Recent advancements in high-performance networking interconnect significantly narrow the performance gap between intra-node and inter-node communications, and open up opportunities for distributed memory platforms to enforce cache coherency among distributed nodes. To this end, we propose GAM, an efficient distributed in-memory platform that provides a directory-based cache coherence protocol over remote direct memory access (RDMA). GAM manages the free memory distributed among multiple nodes to provide a unified memory model, and supports a set of userfriendly APIs for memory operations. To remove writes from critical execution paths, GAM allows a write to be reordered with the following reads and writes, and hence enforces partial store order (PSO) memory consistency. A lightweight logging scheme is designed to provide fault tolerance in GAM. We further build a transaction engine and a distributed hash table (DHT) atop GAM to show the ease-of-use and applicability of the provided APIs. Finally, we conduct an extensive micro benchmark to evaluate the read/write/lock performance of GAM under various workloads, and a macro benchmark against the transaction engine and DHT. The results show the superior performance of GAM over existing distributed memory platforms.

Modern Internet applications often produce a large volume of user activity records. Data analysts are interested in cohort analysis, or finding unusual user behavioral trends, in these large tables of activity records. In a traditional database system, cohort analysis queries are both painful to specify and expensive to evaluate. We propose to extend database systems to support cohort analysis. We do so by extending SQL with three new operators. We devise three different evaluation schemes for cohort query processing. Two of them adopt a non-intrusive approach. The third approach employs a columnar based evaluation scheme with optimizations specifically designed for cohort query processing. Our experimental results confirm the performance benefits of our proposed columnar database system, compared against the two non-intrusive approaches that implement cohort queries on top of regular relational databases.

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