AggregateKMeansRequest (Kinetica Java API 7.0.19.0 API)

java.lang.Object
- com.gpudb.protocol.AggregateKMeansRequest

All Implemented Interfaces:

org.apache.avro.generic.GenericContainer, org.apache.avro.generic.IndexedRecord
```
public class AggregateKMeansRequest
extends Object
implements org.apache.avro.generic.IndexedRecord
```
A set of parameters for GPUdb.aggregateKMeans(AggregateKMeansRequest).
This endpoint runs the k-means algorithm - a heuristic algorithm that attempts to do k-means clustering. An ideal k-means clustering algorithm selects k points such that the sum of the mean squared distances of each member of the set to the nearest of the k points is minimized. The k-means algorithm however does not necessarily produce such an ideal cluster. It begins with a randomly selected set of k points and then refines the location of the points iteratively and settles to a local minimum. Various parameters and options are provided to control the heuristic search.
NOTE: The Kinetica instance being accessed must be running a CUDA (GPU-based) build to service this request.

Nested Class Summary

Nested Classes
Modifier and Type Class and Description

static class AggregateKMeansRequest.Options
Optional parameters.

Nested Classes
Modifier and Type	Class and Description
`static class`	`AggregateKMeansRequest.Options` Optional parameters.

Constructor Summary

Constructors
Constructor and Description
`AggregateKMeansRequest()` Constructs an AggregateKMeansRequest object with default parameters.
`AggregateKMeansRequest(String tableName, List<String> columnNames, int k, double tolerance, Map<String,String> options)` Constructs an AggregateKMeansRequest object with the specified parameters.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`boolean`	`equals(Object obj)`
`Object`	`get(int index)` This method supports the Avro framework and is not intended to be called directly by the user.
`static org.apache.avro.Schema`	`getClassSchema()` This method supports the Avro framework and is not intended to be called directly by the user.
`List<String>`	`getColumnNames()`
`int`	`getK()`
`Map<String,String>`	`getOptions()`
`org.apache.avro.Schema`	`getSchema()` This method supports the Avro framework and is not intended to be called directly by the user.
`String`	`getTableName()`
`double`	`getTolerance()`
`int`	`hashCode()`
`void`	`put(int index, Object value)` This method supports the Avro framework and is not intended to be called directly by the user.
`AggregateKMeansRequest`	`setColumnNames(List<String> columnNames)`
`AggregateKMeansRequest`	`setK(int k)`
`AggregateKMeansRequest`	`setOptions(Map<String,String> options)`
`AggregateKMeansRequest`	`setTableName(String tableName)`
`AggregateKMeansRequest`	`setTolerance(double tolerance)`
`String`	`toString()`

Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - AggregateKMeansRequest
```
public AggregateKMeansRequest()
```
    Constructs an AggregateKMeansRequest object with default parameters.
  - AggregateKMeansRequest
```
public AggregateKMeansRequest(String tableName,
                              List<String> columnNames,
                              int k,
                              double tolerance,
                              Map<String,String> options)
```
    Constructs an AggregateKMeansRequest object with the specified parameters.
    Parameters:
    
    tableName - Name of the table on which the operation will be performed. Must be an existing table or collection.
    
    columnNames - List of column names on which the operation would be performed. If n columns are provided then each of the k result points will have n dimensions corresponding to the n columns.
    
    k - The number of mean points to be determined by the algorithm.
    
    tolerance - Stop iterating when the distances between successive points is less than the given tolerance.
    options - Optional parameters.
    
    WHITEN: When set to 1 each of the columns is first normalized by its stdv - default is not to whiten.
    MAX_ITERS: Number of times to try to hit the tolerance limit before giving up - default is 10.
    NUM_TRIES: Number of times to run the k-means algorithm with a different randomly selected starting points - helps avoid local minimum. Default is 1.
    The default value is an empty Map.
- Method Detail
  - 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.
  - getTableName
```
public String getTableName()
```
    Returns:
    
    Name of the table on which the operation will be performed. Must be an existing table or collection.
  - setTableName
```
public AggregateKMeansRequest setTableName(String tableName)
```
    Parameters:
    
    tableName - Name of the table on which the operation will be performed. Must be an existing table or collection.
    
    Returns:
    
    this to mimic the builder pattern.
  - getColumnNames
```
public List<String> getColumnNames()
```
    Returns:
    
    List of column names on which the operation would be performed. If n columns are provided then each of the k result points will have n dimensions corresponding to the n columns.
  - setColumnNames
```
public AggregateKMeansRequest setColumnNames(List<String> columnNames)
```
    Parameters:
    
    columnNames - List of column names on which the operation would be performed. If n columns are provided then each of the k result points will have n dimensions corresponding to the n columns.
    
    Returns:
    
    this to mimic the builder pattern.
  - getK
```
public int getK()
```
    Returns:
    
    The number of mean points to be determined by the algorithm.
  - setK
```
public AggregateKMeansRequest setK(int k)
```
    Parameters:
    
    k - The number of mean points to be determined by the algorithm.
    
    Returns:
    
    this to mimic the builder pattern.
  - getTolerance
```
public double getTolerance()
```
    Returns:
    
    Stop iterating when the distances between successive points is less than the given tolerance.
  - setTolerance
```
public AggregateKMeansRequest setTolerance(double tolerance)
```
    Parameters:
    
    tolerance - Stop iterating when the distances between successive points is less than the given tolerance.
    
    Returns:
    
    this to mimic the builder pattern.
  - getOptions
```
public Map<String,String> getOptions()
```
    Returns:
    Optional parameters.
    
    WHITEN: When set to 1 each of the columns is first normalized by its stdv - default is not to whiten.
    MAX_ITERS: Number of times to try to hit the tolerance limit before giving up - default is 10.
    NUM_TRIES: Number of times to run the k-means algorithm with a different randomly selected starting points - helps avoid local minimum. Default is 1.
    The default value is an empty Map.
  - setOptions
```
public AggregateKMeansRequest setOptions(Map<String,String> options)
```
    Parameters:
    options - Optional parameters.
    
    WHITEN: When set to 1 each of the columns is first normalized by its stdv - default is not to whiten.
    MAX_ITERS: Number of times to try to hit the tolerance limit before giving up - default is 10.
    NUM_TRIES: Number of times to run the k-means algorithm with a different randomly selected starting points - helps avoid local minimum. Default is 1.
    The default value is an empty Map.
    Returns:
    
    this to 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:
    
    getSchema in interface org.apache.avro.generic.GenericContainer
    
    Returns:
    
    the schema object describing this class.
  - get
```
public Object get(int index)
```
    This method supports the Avro framework and is not intended to be called directly by the user.
    
    Specified by:
    
    get in interface org.apache.avro.generic.IndexedRecord
    
    Parameters:
    
    index - the position of the field to get
    
    Returns:
    
    value of the field with the given index.
    
    Throws:
    
    IndexOutOfBoundsException
  - put
```
public void put(int index,
                Object value)
```
    This method supports the Avro framework and is not intended to be called directly by the user.
    
    Specified by:
    
    put in interface org.apache.avro.generic.IndexedRecord
    
    Parameters:
    
    index - the position of the field to set
    
    value - the value to set
    
    Throws:
    
    IndexOutOfBoundsException
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object

Class AggregateKMeansRequest

Nested Class Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

AggregateKMeansRequest

AggregateKMeansRequest

Method Detail

getClassSchema

getTableName

setTableName

getColumnNames

setColumnNames

getK

setK

getTolerance

setTolerance

getOptions

setOptions

getSchema

get

put

equals

toString

hashCode