Abstract
BG is a benchmark that rates the performance of a data store for processing interactive social networking actions such as view a member’s profile, invite a member to be friends, accept a friend request, and others. It is motivated by a proliferation of data stores from a variety of academic and industrial contributors including social networking companies, e.g., Voldemort by LinkedIn. BG is designed to provide a system architect with insights into alternative design principles such as the use of a weak consistency technique instead of a strong one, different physical data models such as relational and JSON, factors that impact vertical and horizontal scalability of a data store, the consistency versus availability tradeoff in the CAP theorem, among others. While BG is a recently introduced benchmark (less than a year old as of this writing), it combines elements of maturer benchmarks and extends them to simplify its use by the practitioners and experimentalists. This paper provides a synopsis of the BG benchmark by identifying its strengths and limitations in our daily use cases. The identified limitations shape our research activities and the obtained solutions shall be incorporated into future BG releases. Thus, this workshop paper is a mid-flight glimpse into our current research efforts with BG.
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- 1.
Apache Jackrabbit and RavenDB, Titan, Oracle NoSQL, FoundationDB, STSdb, EJDB, FatDB, SAP HANA, CouchBase.
- 2.
\(BGC_j\) may return an error code when the action is not possible. For example, Thaw Friendship using Member A may not be feasible because A has no friends. In these cases, \(BGC_i\) may either abort the action or may reference a new member for the same action.
- 3.
This model is a representative of a web server configured with a maximum number of threads.
- 4.
As of November 12, 2013, Katy Perry had more than forty million Twitter followers.
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Ghandeharizadeh, S., Barahmand, S. (2014). A Mid-Flight Synopsis of the BG Social Networking Benchmark. In: Rabl, T., Raghunath, N., Poess, M., Bhandarkar, M., Jacobsen, HA., Baru, C. (eds) Advancing Big Data Benchmarks. WBDB WBDB 2013 2013. Lecture Notes in Computer Science(), vol 8585. Springer, Cham. https://doi.org/10.1007/978-3-319-10596-3_2
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