A dirty dozen: twelve common metric interpretation pitfalls in online controlled experiments

A dirty dozen: twelve common metric interpretation pitfalls in online controlled experiments Dmitriev et al., KDD 2017 Pure Gold! Here we have twelve wonderful lessons in how to avoid expensive mistakes in companies that are trying their best to be data-driven. A huge thank you to the team from Microsoft for sharing their hard-won experiences ... Continue Reading

Azure Data Lake Store: a hyperscale distributed file service for big data analytics

Azure data lake store: a hyperscale distributed file service for big data analytics Douceur et al., SIGMOD'17 Today's paper takes us inside Microsoft Azure's distributed file service called the Azure Data Lake Store (ADLS). ADLS is the successor to an internal file system called Cosmos, and marries Cosmos semantics with HDFS, supporting both Cosmos and ... Continue Reading

Dhalion: self-regulating stream processing in Heron

Dhalion: Self-regulating stream processing in Heron Floratou et al., VLDB 2017 Dhalion follows on nicely from yesterday's paper looking at the modular architecture of Heron, and aims to reduce the "complexity of configuring, managing, and deploying" streaming applications. In particular, streaming applications deployed as Heron topologies, although the authors are keen to point out the ... Continue Reading