Releases · neo4j/graph-data-science

17 Oct 08:44

laeg

2.2.1

a51a4a3

Graph Data Science 2.2.1

GDS 2.2.1 is compatible with Neo 4.3 versions ≥ 4.3.15 and 4.4 ≥ 4.4.9.

For GDS compatibility with previous releases of 4.3 and 4.4, please use please see GDS 2.1.6. The 2.1 series is also incompatible with Neo4j 3.5.x, 4.0, 4.1, and 4.2. For a 3.5 compatible release, please see GDS 1.1.7. For a 4.0 compatible release, please see GDS 1.6.5. For a 4.1 or 4.2 compatible release, please see GDS 1.8.8

Breaking changes

Change the content of some fields from the output of gds.debug.arrow:
- listenAddress now always returns the same content as advertisedListenAddress
- serverLocation always returns NULL

Assets 4

10 Oct 11:45

laeg

2.2.0

55a96ce

Graph Data Science 2.2.0

GDS 2.2.0 is compatible with Neo 4.3 versions ≥ 4.3.15 and 4.4 ≥ 4.4.9.

Breaking changes

Link Prediction filtering:
- Change graph filtering in gds.beta.pipeline.linkPrediction.train
  - Replace parameter nodeLabels with sourceNodeLabel and targetNodeLabel.
  - Replace parameter relationshipTypes with targetRelationshipType.
- Change graph filtering in gds.beta.pipeline.linkPrediction.predict
  - Replace parameter nodeLabels with optional sourceNodeLabels and targetNodeLabels. By default, they will be derived from the model's train configuration.
  - Change the default value for relationshipTypes with the targetRelationshipType from the model's train configuration.
Node Classification & Regression filtering:
- Change graph filtering in gds.beta.pipeline.nodeClassification.train and gds.beta.pipeline.nodeRegression.train
  - Replace parameter nodeLabels with targetNodeLabels
- Change graph filtering in gds.beta.pipeline.nodeClassification.predict and gds.beta.pipeline.nodeRegression.predict
  - Replace parameter nodeLabels with targetNodeLabels By default, they will be derived from the model's train configuration.
Promoting Collapse Path to beta tier
- Changed the procedure name to gds.beta.collapsePath.mutate
- Use parameter pathTemplates to now specify multiple_path templates_.
Promoting CELF to beta tier
- Moved gds.alpha.influenceMaximization.celf.stream to gds.beta.influenceMaximization.celf.stream
For graphs created, with gds.graph.project.cypher, reduce output of gds.graph.list to only print the names of parameters. This will avoid printing the parameter values, which potentially leads to long procedure execution times.
RandomWalk algorithm promoted to product tier
- gds.beta.randomWalk.stats => gds.randomWalk.stats
- gds.beta.randomWalk.stats.estimate => gds.randomWalk.stats.estimate
- gds.beta.randomWalk.stream => gds.randomWalk.stream
- gds.beta.randomWalk.stream.estimate => gds.randomWalk.stream.estimate
Removed debug_log config field from Arrow Create Database action.
Node2Vec uses new embedding initializer NORMALIZED as default.
Dropped support for older patches:
- for 4.3, only 4.3.15 and later is supported
- for 4.4, only 4.4.9 and later is supported

