David B. Lomet and Mohamed Mokbel
To adapt database technology to new environments like cloud platforms or multi-core hardware, or to try anew to provide an extensible database platform, it is useful to separate transaction services from data management elements that need close physical proximity to data. With “generic”transactional services of concurrency control and recovery in a separate transactional component (TC), indexing, cache and disk management, now in a data component (DC), can be simplified and tailored more easily to the platform or to a data type extension with a special purpose index. This decomposition requires that details of the DC’s management of data be hidden from the TC. Thus, locking and logging need to be “logical”, which poses a number of problems. One problem is the handling of locking for ranges of keys. Locks need to be taken at the TC prior to the records and their keys being known to the TC. We describe generic two approaches for dealing with this. (1) Make a “speculative” visit” to the DC to learn key values. (2) Lock a “covering resource” first, then learn and lock key values and ultimately release the covering resource lock. The “table” is the only logical (and hence known to the TC) covering resourse in the traditional locking hierarchy, but using it limits concurrency. Concurrency is improved with the introduction of new partition resources. We show how partitions as covering resources combine high concurrency with low locking overhead. Using partitions is sufficiently effective to consider adapting it for a traditional database kernel.
|Publisher||Very Large Data Bases Endowment Inc.|
All articles published in this journal are protected by copyright, which covers the exclusive rights to reproduce and distribute the article (e.g., as offprints), as well as all translation rights. No material published in this journal may be reproduced photographically or stored on microfilm, in electronic data bases, video disks, etc., without first obtaining written permission from Very Large Data Bases Endowment Inc.