Work with stored procedures for Apache Spark | BigQuery | Google Cloud
Send feedback Stay organized with collections Save and categorize content based on your preferences. Work with stored procedures for Apache Spark This document is intended for data engineers, data scientists, and data analysts to create and call stored procedures for Spark in BigQuery. Using BigQuery, you can create and run Spark stored procedures that are written in Python, Java, and Scala. You c
High Performance Python on Apache Spark
This document contains the slides from a presentation given by Wes McKinney on high performance Python on Apache Spark. The presentation discusses why Python is an important and productive language, defines what is meant by "high performance Python", and explores techniques for building fast Python software such as embracing limitations of the Python interpreter and using native data structures an
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PEX — The secret sauce for the perfect PySpark deployment of AWS EMR workloads
How Project Zen Improves Python for Apache Spark Users
From CSVs to Tables: Infer Data Types From Raw Spreadsheets
Irina Truong - Adapting from Spark to Dask: what to expect - PyCon 2018
