chore: update db benchmark config/add notebook load testing session/update readme (#1041)

* chore: update db benchmark config

* update project

Author: Genesis929

.kokoro/continuous/notebook.cfg

@@ -6,11 +6,6 @@ env_vars: {
     value: "notebook"
 }
 
-env_vars: {
-    key: "BENCHMARK_AND_PUBLISH"
-    value: "true"
-}
-
 env_vars: {
     key: "GOOGLE_CLOUD_PROJECT"
     value: "bigframes-testing"

.kokoro/load/notebook.cfg

@@ -0,0 +1,17 @@
+# Format: //devtools/kokoro/config/proto/build.proto
+
+# Only run this nox session.
+env_vars: {
+    key: "NOX_SESSION"
+    value: "notebook"
+}
+
+env_vars: {
+    key: "BENCHMARK_AND_PUBLISH"
+    value: "true"
+}
+
+env_vars: {
+    key: "GOOGLE_CLOUD_PROJECT"
+    value: "bigframes-testing"
+}

tests/benchmark/README.md

@@ -11,6 +11,28 @@ This section lists the benchmarks currently available, with descriptions and lin
 - **TPC-H Benchmark**: Based on the TPC-H standards, this benchmark evaluates transaction processing capabilities. It is adapted from code found in the Polars repository, specifically tailored to test and compare these capabilities. Details are available on the [Polars Benchmark GitHub repository](https://github.com/pola-rs/polars-benchmark).
 - **Notebooks**: These Jupyter notebooks showcase BigFrames' key features and patterns, and also enable performance benchmarking. Explore them at the [BigFrames Notebooks repository](https://github.com/googleapis/python-bigquery-dataframes/tree/main/notebooks).
 
+## Benchmark Configuration Using `config.jsonl` Files
+
+For each benchmark, a corresponding `config.jsonl` file exists in the same folder or its parent folder. These configuration files allow users to control various benchmark parameters without modifying the code directly. By updating the relevant `config.jsonl` file in the specific benchmark's folder, you can easily configure settings such as:
+- **benchmark_suffix**: A suffix appended to the benchmark name for identification purposes.
+- **ordered**: Controls the mode for BigFrames, specifying whether to use ordered (`true`) or unordered mode (`false`).
+- **project_id**: The Google Cloud project ID where the benchmark dataset or table is located.
+- **dataset_id**: The dataset ID for querying during the benchmark.
+- **table_id**: This is **required** for benchmarks like `dbbenchmark` that target a specific table, but is **not configurable** for benchmarks like `TPC-H`, which use multiple tables with fixed names.
+
+### Example `config.jsonl` Files
+
+#### `dbbenchmark` Example
+```jsonl
+{"benchmark_suffix": "50g_ordered", "project_id": "your-google-cloud-project", "dataset_id": "dbbenchmark", "table_id": "G1_1e9_1e2_5_0", "ordered": true}
+{"benchmark_suffix": "50g_unordered", "project_id": "your-google-cloud-project", "dataset_id": "dbbenchmark", "table_id": "G1_1e9_1e2_5_0", "ordered": false}
+```
+
+#### `TPC-H` Example
+```jsonl
+{"benchmark_suffix": "10t_unordered", "project_id":  "your-google-cloud-project", "dataset_id": "tpch_0010t", "ordered": false}
+```
+
 ## Usage Examples
 Our benchmarking process runs internally on a daily basis to continuously monitor the performance of BigFrames. However, there are occasions when you might need to conduct benchmarking locally to test specific changes or new features.
 

tests/benchmark/db_benchmark/groupby/config.jsonl

@@ -1,2 +1,2 @@
-{"benchmark_suffix": "50g_ordered", "table_id": "G1_1e9_1e2_5_0", "ordered": true}
-{"benchmark_suffix": "50g_unordered", "table_id": "G1_1e9_1e2_5_0", "ordered": false}
+{"benchmark_suffix": "50g_ordered", "project_id": "bigframes-dev-perf", "dataset_id": "dbbenchmark", "table_id": "G1_1e9_1e2_5_0", "ordered": true}
+{"benchmark_suffix": "50g_unordered", "project_id": "bigframes-dev-perf", "dataset_id": "dbbenchmark", "table_id": "G1_1e9_1e2_5_0", "ordered": false}

tests/benchmark/db_benchmark/groupby/q1.py

@@ -18,9 +18,21 @@
 import bigframes_vendored.db_benchmark.groupby_queries as vendored_dbbenchmark_groupby_queries
 
