GDS 1.6.4

Release date: July 29, 2021

Bug fixes

• Fixed a bug in gds.create.subgraph which could lead to undefined behaviour or an AIOOB exception when executed on GDS Enterprise Edition.

GDS 1.6.3

Release Date: July 22, 2021

Breaking changes

• Remove the sharedUpdater parameter from gds.alpha.ml.linkPrediction and gds.alpha.ml.nodeClassification.

New features

Bug fixes

• Fixed a bug which affected gds.nodeSimilarity.write and gds.alpha.knn.write when being executed in combination with a nodeLabels filter.
  The bug either led to an exception or to wrong results due to an incorrect mapping between internal and Neo4j node ids.
• Fixed a bug in seeded NodeClassification and LinkPrediction which lead to non-deterministic behaviour.
• Fixed a bug where gds.nodeSimilarity.[write|mutate] and gds.beta.knn.[write|mutate] wrote duplicate relationships if the input graph is undirected.
• Fixed a bug in gds.beta.knn where negative values in node properties of type float arrays failed when returning the similarityDistribution.

Improvements

• Lower memory footprint for LinkPrediction and NodeClassification.

GDS 1.6.2

Release Date: July 8, 2021

GDS 1.6.2 is compatible with Neo4j 4.3, 4.2, 4.1, and 4.0. It is not compatible with Neo4j 3.5.x - for a compatible release, please see GDS 1.1.6

Bug Fixes

• Fixed a bug in weighted GraphSAGE where the relationshipWeightProperty was not loaded.
• Fixed a bug in gds.beta.node2vec where using relationship weights would not work when running concurrently.
• Fixed a bug in gds.graph.create where the default value could not be changed for array properties.

1.6.1

Release Date: 17 June 2021

GDS 1.6.1 is compatible with Neo4j 4.0, 4.1, 4.2, and 4.3 but not Neo4j 3.5.x. For a 3.5 compatible release, please see GDS 1.1.6.

Bug fixes

• Fixed a bug regarding weighted graphs with multiple relationship types, which affected gds.beta.graphSage and gds.alpha.spanningTree.
• Fix NaN issue in NodeClassification where computations with very small probability values can cause the result to flip to infinity.
• Progress logging (gds.beta.listProgress)
  • Fixed a bug where progress events would not be released if computation was abandoned before completion.
  • Fixed a bug with Pregel algorithms logging where progress events would not be released on algorithm completion.
• Fixed a bug regarding mutated node properties that could cause an AIOOB exception.
• Fixed a bug where on a node-filtered multi-relationship-type graph KNN and NodeSimilarity could write out of bounds.
• FastRP stream mode explicitly returns a list of floats rather than a list of numbers. This agrees with the other embeddings, and saves users from having to cast/transform when processing the results further in Cypher.

GDS 1.6.0

Release Date: 27 May 2021

GDS 1.6 is compatible with Neo4j 4.0, 4.1, and 4.2 but not Neo4j 3.5.x. For a 3.5 compatible release, please see GDS 1.1.6.

