In preparation for NODES 2022, we are hosting a couple of workshops!

Blazing Fast Graphs: Hands-On With Apache Arrow and Neo4j

Level: Advanced
Prerequisites: Python knowledge (can import modules, write a function, and use core primatives like Dictionaries), familiarity with a Jupyter notebook
Audience: Data Engineers and (partially) Data Scientists

Description

Learn how to leverage Apache Arrow for blazing fast construction of Neo4j graph projections, ludicrously fast exporting of complex graph features, and more. If you're a Data Scientist looking to experiment with your millions of node embeddings or a Data Engineer looking to decrease deployment time, you should check out Neo4j's Apache Arrow support!

We'll work through exercises loading data from cloud object storage and cloud data warehouses directly to Neo4j. Since this is about the full lifecycle, we'll also work through pulling the data back out into other cloud storage systems.

Along the way, we'll cover some best practices related to:

  • Using the Neo4j Graph Data Science Python client
  • How to parallelize in Python without headaches


Other workshops:

Dave Voutila
Sales Engineering Manager, Neo4j


Markus Kubicek
Daimler


Philipp Zacharias
Daimler


Stefan Kolmar
VP Field Engineering EMEA & APAC, Neo4j


Bruno Ungermann
Country Manager Deutschland, Neo4j

 

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