Module datarush.library
Class PartialStaticDataDistribution
- java.lang.Object
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- com.pervasive.datarush.ports.record.DataDistribution
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- com.pervasive.datarush.ports.record.PartialDataDistribution
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- com.pervasive.datarush.ports.record.PartialStaticDataDistribution
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- Direct Known Subclasses:
BalancedDistribution,KeyDrivenDataDistribution,UnspecifiedPartialDistribution
public abstract class PartialStaticDataDistribution extends PartialDataDistribution
Base class for all distributions whose partitioning parameters are specified statically.- See Also:
DataDistribution
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Constructor Summary
Constructors Modifier Constructor Description protectedPartialStaticDataDistribution()Default constructor.
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Method Summary
All Methods Instance Methods Abstract Methods Concrete Methods Modifier and Type Method Description protected abstract PartitioningFunctiongetPartitioningFunction()Subclasses must override this method to provide the partitioning function to be usedprotected abstract booleanrequiresRepartitionFrom(PartialDataDistribution source)Subclasses must override this method to declare whether a repartition is required given the source distribution.protected booleansupportsLocalRepartition()Subclasses may override to indicate that they support a local repartition-
Methods inherited from class com.pervasive.datarush.ports.record.PartialDataDistribution
getGatherScheme
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Methods inherited from class com.pervasive.datarush.ports.record.DataDistribution
getAliases, remap, toString
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Method Detail
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supportsLocalRepartition
protected boolean supportsLocalRepartition()
Subclasses may override to indicate that they support a local repartition- Returns:
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getPartitioningFunction
protected abstract PartitioningFunction getPartitioningFunction()
Subclasses must override this method to provide the partitioning function to be used- Returns:
- a partition function
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requiresRepartitionFrom
protected abstract boolean requiresRepartitionFrom(PartialDataDistribution source)
Subclasses must override this method to declare whether a repartition is required given the source distribution. Implementations may err on the side of caution by always returning true but this may have an impact on performance.- Parameters:
source- the source distribution- Returns:
- true if a repartition is required, false if this data distribution matches what was specified.
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