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David McNeil: "Concurrent Stream Processing"

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When? This feed was archived on March 24, 2016 16:24 (9+ y ago). Last successful fetch was on December 08, 2013 14:58 (12y ago)

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Manage episode 1673572 series 10642
Content provided by Rich Hickey. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Rich Hickey or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
The foundation of our query processing engine is a concurrent data stream processor. This processor is characterized by the need to efficiently perform parallel, non-blocking processing of multiple data streams which are too large to fit in memory. Many such executions need to be executed simultaneously and fairly. The ideas in this talk are relevant to those who work with large scale, parallel data processing within the scope of a single process. A central theme of the talk is the creation of layers of abstractions to eventually create a language tailored to the problem. The talk discusses characteristics of the concurrent stream processor including: core data structures to represent processing nodes connected by data streams, processing plans represented as s-expressions, compiling s-expressions into processing nodes and streams, processing plan optimizations via s-expression manipulations, concurrent processing via a fork/join pool, facilities for debugging and cancelling executions and using the data stream processor as the core of a federated query processor.
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46 episodes

Artwork
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Archived series ("Inactive feed" status)

When? This feed was archived on March 24, 2016 16:24 (9+ y ago). Last successful fetch was on December 08, 2013 14:58 (12y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 1673572 series 10642
Content provided by Rich Hickey. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Rich Hickey or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
The foundation of our query processing engine is a concurrent data stream processor. This processor is characterized by the need to efficiently perform parallel, non-blocking processing of multiple data streams which are too large to fit in memory. Many such executions need to be executed simultaneously and fairly. The ideas in this talk are relevant to those who work with large scale, parallel data processing within the scope of a single process. A central theme of the talk is the creation of layers of abstractions to eventually create a language tailored to the problem. The talk discusses characteristics of the concurrent stream processor including: core data structures to represent processing nodes connected by data streams, processing plans represented as s-expressions, compiling s-expressions into processing nodes and streams, processing plan optimizations via s-expression manipulations, concurrent processing via a fork/join pool, facilities for debugging and cancelling executions and using the data stream processor as the core of a federated query processor.
  continue reading

46 episodes

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