Release Date: 1 February 2023
GDS 2.3.0 is compatible with Neo4j 5 & 4.4 versions (≥ 4.4.9) & 4.3 versions (≥ 4.3.15) Database.
For GDS compatibility with previous releases, please use GDS Compatibility Table.
Breaking changes
- Leiden was promoted to the beta tier. It is now called via the 'gds.beta.leiden' command instead of the
gds.alpha.leiden
command. - K-means was promoted to the beta tier. It is now called via the
gds.beta.kmeans
command instead of thegds.alpha.kmeans
command. - Minimum weighted spanning tree algorithm was promoted to the beta tier. It is now called via the
gds.beta.spanningTree
command instead ofgds.alpha.spanningTree
- The procedures
gds.alpha.spanningTree.minimum
andgds.alpha.spanningTree.maximum
have been removed. You can get the same behaviour by specifying the new parameterobjective
ingds.beta.spanningTree
. - The
weightWriteProperty
has been removed as a configuration parameter. To supply the Relationship Type and Property for the produced relationship, use:mutateRelationshipType
mutateProperty
gds.alpha.spanningTree.kmin
andgds.alpha.spanningTree.kmax
have been removed as the K-Spanning Tree algorithm has been moved in its own spacegds.alpha.kSpanningTree
- The parameter
startNodeId
in all Spanning Tree algorithms has been replaced withsourceNode
. - Arrow: when projecting graphs,
null
will be translated toNaN
for floating point values. This enables users of either the GDS Python Client or PyArrow to loadNaN
properties stored in Pandas DataFrames - Cypher Aggregations will become the primary surface for creating projections with Cypher. Offering a more intuitive and expressive interface than Cypher Projections that can also be used in Fabric or Composite Database setups.
- The algorithm
gds.alpha.influenceMaximization.greedy
has been removed. It's replacement is thegds.beta.influenceMaximization.celf
algorithm which has the same configuration parameters and offers better performance.
- The procedures
New features
Neo4j Database Compatibility
- This release is compatible with all Neo4j 5.x database version <=
5.4.0
. Please see compatibility matrix above.
Minimum Directed Steiner Tree
- Added heuristic for minimum directed Steiner Tree under the
gds.beta.steinerTree
domain.- Added
stats
mode withgds.beta.steinerTree.stats
- Added
stream
mode withgds.beta.steinerTree.stream
- Added
mutate
mode withgds.beta.steinerTree.mutate
- Added
write
mode withgds.beta.steinerTree.write
- Now available in progress tracking –
gds.list.progress()
- Added
Leiden
- New parameter
consecutiveIds
that assigns consecutive ids for the discovered communities. - New parameter
seedProperty
to seed initial communities for nodes. - New parameter
tolerance
to enable convergence criteria based on differences in modularity from one iteration to another. - Now available in progress tracking –
gds.list.progress()
- Added memory estimation mode:
gds.beta.leiden.mutate.estimate
gds.beta.leiden.stats.estimate
gds.beta.leiden.stream.estimate
gds.beta.leiden.write.estimate
Logistic Regression & MLP
- New configuration parameters
classWeights
andfocusWeight
for training methods, supported by procedures:gds.beta.pipeline.nodeClassification.addLogisticRegression
gds.beta.pipeline.nodeClassification.addMLP
gds.beta.pipeline.linkPrediction.addLogisticRegression
gds.beta.pipeline.linkPrediction.addMLP
HashGNN
- New algorithm
gds.alpha.hashgnn.{mutate,stream}
to create HashGNN node embeddings - New estimation procedures
gds.alpha.hashgnn.{mutate,stream}.estimate
to estimate the memory required to run HashGNN
Link Prediction
- Added new optional configuration parameter
negativeRelationshipType
togds.beta.pipeline.linkPrediction.configureSplit
Spanning Tree
- New modes supported:
gds.beta.spanningTree.{stats, stream, mutate}
- New yield outputs for
gds.beta.spanningTree
:- the sum of weights in the discovered spanning tree.
- the number of relationships written or added for write and mutate mode respectively.
