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
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)
- Clang: 5.0 or above (Recommended)
- MSVC: 2019 or later (2022 or above is recommended)
2. Monetdb for Hybrid Engine
- On windows, the required libraries and headers are already included in the repo.
- On Linux, see [Monetdb Easy Setup](https://www.monetdb.org/easy-setup/) for instructions.
- On MacOS, Monetdb can be easily installed in homebrew `brew install monetdb`.
3. Python 3.6 or above and install required packages in requirements.txt by `python3 -m pip install -r requirements.txt`
## Installation
AQuery is tested on mainstream operating systems such as Windows, macOS and Linux
### 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.
- For WSL, Docker or Linux virtual machines, see Linux, Docker sections below
- For Visual Studio (Recommended):
1. Install python3.6 or above from [official website](https://www.python.org/downloads/windows/) or Microsoft Store.
2. Install Microsoft Visual Studio 2022 or later with **Desktop development with C++** selected.
3. Clone AQuery repo from [Github](https://github.com/sunyinqi0508/AQuery2)
5. Change the build_driver variable in aquery_config.py to "MSBuild"
6. The libraries and headers for Monetdb are already included in msc-plugins, however you can also choose to download them from [Monetdb Easy Setup](https://www.monetdb.org/easy-setup/) and put them in the same place.
- For Winlibs (Recommended):
- Download latest winlibs toolchain from the [official website](https://winlibs.com/)
- Since winlibs is linked with native windows runtime libraries (UCRT or MSVCRT), it offers better interoperatibility with other libraries built with MSVC such as python and monetdb.
- Other steps can be either the same as Visual Studio or Cygwin/Mingw (below) without ABI break.
- Copy or link `mingw64/libexec/gcc/<arch>/<version>/liblto-plugin.dll` to `mingw64/lib/bfd-plugins/` For Link time optimization support on gcc-ar and gcc-ranlib
- For CygWin/MinGW:
1. Install gcc and python3 using its **builtin package manager** instead of the one from python.org or windows store. (For Msys2, `pacman -S gcc python3`). Otherwise, ABI breakage may happen.
2. Clone AQuery repo from Github
3. Install python requirements
4. The prebuilt binaries are included in ./lib directory. However, you could also rebuild them from [source](https://github.com/MonetDB/MonetDB).
### macOS
- If you're using an arm-based mac (e.g. M1, M2 processors). Please go to the Application folder and right-click on the Terminal app, select 'Get Info' and ensure that the 'Open using Rosetta' option is unchecked. See the section below for more notes for arm-based macs.
- Install a package manager such as [homebrew](https://brew.sh)
- Install python3 and monetdb using homebrew `brew install python3 monetdb`
- Install C++ compiler come with Xcode commandline tool by `xcode-select --install` or from homebrew
- If you have multiple C++ compilers on the system. Specify C++ compiler by setting the **CXX** environment variable. e.g. `export CXX=clang`
- Install python packages from **requirements.txt**
**for arm64 macOS users**
- In theory, AQuery++ can work on both native arm64 and x86_64 through Rosetta. But for maximum performance, running native is preferred.
- However, they can't be mixed up, i.e. make sure every component, `python` , `C++ compiler`, `monetdb` library and system commandline utilities such as `uname` should have the same architecture.
- Use the script `./arch-check.sh` to check if relevant binaries all have the same architecture.
- In the case where binaries have different architectures, install the software with desired architecture and make an alias or link to ensure the newly installed binary is referred to.
- Because I can't get access to an arm-based mac to fully test this setup, there might still be issues. Please open an issue if you encounter any problems.
### Linux
- Install monetdb, see [Monetdb Easy Setup](https://www.monetdb.org/easy-setup/) for instructions.
- Install python3, C++ compiler and git. (For Ubuntu, run `apt update && apt install -y python3 python3-pip clang-14 libmonetdbe-dev git `)
- If you have multiple C++ compilers on the system. Specify C++ compiler by setting the **CXX** environment variable. e.g. `export CXX=clang++-14`
- Note for anaconda users: the system libraries included in anaconda might differ from the ones your compiler is using. In this case, you might get errors similar to:
>ImportError: libstdc++.so.6: version `GLIBCXX_3.4.26' not found
In this case, upgrade anaconda or your compiler or use the python from your OS or package manager instead. Or (**NOT recommended**) copy/link the library from your system (e.g. /usr/lib/x86_64-linux-gnu/libstdc++.so.6) to anaconda's library directory (e.g. ~/Anaconda3/lib/).
