Apache Spark is a user-friendly open-source platform for large-scale data processing, analytics and for parallel-computing. Using Apache Spark and Python (PySpark), this workshop is aimed at analyzing data sets that are too large to be handled and processed by a single computer.
With hands-on guided examples, the workshop covers the basics of Spark and Resilient Distributed Datasets (RDD) high-level architecture. The examples are mainly written in Python, hence the APIs covered are the ones available in PySpark, including Spark Core API (RDD API), Spark SQL, and Pandas on Spark.
Participants learn how to import data, use functions to transform, reduce and compile the data, and produce parallel algorithms that can run on Alliance clusters.
Prerequisites:
- ACENET Basics (OR experience using command line to log into remote systems)
- How to write functions in Python
The session will be delivered online.
Participants must register using their institutional / organizational email address (not a personal email, ie. gmail)
This session will not be recorded.
For more ACENET events, click here.
