adriangbot commented on PR #25096: URL: https://github.com/apache/datafusion/pull/25096#issuecomment-5596029140
Benchmark for [this request](https://github.com/apache/datafusion/pull/25096#issuecomment-5595863294) failed before finishing (Kubernetes reason: `BackoffLimitExceeded`). Benchmarks requested: `array_agg_distinct` <details><summary>Runner log (last 40 lines)</summary> ``` h2o_big_window_sorted: Window Top-N over a declared-sorted h2o input, large dataset (1e9 rows), default file format is csv h2o_small_window_sorted_parquet: Window Top-N over a declared-sorted h2o input, small dataset (1e7 rows), source file format is parquet h2o_medium_window_sorted_parquet: Window Top-N over a declared-sorted h2o input, medium dataset (1e8 rows), source file format is parquet h2o_big_window_sorted_parquet: Window Top-N over a declared-sorted h2o input, large dataset (1e9 rows), source file format is parquet h2o_small_parquet: h2oai benchmark with small dataset (1e7 rows) for groupby, file format is parquet h2o_medium_parquet: h2oai benchmark with medium dataset (1e8 rows) for groupby, file format is parquet h2o_big_parquet: h2oai benchmark with large dataset (1e9 rows) for groupby, file format is parquet h2o_small_join_parquet: h2oai benchmark with small dataset (1e7 rows) for join, file format is parquet h2o_medium_join_parquet: h2oai benchmark with medium dataset (1e8 rows) for join, file format is parquet h2o_big_join_parquet: h2oai benchmark with large dataset (1e9 rows) for join, file format is parquet h2o_small_window_parquet: Extended h2oai benchmark with small dataset (1e7 rows) for window, file format is parquet h2o_medium_window_parquet: Extended h2oai benchmark with medium dataset (1e8 rows) for window, file format is parquet h2o_big_window_parquet: Extended h2oai benchmark with large dataset (1e9 rows) for window, file format is parquet # Join Order Benchmark (IMDB) imdb: Join Order Benchmark (JOB) using the IMDB dataset converted to parquet # Micro-Benchmarks (specific operators and features) cancellation: How long cancelling a query takes nlj: Benchmark for simple nested loop joins, testing various join scenarios hj: Benchmark for simple hash joins, testing various join scenarios smj: Benchmark for simple sort merge joins, testing various join scenarios dict: Benchmark for dictionary-encoded group-by scenarios compile_profile: Compile and execute TPC-H across selected Cargo profiles, reporting timing and binary size ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Supported Configuration (Environment Variables) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DATA_DIR directory to store datasets CARGO_COMMAND command that runs the benchmark binary DATAFUSION_DIR directory to use (default /workspace/datafusion-base) RESULTS_NAME folder where the benchmark files are stored PREFER_HASH_JOIN Prefer hash join algorithm (default true) SIMULATE_LATENCY Simulate object store latency to mimic S3 (default false) DATAFUSION_* Set the given datafusion configuration stderr: ``` </details> <details><summary>Kubernetes message</summary> ``` Job has reached the specified backoff limit ``` </details> --- [File an issue](https://github.com/adriangb/datafusion-benchmarking/issues) against this benchmark runner -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
