GDS 1.1 Preview

Release date: 26 March, 2020

New features:

• Multiple node label support: You can now load, and reference, multiple node labels in your in memory graph. This allows you to load all the data you need for multiple algorithms once and refer to specific node labels when you call each algorithm. This is specified by the new parameter `nodeLabels`.
• Graph mutability: We’ve introduced the ability to update your in-memory analytics graph when you execute product supported and beta algorithms. This allows you to chain together multiple algorithms, and only write back your final results to your Neo4j database. To support this we’ve added procedures to:
  • Update your in memory graph with the .mutate mode for product supported and beta procedures (not available for alpha)
  • Write mutated data back to your Neo4j database with graph.writeNodeProperties and graph.writeRelationship, and
  • Inspect your in memory graph with gds.util.nodeProperty, which allows you to retrieve node properties from a named in memory graph.
• Heap control: All gds procedures execute on heap, and this may lead to OOMs, so we now block the execution of algorithms that will require more memory than currently available.
• Other features to improve user experience:
  • gds.graph.list now returns a timestamp to indicate when a graph was created
  • Removed redundant `write` config parameter from several alpha procedures
  • Added `validateRelationships` parameter to Cypher projections, to control behaviour when a user accidentally specifies relationships between non-existent nodes (specify drop or fail)
  • New aggregations type, `COUNT`, to summarize parallel relationships based on their total count
  • When a user improperly misconfigures a procedure call, the error message now suggests the possible misspelled key

Bug fixes:

• `gds.alpha.spanningTree` has been fixed so it now creates relationship properties
• Fixed `.estimate` function when run on an in memory graph created via `gds.graph.generate`
• Fixed out of order and incorrect progress logging for `gds.nodeSimilarity`
• Removed default value of `null` for graph names in gds.graph.exists()

Breaking changes:

• Parallel cypher node loading (via use of `SKIP` and `LIMIT`) has been disabled -- data are already loaded in parallel, and this method results in significantly worse performance than the default mode.

The GDS library is compatible with Neo4j 3.5 versions greater than 3.5.8

The GDS library is not compatible with Neo4j 4.0. We plan on releasing a 4.0 compatible version in late April 2020.

<br> Feedback? Please post feedback as issues on our github repo!

1.0.0

Release Date: 5 March, 2020

Important information: The graph data science library is not compatible with Neo4j 4.0 or with the Neo4j graph algorithms plugin.

Highlights:

• Alpha, Beta, and Production Quality Algorithms: We’ve divided the algorithms library into three tiers to indicate the level of support and testing that has gone into each on. Production quality algorithms have been highly optimized and are guaranteed to scale and execute quickly; alpha algorithms are experimental labs implementations; and beta algorithms are candidates for product support.
• New API: In order to simplify the use of the graph data science library and create a more intuitive, expressive, and easy to use surface, the GDS has a new surface and API. Major changes include specifying node and relationships in the configuration parameters, specifying directionality in a single location (only when graphs are initially loaded), and the additions of .write, .stats, and .estimate modes.
• Better error messaging: To help users adjust to the new library, and to prevent common gotchas, we’ve invested in intuitive and easy to understand error messages. Trying to run an algorithm that requires a directed graph on an undirected projection? We’ll tell you!
• Named Graphs: Previously available in the graph algorithms library, but underutilized, the recommended workflow in the GDS is to use name graphs to load and manage data into an in-memory analytics graph. This approach is compatible with production deployment of algorithm or analytics workloads on graphs that contain billions of nodes and relationships.
• Graph Catalog Operations: We’ve introduced graph catalog operations to enable users to create, reshape, and manage multiple named graphs for GDS workflows.
• Multiple Relationship Types and Node Labels: We support multiple node labels and relationship types in loaded graphs, including the ability to load multiple different relationship projections. This was previewed in recent graph algorithms releases, but we’ve expanded the flexibility and expressiveness of these operations under the GDS.
• Bug fixes and feature improvements: We support all the most popular algorithms from the labs library, and continue to provide bug fixes and enhancements.

Compatibility:

• The GDS library is compatible with Neo4j 3.5 versions greater than 3.5.8
• The GDS library is not compatible with Neo4j 4.0. We plan on releasing a 4.0 compatible binary in mid Q2 2020.
• The GDS library is not compatible with the graph algorithms library -- installing both plug ins in the same database will result in an error message.

Ready to get started? Download the jar from the Neo4j download center, or on our github repo, and install it in your plugins directory. We’ve created a browser guide, :play graph-data-science, to familiarize users with the new surface, features, and workflows.

Feedback? Please post feedback as issues on our github repo!

Graph Data Science Library Release 0.9.1

neo4j-graph-data-science-0.9.1

Breaking changes

• Remove syntactic sugar variant that allows defining multiple projections via a piped string.
• Change projection key within a relationship projection to orientation.

New features

Bug fixes

• Fixed a bug where the thread pool size was always limited to 4

Improvements

Other changes

• gds.alpha.balancedTriads.[write,stream] is no longer supported and has been removed.

neo4j-graph-data-science-0.9.1-standalone.jar

This jar contains the Neo4j Graph Data Science Library plugin.
To use it in your Neo4j database, copy the jar into the plugins directory of your Neo4j installation and restart the server.
For more information visit https://neo4j.com/docs/graph-data-science/preview/

Neo4j Graph Data Science library preview release 0.9.0

neo4j-graph-data-science-0.9.0

Breaking changes

• Product-supported algorithms (WCC, Louvain, Label Propagation, Page Rank and Node Similarity) have been ported to the new procedure API.
• Removed beta versions of graph catalog procedures
• Weighted algorithms now run on an unweighted graph copy unless a relationship weight is specified in the procedure configuration.

New features

• Added new catalog procedures:
  • gds.graph.create -- adds a graph to the catalog
  • gds.graph.create.cypher -- adds a graph to the catalog using Cypher
  • gds.graph.list -- lists information about graphs in the catalog
  • gds.graph.exists -- checks if a graph exists in the catalog
  • gds.graph.drop -- drops a graph from the catalog
  • gds.graph.create.estimate -- estimate memory usage for a graph
  • gds.graph.create.cypher.estimate -- estimate memory usage for a graph using Cypher
• Added new catalog function:
  • gds.graph.exists -- checks if a graph exists in the catalog
• Added support for multiple relationship types and properties in Cypher projection.
• For Cypher projections, node properties are initialized from the RETURN statement if no nodeProperties are given.

Bug fixes

• Fixed potential assertion error when running memory estimation on pre-sized graph.
• Fixed bug in Node Similarity where it would return wrong node ids.
• Fixed failure when assigning integer values to parameters that expect doubles in procedures.

neo4j-graph-data-science-0.9.0-standalone.jar

This jar contains the Neo4j Graph Data Science Library plugin.
To use it in your Neo4j database, copy the jar into the plugins directory of your Neo4j 3.5 installation and restart the server.
For more information visit https://neo4j.com/docs/graph-data-science/preview/