# 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](https://github.com/klahnakoski/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
- [x] SQL Parser -> AQuery Parser (Front End)
- [ ] AQuery-C++ Compiler (Back End)
   -  [x] Schema and Data Model 
   -  [x] Data acquisition/output from/to csv file
   -  [x] Single table queries
      -  [x] Projections and Single Table Aggregations 
      -  [x] Group by Aggregations
      -  [x] Filters
      -  [x] Order by
      -  [x] Assumption
      -  [x] Flatten
   -  [x] Multi-table 
      -  [x] 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` <br>
   `xexec`