The case for a learned sorting algorithm

I’m super excited about the new chapter emerging in our research on a programmable cloud. This is what comes after serverless, people. In this thread, a few recent talks/papers on the vision. First off — 10 minute pitch from CIDR is here. https://t.co/fEMboOGF7Q — Joe Hellerstein (@joe_hellerstein) January 28, 2021

An overview of end-to-end entity resolution for big data, Christophides et al., ACM Computing Surveys, Dec. 2020, Article No. 127 The ACM Computing Surveys are always a great way to get a quick orientation in a new subject area, and hot off the press is this survey on the entity resolution (aka record linking) problem. It’s an important part of...

Bias in word embeddings, Papakyriakopoulos et al., FAT*’20 There are no (stochastic) parrots in this paper, but it does examine bias in word embeddings, and how that bias carries forward into models that are trained using them. There are definitely some dangers to be aware of here, but also some cause for hope as we also see that bias can be...

Seeing is believing: a client-centric specification of database isolation, Crooks et al., PODC’17. Last week we looked at Elle, which detects isolation anomalies by setting things up so that the inner workings of the database, in the form of the direct serialization graph (DSG), can be externally recovered. Today’s paper choice, ‘Seeing is...

Elle: inferring isolation anomalies from experimental observations, Kingsbury & Alvaro, VLDB’20 Is there anything more terrifying, and at the same time more useful, to a database vendor than Kyle Kingsbury’s Jepsen? As the abstract to today’s paper choice wryly puts it, “experience shows that many databases do not provide the isolation guarantees...