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84 lines
4.4 KiB
84 lines
4.4 KiB
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# AQuery++ Database
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## Introduction
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AQuery++ Database is a cross-platform, In-Memory Column-Store Database that incorporates compiled query execution.
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## Architecture
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### AQuery Compiler
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- 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.
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- 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.
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- 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.
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### Execution Engines
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- AQuery++ supports different execution engines thanks to the decoupled compiler structure.
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- AQuery Execution Engine: executes query by compiling the query plan to C++ code. Doesn't support joins and udf functions.
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- 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.
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- K9 Execution Engine: (discontinued).
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## Roadmap
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- [x] SQL Parser -> AQuery Parser (Front End)
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- [x] AQuery-C++ Compiler (Back End)
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- [x] Schema and Data Model
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- [x] Data acquisition/output from/to csv file
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- [ ] Execution Engine
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- [x] Projections and single-group Aggregations
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- [x] Group by Aggregations
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- [x] Filters
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- [x] Order by
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- [x] Assumption
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- [x] Flatten
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- [x] UDFs (Hybrid Engine only)
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- [x] User Module
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- [ ] Triggers
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- [x] Join (Hybrid Engine only)
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- [ ] Subqueries
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- [x] Query Optimization
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- [x] Selection/Order by push-down
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- [x] Join Optimization (Only in Hybrid Engine)
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## TODO:
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- [x] User Module load syntax parsing (fn definition/registration)
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- [x] User Module initialize location
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-> User Module test
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-> Interval based triggers
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-> Optimize Compilation Process, using static libraries, hot reloading server binary
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- [x] Bug fixes: type deduction misaligned in Hybrid Engine
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-> Investigation: Using postproc only for q1 in Hybrid Engine (make is_special always on)
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- [x] Limitation: putting ColRefs back to monetdb.
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- [ ] Limitation: String operations and Date/Time data type.
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- [ ] C++ Meta-Programming: Eliminate template recursions as much as possible.
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- [ ] Limitation: Date and Time, String operations, Funcs in groupby agg.
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# Installation
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## Requirements
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1. Recent version of Linux, Windows or MacOS, with recent C++ compiler that has C++17 (1z) support. (however c++20 is recommended if available for heterogeneous lookup on unordered containers)
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- GCC: 9.0 or above (g++ 7.x, 8.x fail to handle fold-expressions due to a compiler bug)
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- Clang: 5.0 or above (Recommended)
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- MSVC: 2017 or later (2022 or above is recommended)
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2. Monetdb for Hybrid Engine
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- On windows, the required libraries and headers are already included in the repo.
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- On Linux, see [Monetdb Easy Setup](https://www.monetdb.org/easy-setup/) for instructions.
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- On MacOS, Monetdb can be easily installed in homebrew `brew install monetdb`.
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3. Python 3.6 or above and install required packages in requirements.txt by `python3 -m pip install -r requirements.txt`
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## Usage
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`python3 prompt.py` will launch the interactive command prompt. The server binary will be autometically rebuilt and started.
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#### Commands:
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- `<sql statement>`: parse sql statement
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- `f <filename>`: parse all sql statements in file
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- `dbg` start debugging session
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- `print`: printout parsed sql statements
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- `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.
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- `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.
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- `r`: run the last generated code snippet
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- `save <OPTIONAL: filename>`: save current code snippet. will use random filename if not specified.
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- `exit`: quit the prompt
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#### Example:
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`f moving_avg.a` <br>
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`xexec`
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