Package com.gpudb.protocol
Class AggregateKMeansResponse
java.lang.Object
com.gpudb.protocol.AggregateKMeansResponse
All Implemented Interfaces:
org.apache.avro.generic.GenericContainer, org.apache.avro.generic.IndexedRecordpublic class AggregateKMeansResponse extends Object implements org.apache.avro.generic.IndexedRecord
A set of results returned by
GPUdb.aggregateKMeans.Nested Class Summary
Nested ClassesModifier and TypeClassDescriptionstatic final classA set of string constants for theAggregateKMeansResponseparameterinfo.Constructor Summary
ConstructorsConstructorDescriptionConstructs an AggregateKMeansResponse object with default parameters.Method Summary
Modifier and TypeMethodDescriptionbooleanget(int index) This method supports the Avro framework and is not intended to be called directly by the user.static org.apache.avro.SchemaThis method supports the Avro framework and is not intended to be called directly by the user.longgetCount()The total count of all the clusters - will be the size of the input table.The number of elements in the cluster closest the corresponding k-means values.getInfo()Additional information.getMeans()The k-mean values found.intThe number of iterations the algorithm executed before it quit.doubleThe sum of all the rms_dists - the value the k-means algorithm is attempting to minimize.The root mean squared distance of the elements in the cluster for each of the k-means values.org.apache.avro.SchemaThis method supports the Avro framework and is not intended to be called directly by the user.doubleThe distance between the last two iterations of the algorithm before it quit.inthashCode()voidThis method supports the Avro framework and is not intended to be called directly by the user.setCount(long count) The total count of all the clusters - will be the size of the input table.The number of elements in the cluster closest the corresponding k-means values.Additional information.The k-mean values found.setNumIters(int numIters) The number of iterations the algorithm executed before it quit.setRmsDist(double rmsDist) The sum of all the rms_dists - the value the k-means algorithm is attempting to minimize.setRmsDists(List<Double> rmsDists) The root mean squared distance of the elements in the cluster for each of the k-means values.setTolerance(double tolerance) The distance between the last two iterations of the algorithm before it quit.toString()
Method Details
getClassSchema
public static org.apache.avro.Schema getClassSchema()This method supports the Avro framework and is not intended to be called directly by the user.Returns:The schema for the class.setMeans
The k-mean values found.Parameters:means- The new value formeans.Returns:thisto mimic the builder pattern.setCounts
The number of elements in the cluster closest the corresponding k-means values.Parameters:counts- The new value forcounts.Returns:thisto mimic the builder pattern.setRmsDists
The root mean squared distance of the elements in the cluster for each of the k-means values.Parameters:rmsDists- The new value forrmsDists.Returns:thisto mimic the builder pattern.getCount
public long getCount()The total count of all the clusters - will be the size of the input table.Returns:The current value ofcount.setCount
The total count of all the clusters - will be the size of the input table.Parameters:count- The new value forcount.Returns:thisto mimic the builder pattern.getRmsDist
public double getRmsDist()The sum of all the rms_dists - the value the k-means algorithm is attempting to minimize.Returns:The current value ofrmsDist.setRmsDist
The sum of all the rms_dists - the value the k-means algorithm is attempting to minimize.Parameters:rmsDist- The new value forrmsDist.Returns:thisto mimic the builder pattern.getTolerance
public double getTolerance()The distance between the last two iterations of the algorithm before it quit.Returns:The current value oftolerance.setTolerance
The distance between the last two iterations of the algorithm before it quit.Parameters:tolerance- The new value fortolerance.Returns:thisto mimic the builder pattern.getNumIters
public int getNumIters()The number of iterations the algorithm executed before it quit.Returns:The current value ofnumIters.setNumIters
The number of iterations the algorithm executed before it quit.Parameters:numIters- The new value fornumIters.Returns:thisto mimic the builder pattern.setInfo
Additional information.QUALIFIED_RESULT_TABLE_NAME: The fully qualified name of the result table (i.e. including the schema) used to store the results.
Map.Parameters:info- The new value forinfo.Returns:thisto mimic the builder pattern.getSchema
public org.apache.avro.Schema getSchema()This method supports the Avro framework and is not intended to be called directly by the user.Specified by:getSchemain interfaceorg.apache.avro.generic.GenericContainerReturns:The schema object describing this class.get
This method supports the Avro framework and is not intended to be called directly by the user.Specified by:getin interfaceorg.apache.avro.generic.IndexedRecordParameters:index- the position of the field to getReturns:value of the field with the given index.Throws:put
This method supports the Avro framework and is not intended to be called directly by the user.Specified by:putin interfaceorg.apache.avro.generic.IndexedRecordParameters:index- the position of the field to setvalue- the value to setThrows: