June 09, 2021

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

42 minutes

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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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

@merlimat on Twitter

merlimat on GitHub

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.

Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.

If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story.

To help other people find the show please leave a review on iTunes and tell your friends and co-workers

Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat

Links

Apache BookKeeper

Apache Pulsar

Podcast Episode

StreamNative

Podcast Episode

Hadoop NameNode

Apache Zookeeper

Podcast Episode

ActiveMQ

Write Ahead Log (WAL)

BookKeeper Architecture

RocksDB

LSM == Log-Structured Merge-Tree

RAID Controller

Pravega

Podcast Episode

BookKeeper etcd Metadata Storage

LevelDB

Ceph

Podcast Episode

Direct IO

Page Cache

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

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By Tobias Macey

4.6

135135 ratings

June 09, 2021

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

42 minutes

Summary

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management

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

@merlimat on Twitter

merlimat on GitHub

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.

Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.

If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story.

To help other people find the show please leave a review on iTunes and tell your friends and co-workers

Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat

Links

Apache BookKeeper

Apache Pulsar

Podcast Episode

StreamNative

Podcast Episode

Hadoop NameNode

Apache Zookeeper