Release Notes: Graph Data Science 1.5.0 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]