java.lang.Object
- com.pervasive.datarush.operators.AbstractLogicalOperator
- - com.pervasive.datarush.operators.CompositeOperator
  - - com.pervasive.datarush.analytics.stats.SummaryStatistics

All Implemented Interfaces:

LogicalOperator, RecordSinkOperator, SinkOperator<RecordPort>
```
public final class SummaryStatistics
extends CompositeOperator
implements RecordSinkOperator
```
Discovers various metrics of an input dataset, based on the configured detail level. The types of the fields, combined with the DetailLevel determine the set of metrics that are calculated.

See Also:

DetailLevel

Constructor Summary

Constructors
Constructor Description

SummaryStatistics()
Discover summary statistics.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`protected void`	`compose(CompositionContext ctx)`	Compose the body of this operator.
`DetailLevel`	`getDetailLevel()`	Returns the detail level that we use to compute statistics.
`List<String>`	`getIncludedFields()`	Gets the fields from the input dataset for which we are collecting statistics.
`RecordPort`	`getInput()`	Returns an input port for the input dataset.
`PMMLPort`	`getOutput()`	Returns an output port that will produce a `PMMLSummaryStatisticsModel`.
`List<BigDecimal>`	`getQuantilesToCalculate()`	Gets the `quantiles` to calculate for each numeric field.
`int`	`getRangeCount()`	Returns the number of `intervalCounts` to calculate for each numeric field.
`int`	`getShowTopHowMany()`	Provides a cap on the number of `valueCounts` to calculate.
`boolean`	`isFewDistinctValuesHint()`	Returns a hint as to whether there are expected to be a small number of distinct values.
`void`	`setDetailLevel(DetailLevel detailLevel)`	Sets the detail level that we use to compute statistics.
`void`	`setFewDistinctValuesHint(boolean fewDistinctValuesHint)`	Sets a hint as to whether there are expected to be a small number of distinct values.
`void`	`setIncludedFields(List<String> includedFields)`	Sets the fields from the input dataset for which we are collecting statistics.
`void`	`setQuantilesToCalculate(List<BigDecimal> quantilesToCalculate)`	Sets the `quantiles` to calculate for each numeric field.
`void`	`setRangeCount(int rangeCount)`	Sets the number of `intervalCounts` to calculate for each numeric field.
`void`	`setShowTopHowMany(int showTopHowMany)`	Sets a cap on the number of `valueCounts` to calculate.

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
  - SummaryStatistics
```
public SummaryStatistics()
```
    Discover summary statistics. By default we discover singlePass statistics; configure detailLevel to provide more or less detail.
- Method Detail
  - getInput
```
public RecordPort getInput()
```
    Returns an input port for the input dataset. This dataset is used to build the summary model.
    
    Specified by:
    
    getInput in interface RecordSinkOperator
    
    Specified by:
    
    getInput in interface SinkOperator<RecordPort>
    
    Returns:
    
    an input port for the input dataset
  - getOutput
```
public PMMLPort getOutput()
```
    Returns an output port that will produce a PMMLSummaryStatisticsModel.
    
    Returns:
    
    an output port that will produce a PMMLSummaryStatisticsModel.
  - getDetailLevel
```
public DetailLevel getDetailLevel()
```
    Returns the detail level that we use to compute statistics. The default value is DetailLevel.SINGLE_PASS_ONLY.
    
    Returns:
    
    the detail level
  - setDetailLevel
```
public void setDetailLevel(DetailLevel detailLevel)
```
    Sets the detail level that we use to compute statistics. The default value is DetailLevel.SINGLE_PASS_ONLY.
    
    Parameters:
    
    detailLevel - the detail level
  - getShowTopHowMany
```
public int getShowTopHowMany()
```
    Provides a cap on the number of valueCounts to calculate. The default is 25. Memory usage is proportional to the number of distinct values; thus only the top n values are calculated in order to avoid excessive memory consumption in the event that the number of distinct values for a given field is large. This setting is ignored if detail level is not DetailLevel.MULTI_PASS.
    
    Returns:
    
    the cap the number of valueCounts to calculate.
  - setShowTopHowMany
```
public void setShowTopHowMany(int showTopHowMany)
```
    Sets a cap on the number of valueCounts to calculate. The default is 25. Memory usage is proportional to the number of distinct values; thus only the top n values are calculated in order to avoid excessive memory consumption in the event that the number of distinct values for a given field is large. This setting is ignored if detail level is not DetailLevel.MULTI_PASS.
    
