Fugue: Unifying Spark and Non-Spark Ecosystems for Big Data Analytics
Description
While struggling to choose between Apache Spark, Tensorflow, Druid, Dask, Flink, etc for your ETL and Machine Learning projects, have you thought about unifying them into one ecosystem to use? In this talk, we will talk about such a framework we developed — Fugue. It’s an abstraction layer on top of different solutions, providing a SQL-like language that can represent your pipelines from end to end, which is also highly extendable by Python. With the Fugue framework, it’s a lot easier and faster to create reliable, performant and maintainable pipelines than using native Spark, especially for entry-level users. Within a unified environment based on K8S Spark, we will show how a user can use the custom environment for interactive development (Jupyter notebook), batch processing or near real-time streaming jobs in their dedicated workspace. We will demo how to instantly update dependency, instantly start and stop an on-demand Spark K8s cluster in our environment, even with a large number of pods. We also developed Fugue extensions for Kinesis, and Kafka so that developers can connect to those resources and write Spark streaming pipelines in the same framework. Moreover, real-time ser…
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