Data Engineering Podcast


This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.

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09 June 2021

Make Sure Your Records Are Reliable With The BookKeeper Distributed Storage Layer - E193

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Summary

The way to build maintainable software and systems is through composition of individual pieces. By making those pieces high quality and flexible they can be used in surprising ways that the original creators couldn’t have imagined. One such component that has gone above and beyond its originally envisioned use case is BookKeeper, a distributed storage system that is optimized for durability and speed. In this episode Matteo Merli shares the story behind the creation of BookKeeper, the various ways that it is being used today, and the architectural aspects that make it such a strong building block for projects such as Pulsar. He also shares some of the other interesting systems that have been built on top of it and an amusing war story of running it at scale in its early years.

Announcements

  • Hello and welcome to the Data Engineering Podcast, the show about modern data management
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  • We’ve all been asked to help with an ad-hoc request for data by the sales and marketing team. Then it becomes a critical report that they need updated every week or every day. Then what do you do? Send a CSV via email? Write some Python scripts to automate it? But what about incremental sync, API quotas, error handling, and all of the other details that eat up your time? Today, there is a better way. With Census, just write SQL or plug in your dbt models and start syncing your cloud warehouse to SaaS applications like Salesforce, Marketo, Hubspot, and many more. Go to dataengineeringpodcast.com/census today to get a free 14-day trial.
  • Your host is Tobias Macey and today I’m interviewing Matteo Merli about Apache BookKeeper, a scalable, fault-tolerant, and low-latency storage service optimized for real-time workloads

Interview

  • Introduction
  • How did you get involved in the area of data management?
  • Can you describe what BookKeeper is and the story behind it?
  • What are the most notable features/capabilities of BookKeeper?
  • What are some of the ways that BookKeeper is being used?
  • How has your work on Pulsar influenced the features and product direction of BookKeeper?
  • Can you describe the architecture of a BookKeeper cluster?
    • How have the design and goals of BookKeeper changed or evolved over time?
  • What is the impact of record-oriented storage on data distribution/allocation within the cluster when working with variable record sizes?
  • What are some of the operational considerations that users should be aware of?
  • What are some of the most interesting/compelling features from your perspective?
  • What are some of the most often overlooked or misunderstood capabilities of BookKeeper?
  • What are the most interesting, innovative, or unexpected ways that you have seen BookKeeper used?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on BookKeeper?
  • When is BookKeeper the wrong choice?
  • What do you have planned for the future of BookKeeper?

Contact Info

Parting Question

  • From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

  • Thank you for listening! Don’t forget to check out our other show, Podcast.__init__ to learn about the Python language, its community, and the innovative ways it is being used.
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Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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