Cache Augmented Data Stores: Solutions and Opportunities
First floor of Chemistry department, Jaber ibn Hayyan Hall
Date and Time
Wednesday, 27 December 2017
09:30 - 10:30
Numerous organizations augment a data store with a cache to enhance application performance. Redis and Memcached are two popular cache managers in use by popular internet destinations including Facebook, YouTube, and Wikipedia. One may purchase these cache managers as a service from a cloud provider such as Amazon AWS, Microsoft Azure, and Google Cloud. In this talk, I provide an overview of how these caches are used. I present today's solutions and future research opportunities, outlining the research activities we are pursuing at the USC database laboratory. Solutions include CAMP as a smart cache space management technique, alternative write policies including their tradeoffs, the Inhibit, and Quarantine leases to provide strong consistency, support for range predicates using RangeQC, data migration, and programmable switches to resolve hotspots and bottlenecks. Opportunities include support for the emerging Non-Volatile Memory (NVM), auto-scaling of cache size based on demand, and frameworks that make these caches transparent. I present the system methodology we use to build prototypes and how we establish correctness using frameworks such as Polygraph.
Dr. Shahram Ghandeharizadeh is a Computer Scientist, a faculty member and the director of the database laboratory at the University of Southern California. He specializes in the design and implementation of scalable, highly available (always-on), and elastic data-driven infrastructure. He is a co-author of more than one hundred refereed conference and journal papers. His research contributions have been recognized by numerous awards including the ACM Software Systems award and the National Science Foundation Young Investigator's award. He has organized numerous workshops and conferences. He is serving as the program chair of the Symposium on Foundations and Applications of Blockchain (FAB) 2018 and the general chair of Very Large Databases (VLDB) 2019.