[GLUTEN-7641][VL] Add perf analysis scripts for TPCH workload

.gitignore

@@ -98,3 +98,5 @@ dist/
 
 # For Hive
 metastore_db/
+
+.ipynb_checkpoints

tools/workload/benchmark_velox/README.md

@@ -36,3 +36,30 @@ We also provide a script [run_tpc_workload.sh](./run_tpc_workload.sh). This scri
 ## Analyzing Performance Results
 
 You can check the **Show Performance** section in the output notebook after execution. It shows the cpu% per query, and draws charts for the cpu%, memory throughput, disk throughput/util%, network throughput and pagefaults.
+
+## Set up Performance Analysis Tools
+
+Please check the **Set up perf analysis tools (optional)** section in [initialize.ipynb](./initialize.ipynb) to set up the environment required for running performance analysis scripts. Once the setup is complete, update the following variables in your YAML file (as documented in [params.yaml.template](./params.yaml.template)) before running TPC-H/TPC-DS Benchmarks:
+
+- server: Hostname or IP to server for perf analysis. Able to connect via ssh. Can be localhost if you deploy the perf analysis scripts on the local cluster.
+- base_dir: Specify the directory on perf analysis server. Usually a codename for this run.
+- analyze_perf: Whether to upload profile to perf analysis server and run perf analysis scripts. Only takes effect if server is set. In this case set to `True`
+- proxy: Proxy used to connect to server for perf analysis. Only needed if the perf analysis server is accessed via proxy.
+
+After the workload completes, the tool generates a notebook, executes it automatically, and saves the output notebook in the `$HOME/PAUS/base_dir` directory with a suffix of `[APPLICATION ID].nbconvert.ipynb`. Additionally, the output notebook is converted into an HTML format for improved readability, with the same filename, and stored in the `html` sub-folder.
+
+A sample generated notebook for TPCH Q1 and its corresponding HTML file are available for reference:
+- Notebook: [tpch_q1.nbconvert.ipynb](./sample/tpch_q1.nbconvert.ipynb)
+- HTML file: [tpch_q1.html](./sample/tpch_q1.html)
+
+The notebook also produces a trace-viewer JSON file to analyze workload statistics. This includes SAR metrics and stage/task-level breakdowns. Using this tool, users can compare statistics across stages and queries, identify performance bottlenecks, and target specific stages for optimization.
+
+You can explore the sample trace-viewer JSON file using the Google Chrome browser. To do so: 
+
+1. Download the sample file [trace_result_tpch_q1.json](./sample/trace_result_tpch_q1.json)
+2. Launch Google Chrome. In the address bar, enter "chrome://tracing/".
+3. Use the "Load" button to upload the sample JSON file.
+
+This will allow you to check the sample trace data interactively.
+
+![trace-result-tpch-q1](./sample/Trace-viewer.png)