In the Pipeline execution engine, we split the execution plan tree of each Instance into multiple small Pipeline Tasks and execute them under our custom Pipeline scheduler. Therefore, in an environment with a large number of Pipeline Tasks executing, how these Tasks are scheduled across threads and CPU cores is an important factor for execution performance. We have developed a specialised tool to observe the scheduling process on a particular query or time period, which we call "Pipeline Tracing".
This tool converts record files to proper JSON format for visualization.
python3 origin-to-show.py -s <SOURCE_FILE> -d <DEST>.jsonto transfer record file <SOURCE_FILE> to <DEST>.json. Then it could be visualized.
python3 origin-to-show.py --helpfor help details.