Breaking changes

• Degree centrality has been promoted to the product tier
  • Added procedures:
    • gds.degree.stream.estimate
    • gds.degree.write.estimate
    • gds.degree.mutate
    • gds.degree.mutate.estimate
    • gds.degree.stats
    • gds.degree.stats.estimate
  • Removed alpha procedures:
    • gds.alpha.degree.stream
    • Gds.alpha.degree.write
• Article Rank has been promoted to the product tier
  • Added procedures:
    • gds.articleRank.stream
    • gds.articleRank.stream.estimate
    • gds.articleRank.write
    • gds.articleRank.write.estimate
    • gds.articleRank.mutate
    • gds.articleRank.mutate.estimate
    • gds.articleRank.stats
    • gds.articleRank.stats.estimate
  • Removed alpha procedures:
    • gds.alpha.articleRank.stream
    • gds.alpha.articleRank.write
• Eigenvector Centrality has been promoted to the product tier
  • Added procedures:
    • gds.eigenvector.stream
    • gds.eigenvector.stream.estimate
    • gds.eigenvector.write
    • gds.eigenvector.write.estimate
    • gds.eigenvector.mutate
    • gds.eigenvector.mutate.estimate
    • gds.eigenvector.stats
    • gds.eigenvector.stats.estimate
  • Removed alpha procedures:
    • gds.alpha.eigenvector.stream
    • Gds.alpha.eigenvector.write
• AStar has been promoted to the product tier
  • Added procedures:
    • gds.astar.stream
    • gds.astar.stream.estimate
    • gds.astar.write
    • gds.astar.write.estimate
    • gds.astar.mutate
    • gds.astar.mutate.estimate
  • Removed alpha procedures:
    • gds.beta.astar.stream
    • gds.beta.astar.stream.estimate
    • gds.beta.astar.write
    • gds.beta.astar.write.estimate
    • gds.beta.astar.mutate
    • gds.beta.astar.mutate.estimate
  • The parameter path was removed. The path computation is controlled by the YIELD.
• Yens K Shortest Paths has been promoted to the product tier:
  • Added procedures:
    • gds.yens.stream
    • gds.yens.stream.estimate
    • gds.yens.write
    • gds.yens.write.estimate
    • gds.yens.mutate
    • gds.yens.mutate.estimate
  • Removed alpha procedures:
    • gds.beta.yens.stream
    • gds.beta.yens.stream.estimate
    • gds.beta.yens.write
    • gds.beta.yens.write.estimate
    • gds.beta.yens.mutate
    • gds.beta.yens.mutate.estimate
  • The parameter path was removed. The path computation is controlled by the cypher YIELD sub-clause.
• Dijkstra Source-Target has been promoted to the product tier:
  • Added procedures:
    • gds.shortestPath.dijkstra.stream
    • gds.shortestPath.dijkstra.stream.estimate
    • gds.shortestPath.dijkstra.write
    • gds.shortestPath.dijkstra.write.estimate
    • gds.shortestPath.dijkstra.mutate
    • gds.shortestPath.dijkstra.mutate.estimate
  • Removed alpha procedures:
    • gds.beta.shortestPath.dijkstra.stream
    • gds.beta.shortestPath.dijkstra.stream.estimate
    • gds.beta.shortestPath.dijkstra.write
    • gds.beta.shortestPath.dijkstra.write.estimate
    • gds.beta.shortestPath.dijkstra.mutate
    • gds.beta.shortestPath.dijkstra.mutate.estimate
  • The parameter path was removed. The path computation is controlled by the cypher YIELD sub-clause.
• Dijkstra Single-Source has been promoted to the product tier:
  • Added procedures:
    • gds.allShortestPath.dijkstra.stream
    • gds.allShortestPath.dijkstra.stream.estimate
    • gds.allShortestPath.dijkstra.write
    • gds.allShortestPath.dijkstra.write.estimate
    • gds.allShortestPath.dijkstra.mutate
    • gds.allShortestPath.dijkstra.mutate.estimate
  • Removed alpha procedures:
    • gds.beta.allShortestPath.dijkstra.stream
    • gds.beta.allShortestPath.dijkstra.stream.estimate
    • gds.beta.allShortestPath.dijkstra.write
    • gds.beta.allShortestPath.dijkstra.write.estimate
    • gds.beta.allShortestPath.dijkstra.mutate
    • gds.beta.allShortestPath.dijkstra.mutate.estimate
  • The parameter path was removed. The path computation is controlled by the cypher YIELD sub-clause.
• Node2Vec has been promoted to the beta tier
  • Added procedures:
    • gds.beta.node2vec.stream
    • gds.beta.node2vec.stream.estimate
    • gds.beta.node2vec.write
    • gds.beta.node2vec.write.estimate
    • gds.beta.node2vec.mutate
    • gds.beta.node2vec.mutate.estimate
  • Removed alpha procedures:
    • gds.alpha.node2vec.stream
    • gds.alpha.node2vec.write
• The parameter centerSamplingFactor is renamed to positiveSamplingFactor
• The parameter contextSamplingExponent is renamed to negativeSamplingExponent

