RecStep

The repo contains the code of RecStep which was described in the PVLDB 2019 paper http://www.vldb.org/pvldb/vol12/p695-fan.pdf , a reasearch Datalog engine prototype built on top of a parallel single-node relational system Quickstep. If you find RecStep useful in your research, please consider citing:

@article{10.14778/3311880.3311886,
author = {Fan, Zhiwei and Zhu, Jianqiao and Zhang, Zuyu and Albarghouthi, Aws and Koutris, Paraschos and Patel, Jignesh M.},
title = {Scaling-up in-Memory Datalog Processing: Observations and Techniques},
year = {2019},
issue_date = {February 2019},
publisher = {VLDB Endowment},
volume = {12},
number = {6},
issn = {2150-8097},
url = {https://doi.org/10.14778/3311880.3311886},
doi = {10.14778/3311880.3311886},
journal = {Proc. VLDB Endow.},
month = feb,
pages = {695–708},
numpages = {14}
}

Note: The following set-up steps have been specifically tested on Ubuntu 18.04.1 LTS. And thus we recommend using Ubuntu 18.04.1 LTS as your testbed OS if you want to play with RecStep. It should also be feasible to set-up the RecStep backend on Ubuntu of other versions (e.g., 14.04, 16.04), but it may require more efforts as configuring the corresponding dependencies as required in Ubuntu of different versions might be different.

Set-up Instructions

1. Before getting started, let's first set-up the relational backend Quickstep

The instruction can be found at https://github.com/Hacker0912/quickstep-datalog

2. Check/Resolve potential dependency issues:

sudo apt-get install -y python3-pip python-dev build-essential
pip3 install --upgrade pip
sudo pip3 install cython
sudo pip3 install matplotlib
sudo pip3 install psutil
sudo pip3 install antlr4-python3-runtime==4.8
sudo pip3 install networkx

Note: python version >= 3.8 is required.

3. Checkout the code:

git clone https://github.com/Hacker0912/RecStep/

• We need to change the value of "Quickstep_Shell_Dir" in "Config.json" to be the directory containing the compiled Quickstep executable binaries (quickstep_client and quickstep_cli_shell). For example, if quickstep-datalog repo is cloned into the path /fastdisk/local/quickstep-datalog, then you should set the value to be "/fastdisk/local/quickstep-datalog/build"

• You can also change the values of other configuraiton variables in "Config.json" for your purposes, such as the input data directory Input_Dir and the number of threads you want to use when running RecStep threads_num. But I recommend you to keep other configuration values as they are for easiness. Also, the Logging, Debug configuration variables were only there for debugging/analysis purposes just as their names suggest - so you can just leave them unchanged. Optimization configuration variables are already set in the optimal way as stated in the paper, but we may temporarily need to change them a little bit for now if we want to run datalog programs involving recursive-aggregation (e.g., benchmark_programs/cc.datalog, benchmark_programs/sssp.datalog) - set dynamic_set_diff to be false. This is mainly due to the emerging bugs recently found in the backend due to the third-party dependency updates.

That's it! And now you can start playing with RecStep, let's get into more details with a toy example:

1. You should first define the datalog program including IDB/EDB relations along with the datalog rules. Example datalog program files are provided in the folder benchmark_datalog_programs, the suffix of which is ".datalog". The syntax is very simple and it should be easy to follow what are presented in these examples and write your own datalog program. As a research prototype, we note that we mainly focus relations in which all data types are int. Though RecStep techniqcally supports other data types that are supported by Quickstep as well, we have not fully teseted these types and we hope users are aware of this fact when they are trying RecStep. We will use tc.datalog here as an example due to its simplicity.

2. Now you should put the input files (which should be in csv format as required) into the input directory as configured earlier (which by default is "./Input"). For example, in tc.datalog, the only input/EDB is arc(x int, y int), a relation with two integer attributes. Then the input file should have exactly the same name as the relation plus the .csv after. Each line of the input file represents a single tuple and attributes are seperated by ','. An example file could also be found in the folder Input.

3. Finally, you can start run RecStep to evaluate the datalog program

python3 interpreter.py --program <datalog_program_file_path> 

For this specific example, you should run the command:

python3 interpreter.py --program ./benchmark_datalog_programs/tc.datalog

5. Check your results directly using the interactive quickstep shell: One of the advantage of RecStep is that after running your program, you can look at your results and may perform further analysis using by running familiar SQL queries! To enter the quickstep shell in the interactive mode, run the command:

python3 quickstep_shell.py --mode interactive

command "\d" could be used to list all the tables in the current quickstep database instance. The "qsstor" folder contains all the data files of the current database instance. More details regarding the use of quickstep can be found at Quickstep. If you encounter other issues when using RecStep or the quickstep shell, you could send an email to zhiwei@cs.wisc.edu for more help and we will get back to you at our earliest convenience.

Note: Parallel Bit-Matrix Evaluation (PBME) has not been intergrated into the RecStep compiler yet. PBME has been designed/implemented specifically for the "dense graph" computation to prove its efficiency in cases where the size of input graph is relatively small in terms of number of vertices but the intermediate results are huge. We currently support PBME evaluation on Transitive Closure (tc) and Same Generation (sg) as stated in the paper but they are not directly runnable from the compiler itself.

Running Recstep directly through command line from any directory

It is possible to run RecStep directly through the command line from any directory and overwrite the configraution values at runtime for convenience of experiments. To achieve this, a few additional simple steps are needed:

1. Generate the executable RecStep file named "recstep" and add the directory in which RecStep is installed to $PATH variable:

./configure

2. Add the directory in which the configuration json file (named Config.json) is located to the environment variable CONFIG_FILE_DIR. For example, if the Recstep is install in the directory /fastdisk/RecStep and there is a configuration file under the directory (/fastdisk/RecStep/Config.json), you could execute the following bash commands:

echo "export CONFIG_FILE_DIR=/fastdisk/RecStep" >> ~/.bashrc
source ~/.bashrc

3. Then you should be able to run recstep directly through the command line:

recstep --program <Datalog Program Path> --input <Input Directory> --jobs <Workers/Number of Threads>