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AQuery/README.md

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AQuery++ DB

Introduction

AQuery++ Database is a cross-platform, In-Memory Column-Store Database that incorporates compiled query execution.

Architecture

AQuery Compiler

  • The query is first processed by the AQuery Compiler which is composed of a frontend that parses the query into AST and a backend that generates target code that delivers the query.
  • Front end of AQuery++ Compiler is built on top of mo-sql-parsing with modifications to handle AQuery dialect and extension.
  • Backend of AQuery++ Compiler generates target code dependent on the Execution Engine. It can either be the C++ code for AQuery Execution Engine or sql and C++ post-processor for Hybrid Engine or k9 for the k9 Engine.

Execution Engines

  • AQuery++ supports different execution engines thanks to the decoupled compiler structure.
  • AQuery Execution Engine: executes query by compiling the query plan to C++ code. Doesn't support joins and udf functions.
  • Hybrid Execution Engine: decouples the query into two parts. The sql-compliant part is executed by an Embedded version of Monetdb and everything else is executed by a post-process module which is generated by AQuery++ Compiler in C++ and then compiled and executed.
  • K9 Execution Engine (discontinued).

Roadmap

  • SQL Parser -> AQuery Parser (Front End)
  • AQuery-C++ Compiler (Back End)
    • Schema and Data Model
    • Data acquisition/output from/to csv file
    • Single table queries
      • Projections and Single Table Aggregations
      • Group by Aggregations
      • Filters
      • Order by
      • Assumption
      • Flatten
    • Multi-table
      • Join
    • Subqueries
  • -> Optimizing Compiler

TODO:

  • User Module load syntax parsing (fn definition/registration)
  • User Module test
  • Interval based triggers
  • C++ Meta-Programming: Eliminate template recursions as much as possible.
  • IPC: Better ways to communicate between Interpreter (Python) and Executer (C++).
    • Sockets? stdin/stdout capture?

Requirements

Recent version of Linux, Windows or MacOS, with recent C++ compiler that has C++17 (1z) support.

  • GCC: 9.0 or above (g++ 7.x, 8.x fail to handle variadic template expansion due to compiler bug)
  • Clang: 6.0 or above (Recommended)
  • MSVC: 2019 or later

Usage

python3 prompt.py will launch the interactive command prompt. The server binary will be autometically rebuilt and started.

Commands:

  • <sql statement>: parse sql statement

  • f <filename>: parse all sql statements in file

  • dbg start debugging session

  • print: printout parsed sql statements

  • exec: execute last parsed statement(s) with AQuery Execution Engine. AQuery Execution Engine executes query by compiling it to C++ code and then executing it.

  • xexec: execute last parsed statement(s) with Hybrid Execution Engine. Hybrid Execution Engine decouples the query into two parts. The sql-compliant part is executed by an Embedded version of Monetdb and everything else is executed by a post-process module which is generated by AQuery++ Compiler in C++ and then compiled and executed.

  • r: run the last generated code snippet

  • save <OPTIONAL: filename>: save current code snippet. will use random filename if not specified.

  • exit: quit the prompt

Example:

f moving_avg.a
xexec