The model catalog list feature no longer throws an error when a non-existent model name is given

Node Classification and Link Prediction”

• maxStreakCount configuration parameter is renamed to patience. It is used in the train modes of Node Classification and Link Prediction.
• maxIterations and minIterations configuration parameters are renamed to maxEpochs and minEpochs. It is used in the train modes of Node Classification and Link Prediction.
• windowSize configuration parameters is removed from the train modes of Node Classification and Link Prediction.

gds.alpha.ml.linkPrediction.train configuration parameter classRatio is renamed to negativeClassWeight. It is also mandatory now.

Removed degreeAsProperty configuration parameter from GraphSAGE

• The same effect can be achieved by using gds.degree.mutate and use the mutated property as feature for GraphSAGE training.
• Important: GraphSAGE models persisted with earlier versions of GDS are not compatible with this version.

New features

• New ScaleProperties procedures to transform and scale node properties. Available scalers: Min-max, Max, Mean, Log, Standard Score, L1 Norm, L2 Norm
  • gds.alpha.scaleProperties.stream
  • gds.alpha.scaleProperties.mutate
• Added ability to create new in-memory graphs by filtering existing named graphs based on node and relationship properties with new catalog procedure gds.beta.graph.create.subgraph
• Two new centrality algorithms for influence maximization were contributed by community member @xkitsios
  • gds.alpha.influenceMaximization.celf.stream
  • gds.alpha.influenceMaximization.greedy.stream
• Link Prediction:
  • Added support for storing, loading and publishing Link Prediction models.
  • Added progress logging for gds.alpha.ml.linkPrediction.train and gds.alpha.ml.linkPrediction.predict.
  • Added write and stream modes to gds.alpha.ml.linkPrediction.predict
    • gds.alpha.ml.linkPrediction.stream
    • gds.alpha.ml.linkPrediction.write
  • Added estimate mode for Link Prediction:
    • gds.alpha.ml.linkPrediction.train.estimate
    • gds.alpha.ml.lin...

GDS 1.6 Preview

Release Date: 20 May 2021

GDS 1.6 is compatible with Neo4j 4.0, 4.1, and 4.2 but not Neo4j 3.5.x. For a 3.5 compatible release, please see GDS 1.1.6.

