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LDBC SNB Interactive Umbra implementation

Umbra implementation of the LDBC Social Network Benchmark's Interactive workload.

Setup

The recommended environment is that the benchmark scripts (Bash) and the LDBC driver (Java 8) run on the host machine, while the Umbra database runs in a Docker container. Therefore, the requirements are as follows:

  • Bash
  • Java 8
  • Docker 19+
  • the psycopg2 Python library: scripts/install-dependencies.sh
  • enough free space in the directory ${UMBRA_DATABASE_DIR} (its default value is specified in scripts/vars.sh)

The default configuration of the database (e.g. database name, user, password) is set in the scripts/vars.sh file.

Building the container

Set the UMBRA_URL environment variable and build the container:

export UMBRA_URL=
scripts/build-container.sh

Loading the data set

Umbra uses the same data format at PostgreSQL (CsvMergeForeign).

  1. Set the ${UMBRA_CSV_DIR} environment variable to point to the data set, e.g.:

    export UMBRA_CSV_DIR=`pwd`/../postgres/test-data/

  2. To start the DBMS, create a database and load the data, run:

    scripts/load-in-one-step.sh

Running the benchmark

  1. To run the scripts of benchmark framework, edit the driver/{create-validation-parameters,validate,benchmark}.properties files, then run their script, one of:

    driver/create-validation-parameters.sh
driver/validate.sh
driver/benchmark.sh

⚠️ SNB data sets of different scale factors require different configurations for the benchmark runs. Therefore, make sure you use the correct values (update_interleave and query frequencies) based on the files provided in the sf-properties directory.

  • The default workload contains updates which are persisted in the database. Therefore, the database needs to be reloaded or restored from backup before each run. Use the provided scripts/backup-database.sh and scripts/restore-database.sh scripts to achieve this.