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
- Promoted 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
- This adds procedures
- 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
- Add
- 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.
- Add
- 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
andgds.alpha.hits.mutate.estimate
gds.alpha.hits.stats
andgds.alpha.hits.stats.estimate
gds.alpha.hits.stream
andgds.alpha.hits.stream.estimate
gds.alpha.hits.write
andgds.alpha.hits.write.estimate
- Added Speaker-Listener Label Propagation Algorithm (SLLPA) to the alpha tier
gds.alpha.sllpa.mutate
andgds.alpha.sllpa.mutate.estimate
gds.alpha.sllpa.stats
andgds.alpha.sllpa.stats.estimate
gds.alpha.sllpa.stream
andgds.alpha.sllpa.stream.estimate
gds.alpha.sllpa.write
andgds.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 withgds.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
andgds.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
usingrelationshipDistribution: 'POWER_LAW'
applies the distribution to the native orientation.- Added
centralityDistribution
as a return field ingds.betweenness.[write/mutate/stats]
- Added
getNeighbours
andisMultiGraph
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. - Deprecate
minimumScore, maximumScore, scoreSum
return fields ingds.betweenness.[write/mutate/stats]
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