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Neo4j Graph Data Science :: Procedures :: Machine Learning
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/*
* Copyright (c) "Neo4j"
* Neo4j Sweden AB [http://neo4j.com]
*
* This file is part of Neo4j.
*
* Neo4j is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see .
*/
package org.neo4j.gds.ml.kge;
import org.neo4j.gds.algorithms.machinelearning.KGEPredictResult;
import org.neo4j.gds.algorithms.machinelearning.KGEPredictStreamConfig;
import org.neo4j.gds.algorithms.machinelearning.TopKMapComputer;
import org.neo4j.gds.executor.AlgorithmSpec;
import org.neo4j.gds.executor.ComputationResultConsumer;
import org.neo4j.gds.executor.ExecutionContext;
import org.neo4j.gds.executor.GdsCallable;
import org.neo4j.gds.procedures.algorithms.configuration.NewConfigFunction;
import org.neo4j.gds.procedures.algorithms.machinelearning.KGEStreamResult;
import java.util.stream.Stream;
import static org.neo4j.gds.LoggingUtil.runWithExceptionLogging;
import static org.neo4j.gds.executor.ExecutionMode.STREAM;
@GdsCallable(
name = "gds.ml.kge.predict.stream",
description = "Predicts new relationships using an existing KGE model",
executionMode = STREAM
)
public class KGEPredictStreamSpec implements AlgorithmSpec<
TopKMapComputer,
KGEPredictResult,
KGEPredictStreamConfig,
Stream,
KGEPredictAlgorithmFactory> {
@Override
public String name() {
return "KGEPredictStream";
}
@Override
public KGEPredictAlgorithmFactory algorithmFactory(ExecutionContext executionContext) {
return new KGEPredictAlgorithmFactory<>();
}
@Override
public NewConfigFunction newConfigFunction() {
return (__, config) -> KGEPredictStreamConfig.of(config);
}
@Override
public ComputationResultConsumer> computationResultConsumer() {
return (computationResult, executionContext) -> runWithExceptionLogging(
"Result streaming failed",
executionContext.log(),
() -> computationResult.result()
.map(result -> {
var graphStore = computationResult.graphStore();
var graph = graphStore.getGraph();
return result.topKMap().stream((node1, node2, similarity) -> new KGEStreamResult(
graph.toOriginalNodeId(node1),
graph.toOriginalNodeId(node2),
similarity
));
}).orElseGet(Stream::empty)
);
}
}