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How to monitor Kafka consumption / lag when working with spark structured streaming?

Maatari
New Contributor III

I have just find out spark structured streaming do not commit offset to kafka but use its internal checkpoint system and that there is no way to visualize its consumption lag in typical kafka UI

- https://community.databricks.com/t5/data-engineering/can-we-commit-offset-in-spark-structured-stream... ?

Lag being important in stream processing, I can't imagine that the community did not come up with workaround to help with consumer lag tracking, but so far i could not find any out of the box solutions.

In any case, as i do not want to reinvent the will, I won't if anyone can share solution either out of the box or custom that people typically uses for this ?

 

1 ACCEPTED SOLUTION

Accepted Solutions

Slash
Contributor

Hi @Maatari ,

In spark structured streaming, current offset information is written to checkpoint files continuously. You can create piece of code that will extract information from checkpoint files aobut currently consumed offset, extract offset from Kafka and compare it.

As an example, look at below article. Unfortunately, I don't know anything about out of the box solution for this kind of problem.

Monitoring Spark Structured Streaming/Kafka Offsets with Prometheus and Grafana | by Lim Yow Cheng |...

PS. There is Kafka offset commiter for Spark Structured Streaming, but last commits are from 4 years ago 🙂

HeartSaVioR/spark-sql-kafka-offset-committer: Kafka offset committer for structured streaming query ...

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Rishabh_Tiwari
Community Manager
Community Manager

Hi @Maatari ,

Thank you for reaching out to our community! We're here to help you. 

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Thanks,

Rishabh

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