Field specialization and cloud applications go well together, in four advantageous ways. First, field specialization speeds up DBMSes and other data-intensive enterprise applications. This results in a more responsive cloud service, while reducing hardware provisioning costs. Both the cloud vendor and end users benefit. More efficient application also directly translate to lower energy consumption, thereby reducing operation cost. Second, continuous specialization works espec

Recall that a spiff is code added to the DBMS source that, given values of invariants known in cold code, generate specialized code (termed “speccode”) that will be called in hot code when the query is executed. How big are they? There are several senses of “how big” that are important. The first is the amount of original code that is specialized by each spiff. In our experience over trials on four proprietary DBMSes and four open-source DBMSes, that the code to be specialize

Our field specialization process proceeds through nine basic steps, supported along the way with proprietary tools that can contend with code bases comprised of millions of lines of source code. Starting from representative workloads, dynamic analysis creates a runtime profile to identify hot routines. A particular hotspot function may be invoked from multiple different calling contexts. Not all such invocations will result the function to be a hotspot, e.g., some contexts ma

Most organizations with non-trivial data processing needs—including virtually all medium and large businesses and corporations—rely on enterprise application software (EAS), e.g.,CRM, SCM, and ERP, for their data processing and analysis. These EAS applications generally run on top of a DBMS, which handles the actual storage and retrieval of data. The performance of the underlying DBMS—i.e., its ability to process large amounts of data within an acceptable amount of time—is t

Dataware speeds up relational databases through a new technology we call field specialization. Just how well might field specialization work with your DBMS? To help answer this question, we applied Dataware’s field specialization to three DBMSes and evaluated its effectiveness using the TPC benchmarks. We applied a handful of specializations to the 380,000-line PostgreSQL DBMS, touching less than 1% of the code, but producing big improvements in execution time: speedups of up

Field specialization is new technology introduced by Dataware that can realize large performance increases when applied to modern DBMSes. But how does it actually work? As an anology, consider the complex road network throughout Dallas: stop signs, stop lights, interchanges, and crossroads. The road infrastructure is general purpose, in that it is designed so that anyone can drive from anywhere to anywhere else. However, think of Bob on a given day, who has to drive from the

The core technology offered by Dataware is field specialization. The benefit of this technology is simple to state: field specialization speeds up DBMSes by substantial amounts: 3X for some queries and approaching a factor of 2X for industry-standard benchmarks. The basic underlying approach of this technology is also easy to state: field specialization removes machine instructions that have been, through prior analyses, determined to be unneeded. Doing so requires a very car