https://github.com/ldbc/gcore-spark
Implementation of the G-CORE graph query language on Spark
https://github.com/ldbc/gcore-spark
Last synced: 12 months ago
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Implementation of the G-CORE graph query language on Spark
- Host: GitHub
- URL: https://github.com/ldbc/gcore-spark
- Owner: ldbc
- License: apache-2.0
- Created: 2018-01-10T12:31:31.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2021-08-25T18:01:49.000Z (almost 5 years ago)
- Last Synced: 2025-03-27T17:12:10.635Z (about 1 year ago)
- Language: Scala
- Homepage:
- Size: 7.83 MB
- Stars: 15
- Watchers: 7
- Forks: 5
- Open Issues: 20
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# G-CORE interpreter on Spark
## To build and run
The project will build successfully under Java 8. Spark 2.2.0 is needed to run
the application. Spark can be downloaded from
https://spark.apache.org/downloads.html.
To sumbit on Spark, the project needs to be compiled as an uber-jar. The
```-DskipTests``` flag can be used with the mvn package command to avoid running
the tests when packaging the uber-jar.
The Spoofax parser uses Guice as a dependency injection framework. The Guice 4.0
jar needs to be passed separately to the driver as a
```spark.driver.extraClassPath``` property, otherwise the driver is not able to
find it.
```bash
mvn package -DskipTests
spark-submit \
--class GcoreRunner \
--master local[2] \
--conf "spark.driver.extraClassPath=/path_to/guice-4.0.jar" \
target/gcore-interpreter-1.0-SNAPSHOT-jar-with-dependencies.jar
```
## To run tests
```bash
mvn test
```