Benchmarking spreadsheet systems

Benchmarking spreadsheet systems Rahman et al., Preprint A recent TwThread drew my attention to this pre-print paper. When spreadsheets were originally conceived, data and formula were input by hand and so everything operated at human scale. Increasingly we’re dealing with larger and larger datasets — for example, data imported via csv files — and spreadsheets … Continue reading Benchmarking spreadsheet systems

Even more amazing papers at VLDB 2019 (that I didn’t have space to cover yet)

We’ve been covering papers from VLDB 2019 for the last three weeks, and next week it will be time to mix things up again. There were so many interesting papers at the conference this year though that I haven’t been able to cover nearly as many as I would like. So today’s post is a … Continue reading Even more amazing papers at VLDB 2019 (that I didn’t have space to cover yet)

Updating graph databases with Cypher

Updating graph databases with Cypher Green et al., VLDB'19 This is the story of a great collaboration between academia, industry, and users of the Cypher graph querying language as created by Neo4j. Beyond Neo4j, Cypher is also supported in SAP HANA Graph, RedisGraph, Agnes Graph, and Memgraph. Cypher for Apache Spark, and Cypher over Gremlin … Continue reading Updating graph databases with Cypher

Declarative recursive computation on an RDBMS

Declarative recursive computation on an RDBMS... or, why you should use a database for distributed machine learing Jankov et al., VLDB'19 If you think about a system like Procella that’s combining transactional and analytic workloads on top of a cloud-native architecture, extensions to SQL for streaming, dataflow based materialized views (see e.g. Naiad, Noria, Multiverses, … Continue reading Declarative recursive computation on an RDBMS

Procella: unifying serving and analytical data at YouTube

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., VLDB'19 Academic papers aren’t usually set to music, but if they were the chorus of Queen’s "I want it all (and I want it now...)" seems appropriate here. Anchored in the primary use case of supporting Google’s YouTube business, what we’re looking at here … Continue reading Procella: unifying serving and analytical data at YouTube

Experiences with approximating queries in Microsoft’s production big-data clusters

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., VLDB'19 I’ve been excited about the potential for approximate query processing in analytic clusters for some time, and this paper describes its use at scale in production. Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of … Continue reading Experiences with approximating queries in Microsoft’s production big-data clusters

IPA: invariant-preserving applications for weakly consistent replicated databases

IPA: invariant-preserving applications for weakly consistent replicated databases Balegas et al., VLDB'19 IPA for developers, happy days! Last we week looked at automating checks for invariant confluence, and extending the set of cases where we can show that an object is indeed invariant confluent. I’m not going to re-cover that background in this write-up, so … Continue reading IPA: invariant-preserving applications for weakly consistent replicated databases