- java.lang.Object
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- com.pervasive.datarush.operators.AbstractLogicalOperator
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- com.pervasive.datarush.operators.StreamingOperator
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- com.pervasive.datarush.operators.ExecutableOperator
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- com.pervasive.datarush.operators.join.CrossJoin
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- All Implemented Interfaces:
LogicalOperator
public final class CrossJoin extends ExecutableOperator
Produce the cartesian product of two sets of records. The output is typed using the merge of the two input types; if the right type contains a field already named in the left type, it will be renamed to avoid collision. SeeTypeUtil.merge(RecordTokenType...)
for details on the renaming process.To generate pairs, the right-hand data is temporarily stored to disk for multiple passes. The left-hand data is read into memory in chunks, which are then used to generate a full set of pairs with the iterable right-hand data. This process is repeated until the left-hand data is exhausted.
No guarantee is made in respect to the ordering of the output data.
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Constructor Summary
Constructors Constructor Description CrossJoin()
Performs a cross join between two inputs
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description protected void
computeMetadata(StreamingMetadataContext ctx)
Implementations must adhere to the following contractsprotected void
execute(ExecutionContext ctx)
The controller handles chunking the LHS data into reasonable chunks that can be loaded into memory.int
getBufferRows()
Gets the size (in rows) of the memory buffer used to generate output records.RecordPort
getLeftInput()
Returns the left input portRecordPort
getOutput()
Returns the input portRecordPort
getRightInput()
Returns the right input portvoid
setBufferRows(int rows)
Sets the size (in rows) of the memory buffer used to generate output record.-
Methods inherited from class com.pervasive.datarush.operators.ExecutableOperator
cloneForExecution, getNumInputCopies, getPortSettings, handleInactiveOutput
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Methods inherited from class com.pervasive.datarush.operators.AbstractLogicalOperator
disableParallelism, getInputPorts, getOutputPorts, newInput, newInput, newOutput, newRecordInput, newRecordInput, newRecordOutput, notifyError
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Method Detail
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getLeftInput
public RecordPort getLeftInput()
Returns the left input port- Returns:
- the left input port
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getRightInput
public RecordPort getRightInput()
Returns the right input port- Returns:
- the right input port
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getOutput
public RecordPort getOutput()
Returns the input port- Returns:
- the output port
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setBufferRows
public void setBufferRows(int rows)
Sets the size (in rows) of the memory buffer used to generate output record. Larger values can increase performance due to decreased intermediate file buffering.- Parameters:
rows
- number of rows to store in memory buffer
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getBufferRows
public int getBufferRows()
Gets the size (in rows) of the memory buffer used to generate output records.- Returns:
- the number of rows allowed in the memory buffer
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computeMetadata
protected void computeMetadata(StreamingMetadataContext ctx)
Description copied from class:StreamingOperator
Implementations must adhere to the following contractsGeneral
Regardless of input ports/output port types, all implementations must do the following:- Validation. Validation of configuration should always be performed first.
- Declare parallelizability.. Implementations must declare parallelizability by calling
StreamingMetadataContext.parallelize(ParallelismStrategy)
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Input record ports
Implementations with input record ports must declare the following:- Required data ordering: Implementations that have data ordering requirements must declare them by calling
- Required data distribution (only applies to parallelizable operators): Implementations that have data distribution requirements must declare them by calling
RecordPort#setRequiredDataOrdering
, otherwise data may arrive in any order.RecordPort#setRequiredDataDistribution
, otherwise data will arrive in anunspecified partial distribution
.RecordPort#getSourceDataDistribution
andRecordPort#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:- Type: Implementations must declare their output type by calling
RecordPort#setType
.
- Output data ordering: Implementations that can make guarantees as to their output
ordering may do so by calling
RecordPort#setOutputDataOrdering
- 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
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:- Merge handler: Model reducers must declare a merge handler by
calling
AbstractModelPort#setMergeHandler
.
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:- pmmlModelSpec: Implementations must declare the PMML model spec
by calling
PMMLPort.setPMMLModelSpec
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- Specified by:
computeMetadata
in classStreamingOperator
- Parameters:
ctx
- the context
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execute
protected void execute(ExecutionContext ctx)
The controller handles chunking the LHS data into reasonable chunks that can be loaded into memory. The LHS chunks are then joined (cartesian product) against an iteration of the RHS data. Having to use an application graph and export many ports from that graph, the partitioning has to be handled directly. Subgraphs are run until the LHS data is exhausted.- Specified by:
execute
in classExecutableOperator
- Parameters:
ctx
- context in which to lookup physical ports bound to logical ports
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