Breaking changes

• Degree centrality has been promoted to the product tier
  • Added procedures:
    • gds.degree.stream.estimate
    • gds.degree.write.estimate
    • gds.degree.mutate
    • gds.degree.mutate.estimate
    • gds.degree.stats
    • gds.degree.stats.estimate
  • Removed alpha procedures:
    • gds.alpha.degree.stream
    • Gds.alpha.degree.write
• Article Rank has been promoted to the product tier
  • Added procedures:
    • gds.articleRank.stream
    • gds.articleRank.stream.estimate
    • gds.articleRank.write
    • gds.articleRank.write.estimate
    • gds.articleRank.mutate
    • gds.articleRank.mutate.estimate
    • gds.articleRank.stats
    • gds.articleRank.stats.estimate
  • Removed alpha procedures:
    • gds.alpha.articleRank.stream
    • gds.alpha.articleRank.write
• Eigenvector Centrality has been promoted to the product tier
  • Added procedures:
    • gds.eigenvector.stream
    • gds.eigenvector.stream.estimate
    • gds.eigenvector.write
    • gds.eigenvector.write.estimate
    • gds.eigenvector.mutate
    • gds.eigenvector.mutate.estimate
    • gds.eigenvector.stats
    • gds.eigenvector.stats.estimate
  • Removed alpha procedures:
    • gds.alpha.eigenvector.stream
    • Gds.alpha.eigenvector.write
• AStar has been promoted to the product tier
  • Added procedures:
    • gds.astar.stream
    • gds.astar.stream.estimate
    • gds.astar.write
    • gds.astar.write.estimate
    • gds.astar.mutate
    • gds.astar.mutate.estimate
  • Removed alpha procedures:
    • gds.beta.astar.stream
    • gds.beta.astar.stream.estimate
    • gds.beta.astar.write
    • gds.beta.astar.write.estimate
    • gds.beta.astar.mutate
    • gds.beta.astar.mutate.estimate
  • The parameter path was removed. The path computation is controlled by the YIELD.
• Yens K Shortest Paths has been promoted to the product tier:
  • Added procedures:
    • gds.yens.stream
    • gds.yens.stream.estimate
    • gds.yens.write
    • gds.yens.write.estimate
    • gds.yens.mutate
    • gds.yens.mutate.estimate
  • Removed alpha procedures:
    • gds.beta.yens.stream
    • gds.beta.yens.stream.estimate
    • gds.beta.yens.write
    • gds.beta.yens.write.estimate
    • gds.beta.yens.mutate
    • gds.beta.yens.mutate.estimate
  • The parameter path was removed. The path computation is controlled by the cypher YIELD sub-clause.
• Dijkstra Source-Target has been promoted to the product tier:
  • Added procedures:
    • gds.shortestPath.dijkstra.stream
    • gds.shortestPath.dijkstra.stream.estimate
    • gds.shortestPath.dijkstra.write
    • gds.shortestPath.dijkstra.write.estimate
    • gds.shortestPath.dijkstra.mutate
    • gds.shortestPath.dijkstra.mutate.estimate
  • Removed alpha procedures:
    • gds.beta.shortestPath.dijkstra.stream
    • gds.beta.shortestPath.dijkstra.stream.estimate
    • gds.beta.shortestPath.dijkstra.write
    • gds.beta.shortestPath.dijkstra.write.estimate
    • gds.beta.shortestPath.dijkstra.mutate
    • gds.beta.shortestPath.dijkstra.mutate.estimate
  • The parameter path was removed. The path computation is controlled by the cypher YIELD sub-clause.
• Dijkstra Single-Source has been promoted to the product tier:
  • Added procedures:
    • gds.allShortestPath.dijkstra.stream
    • gds.allShortestPath.dijkstra.stream.estimate
    • gds.allShortestPath.dijkstra.write
    • gds.allShortestPath.dijkstra.write.estimate
    • gds.allShortestPath.dijkstra.mutate
    • gds.allShortestPath.dijkstra.mutate.estimate
  • Removed alpha procedures:
    • gds.beta.allShortestPath.dijkstra.stream
    • gds.beta.allShortestPath.dijkstra.stream.estimate
    • gds.beta.allShortestPath.dijkstra.write
    • gds.beta.allShortestPath.dijkstra.write.estimate
    • gds.beta.allShortestPath.dijkstra.mutate
    • gds.beta.allShortestPath.dijkstra.mutate.estimate
  • The parameter path was removed. The path computation is controlled by the cypher YIELD sub-clause.
• Node2Vec has been promoted to the beta tier
  • Added procedures:
    • gds.beta.node2vec.stream
    • gds.beta.node2vec.stream.estimate
    • gds.beta.node2vec.write
    • gds.beta.node2vec.write.estimate
    • gds.beta.node2vec.mutate
    • gds.beta.node2vec.mutate.estimate
  • Removed alpha procedures:
    • gds.alpha.node2vec.stream
    • gds.alpha.node2vec.write
• The parameter centerSamplingFactor is renamed to positiveSamplingFactor
• The parameter contextSamplingExponent is renamed to negativeSamplingExponent

The model catalog list feature no longer throws an error when a non-existent model name is given

Node Classification and Link Prediction”

• maxStreakCount configuration parameter is renamed to patience. It is used in the train modes of Node Classification and Link Prediction.
• maxIterations and minIterations configuration parameters are renamed to maxEpochs and minEpochs. It is used in the train modes of Node Classification and Link Prediction.
• windowSize configuration parameters is removed from the train modes of Node Classification and Link Prediction.

gds.alpha.ml.linkPrediction.train configuration parameter classRatio is renamed to negativeClassWeight. It is also mandatory now.

