de.lmu.ifi.dbs.elki.database

Class QueryUtil

java.lang.Object

de.lmu.ifi.dbs.elki.database.QueryUtil

public final class QueryUtil
extends java.lang.Object

Static class with utilities related to querying a database.

Since:

0.4.0

Author:

Erich Schubert

Constructor Summary

Constructors

Modifier	Constructor and Description
private	QueryUtil() Private constructor.

Method Summary

Modifier and Type	Method and Description
static <O> DistanceQuery<O>	getDistanceQuery(Database database, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a distance query for a given distance function, automatically choosing a relation.
static <O> KNNQuery<O>	getKNNQuery(Database database, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a KNN query object for the given distance function.
static <O> KNNQuery<O>	getKNNQuery(Relation<O> relation, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a KNN query object for the given distance function.
static <O> KNNQuery<O>	getLinearScanKNNQuery(DistanceQuery<O> distanceQuery) Get a linear scan query for the given distance query.
static <O> RangeQuery<O>	getLinearScanRangeQuery(DistanceQuery<O> distanceQuery) Get a linear scan query for the given distance query.
static <O> RangeQuery<O>	getLinearScanSimilarityRangeQuery(SimilarityQuery<O> simQuery) Get a linear scan query for the given similarity query.
static <O> RangeQuery<O>	getRangeQuery(Database database, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a range query object for the given distance function for radius-based neighbor search.
static <O> RangeQuery<O>	getRangeQuery(Relation<O> relation, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a range query object for the given distance function for radius-based neighbor search.
static <O> RKNNQuery<O>	getRKNNQuery(Relation<O> relation, DistanceFunction<? super O> distanceFunction, java.lang.Object... hints) Get a rKNN query object for the given distance function.
static <O> SimilarityQuery<O>	getSimilarityQuery(Database database, SimilarityFunction<? super O> similarityFunction, java.lang.Object... hints) Get a similarity query, automatically choosing a relation.

Methods inherited from class java.lang.Object

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

Constructor Detail

QueryUtil

private QueryUtil()

Private constructor. Static methods only.

Method Detail

getDistanceQuery

public static <O> DistanceQuery<O> getDistanceQuery(Database database,
                                                    DistanceFunction<? super O> distanceFunction,
                                                    java.lang.Object... hints)

Get a distance query for a given distance function, automatically choosing a relation.

Type Parameters:

O - Object type

Parameters:

database - Database

distanceFunction - Distance function

hints - Optimizer hints

Returns:

Distance query

getSimilarityQuery

public static <O> SimilarityQuery<O> getSimilarityQuery(Database database,
                                                        SimilarityFunction<? super O> similarityFunction,
                                                        java.lang.Object... hints)

Get a similarity query, automatically choosing a relation.

Type Parameters:

O - Object type

Parameters:

database - Database

similarityFunction - Similarity function

hints - Optimizer hints

Returns:

Similarity Query

getKNNQuery

public static <O> KNNQuery<O> getKNNQuery(Database database,
                                          DistanceFunction<? super O> distanceFunction,
                                          java.lang.Object... hints)

Get a KNN query object for the given distance function. An index is used when possible, but it may fall back to a linear scan. Hints include:

• Integer: maximum value for k needed
• DatabaseQuery.HINT_BULK bulk query needed

Type Parameters:

O - Object type

Parameters:

database - Database

distanceFunction - Distance function

hints - Optimizer hints

Returns:

KNN Query object

getKNNQuery

public static <O> KNNQuery<O> getKNNQuery(Relation<O> relation,
                                          DistanceFunction<? super O> distanceFunction,
                                          java.lang.Object... hints)

Get a KNN query object for the given distance function. An index is used when possible, but it may fall back to a linear scan. Hints include:

• Integer: maximum value for k needed
• DatabaseQuery.HINT_BULK bulk query needed

Type Parameters:

O - Object type

Parameters:

relation - Relation used

distanceFunction - Distance function

hints - Optimizer hints

Returns:

KNN Query object

getRangeQuery

public static <O> RangeQuery<O> getRangeQuery(Database database,
                                              DistanceFunction<? super O> distanceFunction,
                                              java.lang.Object... hints)

Get a range query object for the given distance function for radius-based neighbor search. (Range queries in ELKI refers to radius-based ranges, not rectangular query windows.) An index is used when possible, but it may fall back to a linear scan. Hints include:

• Range: maximum range requested
• DatabaseQuery.HINT_BULK bulk query needed

Type Parameters:

O - Object type

Parameters:

database - Database

distanceFunction - Distance function

hints - Optimizer hints

Returns:

KNN Query object

getRangeQuery

public static <O> RangeQuery<O> getRangeQuery(Relation<O> relation,
                                              DistanceFunction<? super O> distanceFunction,
                                              java.lang.Object... hints)

Get a range query object for the given distance function for radius-based neighbor search. (Range queries in ELKI refers to radius-based ranges, not rectangular query windows.) An index is used when possible, but it may fall back to a linear scan. Hints include:

• Range: maximum range requested
• DatabaseQuery.HINT_BULK bulk query needed

Type Parameters:

O - Object type

Parameters:

relation - Relation used

distanceFunction - Distance function

hints - Optimizer hints

Returns:

KNN Query object

getRKNNQuery

public static <O> RKNNQuery<O> getRKNNQuery(Relation<O> relation,
                                            DistanceFunction<? super O> distanceFunction,
                                            java.lang.Object... hints)

Get a rKNN query object for the given distance function. When possible, this will use an index, but it may default to an expensive linear scan. Hints include:

• Integer: maximum value for k needed
• DatabaseQuery.HINT_BULK bulk query needed

Type Parameters:

O - Object type

Parameters:

relation - Relation used

distanceFunction - Distance function

hints - Optimizer hints

Returns:

RKNN Query object

getLinearScanKNNQuery

public static <O> KNNQuery<O> getLinearScanKNNQuery(DistanceQuery<O> distanceQuery)

Get a linear scan query for the given distance query.

Type Parameters:

O - Object type

Parameters:

distanceQuery - distance query

Returns:

KNN query

getLinearScanRangeQuery

public static <O> RangeQuery<O> getLinearScanRangeQuery(DistanceQuery<O> distanceQuery)

Get a linear scan query for the given distance query.

Type Parameters:

O - Object type

Parameters:

distanceQuery - distance query

Returns:

Range query

getLinearScanSimilarityRangeQuery

public static <O> RangeQuery<O> getLinearScanSimilarityRangeQuery(SimilarityQuery<O> simQuery)

Get a linear scan query for the given similarity query.

Type Parameters:

O - Object type

Parameters:

simQuery - similarity query

Returns:

Range query