MixT: A Language for Mixing Consistency in Geodistributed Transactions
Programming concurrent, distributed systems is hard—especially when these systems mutate shared, persistent state replicated at geographic scale. To enable high availability and scalability, a new class of weakly consistent data stores has become popular. However, some data needs strong consistency. To manipulate both weakly and strongly consistent data in a single transaction, we introduce a new abstraction: mixed-consistency transactions, embodied in a new embedded language, MixT. Programmers explicitly associate consistency models with remote storage sites; each atomic, isolated transaction can access a mixture of data with different consistency models. Compile-time information-flow checking, applied to consistency models, ensures that these models are mixed safely and enables the compiler to automatically partition transactions into a single sub-transaction per consistency model. New run-time mechanisms ensure that consistency models can also be mixed safely, even when the data used by a transaction resides on separate, mutually unaware stores. Performance measurements show that despite their stronger guarantees, mixed-consistency transactions retain much of the speed of weak consistency, significantly outperforming traditional serializable transactions.
Wed 20 Jun
|16:10 - 16:35|
|16:35 - 17:00|
|17:00 - 17:25|
Stephen DolanUniversity of Cambridge, KC SivaramakrishnanUniversity of Cambridge, Anil MadhavapeddyOCaml LabsMedia Attached