de.lmu.ifi.dbs.elki.database.relation

Interface Relation<O>

Type Parameters:

O - Object type

All Superinterfaces:

DatabaseQuery, HierarchicalResult, Result

All Known Subinterfaces:

DoubleRelation, ModifiableRelation<O>

All Known Implementing Classes:

AbstractRelation, ConvertToStringView, DBIDView, MaterializedDoubleRelation, MaterializedRelation, ProjectedView, ProxyView

public interface Relation<O>
extends DatabaseQuery, HierarchicalResult

An object representation from a database.

Author:

Erich Schubert

Field Summary

Fields inherited from interface de.lmu.ifi.dbs.elki.database.query.DatabaseQuery

HINT_BULK, HINT_EXACT, HINT_HEAVY_USE, HINT_NO_CACHE, HINT_OPTIMIZED_ONLY, HINT_SINGLE

Method Summary

Modifier and Type	Method and Description
O	get(DBIDRef id) Get the representation of an object.
SimpleTypeInformation<O>	getDataTypeInformation() Get the data type of this representation
DBIDs	getDBIDs() Get the IDs the query is defined for.
DistanceQuery<O>	getDistanceQuery(DistanceFunction<? super O> distanceFunction, Object... hints) Get the distance query for a particular distance function.
KNNQuery<O>	getKNNQuery(DistanceFunction<? super O> distanceFunction, Object... hints) Get a KNN query object for the given distance query.
KNNQuery<O>	getKNNQuery(DistanceQuery<O> distanceQuery, Object... hints) Get a KNN query object for the given distance query.
RangeQuery<O>	getRangeQuery(DistanceFunction<? super O> distanceFunction, Object... hints) Get a range query object for the given distance query.
RangeQuery<O>	getRangeQuery(DistanceQuery<O> distanceQuery, Object... hints) Get a range query object for the given distance query.
RKNNQuery<O>	getRKNNQuery(DistanceFunction<? super O> distanceFunction, Object... hints) Get a rKNN query object for the given distance query.
RKNNQuery<O>	getRKNNQuery(DistanceQuery<O> distanceQuery, Object... hints) Get a rKNN query object for the given distance query.
SimilarityQuery<O>	getSimilarityQuery(SimilarityFunction<? super O> similarityFunction, Object... hints) Get the similarity query for a particular similarity function.
DBIDIter	iterDBIDs() Get an iterator access to the DBIDs.
int	size() Get the number of DBIDs.

Methods inherited from interface de.lmu.ifi.dbs.elki.result.HierarchicalResult

getHierarchy, setHierarchy

Methods inherited from interface de.lmu.ifi.dbs.elki.result.Result

getLongName, getShortName

Method Detail

get

O get(DBIDRef id)

Get the representation of an object.

Parameters:

id - Object ID

Returns:

object instance

getDataTypeInformation

SimpleTypeInformation<O> getDataTypeInformation()

Get the data type of this representation

Returns:

Data type

getDBIDs

DBIDs getDBIDs()

Get the IDs the query is defined for. If possible, prefer iterDBIDs().

Returns:

IDs this is defined for

iterDBIDs

DBIDIter iterDBIDs()

Get an iterator access to the DBIDs. To iterate over all IDs, use the following code fragment:

 
 for(DBIDIter iter = relation.iterDBIDs(); iter.valid(); iter.advance()) {
    relation.get(iter); // Get the current element
 }
 
 

Returns:

iterator for the DBIDs.

size

int size()

Get the number of DBIDs.

Returns:

Size

getDistanceQuery

DistanceQuery<O> getDistanceQuery(DistanceFunction<? super O> distanceFunction,
                                  Object... hints)

Get the distance query for a particular distance function.

Parameters:

distanceFunction - Distance function to use

hints - Optimizer hints (optional)

Returns:

Instance to query the database with this distance

getSimilarityQuery

SimilarityQuery<O> getSimilarityQuery(SimilarityFunction<? super O> similarityFunction,
                                      Object... hints)

Get the similarity query for a particular similarity function.

Parameters:

similarityFunction - Similarity function to use

hints - Optimizer hints (optional)

Returns:

Instance to query the database with this similarity

getKNNQuery

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

Get a KNN query object for the given distance query. 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

Parameters:

distanceQuery - Distance query

hints - Optimizer hints (optional)

Returns:

KNN Query object

getKNNQuery

KNNQuery<O> getKNNQuery(DistanceFunction<? super O> distanceFunction,
                        Object... hints)

Get a KNN query object for the given distance query. 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

Parameters:

distanceFunction - Distance function to use

hints - Optimizer hints (optional)

Returns:

KNN Query object

getRangeQuery

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

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

• Distance object: Maximum query range
• DatabaseQuery.HINT_BULK bulk query needed

Parameters:

distanceQuery - Distance query

hints - Optimizer hints (optional)

Returns:

KNN Query object

getRangeQuery

RangeQuery<O> getRangeQuery(DistanceFunction<? super O> distanceFunction,
                            Object... hints)

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

• Distance object: Maximum query range
• DatabaseQuery.HINT_BULK bulk query needed

Parameters:

distanceFunction - Distance function to use

hints - Optimizer hints (optional)

Returns:

KNN Query object

getRKNNQuery

RKNNQuery<O> getRKNNQuery(DistanceQuery<O> distanceQuery,
                          Object... hints)

Get a rKNN query object for the given distance query. 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

Parameters:

distanceQuery - Distance query

hints - Optimizer hints (optional)

Returns:

KNN Query object

getRKNNQuery

RKNNQuery<O> getRKNNQuery(DistanceFunction<? super O> distanceFunction,
                          Object... hints)

Get a rKNN query object for the given distance query. 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

Parameters:

distanceFunction - Distance function to use

hints - Optimizer hints (optional)

Returns:

KNN Query object