    Parameters:
    
    showTopHowMany - the cap the number of valueCounts to calculate.
  - getRangeCount
```
public int getRangeCount()
```
    Returns the number of intervalCounts to calculate for each numeric field. The default value is 10. This setting is ignored if detail level is not DetailLevel.MULTI_PASS.
    
    Returns:
    
    the number of intervalCounts to calculate for each numeric field.
  - setRangeCount
```
public void setRangeCount(int rangeCount)
```
    Sets the number of intervalCounts to calculate for each numeric field. The default value is 10. This setting is ignored if detail level is not DetailLevel.MULTI_PASS.
    
    Parameters:
    
    rangeCount - the number of intervalCounts to calculate for each numeric field.
  - getQuantilesToCalculate
```
public List<BigDecimal> getQuantilesToCalculate()
```
    Gets the quantiles to calculate for each numeric field. By default this is 0.25, 0.50, and 0.75 (the 25th, 50th, and 75th percentiles). This setting is ignored if detail level is not DetailLevel.MULTI_PASS.
    
    Returns:
    
    the quantiles to calculate for each numeric field.
  - setQuantilesToCalculate
```
public void setQuantilesToCalculate(List<BigDecimal> quantilesToCalculate)
```
    Sets the quantiles to calculate for each numeric field. By default this is 0.25, 0.50, and 0.75 (the 25th, 50th, and 75th percentiles). This setting is ignored if detail level is not DetailLevel.MULTI_PASS.
    
    Parameters:
    
    quantilesToCalculate - the quantiles to calculate for each numeric field.
  - getIncludedFields
```
public List<String> getIncludedFields()
```
    Gets the fields from the input dataset for which we are collecting statistics. The default value of "empty list" implies "all fields".
    
    Returns:
    
    the fields from the input dataset for which we are collecting statistics.
  - setIncludedFields
```
public void setIncludedFields(List<String> includedFields)
```
    Sets the fields from the input dataset for which we are collecting statistics. The default value of "empty list" implies "all fields".
    
    Parameters:
    
    includedFields - the fields from the input dataset for which we are collecting statistics.
  - isFewDistinctValuesHint
```
public boolean isFewDistinctValuesHint()
```
    Returns a hint as to whether there are expected to be a small number of distinct values. If not, we eagerly sort each column up-front and perform a parallelized computation of quantiles and frequent items. This setting is ignored if detail level is not DetailLevel.MULTI_PASS.
    
    Returns:
    
    whether few distinct values are expected
  - setFewDistinctValuesHint
```
public void setFewDistinctValuesHint(boolean fewDistinctValuesHint)
```
    Sets a hint as to whether there are expected to be a small number of distinct values. If not, we eagerly sort each column up-front and perform a parallelized computation of quantiles and frequent items. This setting is ignored if detail level is not DetailLevel.MULTI_PASS.
    
    Parameters:
    
    fewDistinctValuesHint - whether few distinct values are expected
  - compose
```
protected void compose(CompositionContext ctx)
```
    Description copied from class: CompositeOperator
    Compose the body of this operator. Implementations should do the following:
    
    Perform any validation of configuration, input types, etc
    
    Instantiate and configure sub-operators, adding them to the provided context via the method OperatorComposable.add(O)
    
    Create necessary connections via the method OperatorComposable.connect(P, P). This includes connections from the composite's input ports to sub-operators, connections between sub-operators, and connections from sub-operators output ports to the composite's output ports
    Specified by:
    
    compose in class CompositeOperator
    
    Parameters:
    
    ctx - the context

Class SummaryStatistics

Constructor Summary

Method Summary

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

Methods inherited from class java.lang.Object

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

Constructor Detail

SummaryStatistics

Method Detail

getInput

getOutput

getDetailLevel

setDetailLevel

getShowTopHowMany

setShowTopHowMany

getRangeCount

setRangeCount

getQuantilesToCalculate

setQuantilesToCalculate

getIncludedFields

setIncludedFields

isFewDistinctValuesHint

setFewDistinctValuesHint

compose