### Docker:
- Alternatively, you can also use docker to run AQuery.
- 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.
## Usage
`python3 prompt.py` will launch the interactive command prompt. The server binary will be automatically rebuilt and started.
#### Commands:
- `<sql statement>`: parse AQuery statement
- `f <filename>`: parse all AQuery statements in file
- `exec`: execute last parsed statement(s) with Hybrid Execution Engine. Hybrid Execution Engine decouples the query into two parts. The standard SQL (MonetDB dialect) 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.
- `dbg` start debugging session
- `print`: printout parsed AQuery statements
- `save <OPTIONAL: filename>`: save current code snippet. will use random filename if not specified.
- `exit`: quit the prompt
- `r`: run the last generated code snippet
### Example:
`f moving_avg.a`<br>
`xexec`
See ./tests/ for more examples.
## Architecture
## Architecture
@ -40,53 +126,12 @@ AQuery++ Database is a cross-platform, In-Memory Column-Store Database that inco
## Known Issues:
## Known Issues:
- [x] User Module test
- [ ] Interval based triggers
- [ ] Interval based triggers
- [x] Hot reloading server binary
- [] Hot reloading server binary
- [x] Bug fixes: type deduction misaligned in Hybrid Engine
- [x] Bug fixes: type deduction misaligned in Hybrid Engine
- [ ] Investigation: Using postproc only for q1 in Hybrid Engine (make is_special always on)
- [ ] Investigation: Using postproc only for q1 in Hybrid Engine (make is_special always on)
- [x] Limitation: putting ColRefs back to monetdb. (Comparison)
- [ ] C++ Meta-Programming: Eliminate template recursions as much as possible.
- [ ] C++ Meta-Programming: Eliminate template recursions as much as possible.
- [x] Limitation: Date and Time, String operations, Funcs in groupby agg.
- [ ] Functionality: Basic helper functions in aquery
- [ ] Functionality: Basic helper functions in aquery
- [] Improvement: More DDLs, e.g. drop table, update table, etc.
- [x] Improvement: More DDLs, e.g. drop table, update table, etc.
- [ ] Bug: Join-Aware Column management
- [ ] Bug: Join-Aware Column management
- [ ] Bug: Order By after Group By
- [ ] Bug: Order By after Group By
# 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)
- 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)
- MSVC: 2017 or later (2022 or above is recommended)
2. Monetdb for Hybrid Engine
- On windows, the required libraries and headers are already included in the repo.
- On Linux, see [Monetdb Easy Setup](https://www.monetdb.org/easy-setup/) for instructions.
- On MacOS, Monetdb can be easily installed in homebrew `brew install monetdb`.
3. Python 3.6 or above and install required packages in requirements.txt by `python3 -m pip install -r requirements.txt`
## Usage
`python3 prompt.py` will launch the interactive command prompt. The server binary will be autometically rebuilt and started.
#### Commands:
- `<sql statement>`: parse AQuery statement
- `f <filename>`: parse all AQuery statements in file
- `dbg` start debugging session
- `print`: printout parsed AQuery statements
- `xexec`: execute last parsed statement(s) with Hybrid Execution Engine. Hybrid Execution Engine decouples the query into two parts. The standard SQL (MonetDB dialect) 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.
- `save <OPTIONAL: filename>`: save current code snippet. will use random filename if not specified.
- `exit`: quit the prompt
- `exec`: execute last parsed statement(s) with AQuery Execution Engine (Old). AQuery Execution Engine executes query by compiling it to C++ code and then executing it.
- `r`: run the last generated code snippet
### Example:
`f moving_avg.a`<br>
`xexec`
See ./tests/ for more examples.
## Notes for arm64 macOS users
- In theory, AQuery++ could work on both native arm64 and x86_64 through Rosetta. But for maximum performance, running native is preferred.
- However, they can't be mixed up, i.e. make sure every component, `python` binary, `C++ compiler`, `monetdb` library and system commandline utilities such as `uname` should have the same architecture.
- Because I can't get access to an arm-based mac to fully test this setup, there might still be issues. Please open an issue if you encounter any problems.
