify a JS compliant identifier

compile

public static String compile(String scriptSource)

Compile the given snippet of JavaScript and capture any warnings or errors. The detailed information about the warnings or errors will be contained in the returned string.

Parameters:

scriptSource - String containing the script to compile

Returns:

a string containing any compiler warnings or errors, may be null or empty

compile

public static String[] compile(Map<String,Object> variables,
                               String... scriptSources)

Compile the given snippets of JavaScript code and capture any errors or warnings that occur. Detailed information about warnings or errors are contained in the array of output messages. Each output message corresponds in order to the input script.

The input variables are set into a JavaScript scope. The scope is used when evaluating each script. Set up the variables that need to be defined for the given scripts. The values can be default values allowing a simple evaluation of the scripts to catch warning and error messages.

Parameters:

variables - initial settings of input variables used by the given scripts

scriptSources - sources of scripts to compile and evaluate

Returns:

output messages resultant from evaluating each input script