Composite-object views in relational DBMS: an implementation perspective

We present a novel approach for supporting Composite Objects (CO) as an abstraction over the relational data. This approach brings the advanced CO model to existing relational databases and applications, without requiring an expensive migration to other DBMSs which support CO. The concept of views in relational DBMSs (RDBMS) gives the basis for providing the CO abstraction. This model is strictly an extension to the relational model, and it is fully upward compatible with it. We present an overview of the data model. We put emphasis in this paper on showing how we have made the extensions to the architecture and implementation of an RDBMS (Starburst) to support this model. We show that such a major extension to the data model is in fact quite attractive both in terms of implementation cost and query performance. We introduce a CO cache for navigation through components of a CO. With this technique, the performance of navigation through COs, which has been of a concern in RDBMSs in the past, is in fact quite satisfactory. We present our practical experience in using this facility. We show that our work on CO enables existing RDBMSs to incorporate efficient CO facilities at a low cost and at a high degree of application reusability and database sharability

Recovery algorithms for in-memory OLTP databases

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 63-66).Fine-grained, record-oriented write-ahead logging, as exemplified by systems like ARIES, has been the gold standard for relational database recovery. In this thesis, we show that in modern high-throughput transaction processing systems, this is no longer the optimal way to recover a database system. In particular, as transaction throughputs get higher, ARIES-style logging starts to represent a non-trivial fraction of the overall transaction execution time. We propose a lighter weight, coarse-grained command logging technique which only records the transactions that were executed on the database. It then does recovery by starting from a transactionally consistent checkpoint and replaying the commands in the log as if they were new transactions. By avoiding the overhead of fine-grained, page-level logging of before and after images (and substantial associated I/O), command logging can yield significantly higher throughput at run-time. Recovery times for command logging are higher compared to ARIES, but especially with the advent of high-availability techniques that can mask the outage of a recovering node, recovery speeds have become secondary in importance to run-time performance for most applications. We evaluated our approach on an implementation of TPC-C in a main memory database system (VoltDB), and found that command logging can offer 1.5x higher throughput than a main-memory optimized implementation of ARIES.by Nirmesh Malviya.S.M