Paper Trail

Computer Systems, Distributed Algorithms and Databases

Category: Paper notes

Paper notes: MemC3, a better Memcached

MemC3: Compact and Concurrent MemCache with Dumber Caching and Smarter Hashing Fan and Andersen, NSDI 2013 The big idea: This is a paper about choosing your data structures and algorithms carefully. By paying careful attention to the workload and functional requirements, the authors reimplement memcached to achieve a) better concurrency and b) better space efficiency. […]

Paper notes: Anti-Caching

Anti-Caching: A New Approach to Database Management System Architecture DeBrabant et. al., VLDB 2013 The big idea: Traditional databases typically rely on the OS page cache to bring hot tuples into memory and keep them there. This suffers from a number of problems: No control over granularity of caching or eviction (so keeping a tuple […]

Paper notes: Stream Processing at Google with Millwheel

MillWheel: Fault-Tolerant Stream Processing at Internet Scale Akidau et. al., VLDB 2013 The big idea: Streaming computations at scale are nothing new. Millwheel is a standard DAG stream processor, but one that runs at ‘Google’ scale. This paper really answers the following questions: what guarantees should be made about delivery and fault-tolerance to support most […]

Paper notes: DB2 with BLU Acceleration

DB2 with BLU Acceleration: So Much More than Just a Column Store Raman et. al., VLDB 2013 The big idea: IBM’s venerable DB2 technology was based on traditional row-based technology. By moving to a columnar execution engine, and crucially then by taking full advantage of the optimisations that columnar formats allow, the ‘BLU Acceleration’ project […]