de.lmu.ifi.dbs.elki.index.vafile

Class VAFile<V extends NumberVector>

java.lang.Object

de.lmu.ifi.dbs.elki.index.AbstractIndex<O>

de.lmu.ifi.dbs.elki.index.AbstractRefiningIndex<V>

de.lmu.ifi.dbs.elki.index.vafile.VAFile<V>

Type Parameters:

V - Vector type

All Implemented Interfaces:

Index, KNNIndex<V>, RangeIndex<V>, Result

@Title(value="An approximation based data structure for similarity search")
@Reference(authors="Weber, R. and Blott, S.",
           title="An approximation based data structure for similarity search",
           booktitle="Report TR1997b, ETH Zentrum, Zurich, Switzerland",
           url="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.40.480&rep=rep1&type=pdf")
public class VAFile<V extends NumberVector>
extends AbstractRefiningIndex<V>
implements KNNIndex<V>, RangeIndex<V>

Vector-approximation file (VAFile) Reference:

Weber, R. and Blott, S.
An approximation based data structure for similarity search
in: Report TR1997b, ETH Zentrum, Zurich, Switzerland

Author:

Thomas Bernecker, Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	VAFile.Factory<V extends NumberVector> Index factory class.
class	VAFile.VAFileKNNQuery KNN query for this index.
class	VAFile.VAFileRangeQuery Range query for this index.

Nested classes/interfaces inherited from class de.lmu.ifi.dbs.elki.index.AbstractRefiningIndex

AbstractRefiningIndex.AbstractKNNQuery, AbstractRefiningIndex.AbstractRangeQuery

Field Summary

Fields

Modifier and Type	Field and Description
private static Logging	LOG Logging class.
(package private) int	pageSize Page size, for estimating the VA file size.
private int	partitions Number of partitions.
(package private) int	scans Number of scans we performed.
private double[][]	splitPositions Quantile grid we use.
private List<VectorApproximation>	vectorApprox Approximation index.

Fields inherited from class de.lmu.ifi.dbs.elki.index.AbstractIndex

relation

Constructor Summary

Constructors

Constructor and Description
VAFile(int pageSize, Relation<V> relation, int partitions) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
VectorApproximation	calculateApproximation(DBID id, V dv) Calculate the VA file position given the existing borders.
KNNQuery<V>	getKNNQuery(DistanceQuery<V> distanceQuery, Object... hints) Get a KNN query object for the given distance query and k.
Logging	getLogger() Get the class logger.
String	getLongName() A "pretty" name for the result, for use in titles, captions and menus.
RangeQuery<V>	getRangeQuery(DistanceQuery<V> distanceQuery, Object... hints) Get a range query object for the given distance query and k.
long	getScannedPages() Get the number of scanned bytes.
String	getShortName() A short name for the result, useful for file names.
void	initialize() Initialize the index.
void	logStatistics() Send statistics to the logger, if enabled.
void	setPartitions(Relation<V> relation) Initialize the data set grid by computing quantiles.

Methods inherited from class de.lmu.ifi.dbs.elki.index.AbstractRefiningIndex

countRefinements, refine

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

LOG

private static final Logging LOG

Logging class.

vectorApprox

private List<VectorApproximation> vectorApprox

Approximation index.

partitions

private int partitions

Number of partitions.

splitPositions

private double[][] splitPositions

Quantile grid we use.

pageSize

int pageSize

Page size, for estimating the VA file size.

scans

int scans

Number of scans we performed.

Constructor Detail

VAFile

public VAFile(int pageSize,
      Relation<V> relation,
      int partitions)

Constructor.

Parameters:

pageSize - Page size of simulated index

relation - Relation to index

partitions - Number of partitions for each dimension.

Method Detail

initialize

public void initialize()

Description copied from interface: Index

Initialize the index. For static indexes, this is the moment the index is bulk loaded.

Specified by:

initialize in interface Index

setPartitions

public void setPartitions(Relation<V> relation)
                   throws IllegalArgumentException

Initialize the data set grid by computing quantiles.

Parameters:

relation - Data relation

Throws:

IllegalArgumentException

calculateApproximation

public VectorApproximation calculateApproximation(DBID id,
                                         V dv)

Calculate the VA file position given the existing borders.

Parameters:

id - Object ID

dv - Data vector

Returns:

Vector approximation

getScannedPages

public long getScannedPages()

Get the number of scanned bytes.

Returns:

Number of scanned bytes.

getLogger

public Logging getLogger()

Description copied from class: AbstractRefiningIndex

Get the class logger.

Specified by:

getLogger in class AbstractRefiningIndex<V extends NumberVector>

Returns:

Logger

logStatistics

public void logStatistics()

Description copied from interface: Index

Send statistics to the logger, if enabled. Note: you must have set the logging level appropriately before initializing the index! Otherwise, the index might not have collected the desired statistics.

Specified by:

logStatistics in interface Index

Overrides:

logStatistics in class AbstractRefiningIndex<V extends NumberVector>

getLongName

public String getLongName()

Description copied from interface: Result

A "pretty" name for the result, for use in titles, captions and menus.

Specified by:

getLongName in interface Result

Specified by:

getLongName in class AbstractIndex<V extends NumberVector>

Returns:

result name

getShortName

public String getShortName()

Description copied from interface: Result

A short name for the result, useful for file names.

Specified by:

getShortName in interface Result

Specified by:

getShortName in class AbstractIndex<V extends NumberVector>

Returns:

result name

getKNNQuery

public KNNQuery<V> getKNNQuery(DistanceQuery<V> distanceQuery,
                      Object... hints)

Description copied from interface: KNNIndex

Get a KNN query object for the given distance query and k. This function MAY return null, when the given distance is not supported!

Specified by:

getKNNQuery in interface KNNIndex<V extends NumberVector>

Parameters:

distanceQuery - Distance query

hints - Hints for the optimizer

Returns:

KNN Query object or null

getRangeQuery

public RangeQuery<V> getRangeQuery(DistanceQuery<V> distanceQuery,
                          Object... hints)

Description copied from interface: RangeIndex

Get a range query object for the given distance query and k. This function MAY return null, when the given distance is not supported!

Specified by:

getRangeQuery in interface RangeIndex<V extends NumberVector>

Parameters:

distanceQuery - Distance query

hints - Hints for the optimizer

Returns:

KNN Query object or null