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Low Latancy Timer Data-Structure for Large Scale Systems

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Lawn - Low Latancy Timer Data-Structure for Large Scale Systems

TL;DR - A Lawn is a timer data store, not unlike Timer-Wheel, but with unlimited timer span with no degradation in performance over a large set of timers with this API.

Lawn is a high throughput data structure that is based on the assumption that most timers are set to a small set of TTLs to boost overall DS performance. It can assist when handling a large set of timers with relatively small variance in TTL by effectively using minimal queues to store timer data. Achieving O(1) for insertion and deletion of timers, and O(1) for timer expiration.

Lawns can be used for anything from keeping track of multiple real-time TTLs of elements, to implement a straightforward dehydration system as depicted in the article “Fast Data”.

You can see the API provided by this implementation of the Lawn Data structure here.

You can read further on the algorithm behind Lawn here.

Common Use Cases

  • Stream Coordination - Make data from one stream wait for the corresponding data from another (preferably using sliding-window style timing).
  • Event Rate Limitation - Delay any event beyond current max throughput to the next available time slot, while preserving order.
  • Self Cleaning Claims-Check - Store data for a well known period, without the need to search for it when it is expired or clear it from the data-store yourself.
  • Task Timer - Postpone actions and their respective payloads to a specific point in time.

About This Project

This project is based off a python version of the same concepts designed by Adam Lev-Libfeld and developed in Tamar Labs by Adam Lev-Libfeld and Alexander Margolin in mid-2015.

A Redis module using these concepts was created by Adam Lev-Libfeld during the RedisModulesHackathon in late 2016.

This code is meant for public use and is maintained solely by Adam Lev-Libfled.

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