Meaning from Maps/Graphs - Entity Resolution in GraphFrames

Code examples for the Spark+AI Summit Europe 2019 talk "Maps and Meaning: Graph-bases Entity resolution". Dive into a toy example via the notebooks (ER-Graphframes & ER-GraphX).

For further details, or if you'd like to try this on a specific use case, please do get in touch.

Easy Ways to get started:

• Get the pyspark Docker container (with GraphFrames preinstalled). You can get it on Docker Hub here

• The Dockerfile explains the extra layer on top of the jupyter/pyspark-notebook base container (install of GraphFrames)

• The container can be launched via docker-compose up

• Jupyter notebooks are running on localhost:8888 (see docker-compose.yml)

• You can also run the test of the gfresolver to make sure everything works well from within the container.