Removed degreeAsProperty configuration parameter from GraphSAGE

• The same effect can be achieved by using gds.degree.mutate and use the mutated property as feature for GraphSAGE training.
• Important: GraphSAGE models persisted with earlier versions of GDS are not compatible with this version.

New features

• New ScaleProperties procedures to transform and scale node properties. Available scalers: Min-max, Max, Mean, Log, Standard Score, L1 Norm, L2 Norm
  • gds.alpha.scaleProperties.stream
  • gds.alpha.scaleProperties.mutate
• Added ability to create new in-memory graphs by filtering existing named graphs based on node and relationship properties with new catalog procedure gds.beta.graph.create.subgraph
• Two new centrality algorithms for influence maximization were contributed by community member @xkitsios
  • gds.alpha.influenceMaximization.celf.stream
  • gds.alpha.influenceMaximization.greedy.stream
• Link Prediction:
  • Added support for storing, loading and publishing Link Prediction models.
  • Added progress logging for gds.alpha.ml.linkPrediction.train and gds.alpha.ml.linkPrediction.predict.
  • Added write and stream modes to gds.alpha.ml.linkPrediction.predict
    • gds.alpha.ml.linkPrediction.stream
    • gds.alpha.ml.linkPrediction.write
  • Added estimate mode for Link Prediction:
    • gds.alpha.ml.linkPrediction.train.estimate
    • gds.alpha.ml.lin...

1.5.2

Release Date: 11 May 2021

GDS 1.5 is compatible with Neo4j 4.0, 4.1, and 4.2 but not Neo4j 3.5.x. For a 3.5 compatible release, please see GDS 1.1.6.

Bug fixes

• Fixed a bug in FastRPExtended concerning implementation internals, especially when propertyDimesion == embeddingDimension output contained NaNs.
• Fixed a bug where Alpha similarity algorithms in some cases could fail on division by 0 when writing results back.
• Fixed an issue where gds.graph.drop could take a long time when the graph contained node embeddings.
• Fixed a bug where gds.beta.graphSage.train was failing in the presence of array properties.

1.5.1

Release Date: 3 March, 2021

GDS 1.5 is compatible with Neo4j 4.0 and 4.1, but not Neo4j 3.5.x. For a 3.5 compatible release, please see GDS 1.1.6.

Bug fixes

• Fixed a bug which caused gds.graph.list and gds.graph.drop to throw an error when specifying a graph with duplicate property keys by failing early.
• Fixed potential ArrayIndexOutOfBoundsException when running gds.triangleCount on a relationship-filtered graph.
• Fixed a bug that can lead to inconsistencies when writing or mutating new relationships created from a label-filtered graph.

Improvements

• Progress logging: Removed a "disabled" log message from the database startup when GDS was running in its default configuration. It is replaced with a more elaborate "enabled" message when the progress tracking feature is enabled.
• We now return the name of the current database in the error message if graph is not found.

1.5.0

Release Date: 9 February, 2021

GDS 1.5 is compatible with Neo4j 4.0 and 4.1, but not Neo4j 3.5.x. For a 3.5 compatible release, please see GDS 1.1.6.

