DataFrame - a Swiss Army Knife of Java Data Processing

Can we use big data techniques without big data infrastructure? As Java developers, we deal with data processing all the time. We may be analyzing app logs, extracting data from Excel files, copying tables between different databases (simple ETL), etc. Yet, the “standard” Java falls short in processing capabilities when compared to more complex and heavy “big data” solutions like Spark or Flink. This talk will focus on “DataFrame” - an in-memory 2-dimensional table with operations like filtering, column / row transformations, joins, aggregations, etc. I will use an open source DFLib library (dflib.org) and Jupyter notebook to demonstrate how to do data processing and visualization in any Java app without much fuss.
A cura di Andrus Adamchik:
Andrus is a passionate open-source developer and a member of the Apache Software Foundation. He started programming in Java back in 1998, and founded a number of open-source projects: Apache Cayenne - a developer-friendly ORM, Bootique.io - a lightweight Java app platform, Agrest.io - a framework for dynamic REST services, and DFLib - DataFrame for Java. In his day job, Andrus is an IT entrepreneur, running a software company called ObjectStyle.
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