New features

Link Prediction filtering:
- Supports heterogeneous LinkPrediction pipelines by allowing configuring which node labels and relationship type to train and predict for.
- See Breaking changes above for more details.
K-means:
- Added centroids and average node-centroid distance to result for Mutate, Stats, and Write modes.
- Added distance to centroid per node result in Stream mode.
- Introduced a parameter numberOfRestarts that runs K-Means multiple times and picks the one with the minimum node-centroid distance.
- Introduced a parameter computeSilhouette that if enabled will compute silhouette related metrics.
- Introduced a parameter initialSampler which can select different sampling strategies for picking the first centroids.
  - Added the K-means++ initialization algorithm which can be enabled by setting initialSampler=kmeans++.
- Introduced the parameter seedCentroids which seeds input centroids to k-means (in negation of the above).
Introduced a new scaler Center for ScaleProperties that subtracts the mean from each value.
Expose penaltyL2 to configure the l2 regularization term to the loss function in gds.beta.graphSage.train.
Add Multilayer Perceptron as a training method for node classification (gds.alpha.pipeline.nodeClassification.addMLP) and link prediction (gds.alpha.pipeline.linkPrediction.addMLP).
Add SAME_CATEGORY feature type to gds.beta.pipeline.linkPrediction.addFeature.
Added new procedure gds.beta.graph.relationships.stream that streams relationship topology.
Added arrow export endpoint gds.beta.graph.relationships.stream that streams relationship topology.
Added new procedure gds.alpha.graph.sample.rwr that creates a new graph projection by sampling using random walk with restarts.
Added the ability to collapse multiple paths using gds.beta.collapsePath.mutate.
Promoting CELF algorithm to beta tier.
- Added gds.beta.influenceMaximization.celf.stats
- Added gds.beta.influenceMaximization.celf.mutate
- Added gds.beta.influenceMaximization.celf.write
- Added progress tracking capabilities.
- Added memory estimation.
Progress tracking for KMeans algorithm.
Memory estimation for KMeans.
- added gds.alpha.kmeans.mutate.estimate
- added gds.alpha.kmeans.stats.estimate
- added gds.alpha.kmeans.stream.estimate
- added gds.alpha.kmeans.write.estimate
Added procedure to compute modularity for pre-computed communities.
- gds.alpha.modularity.stats
- gds.alpha.modularity.stream
Added new config options to the GDS Flight server.
- gds.arrow.encryption.never deactivates the server encryption even if it would otherwise be enabled.
- gds.arrow.advertised_listen_address sets the server location that clients should connect to.
Added support for importing String node identifiers for the Arrow CREATE_DATABASE action.
Added capability to run BetweennessCentrality using relationship weights.
- Added relationshipWeightProperty optional configuration parameter.
Added stats mode procedures for RandomWalk.
- gds.beta.randomWalk.stats
- gds.beta.randomWalk.stats.estimate
Introduced the ability to configure defaults and limits for configuration parameters.
- gds.alpha.config.defaults.list
- gds.alpha.config.defaults.set
- gds.alpha.config.limits.list
- gds.alpha.config.limits.set
Introduce new configuration parameters contextNodeLabels and contextRelationshipTypes in nodePropertySteps.
- gds.beta.pipeline.linkPrediction.addNodeProperty
- gds.beta.pipeline.nodeClassification.addNodeProperty
- gds.alpha.pipeline.nodeRegression.addNodeProperty
- The context is used to enlarge the input graph to the node property steps when running gds.beta.pipeline.linkPrediction.addNodeProperty.[train|predict], gds.beta.pipeline.nodeClassification.[train|predict] and gds.alpha.pipeline.nodeRegression.[train|predict].
Leiden
- Add capability to mutate intermediateCommunities when includeIntermediateCommunities is set to true.
- Add capability to write intermediateCommunities when includeIntermediateCommunities is set to true.
Node2Vec adds new embedding initializer NORMALIZED configured with the parameter embeddingInitializer.

Bug fixes

Fixed a bug where eager checking for business rules around GDS on a Neo4j cluster would cause the cluster to fail to start.
Fixed a bug where Neo4j users with admin role could not see all graphs in the catalog on GDS enterprise.
Fixed a bug in random graph generation where the resulting graph can end up with an incorrect relationship schema.
Fixed a bug where a schema filter would not create a deep copy of the property schema map.
Fixed a bug where modularity could have been incorrectly updated in ModularityOptimization. This may affect the number of performed iterations for ModularityOptimization or number of levels for Louvain.
Fixed a bug where restoring from csv could not read values wrapped in quotes.
Fixed a bug where KNN did not use the expected search space. This will improve the result but also increase the runtime.
Fixed a bug in ML autotuning where maxTrials included model evaluations with concrete configs.
Fixed a bug where gds.triangleCount and gds.localClusteringCoefficient were allowed to run on directed graphs.
Fixed a bug in gds.graph.export and Arrow DB import where the writeConcurrency was not respected.
Fixed a bug with Node Operations where gds.graph.nodeProperties.write, gds.graph.nodeProperties.drop and gds.graph.nodeProperties/y.stream would not accept String input for parameters nodeLabels and/or nodeProperties.
Fixed a bug, where Node2Vec would report negative losses.
Fixed a bug with gds.graph.nodeProperties/y.stream, where the wrong nodes where returned when specifying a nodeLabels filter and using Arrow.
Fixed a bug in the Louvain algorithm, where aggregating dense communities could potentially lead to an exception.
Fixed a bug where model loading is attempted even for unlicensed user, which might fail database startup.

Improvements

Better error handling in K-means
Improve memory estimation for gds.beta.pipeline.linkPrediction.train when the nodePropertySteps used a weighted graph.
Improve runtime of feature generation in gds.beta.linkPrediction.[train|predict].
Improve performance of gds.graph.project.cypher by using the subscriber API.
Improve convergence criteria for LogisticRegression and LinearRegression trainers, by making it independent of the number of batches. This affects gds.alpha.pipeline.nodeRegression.train, gds.beta.pipeline.[linkPrediction|nodeClassification].train.
Improve error handling on invalid user input.
Cypher on GDS projections is now capable of setting labels on nodes.
Promoting CELF algorithm to `bet...

Assets 4

29 Sep 18:22

laeg

2.1.13

a156150

Graph Data Science 2.1.13

GDS 2.1.13 is compatible with Neo 4.3 versions ≥ 4.3.15 and 4.4 ≥ 4.4.9.

Bug Fixes

gds.graph.nodeProperties.write, gds.graph.nodeProperties.drop, gds.graph.nodeProperty.stream and gds.graph.nodeProperties.stream now accept String input for parameters nodeLabels and/or nodeProperties.
gds.graph.nodeProperty.stream and gds.graph.nodeProperties.stream, would return the wrong nodes when specifying a nodeLabels filter when using Arrow.
Louvain algorithm would throw an exception when aggregating dense communities.