 if __name__ == "__main__":
-    table_id, session, suffix = utils.get_dbbenchmark_configuration()
+    (
+        project_id,
+        dataset_id,
+        table_id,
+        session,
+        suffix,
+    ) = utils.get_configuration(include_table_id=True)
     current_path = pathlib.Path(__file__).absolute()
 
     utils.get_execution_time(
-        vendored_dbbenchmark_groupby_queries.q1, current_path, suffix, table_id, session
+        vendored_dbbenchmark_groupby_queries.q1,
+        current_path,
+        suffix,
+        project_id,
+        dataset_id,
+        table_id,
+        session,
     )

tests/benchmark/db_benchmark/groupby/q10.py

@@ -18,13 +18,21 @@
 import bigframes_vendored.db_benchmark.groupby_queries as vendored_dbbenchmark_groupby_queries
 
 if __name__ == "__main__":
-    table_id, session, suffix = utils.get_dbbenchmark_configuration()
+    (
+        project_id,
+        dataset_id,
+        table_id,
+        session,
+        suffix,
+    ) = utils.get_configuration(include_table_id=True)
     current_path = pathlib.Path(__file__).absolute()
 
     utils.get_execution_time(
         vendored_dbbenchmark_groupby_queries.q10,
         current_path,
         suffix,
+        project_id,
+        dataset_id,
         table_id,
         session,
     )

tests/benchmark/db_benchmark/groupby/q2.py

@@ -18,9 +18,21 @@
 import bigframes_vendored.db_benchmark.groupby_queries as vendored_dbbenchmark_groupby_queries
 
 if __name__ == "__main__":
-    table_id, session, suffix = utils.get_dbbenchmark_configuration()
+    (
+        project_id,
+        dataset_id,
+        table_id,
+        session,
+        suffix,
+    ) = utils.get_configuration(include_table_id=True)
     current_path = pathlib.Path(__file__).absolute()
 
     utils.get_execution_time(
-        vendored_dbbenchmark_groupby_queries.q2, current_path, suffix, table_id, session
+        vendored_dbbenchmark_groupby_queries.q2,
+        current_path,
+        suffix,
+        project_id,
+        dataset_id,
+        table_id,
+        session,
     )

tests/benchmark/db_benchmark/groupby/q3.py

@@ -18,9 +18,21 @@
 import bigframes_vendored.db_benchmark.groupby_queries as vendored_dbbenchmark_groupby_queries
 
 if __name__ == "__main__":
-    table_id, session, suffix = utils.get_dbbenchmark_configuration()
+    (
+        project_id,
+        dataset_id,
+        table_id,
+        session,
+        suffix,
+    ) = utils.get_configuration(include_table_id=True)
     current_path = pathlib.Path(__file__).absolute()
 
     utils.get_execution_time(
-        vendored_dbbenchmark_groupby_queries.q3, current_path, suffix, table_id, session
+        vendored_dbbenchmark_groupby_queries.q3,
+        current_path,
+        suffix,
+        project_id,
+        dataset_id,
+        table_id,
+        session,
     )

tests/benchmark/db_benchmark/groupby/q4.py

@@ -18,9 +18,21 @@
 import bigframes_vendored.db_benchmark.groupby_queries as vendored_dbbenchmark_groupby_queries
 
 if __name__ == "__main__":
-    table_id, session, suffix = utils.get_dbbenchmark_configuration()
+    (
+        project_id,
+        dataset_id,
+        table_id,
+        session,
+        suffix,
+    ) = utils.get_configuration(include_table_id=True)
     current_path = pathlib.Path(__file__).absolute()
 
     utils.get_execution_time(
-        vendored_dbbenchmark_groupby_queries.q4, current_path, suffix, table_id, session
+        vendored_dbbenchmark_groupby_queries.q4,
+        current_path,
+        suffix,
+        project_id,
+        dataset_id,
+        table_id,
+        session,
     )

tests/benchmark/db_benchmark/groupby/q5.py

@@ -18,9 +18,21 @@
 import bigframes_vendored.db_benchmark.groupby_queries as vendored_dbbenchmark_groupby_queries
 
 if __name__ == "__main__":
-    table_id, session, suffix = utils.get_dbbenchmark_configuration()
+    (
+        project_id,
+        dataset_id,
+        table_id,
+        session,
+        suffix,
+    ) = utils.get_configuration(include_table_id=True)
     current_path = pathlib.Path(__file__).absolute()
 
     utils.get_execution_time(
-        vendored_dbbenchmark_groupby_queries.q5, current_path, suffix, table_id, session
+        vendored_dbbenchmark_groupby_queries.q5,
+        current_path,
+        suffix,
+        project_id,
+        dataset_id,
+        table_id,
+        session,
     )