Breaking changes

• Promote several shortest path algorithms to beta tier: Dijkstra, A*, and Yens k-shortest paths. The APIs have been standardized, and all include the ability to return source/target nodes, nodes traversed, and paths.
  • This adds procedures
    • gds.beta.shortestPath.dijkstra.mutate
    • gds.beta.shortestPath.dijkstra.mutate.estimate
    • gds.beta.shortestPath.dijkstra.stream
    • gds.beta.shortestPath.dijkstra.stream.estimate
    • gds.beta.shortestPath.dijkstra.write
    • gds.beta.shortestPath.dijkstra.write.estimate
    • gds.beta.shortestPath.astar.mutate
    • gds.beta.shortestPath.astar.mutate.estimate
    • gds.beta.shortestPath.astar.stream
    • gds.beta.shortestPath.astar.stream.estimate
    • gds.beta.shortestPath.astar.write
    • gds.beta.shortestPath.astar.write.estimate
    • gds.beta.shortestPath.yens.mutate
    • gds.beta.shortestPath.yens.mutate.estimate
    • gds.beta.shortestPath.yens.stream
    • gds.beta.shortestPath.yens.stream.estimate
    • gds.beta.shortestPath.yens.write
    • gds.beta.shortestPath.yens.write.estimate
    • gds.beta.allShortestPaths.dijkstra.mutate
    • gds.beta.allShortestPaths.dijkstra.mutate.estimate
    • gds.beta.allShortestPaths.dijkstra.stream
    • gds.beta.allShortestPaths.dijkstra.stream.estimate
    • gds.beta.allShortestPaths.dijkstra.write
    • gds.beta.allShortestPaths.dijkstra.write.estimate
  • And removes alpha procedures
    • gds.alpha.shortestPath.stream
    • gds.alpha.shortestPath.write
    • gds.alpha.shortestPath.astar.stream
    • gds.alpha.kShortestPaths.stream
    • gds.alpha.kShortestPaths.write
    • gds.alpha.shortestPaths.stream
    • gds.alpha.shortestPaths.write
• GDS will now throw an error when a user tries to use a mutate procedure on graphs not stored in the graph catalog (anonymous graphs)

New Features

• Introduced machine learning based multi-class node classification procedures:
  • Add gds.alpha.ml.nodeClassification.train to train a model to predict a node label
  • Add gds.alpha.ml.nodeClassification.predict.mutate to make predictions using a trained model
• Introduced machine learning based link prediction procedures:
  • Add gds.alpha.linkPrediction.train procedure for training Link Prediction models.
  • Added gds.alpha.linkPrediction.predict.mutate procedure for predicting relationships based on a trained Link Prediction model.
• Added support for list properties as features for
  • gds.alpha.nodeClassification
  • gds.beta.fastRPExtended
  • gds.beta.graphSage
• Added support for storing trained models on disk (Enterprise only)
  • gds.alpha.model.store
  • gds.alpha.model.load
  • gds.alpha.model.delete
• Added procedure for publishing trained models (Enterprise only)
  • gds.alpha.model.publish
• Added HITS algorithm to the alpha tier
  • gds.alpha.hits.mutate and gds.alpha.hits.mutate.estimate
  • gds.alpha.hits.stats and gds.alpha.hits.stats.estimate
  • gds.alpha.hits.stream and gds.alpha.hits.stream.estimate
  • gds.alpha.hits.write and gds.alpha.hits.write.estimate
• Added Speaker-Listener Label Propagation Algorithm (SLLPA) to the alpha tier
  • gds.alpha.sllpa.mutate and gds.alpha.sllpa.mutate.estimate
  • gds.alpha.sllpa.stats and gds.alpha.sllpa.stats.estimate
  • gds.alpha.sllpa.stream and gds.alpha.sllpa.stream.estimate
  • gds.alpha.sllpa.write and gds.alpha.sllpa.write.estimate
• Added CSV export capabilities with the gds.beta.graph.export.csv procedure to allow users to export their in-memory graph to CSV
• Add message reducer capability to Pregel framework to improve memory consumption and computation runtime.
• Added a progress logging procedure with gds.beta.listProgress, to return status of running algorithms. This is turned off by default, but can be enabled with gds.progress_tracking_enabled in the config.
• Add a new BitIdMap data structure to represent node id mappings (Enterprise only)
  • The data structure can lead to a significant reduction in required heap space for an in-memory graph.
  • The data structure is used for native graph projections and in some algorithms, e.g., Louvain.
  • The data structure is not used in Cypher projections.
  • The feature is enabled by default on GDS Enterprise Edition and can be disabled using the USE_BIT_ID_MAP feature toggle.

