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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
