AQuery++ Database is a cross-platform, In-Memory Column-Store Database that incorporates compiled query execution.
AQuery++ Database is a cross-platform, In-Memory Column-Store Database that incorporates compiled query execution.
## Requirements
## Docker (Recommended):
- See installation instructions from [docker.com](https://www.docker.com). Run **docker desktop** to start docker engine.
- In AQuery root directory, type `make docker` to build the docker image from scratch.
- For Arm-based Mac users, you would have to build and run the **x86_64** docker image because MonetDB doesn't offer official binaries for arm64 Linux. (Run `docker buildx build --platform=linux/amd64 -t aquery .` instead of `make docker`)
- Finally run the image in **interactive** mode (`docker run -it --rm aquery`)
- If there is a need to access the system shell, type `dbg` to activate python interpreter and type `os.system('sh')` to launch a shell.
## Native Installation:
### Requirements
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)
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)
- GCC: 9.0 or above (g++ 7.x, 8.x fail to handle fold-expressions due to a compiler bug)
- GCC: 9.0 or above (g++ 7.x, 8.x fail to handle fold-expressions due to a compiler bug)
- Clang: 5.0 or above (Recommended)
- Clang: 5.0 or above (Recommended)
@ -17,15 +25,9 @@ AQuery++ Database is a cross-platform, In-Memory Column-Store Database that inco
3. Python 3.6 or above and install required packages in requirements.txt by `python3 -m pip install -r requirements.txt`
3. Python 3.6 or above and install required packages in requirements.txt by `python3 -m pip install -r requirements.txt`
## Installation
### Installation
AQuery is tested on mainstream operating systems such as Windows, macOS and Linux
AQuery is tested on mainstream operating systems such as Windows, macOS and Linux
### Docker (Recommended):
- See installation instructions from [docker.com](https://www.docker.com). Run **docker desktop** to start docker engine.
- In AQuery root directory, type `make docker` to build the docker image from scratch.
- For Arm-based Mac users, you would have to build and run the **x86_64** docker image because MonetDB doesn't offer official binaries for arm64 Linux. (Run `docker buildx build --platform=linux/amd64 -t aquery .` instead of `make docker`)
- Finally run the image in **interactive** mode (`docker run -it --rm aquery`)
- If there is a need to access the system shell, type `dbg` to activate python interpreter and type `os.system('sh')` to launch a shell.
### Windows
### Windows
There're multiple options to run AQuery on Windows. You can use the native toolchain from Microsoft Visual Studio or gcc from Cygwin/MinGW or run it under Windows Subsystem for Linux.
There're multiple options to run AQuery on Windows. You can use the native toolchain from Microsoft Visual Studio or gcc from Cygwin/MinGW or run it under Windows Subsystem for Linux.
@ -86,6 +88,7 @@ There're multiple options to run AQuery on Windows. You can use the native toolc
- no options: show statistics for all queries so far.
- no options: show statistics for all queries so far.
- `on` : statistics will be shown for every future query.
- `on` : statistics will be shown for every future query.
- `off`: statistics will not be shown for every future query.
- `off`: statistics will not be shown for every future query.
- `script <filename>`: use automated testing script, this will execute all commands in the script
- `dbg` start python interactive interpreter at the current context.
- `dbg` start python interactive interpreter at the current context.
- `print`: print parsed AQuery statements (AST in JSON form)
- `print`: print parsed AQuery statements (AST in JSON form)
- `save <OPTIONAL: filename>`: save current code snippet. will use random filename if not specified.
- `save <OPTIONAL: filename>`: save current code snippet. will use random filename if not specified.
@ -97,7 +100,10 @@ There're multiple options to run AQuery on Windows. You can use the native toolc
See ./tests/ for more examples.
See ./tests/ for more examples.
### Automated Testing Scripts
- A series of commands can be put in a script file and execute using `script` command.