⚡tormFront is a notebook front end for the dbstress concurrency benchmarking tool. It lets the user send multiple queries to a JDBC SQL endpoint without having to navigate too much code or manually edit config files.
⚡tormFront is meant to run in a Databricks workspace, and uses ipywidgets to generate the UI.
Download StormFront.ipynb and import into your Databricks Workspace. Run each cell one by one to select which sql files to run and which SQL endpoint to query.
install StormFront either as a cluster library using git+https://www.github.com/PavanDendi/StormFront as the library name, or as a notebook scoped library using %pip install git+https://www.github.com/PavanDendi/StormFront
Install sqlstorm jar from https://github.com/PavanDendi/sqlstorm/ to your cluster.
Compiled binary can be found in the github Releases HERE, or compile from source using sbt assembly from the sql⚡torm repo root directory.
Cluster can be a single node using a weak instance type since the cluster will only be sending API calls, and processing minimal data itself.
Cluster must be running a DBR version that supports ipykernel. Tested on DBR 10.4 LTS
If using DBR 11+, ipykernel is enabled by default. For 11 > DBR >= 10.3, enable ipykernel by adding to cluster config
spark.databricks.python.defaultPythonRepl ipykernel