Extensible Distributed Coordination

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Extensible Distributed Coordination - Distler et al. 2015 Coordination services such as ZooKeeper offer a deliberately limited API. As a consequence, more complex coordination tasks have to be implemented as multiple RPCs. In Extensible Distributed Coordination, Distler et al. describe a sandboxed extension mechanism for coordination services that allows execution of client logic in the … Continue reading Extensible Distributed Coordination

Taming uncertainty in distributed systems with help from the network

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Taming uncertainty in distributed systems with help from the network - Leners et al. 2015 Albatross is a membership service with a very interesting new twist: it exploits SDN functionality to actively enforce partitions! Perhaps it is not immediately obvious why that might be a good thing :). It turns out there are several benefits: … Continue reading Taming uncertainty in distributed systems with help from the network

Putting Consistency Back into Eventual Consistency

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Putting Consistency Back into Eventual Consistency - Balegas et al. 2015 Today's choice is another pick from the recent crop of Eurosys 2015 papers. Balegas et al. show us that we don't have to put up with weak forms of eventual consistency, even in geo-replicated settings. In Building on Quicksand Helland argued that we need … Continue reading Putting Consistency Back into Eventual Consistency

Staring into the abyss: An evaluation of concurrency control with one thousand cores

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Staring into the abyss: An evaluation of concurrency control with one thousand cores - Yu et al. 2014 A look at the 7 major concurrency control algorithms for OLTP DBMSs , and how well they perform when scaled to large numbers (1024) of cores. Each algorithm is optimised for the best in-memory performance possible, but … Continue reading Staring into the abyss: An evaluation of concurrency control with one thousand cores

Scaling Concurrent Log-Structured Data Stores

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Scaling Concurrent Log-Structured Data Stores - Golan-Gueta et al. 2015 Key-value stores based on log-structured merge trees are everywhere. The original design was intended to mitigate slow disk I/O. Once this is achieved, as we scale to more and more cores the authors find that in-memory contention now becomes the bottleneck (see yesterday's piece on … Continue reading Scaling Concurrent Log-Structured Data Stores

Applying the Universal Scalability Law to organisations

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How to Quantify Scalability: The Universal Scalability Law (USL) - Gunther Update: corrected sign in USL equation - many thanks to Rob Fielding for pointing out the error. TL;DR: The Universal Scalability Law, Little's Law, and Kingman's Formula can tell you a lot about the behaviour of your systems, and also your organisation. From these … Continue reading Applying the Universal Scalability Law to organisations

Musketeer – Part II: all for one, and one for all in data processing systems

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Musketeer: all for one, one for all in data processing systems - Gog et al. 2015 Musketeer gives you portability of data processing workflows across across data processing systems. It can even analyse your workflow and recommend the best system to run it on, as well as combining systems for different parts of the workflow. … Continue reading Musketeer – Part II: all for one, and one for all in data processing systems