Bug fixes

• Adding projection parameters as additional configuration in gds.graph.create and gds.graph.create.cypher will throw an exception if improperly configured, instead of being silently ignored.
• Fixed a bug in gds.alpha.articleRank where centrality scores were not normalized correctly
• Fixed a bug in path stream procedures where the path object (path: true) used incorrect node identifiers.
• Fixed a bug in path write procedures where the relationship property nodeIds contained incorrect node identifiers.
• Fixed a race condition that could cause exceptions thrown by scheduled tasks to be supressed.

Improvements

• Improved progress logging to write progress per individual node label in gds.graph.writeNodeProperties.
• When a named graph does not exist, the graph catalog will display similarly named stored graphs.
• When a saved model does not exist, the model catalog will display similarly named stored graphs.
• Added centralityDistribution to the return fields for the write mode of the alpha centrality algorithms.
• gds.beta.graph.generate using relationshipDistribution: 'POWER_LAW' applies the distribution to the native orientation.
• Added centralityDistribution as a return field in gds.betweenness.[write/mutate/stats]
• Added getNeighbours and isMultiGraph to the Pregel-API.
• Added new message queue implementations for the Pregel framework, which
  • replace the previously used JCTools queue and work with primitive double arrays instead of boxed values.
  • lead to 3x to 5x faster runtimes for Pregel based algorithms.
  • reduce GC pressure due to less object allocations which leads to more predictable runtimes.
  • support synchronous and asynchronous Pregel computations.

Other Changes

• The PageRank configuration parameter cacheWeights has been deprecated. The parameter had no effect.
• Deprecated minimumScore, maximumScore, scoreSum return fields in gds.betweenness.[write/mutate/stats]

GDS 1.5 Preview

Release date: 29 January, 2021

Warning: This is a preview release and not intended for production use. If you have any feedback, please let us know: https://github.com/neo4j/graph-data-science/issues

GDS 1.5 is compatible with Neo4j 4.0 and 4.1, but not Neo4j 3.5.x. For a 3.5 compatible release, please see GDS 1.1.6.

Breaking changes

• Promote several shortest path algorithms to beta tier: Dijkstra, A*, and Yens k-shortest paths. The APIs have been standardized, and all include the ability to return source/target nodes, nodes traversed, and paths.
  • This adds procedures
    • gds.beta.shortestPath.dijkstra.mutate
    • gds.beta.shortestPath.dijkstra.mutate.estimate
    • gds.beta.shortestPath.dijkstra.stream
    • gds.beta.shortestPath.dijkstra.stream.estimate
    • gds.beta.shortestPath.dijkstra.write
    • gds.beta.shortestPath.dijkstra.write.estimate
    • gds.beta.shortestPath.astar.mutate
    • gds.beta.shortestPath.astar.mutate.estimate
    • gds.beta.shortestPath.astar.stream
    • gds.beta.shortestPath.astar.stream.estimate
    • gds.beta.shortestPath.astar.write
    • gds.beta.shortestPath.astar.write.estimate
    • gds.beta.shortestPath.yens.mutate
    • gds.beta.shortestPath.yens.mutate.estimate
    • gds.beta.shortestPath.yens.stream
    • gds.beta.shortestPath.yens.stream.estimate
    • gds.beta.shortestPath.yens.write
    • gds.beta.shortestPath.yens.write.estimate
    • gds.beta.allShortestPaths.dijkstra.mutate
    • gds.beta.allShortestPaths.dijkstra.mutate.estimate
    • gds.beta.allShortestPaths.dijkstra.stream
    • gds.beta.allShortestPaths.dijkstra.stream.estimate
    • gds.beta.allShortestPaths.dijkstra.write
    • gds.beta.allShortestPaths.dijkstra.write.estimate
  • And removes alpha procedures
    • gds.alpha.shortestPath.stream
    • gds.alpha.shortestPath.write
    • gds.alpha.shortestPath.astar.stream
    • gds.alpha.kShortestPaths.stream
    • gds.alpha.kShortestPaths.write
    • gds.alpha.shortestPaths.stream
    • gds.alpha.shortestPaths.write
• GDS will now throw an error when a user tries to use a mutate procedure on graphs not stored in the graph catalog (anonymous graphs)

