Posts

Showing posts from November, 2014

Google Cloud Messaging (GCM): An evaluation

Image
I had written about our work on building a crowdsourced superplayer for the "Who wants to be a millionaire (WWTBAM)" quiz show earlier. In that work we developed an Android app that enabled the app users in Turkey to participate in WWTBAM in real time as the show was airing on TV. When a question was read by the show host, my PhD students typed the question and the multiple-choice options, which were transmitted via Google Cloud Messaging (GCM) to the app users. App users played the game, and enjoyed competing with other app users, and we got a chance to collect precious data about MCQA dynamics in crowdsourcing. Our app was downloaded 300K+ times, and at the peak of its popularity 20K participants played the game simultaneously.

We used GCM to send the questions to the participants because we wanted to keep the app simple. GCM is the default push messaging solution for the Android platform and is maintained by Google as a free service with no quotas. GCM allows app develope…

Paper Summary: Granola, Low overhead distributed transaction coordination

Image
This paper is by Cowling and Liskov, and it appeared at Usenix ATC'12.  Most closely related papers to this paper are the Sinfonia and Calvin papers. So, it may be helpful to also read the summaries of those papers from the links above to familiarize yourself with them.

This paper looks at coordination of 1-round transactions, which are different from general transactions that involve multi-round interaction with the client. 1-round transactions execute at the participant nodes, with no communication with other nodes except for at most a single commit/abort vote.

Figure 1 shows the system architecture. The clients are the transaction managers for these 1-round transactions. They initiate transactions and evaluate the commit/conflict/abort decisions returned for the transactions. The repositories communicate with one another (for at most a single commit/abort vote) to coordinate transactions.

There are 2 types of transactions in Granola: coordinated ones, and uncoordinated ones. Ac…

Paper Summary: Calvin, Distributed transactions for database systems

Calvin is a transaction scheduling and replication management layer for distributed storage systems. By first writing transaction requests to a durable, replicated log, and then using a concurrency control mechanism that emulates a deterministic serial execution of the log's transaction requests, Calvin supports strongly consistent replication and fully ACID distributed transactions, and manages to incur lower inter-partition transaction coordination costs than traditional distributed database systems.

Calvin emphasizes modularity. The holy trinity in Calvin is: log, scheduler, executor. When a client submits a transaction request to Calvin, this is immediately appended to a durable log, before any actual execution begins. Calvin's scheduling mechanism then processes this request log, deciding when each transaction should be executed in a way that maintains an invariant slightly stronger than serializable isolation: Transaction execution may be parallelized but must be equival…

Paper Summary: Coordination Avoidance in Database Systems

Image
Serializing transactions is sufficient for correctness, but it is not necessary for all operations of all applications. The downside of serialization is that it kills scalability and is overkill in many cases.

This paper (which will appear in VLDB'15) has the following insight: Given knowledge of application transactions and correctness criteria (i.e., invariants), it is possible to avoid this over-coordination of serializability and execute some transactions without coordination while still preserving those correctness criteria (invariants).

In particular the authors propose the concept of "invariant confluence" to relax the use of serialization for some operations of a coordination-requiring application. By operating on application-level invariants over database states (e.g., integrity constraints), the invariant confluence analysis provides a necessary and sufficient condition for safe, coordination-free execution. When programmers specify application invariants, this …

Popular posts from this blog

I have seen things

SOSP19 File Systems Unfit as Distributed Storage Backends: Lessons from 10 Years of Ceph Evolution

PigPaxos: Devouring the communication bottlenecks in distributed consensus

Learning about distributed systems: where to start?

My Distributed Systems Seminar's reading list for Fall 2020

Fine-Grained Replicated State Machines for a Cluster Storage System

My Distributed Systems Seminar's reading list for Spring 2020

Cross-chain Deals and Adversarial Commerce

Book review. Tiny Habits (2020)

Zoom Distributed Systems Reading Group