com.pervasive.datarush.matching.block

Class GroupPairsSortedRows

java.lang.Object

com.pervasive.datarush.operators.AbstractLogicalOperator

com.pervasive.datarush.operators.StreamingOperator

com.pervasive.datarush.operators.ExecutableOperator

com.pervasive.datarush.matching.block.GroupPairsSortedRows

All Implemented Interfaces:

LogicalOperator

public class GroupPairsSortedRows
extends ExecutableOperator

Finds key groupings within the input key fields and, for each key group, generates all pairwise combinations of distinct rows in that group.

The output is similar to an inner join of the data against itself, except that only distinct combinations are generated. These combinations are useful for comparing rows that may be duplicates, and for mining association rules.

For example, given three rows A, B, C in a key group, a join would generate all nine of the combinations shown in the matrix below. For efficiency, this operator generates only 4, 7, and 8: just the "strictly upper triangular" entries marked with a * in the matrix:

 1  A with A  4* B with A  7* C with A
 2  A with B  5  B with B  8* C with B
 3  A with C  6  B with C  9  C with C
 

Combinations 1, 5, and 9 are omitted because they join a row with itself, and are thus not useful candidates when looking for duplicate rows or mining association rules.

Combinations 2, 3, and 6 are omitted because they are the same as combinations 4, 7, and 8 respectively, with field order reversed.

As with GroupSortedRows and JoinSortedRows, the input for this operator must be sorted so that values in the same key group are consecutive, and the output is sorted by the same key.

Field Summary

Fields

Modifier and Type	Field and Description
protected RecordPort	input The input control port.
protected String[]	keys

Constructor Summary

Constructors

Constructor and Description
GroupPairsSortedRows() Block records from a single source.

Method Summary

Methods

Modifier and Type	Method and Description
protected void	computeMetadata(StreamingMetadataContext ctx) Implementations must adhere to the following contracts
protected void	endOfData(boolean emptyInput) Called once at the end of run.
protected void	execute(ExecutionContext ctx) Executes the operator.
RecordPort	getInput()
String[]	getKeys()
String	getLeftFieldPattern() Gets the output naming pattern for fields on the left hand side of the pair.
protected int	getNumInputCopies(LogicalPort inputPort) May be overridden to specify that multiple input copies are needed for a given input port.
RecordPort	getOutput() Gets the record port providing the results of the pair generation.
String	getRightFieldPattern() Gets the output naming pattern for fields on the right hand side of the pair.
protected void	handleRow(boolean endOfGroup) Called once per input row.
protected RecordInput	nextKey(ExecutionContext ctx)
protected RecordInput	recordsIn(ExecutionContext ctx)
void	setKeys(String[] keys)
void	setLeftFieldPattern(String pattern) Sets the output naming pattern for fields on the left hand side of pairs.
void	setRightFieldPattern(String pattern) Sets the output naming pattern for fields on the right hand side of pairs.

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

cloneForExecution, 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

Field Detail

input

protected final RecordPort input

The input control port. Contains the an identifier that is unique per key group. A change in the input value signifies the end of a group.

keys

protected String[] keys

Constructor Detail

GroupPairsSortedRows

public GroupPairsSortedRows()

Block records from a single source. Records from the source will be blocked based on key sets and record pairs generated from these groups. Key fields must be identified before execution.

See Also:

setKeys(String[])

Method Detail

getOutput

public RecordPort getOutput()

Gets the record port providing the results of the pair generation.

Returns:

the output port for the operation

getLeftFieldPattern

public String getLeftFieldPattern()

Gets the output naming pattern for fields on the left hand side of the pair.

Returns:

the pattern for the left hand side field names in output.

setLeftFieldPattern

public void setLeftFieldPattern(String pattern)

Sets the output naming pattern for fields on the left hand side of pairs. This is used to ensure distinct names in the output pairs.

Parameters:

pattern - name pattern for the left hand side field names

getRightFieldPattern

public String getRightFieldPattern()

Gets the output naming pattern for fields on the right hand side of the pair.

Returns:

the pattern for the right hand side field names in output.

setRightFieldPattern

public void setRightFieldPattern(String pattern)

Sets the output naming pattern for fields on the right hand side of pairs. This is used to ensure distinct names in the output pairs.

Parameters:

pattern - name pattern for the eight hand side field names

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.

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.

Parameters:

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

handleRow

protected void handleRow(boolean endOfGroup)

Called once per input row. Aggregators must step to the next row of their inputs and handle group boundaries indicated by endOfGroup.

Parameters:

endOfGroup - true iff the input row is the last in the key group

endOfData

protected void endOfData(boolean emptyInput)

Called once at the end of run. Aggregators must step to the end of their inputs and push EOD on their outputs.

Parameters:

emptyInput - true iff handleRow was called zero times (no input rows to aggregate)

getInput

public RecordPort getInput()

getKeys

public String[] getKeys()

setKeys

public void setKeys(String[] keys)

recordsIn

protected final RecordInput recordsIn(ExecutionContext ctx)

nextKey

protected final RecordInput nextKey(ExecutionContext ctx)

getNumInputCopies

protected int getNumInputCopies(LogicalPort inputPort)

Description copied from class: ExecutableOperator

May be overridden to specify that multiple input copies are needed for a given input port. By default this is one. This can be used in rare cases when we must examine multiple positions in the same input stream.

Overrides:

getNumInputCopies in class ExecutableOperator

Parameters:

inputPort - the port

Returns:

the number of input copies for the port