FinBench DataGen
The LDBC FinBench Data Generator (Datagen) produces the datasets for
the LDBC FinBench's workloads.
This data generator produces labelled directred property graphs based on the simulation of financial activities in
business systems. The key features include generation, factorization and transformation. A detailed description of the
schema produced by Datagen, as well as the format of the output files, can be found in the latest version of official
LDBC FinBench specification document.
DataGen Design
Data Schema
Implementation
- Generation: Generation simulates financial activities in business systems to produce the raw data.
- Factorization: Factorization profiles of the raw data to produce factor tables used for further parameter curation.
- Transformation: Transformation transforms the raw data to the data for SUT and benchmark driver.
Note:
- Generation and Factorization are implemented in Scala while transformation is implemented in Python
under
transformation/
.
- SUT stands for System Under Test.
Quick Start
Pre-requisites
- Java 8 installed.
- Python3 and related packages installed. See each
install-dependencies.sh
for details.
- Scala 2.12, note that it will be integrated when maven builds.
- Spark deployed. Spark 3.2.x is the recommended runtime to use. The rest of the instructions are provided assuming
Spark 3.2.x.
Workflow
- Use the spark application to generate the factor tables and raw data.
- Use the python scripts to transform the data to snapshot data and write queries.
Generation of Raw Data
- Deploy Spark
- use
scripts/get-spark-to-home.sh
to download pre-built spark to home directory and then decompress it.
- Set the PATH environment variable to include the Spark binaries.
- Build the project
- run
mvn clean package -DskipTests
to package the artifacts.
- Run locally with scripts
- See
scripts/run_local.sh
for details. It uses spark-submit to run the data generator. Please make sure you have
the pre-requisites installed and the build is successful.
- Run in cloud: To be supported
- Run in cluster: To be supported
Transformation of Raw Data
- set the
${FinBench_DATA_ROOT}
variable in transformation/transform.sh
and run.
TroubleShooting
N/A yet
Related Work