neo4j-spark-connector (homepage)

Neo4j Connector for Apache Spark, which provides bi-directional read/write access to Neo4j from Spark, using the Spark DataSource APIs

@neo4j / (0)

The Neo4j Connector for Apache Spark is intended to make integrating graphs together with spark easy. There are effectively two ways of using the connector:

- As a data source: read any set of nodes or relationships as a DataFrame in Spark
- As a sink: write any DataFrame to Neo4j as a collection of nodes or relationships, or alternatively; use a Cypher statement to process records in a DataFrame into the graph pattern of your choice.

Because the connector is based on the new Spark DataSource API, other spark interpreters for languages such as Python and R will work.

The API remains the same, and mostly only slight syntax changes are necessary to accomodate the differences between (for example) Python and Scala.

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How to

Include this package in your Spark Applications using:

spark-shell, pyspark, or spark-submit

> $SPARK_HOME/bin/spark-shell --packages neo4j:neo4j-spark-connector:5.3.2-s_2.13

sbt

If you use the sbt-spark-package plugin, in your sbt build file, add:

spDependencies += "neo4j/neo4j-spark-connector:5.3.2-s_2.13"

Otherwise,

resolvers += "Spark Packages Repo" at "https://repos.spark-packages.org/"

libraryDependencies += "neo4j" % "neo4j-spark-connector" % "5.3.2-s_2.13"

Maven

In your pom.xml, add: 
<dependencies>
  <!-- list of dependencies -->
  <dependency>
    <groupId>neo4j</groupId>
    <artifactId>neo4j-spark-connector</artifactId>
    <version>5.3.2-s_2.13</version>
  </dependency>
</dependencies>
<repositories>
  <!-- list of other repositories -->
  <repository>
    <id>SparkPackagesRepo</id>
    <url>https://repos.spark-packages.org/</url>
  </repository>
</repositories>

Releases

Version: 5.3.2-s_2.13 ( d9acd7 | zip | jar ) / Date: 2024-09-25 / License: Apache-2.0

Version: 5.3.2-s_2.12 ( d9acd7 | zip | jar ) / Date: 2024-09-25 / License: Apache-2.0