- Added memory estimation mode :
gds.beta.spanningTree.stream.estimate
gds.beta.spanningTree.mutate.estimate
gds.beta.spanningTree.stats.estimate
gds.beta.spanningTree.write.estimate
Write Labels
gds.alpha.graph.nodeLabel.mutate
allows for the Graph Projection to be mutated with new labelsgds.alpha.graph.nodeLabel.write
allows for Node Labels to be written back from projections to a Neo4j Database
Graph Projections
- Arrow now supports specifying undirected relationship types using the
undirected_relationship_types
configuration argument - Cypher Aggregations (
gds.alpha.graph.project
) now support specifying undirected relationship types using theundirectedRelationshipTypes
configuration option - New procedure to turn directed relationships into undirected relationships:
gds.beta.graph.relationships.toUndirected
- Projections created using either the Native, Arrow and Cypher Aggregation APIs can now be "inverse indexed", this will enable more efficient algorithm implementations
Administration
- Added the
jobId
andusername
to theongoingGdsProcedures
return field ofgds.alpha.systemMonitor
. - Added username as a new return field to
gds.beta.listProgress
. - Added a new return field to
gds.graph.list
calledschemaWithOrientation
which also includes the orientation. - Administrators can now see all running tasks from all users with
gds.beta.listProgress
Bug fixes
- Minimum Weighted Spanning Tree: Graphs with parallel edges could make the discovered tree have wrong weights on relationships
- Cypher Aggregations: When using
gds.alpha.graph.project
:- The projected graph would list relationship types with zero relationships
- AIOOB exceptions could surface due to sizing errors
- Arrow:
CREATE_DATABASE
action would throw anNullPointerException
if missing ID fields in the Arrow record. A more descriptive exception is provided gds.graph.list
could cause issues on some JDKs when calculating the memory usage of Projections- Export relationship progress logging (
gds.beta.graph.export.csv
) reports the correct progress - Graph constructed with Cypher Aggregation using arbitrary IDs are now blocked from write procedures
- The k-Spanning Tree algorithm no longer returns disconnected partitions
- Multi-threading bug when creating projections via Cypher Aggregation or Arrow could lead to lost labels
- Node label filtering could lead to streamed node properties being null when filters are applied
- Cypher projections and Cypher aggregation would throw the wrong error message when loading an invalid relationship
- Node label filtering that would lead to the wrong results. This also affected: gds.beta.graphSage and gds.beta.graph.relationships.stream
Improvements
Arrow
- graph import now fully supports external node ids in the 64 Bit space.
- graph import now supports 16, 32 or 64 Bit node identifiers.
- Arrow server will now check user RBAC permissions for creating and accessing databases
- Database import now creates a Relationship Type index
Leiden
- Better parallelization and improved overall performance improvements
WCC
- Now supports a new and faster sampling strategy ( undirected and directed graphs) by using the new
inverse index
.
Machine Learning
- Inner components of
pipeline
field returned bygds.pipeline.{ linkPrediction | nodeClassification | nodeRegression }.train
procedures are now present directly as part ofmodelInfo
. Thepipeline
field is now deprecated for removal in a future version.
Other Improvements
- Speed improvements for Dijkstra, Astar, Yens, CELF, weighted Betweenness Centrality, and the Spanning Tree algorithms. The improvements will see a slight increase in the memory consumption of these algorithms.
- Improved error message for invalid node labels and relationship types
- Pregel now supports bidirectional computations (allows for messages to be sent along incoming relationships) using the new
inverse index
. - The procedure
gds.graph.export
now creates a Relationship Type index - Extended node property validation to reject projection configuration mappings with the same property keys, but different default values.
Other changes
- Histograms returned such as
degreeDistribution
ingds.graph.list
can have slightly different values for specific percentiles due to changes in floating point operations. - Progress tracking in the Spanning Tree algorithm has been reworked. Progress reporting may differ from earlier versions.
- Mark the yielded field
schema
as deprecated ingds.graph.list
andgds.graph.drop
. In the next major release, theschema
field will use the semantics ofschemaWithOrientation
- In
gds.alpha.model.store
, the positional argumentfailIfUnsupportedType
is renamed tofailIfUnsupported
. Both will be supported until it is promoted to the beta tier. - Progress tracking for Betweenness Centrality has been reworked. Progress reporting may differ from earlier versions.
Pre-release changes
- The Steiner Tree procedures in
gds.beta.SteinerTree
was originally introduced asgds.alpha.SteinerTree
. The update in naming occurred in 2.3.0-alpha04.
Recent Graph Data Science Releases
- Graph Data Science 2.13
- Graph Data Science 2.12
- Graph Data Science 2.11
- Graph Data Science 2.10.1
- Graph Data Science 2.9.0