CROP: Robust Query Processing for Linked Data Fragments

A query engine to execute SPARQL queries over Triple Pattern Fragments using a cost- and robustness-based query plan optimization strategy. The engine also supports Polymorphic Bind Join operators to additionally support robust query execution. The implementation of the engine is based on the Network of Linked Data Eddies.

Installation

The engine is implemented in Python 2.7. It is advised to use a virtual environment for the installation in the following way:

# Install virtualenv
[sudo] python2 -m pip install virtualenv 

# Create a virtual environment
[sudo] python2 -m virtualenv venv

# Activate the environment
source venv/bin/activate

# Install the requirements
python -m pip install -r requirements.txt

Once the requirements are installed, the engine can be executed using the command line.

Usage

Required Parameters:

• -f: SAPRQL Query Filepath
• -s: (TPF) Server to be contacted
• -c: Configuration file for the query planner. (e.g. CROP, nLDE, LDP) Example:

venv/bin/python crop.py -f example.rq -s http://fragments.dbpedia.org/2014/en -c configs/crop_default.yaml

Note that the engine currently only supports conjunctive SPARQL queries (BGPs).

Configuration

The configuration file allows for specifying the parameter for the exectution engine as well as the query planning approach. A set of basic configurations for different planning approaches is provided in the configs directory. The following options can be configured (Note that some combinations might be exclusive):

Execution engine (nLDE)

• eddies: Number of eddies
• timeout: Timeout of the execution in seconds

Planner (crop)

• optimizer: Query planning approach: crop, nlde, left-linear

• height_discount: Cost model: delta value (crop only)

• cost_threshold: Planner: cost threshold gamma (crop only)

• robust_threshold: Planner: robustness threshold rho (crop only)

• top_t: Planner: Top t plans to consider in planner

• k: IDP: block size parameter (crop only)

• adaptive_k: IDP: enable adatptive block size in the planner (crop only)

Operators (operators)

• hash_join_only: HJ: Only place HJ operators (left-linear only)

• poly_hash_join: PHJ: Enable PHJ operator

• hj_request_cost_factor: PHJ: epsilon parameter value of the PHJ

• bind_join_only: BJ: Only place BJ operators (left-linear only)

• poly_bind_join: PBJ: Enable PBJ operator

• poly_bind_rule: PBJ: Set the switch rule of the operator (1/sqrt(T) = 2)

Help

You can find the help using:

venv/bin/python crop.py -h

and get the usage options:

usage: crop.py [-h] -s SOURCES [SOURCES ...] -c CONFIG -f QUERYFILE
               [-o {y,f,dief,all}] [-l {INFO,DEBUG}] [-p]

CROP: An nLDE-based TPF Client supporting different query planning approaches
and polymorphic join operators.

optional arguments:
  -h, --help            show this help message and exit
  -s SOURCES [SOURCES ...], --sources SOURCES [SOURCES ...]
                        URL of the triple pattern fragment servers (required)
  -c CONFIG, --config CONFIG
                        Configuration YAML file. Including options for
                        execution engine, planner, and operators (required)
  -f QUERYFILE, --queryfile QUERYFILE
                        file name of the SPARQL query (required)
  -o {y,f,dief,all}, --output {y,f,dief,all}
                        Format of the output (optional)
  -l {INFO,DEBUG}, --log {INFO,DEBUG}
                        Logging configuration (optional)
  -p, --planning        Just obtain the plan. Do not execute the plan
                        (optional)

Supplemental Material

The supplemental material including the experimental results and analyis are provided in the CROP Analysis repository.

How to Cite

Lars Heling, Maribel Acosta. 
"Cost- and Robustness-based Query Optimization for Triple Pattern Fragment Clients" 
International Semantic Web Conference 2020.

License

This project is licensed under the MIT License.