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Real-Time Exactly-Once Event Processing with Apache Flink, Kafka, and Pinot

Posted Apr 29
# Uber machine learning platform
# Uber Machine Learning
# Real-time Machine Learning
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SPEAKER
Jacob Tsafatinos
Jacob Tsafatinos
Jacob Tsafatinos
Staff Software Engineer @ Elemy

Jacob Tsafatinos is a Staff Software Engineer at Elemy. He led the efforts of the Ad Events Processing system at Uber and has previously worked on a range of problems including data ingestion for search and machine learning recommendation pipelines. In his spare time he can be found playing lead guitar in his band Good Kid.

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Jacob Tsafatinos is a Staff Software Engineer at Elemy. He led the efforts of the Ad Events Processing system at Uber and has previously worked on a range of problems including data ingestion for search and machine learning recommendation pipelines. In his spare time he can be found playing lead guitar in his band Good Kid.

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SUMMARY

A few years ago Uber set out to create an ads platform for the Uber Eats app that relied heavily on three pillars; Speed, Reliability, and Accuracy. Some of the technical challenges they were faced with included exactly-once semantics in real-time.

To accomplish this goal, they created the architecture diagram above with lots of love from Flink, Kafka, Hive, and Pinot. You can dig into the whole paper (https://go.mlops.community/k8gzZd) to see all the reasoning for their design decisions.

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