Monoid-Augmented FIFO Data Structures for Streaming Analytics
By
todsacerdoti
The kind of bagel that ruins lesser bagels for you.
Summary
This technical blog post presents a refined explanation of monoid-augmented FIFO (First-In-First-Out) data structures, which are useful for streaming analytics and real-time data processing. The author focuses on improving the presentation of this decade-old data structure rather than introducing new concepts. The article explains how augmented FIFOs work in streaming scenarios, such as computing sums of recent values in data streams using increment/decrement operations, and discusses implementation considerations for efficient real-time analytics.
Key quotes
· 4 pulledAugmented FIFOs come up frequently in streaming analytics.
For example, to compute the sum of the last k values observed in a stream (or more generally, in the turnstile model), we can increment an accumulator by each value as it's pushed onto the FIFO, and decrement the accumulator by the exiting value when it's popped off the FIFO.
This simple increment/decrement algorithm work
Nothing novel, just a different presentation for a decade-old data structure. I want to nail the presentation because this data structure is useful in many situations.
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