Module datarush.library

Package com.pervasive.datarush.ports.record

Class RangePartitioningFunction

java.lang.Object

com.pervasive.datarush.ports.record.RangePartitioningFunction

All Implemented Interfaces:

PartitioningFunction

public final class RangePartitioningFunction
extends Object
implements PartitioningFunction

A partitioning function that partitions records of data based on specified ranges.

Nested Class Summary

Nested classes/interfaces inherited from interface com.pervasive.datarush.ports.record.PartitioningFunction

PartitioningFunction.Evaluator

Constructor Summary

Constructors

Constructor	Description
RangePartitioningFunction(String key, List<? extends ScalarToken> values)	Range partitions based on a single key
RangePartitioningFunction(List<RecordToken> values)	Range partitions based on multiple keys.

Method Summary

Modifier and Type	Method	Description
List<RecordToken>	getBoundaries()	Returns the boundaries to partition on
RecordTokenType	getBoundaryType()	Returns the boundary type determined by the widest type of all boundaries
PartitioningFunction.Evaluator	getEvaluator(PartitioningFunctionContext ctx)	Create an Evaluator bound to the specified context.
boolean	isEquivalentPartitioning(PartitioningFunction other)	Returns true iff, given a single row of input, this function is guaranteed to produce the same partitioning as the other function.
boolean	isFunctionOfInput()	Returns true iff, given two identical rows of input, this function will return the same value.
RangePartitioningFunction	remapFieldReferences(Map<String,String> oldToNewMapping)	Creates a new function, equivalent to the given function, but with all field references renamed according to the given mapping.
void	validateForType(RecordTokenType type)	Performs validation of the specified input type

Methods inherited from class java.lang.Object

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

Constructor Details

RangePartitioningFunction

public RangePartitioningFunction(String key,
 List<? extends ScalarToken> values)

Range partitions based on a single key

Parameters:

key - the key

values - the boundary values for the key

RangePartitioningFunction

public RangePartitioningFunction(List<RecordToken> values)

Range partitions based on multiple keys. The list of records correspond to each boundary and the elements in each record correspond to each key. All records must have the same names.

Parameters:

values - the values to partition on

Method Details

getBoundaries

public List<RecordToken> getBoundaries()

Returns the boundaries to partition on

Returns:

the boundaries

getBoundaryType

public RecordTokenType getBoundaryType()

Returns the boundary type determined by the widest type of all boundaries

Returns:

the boundary type

validateForType

public void validateForType(RecordTokenType type)

Description copied from interface: PartitioningFunction

Performs validation of the specified input type

Specified by:

validateForType in interface PartitioningFunction

Parameters:

type - the input type

getEvaluator

public PartitioningFunction.Evaluator getEvaluator(PartitioningFunctionContext ctx)

Description copied from interface: PartitioningFunction

Create an Evaluator bound to the specified context.

Specified by:

getEvaluator in interface PartitioningFunction

Parameters:

ctx - the partitioning context

Returns:

an Evaluator bound to the specified context.

isEquivalentPartitioning

public boolean isEquivalentPartitioning(PartitioningFunction other)

Description copied from interface: PartitioningFunction

Returns true iff, given a single row of input, this function is guaranteed to produce the same partitioning as the other function. A return of true thus implies the following:

both functions are deterministic

both function are stateless (not sensitive to previous values read or to input ordering)

In addition, in order to be consistent with PartitioningFunction.isFunctionOfInput(), this function must return false if PartitioningFunction.isFunctionOfInput() returns false.