Building Efficient Query Engines in a High-Level Language

Abstraction without regret refers to the vision of using high-level programming languages for systems development without experiencing a negative impact on performance. A database system designed according to this vision offers both increased productivity and high performance, instead of sacrificing the former for the latter as is the case with existing, monolithic implementations that are hard to maintain and extend. In this article, we realize this vision in the domain of analytical query processing. We present LegoBase, a query engine written in the high-level language Scala. The key technique to regain efficiency is to apply generative programming: LegoBase performs source-to-source compilation and optimizes the entire query engine by converting the high-level Scala code to specialized, low-level C code. We show how generative programming allows to easily implement a wide spectrum of optimizations, such as introducing data partitioning or switching from a row to a column data layout, which are difficult to achieve with existing low-level query compilers that handle only queries. We demonstrate that sufficiently powerful abstractions are essential for dealing with the complexity of the optimization effort, shielding developers from compiler internals and decoupling individual optimizations from each other. We evaluate our approach with the TPC-H benchmark and show that: (a) With all optimizations enabled, LegoBase significantly outperforms a commercial database and an existing query compiler. (b) Programmers need to provide just a few hundred lines of high-level code for implementing the optimizations, instead of complicated low-level code that is required by existing query compilation approaches. (c) The compilation overhead is low compared to the overall execution time, thus making our approach usable in practice for compiling query engines

Guide to Good Practice in using Open Source Compilers with the AGCC Lexical Analyzer

Quality software always demands a compromise between users' needs and hardware resources. To be faster means expensive devices like powerful processors and virtually unlimited amounts of RAM memory. Or you just need reengineering of the code in terms of adapting that piece of software to the client's hardware architecture. This is the purpose of optimizing code in order to get the utmost software performance from a program in certain given conditions. There are tools for designing and writing the code but the ultimate tool for optimizing remains the modest compiler, this often neglected software jewel the result of hundreds working hours by the best specialists in the world. Even though, only two compilers fulfill the needs of professional developers, a proprietary solution from a giant in the IT industry, and the Open source GNU compiler, for which we develop the AGCC lexical analyzer that helps producing even more efficient software applications. It relies on the most popular hacks and tricks used by professionals and discovered by the author who are proud to present them further below.registers, dynamic linkage, cache, null pointers, tweaking

An engineering approach to automatic programming

An exploratory study of the automatic generation and optimization of symbolic programs using DECOM - a prototypical requirement specification model implemented in pure LISP was undertaken. It was concluded, on the basis of this study, that symbolic processing languages such as LISP can support a style of programming based upon formal transformation and dependent upon the expression of constraints in an object-oriented environment. Such languages can represent all aspects of the software generation process (including heuristic algorithms for effecting parallel search) as dynamic processes since data and program are represented in a uniform format

Dynamic Virtual Join Point Dispatch

Conceptually, join points are points in the execution of a program and advice is late-bound to them. We propose the notion of virtual join points that makes this concept explicit not only at a conceptual, but also at implementation level. In current implementations of aspect-oriented languages, binding is performed early, at deploy-time, and only a limited residual dispatch is executed. Current implementations fall in the categories of modifying the application code, modifying the meta-level of an application, or interacting with the application by means of events—the latter two already realizing virtual join points to some degree. We provide an implementation of an aspect-oriented execution environment that supports truly virtual join points and discuss how this approach also favors optimizations in the execution environment

Fast Recompilation of Object Oriented Modules

Once a program file is modified, the recompilation time should be minimized, without sacrificing execution speed or high level object oriented features. The recompilation time is often a problem for the large graphical interactive distributed applications tackled by modern OO languages. A compilation server and fast code generator were developed and integrated with the SRC Modula-3 compiler and Linux ELF dynamic linker. The resulting compilation and recompilation speedups are impressive. The impact of different language features, processor speed, and application size are discussed

Simple and Effective Type Check Removal through Lazy Basic Block Versioning

Dynamically typed programming languages such as JavaScript and Python defer type checking to run time. In order to maximize performance, dynamic language VM implementations must attempt to eliminate redundant dynamic type checks. However, type inference analyses are often costly and involve tradeoffs between compilation time and resulting precision. This has lead to the creation of increasingly complex multi-tiered VM architectures. This paper introduces lazy basic block versioning, a simple JIT compilation technique which effectively removes redundant type checks from critical code paths. This novel approach lazily generates type-specialized versions of basic blocks on-the-fly while propagating context-dependent type information. This does not require the use of costly program analyses, is not restricted by the precision limitations of traditional type analyses and avoids the implementation complexity of speculative optimization techniques. We have implemented intraprocedural lazy basic block versioning in a JavaScript JIT compiler. This approach is compared with a classical flow-based type analysis. Lazy basic block versioning performs as well or better on all benchmarks. On average, 71% of type tests are eliminated, yielding speedups of up to 50%. We also show that our implementation generates more efficient machine code than TraceMonkey, a tracing JIT compiler for JavaScript, on several benchmarks. The combination of implementation simplicity, low algorithmic complexity and good run time performance makes basic block versioning attractive for baseline JIT compilers