Researchers and practitioners alike have long sought to integrate programming
languages and databases. Today's integration solutions focus on the data-types of
the two domains, but today's programs lack transparency. A
transparently persistent program operates over all objects
in a uniform manner, regardless of whether those objects reside in memory or in a
database. Transparency increases modularity and lowers the barrier of adoption in
industry. Unfortunately, fully transparent programs perform so poorly that no one
writes them. The goal of this dissertation is to increase the performance of
these programs to make transparent persistence a viable programming paradigm.
This dissertation contributes two novel techniques that integrate programming
languages and databases. Our first contribution--called query
extraction--is based purely on program analysis. Query extraction analyzes a
transparent, object-oriented program that retrieves and filters collections of
objects. Some of these objects may be persistent, in which case the program
contains implicit queries of persistent data. Our interprocedural program
analysis extracts these queries from the program, translates them to explicit
queries, and transforms the transparent program into an equivalent one that
contains the explicit queries. Query extraction enables programmers to write
programs in a familiar, modular style and to rely on the compiler to transform
their program into one that performs well.
Our second contribution--called RBI-DB+--is an extension
of a new programming language construct called a batch block. A batch
block provides a syntactic barrier around transparent code. It also provides a
latency guarantee: If the batch block compiles, then the code that appears in it
requires only one client-server communication trip. Researchers previously have
proposed batch blocks for databases. However, batch blocks cannot be modularized
or composed, and database batch blocks do not permit programmers to modify
persistent data. We extend database batch blocks to address these concerns and
formalize the results.
Today's technologies integrate the data-types of programming languages and
databases, but they discourage programmers from using procedural abstraction.
Our contributions restore procedural abstraction's use in enterprise
applications, without sacrificing performance. We argue that industry should
combine our contributions with data-type integration. The result would be a
robust, practical integration of programming languages and databases. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2009-12-687 |
| Date | 23 August 2010 |
| Creators | Wiedermann, Benjamin Alan |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
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