New Features

• Introduced machine learning based multi-class node classification procedures:
  • Add gds.alpha.ml.nodeClassification.train to train a model to predict a node label
  • Add gds.alpha.ml.nodeClassification.predict.mutate to make predictions using a trained model
• Introduced machine learning based link prediction procedures:
  • Add gds.alpha.linkPrediction.train procedure for training Link Prediction models.
  • Added gds.alpha.linkPrediction.predict.mutate procedure for predicting relationships based on a trained Link Prediction model.
• Added support for list properties as features for
  • gds.alpha.nodeClassification
  • gds.beta.fastRPExtended
  • gds.beta.graphSage
• Added support for storing trained models on disk (Enterprise only)
  • gds.alpha.model.store
  • gds.alpha.model.load
  • gds.alpha.model.delete
• Added procedure for publishing trained models (Enterprise only)
  • Gds.alpha.model.publish
• Added HITS algorithm to the alpha tier
  • gds.alpha.hits.mutate and gds.alpha.hits.mutate.estimate
  • gds.alpha.hits.stats and gds.alpha.hits.stats.estimate
  • gds.alpha.hits.stream and gds.alpha.hits.stream.estimate
  • gds.alpha.hits.write and gds.alpha.hits.write.estimate
• Added Speaker-Listener Label Propagation Algorithm (SLLPA) to the alpha tier
  • gds.alpha.sllpa.mutate and gds.alpha.sllpa.mutate.estimate
  • gds.alpha.sllpa.stats and gds.alpha.sllpa.stats.estimate
  • gds.alpha.sllpa.stream and gds.alpha.sllpa.stream.estimate
  • gds.alpha.sllpa.write and gds.alpha.sllpa.write.estimate
• Added CSV export capabilities with the gds.beta.graph.export.csv procedure to allow users to export their in-memory graph to CSV
• Added a progress logging procedure with gds.beta.listProgress, to return status of running algorithms. This is turned off by default, but can be enabled with gds.progress_tracking_enabled in the config.
• Add message reducer capability to Pregel framework to improve memory consumption and computation runtime.
• Add a new BitIdMap data structure to represent node id mappings (Enterprise only)
  • The data structure can lead to a significant reduction in required heap space for an in-memory graph.
  • The data structure is used for native graph projections and in some algorithms, e.g., Louvain.
  • The data structure is not used in Cypher projections.
  • The feature is enabled by default on GDS Enterprise Edition and can be disabled using the USE_BIT_ID_MAP feature toggle.

Bug fixes

• Adding projection parameters as additional configuration in gds.graph.create and gds.graph.create.cypher will throw an exception if improperly configured, instead of being silently ignored.
• Fixed a bug in gds.alpha.articleRank where centrality scores were not normalized correctly

Improvements

• Improved progress logging to write progress per individual node label in gds.graph.writeNodeProperties.
• When a named graph does not exist, the graph catalog will display similarly named stored graphs.
• When a saved model does not exist, the model catalog will display similarly named stored graphs.
• Add centralityDistribution to the return fields for the write mode of the alpha centrality algorithms.
• gds.beta.graph.generate using relationshipDistribution: 'POWER_LAW' applies the distribution to the native orientation.
• Add getNeighbours and isMultiGraph to the Pregel-API.
• Add centralityDistribution as a return field in gds.betweenness.[write/mutate/stats]

Other Changes

• The PageRank configuration parameter cacheWeights has been deprecated. The parameter had no effect.
• Deprecate minimumScore, maximumScore, scoreSum return fields in gds.betweenness.[write/mutate/stats]