38 min

Presto with Martin Traverso, Dain Sundstrom and David Phillips Contributor

    • Technology

Eric Anderson (@ericmander) talks to Martin Traverso (@mtraverso), Dain Sundstrom (@daindumb) and David Phillips (@electrum32) about their collaboration on Presto, an open-source distributed SQL query engine for big data. The three engineers worked together at three different companies before deciding to solve an efficiency problem for data analytics at Facebook in 2012. Listen to today’s episode to learn about the careful planning and technical philosophy behind the development and design of Presto.

In this episode we discuss:


Starting an open-source project at Facebook in the early 2010s
The importance of making Presto “dirt simple to install”
What is “documentation driven development”
Bootstrapping the growth of an open-source community
How a single query caused a brownout across Facebook infrastructure


Related Links:


Presto
Starburst
Ning
Netezza
ProofPoint
Hadoop
Postgres
Hive
OpenCompute
@Scale
Arm Treasure Data
Qubole


People mentioned:


Jay Parikh (@jayparikh)

Eric Anderson (@ericmander) talks to Martin Traverso (@mtraverso), Dain Sundstrom (@daindumb) and David Phillips (@electrum32) about their collaboration on Presto, an open-source distributed SQL query engine for big data. The three engineers worked together at three different companies before deciding to solve an efficiency problem for data analytics at Facebook in 2012. Listen to today’s episode to learn about the careful planning and technical philosophy behind the development and design of Presto.

In this episode we discuss:


Starting an open-source project at Facebook in the early 2010s
The importance of making Presto “dirt simple to install”
What is “documentation driven development”
Bootstrapping the growth of an open-source community
How a single query caused a brownout across Facebook infrastructure


Related Links:


Presto
Starburst
Ning
Netezza
ProofPoint
Hadoop
Postgres
Hive
OpenCompute
@Scale
Arm Treasure Data
Qubole


People mentioned:


Jay Parikh (@jayparikh)

38 min

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