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Apache Kafka® ♥ Apache Flink® - Python Data Engineering w/ Pyflink Table API

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Alice R.
Apache Kafka® ♥ Apache Flink® - Python Data Engineering w/ Pyflink Table API

Details

Hello everyone! Join us for a VIRTUAL Apache Kafka® x Apache Flink® meetup on March 26th from 6:00 pm!

Agenda:

  • 18:00pm-18:05pm: Introduction & Online Networking
  • 18:05pm-18:50pm: Diptiman Raichaudhuri, Staff Developer Advocate, Confluent
  • 18:50pm: Q&A

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Speaker:
Diptiman Raichaudhuri, Staff Developer Advocate, Confluent

Talk:
Apache Kafka ♥ Apache Flink - Python data engineering with pyflink Table API

Abstract:
Extracting real-time insights from streaming data and transforming streams to enrich data at source has become a common requirement for businesses. Python data engineers, thus, need a framework to query, aggregate and transform streaming data at scale.PyFlink is a Python API for Apache Flink that allows data engineers to build scalable batch and streaming workloads, such as real-time data processing pipelines, large-scale exploratory data analysis, Machine Learning (ML) pipelines and ETL processes. It has become popular since, most of the data engineers, data scientists and data analysts prefer using python as their main programming language of choice to build complex use cases.In this session, I will deep dive into pyflink Table APIs , Flink SQL written using python wrappers. Pyflink appeals to python developers since complex stream processing techniques like windowing, event time semantics could be written in simple python DSLs,.The session will also have a short demo showcasing how pyflink ingests fast moving data from Apache Kafka topics and runs pyflink Table API DSLs to process such streams.

Join this session to get a hands-on introduction to pyflink, and learn how to process and transform streaming data!

Bio:
Diptiman Raichaudhuri
Staff Developer Advocate at Confluent. Designed and implemented ‘Modern Data Platform’ for large scale enterprise use cases. Works at the intersection of Data(Kafka, Flink, Spark, Kinesis, Redshift, Iceberg, Glue, Hive, Neo4j, Neptune) and AI(torch,sagemaker,vertex ai,kubeflow, LLMs) at cloud scale (AWS and Google Cloud).

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Online Meetup Etiquette:
• Please hold your questions until the end of the presentation or use the zoom chat during!
• Please arrive on time as zoom meetings can become locked for many reasons (though if you get locked out a recording will be available, but you may have to wait a little while for it!)
Important note: If Zoom asks for a password to join please use 'kafka'
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If you would like to speak or host our next event please let us know! community@confluent.io

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