Exploiting Single-Threaded Model in Multi-Core In-Memory Systems

• Published in: IEEE transactions on knowledge and data engineering Vol. 28; no. 10; pp. 2635 - 2650
• Main Authors: Chang Yao, Agrawal, Divyakant, Gang Chen, Qian Lin, Beng Chin Ooi, Weng-Fai Wong, Meihui Zhang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Concurrency control; Hardware; in-memory OLTP system; Instruction sets; Message systems; multi-core; Parallel processing; Protocols; single-threaded model; Transaction management
• ISSN: 1041-4347; 1558-2191
• DOI: 10.1109/TKDE.2016.2578319

The widely adopted single-threaded OLTP model assigns a single thread to each static partition of the database for processing transactions in a partition. This simplifies concurrency control while retaining parallelism. However, it suffers performance loss arising from skewed workloads as well as transactions that span multiple partitions. In this paper, we present a dynamic single-threaded in-memory OLTP system, called LADS, that extends the simplicity of the single-threaded model. The key innovation in LADS is the separation of dependency resolution and execution into two non-overlapping phases for batches of transactions. After the first phase of dependency resolution, the record actions of the transactions are partitioned and ordered. Each independent partition is then executed sequentially by a single thread, avoiding the need for locking. By careful mapping of the tasks to be performed to threads, LADS is able to achieve a high degree of balanced parallelism. We evaluate LADS against H-Store, a partition-based database; DORA, a data-oriented transaction processing system; and SILO, a multi-core in-memory OLTP engine. The experimental study shows that LADS achieves up to 20x higher throughput than existing systems and exhibits better robustness with various workloads.