Fast transactions for multicore in-memory databases
Name
862074778-MIT.pdf
Description
Full printable version
Size
3.43 MB
Format
Adobe PDF
Checksum (MD5)
8e47f70ca468c3ae0e7021a6e4f2f86c
Author(s)
Tu, Stephen Lyle
Advisor(s)
Samuel R. Madden.
Date Issued
2013
Publisher
Massachusetts Institute of Technology
Abstract
Though modern multicore machines have sufficient RAM and processors to manage very large in-memory databases, it is not clear what the best strategy for dividing work among cores is. Should each core handle a data partition, avoiding the overhead of concurrency control for most transactions (at the cost of increasing it for cross-partition transactions)? Or should cores access a shared data structure instead? We investigate this question in the context of a fast in-memory database. We describe a new transactionally consistent database storage engine called MAFLINGO. Its cache-centered data structure design provides excellent base key-value store performance, to which we add a new, cache-friendly serializable protocol and support for running large, read-only transactions on a recent snapshot. On a key-value workload, the resulting system introduces negligible performance overhead as compared to a version of our system with transactional support stripped out, while achieving linear scalability versus the number of cores. It also exhibits linear scalability on TPC-C, a popular transactional benchmark. In addition, we show that a partitioning-based approach ceases to be beneficial if the database cannot be partitioned such that only a small fraction of transactions access multiple partitions, making our shared-everything approach more relevant. Finally, based on a survey of results from the literature, we argue that our implementation substantially outperforms previous main-memory databases on TPC-C benchmarks.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 55-57).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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