Improvements

Export to CSV now enabled when GDS is running on a Causal Cluster Read Replica
- gds.beta.graph.export.csv
- gds.beta.graph.export.csv.estimate

Assets 4

15 Sep 16:30

laeg

2.1.12

e7c23e6

Graph Data Science 2.1.12

GDS 2.1.12 is compatible with Neo 4.3 versions ≥ 4.3.15 and 4.4 ≥ 4.4.9.

Improvements

New procedures for enabling and disabling Arrow database import (default: enabled)
- gds.features.enableArrowDatabaseImport
- gds.features.enableArrowDatabaseImport.reset

Assets 4

02 Sep 13:26

laeg

2.1.11

70f4465

Graph Data Science 2.1.11

GDS 2.1.11 is compatible with Neo 4.3 versions ≥ 4.3.15 and 4.4 ≥ 4.4.9.

Bug Fixes

gds.graph.export and Arrow DB import where the writeConcurrency was not respected

Assets 4

02 Sep 08:50

laeg

2.1.10

f472019

Graph Data Science 2.1.10

GDS 2.1.10 is compatible with Neo 4.3 versions ≥ 4.3.15 and 4.4 ≥ 4.4.9.

Bug Fixes

Modularity Optimization and Louvain may run into an ArrayIndexOutOfBoundsException. This bug was introduced in 2.1.8.
gds.alpha.create.cypherdb would not clean up internal state when encountering an unexpected error.
gds.alpha.backup, gds.alpha.restore and gds.beta.project.subgraph would lose information on relationship projections. This made some algorithms unable to run on graphs produced through the above procedures.

Assets 4

19 Aug 07:56

laeg

2.1.9

27537ca

Graph Data Science 2.1.9

GDS 2.1.9 is compatible with Neo 4.3 versions ≥ 4.3.15 and 4.4 ≥ 4.4.9.

New Features

New setting gds.arrow.advertised_listen_address added to the GDS Flight server.

Bug Fixes

gds.beta.listProgress() would throw due to negative values. This could occur while running procedures such as gds.louvain or gds.graph.project.cypher.
gds.beta.pipeline.[nodeClassification|linkPrediction].train() or gds.alpha.pipeline.nodeRegression.train() would not work when using a pipeline with a graphSage nodeProperty.
ML autotuning included model evaluations with concrete configs when using maxTrials.

Improvements

The gds.debug.sysInfo procedure now shows the license expiration date when run with a valid GDS license.

Assets 4

05 Aug 11:03

laeg

2.1.8

d91f91b

Graph Data Science 2.1.8

GDS 2.1.8 is compatible with Neo 4.3 versions ≥ 4.3.15 and 4.4 ≥ 4.4.9.

New Features

New configuration setting to deactivate encryption for the GDS Flight server.

Bug Fixes

Fixed a bug where KNN did not use the expected search space. This will improve the accuracy of results but may also increase the runtime
Fixed a bug where the GDS plugin would only work with the latest Neo4j patch release. It now works on all 4.3.x & 4.4.x releases.

Improvements

A new column serverLocation has been added to gds.debug.arrow() that presents the actual location of where the server is running, as this can differ to the configured location.

Assets 4

29 Jul 16:53

AliciaFrame

2.1.7

304b3b3

Graph Data Science 2.1.7

GDS 2.1.7 is compatible with Neo 4.3 versions ≥ 4.3.15 and 4.4 ≥ 4.4.9.

Breaking Changes

Link prediction pipeline training no longer accepts directed graphs. This is because the algorithm & ML techniques used by link prediction pipelines are only defined for undirected graphs.

Bug Fixes

Fixed a bug in modularityOptimization could incorrectly update modularity values
Fixed a bug where gds.restore did not correctly read values wrapped in quotes

Assets 4

21 Jul 17:05

AliciaFrame

2.1.6

b83bafc

2.1.6

GDS 2.1.6 is compatible with Neo4j 4.3 and 4.4 but not Neo4j 3.5.x, 4.0, 4.1, or 4.2. For a 3.5 compatible release, please see GDS 1.1.7. For a 4.0 compatible release, please see GDS 1.6.5. For a 4.1 or 4.2 compatible release, please see GDS 1.8.8

Bug Fixes

Fixed a bug where relationship types or node labels were not handled correctly when importing previously exported data via Apache Arrow.
Fixed a bug where gds.graphSage.[stream|write|mutate] did not use the correct relationship weights when run with concurrency > 1.

Assets 4

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Releases: neo4j/graph-data-science

Graph Data Science 2.2.1

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Graph Data Science 2.2.0

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Graph Data Science 2.1.13

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Graph Data Science 2.1.12

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Graph Data Science 2.1.11

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Graph Data Science 2.1.10

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Graph Data Science 2.1.9

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Graph Data Science 2.1.8

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Graph Data Science 2.1.7

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2.1.6

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