[2025-01-10T21:39:54.367Z] Running test renaissance-movie-lens_0 ... [2025-01-10T21:39:54.367Z] =============================================== [2025-01-10T21:39:54.367Z] renaissance-movie-lens_0 Start Time: Fri Jan 10 15:39:54 2025 Epoch Time (ms): 1736545194322 [2025-01-10T21:39:54.367Z] variation: NoOptions [2025-01-10T21:39:54.367Z] JVM_OPTIONS: [2025-01-10T21:39:54.367Z] { \ [2025-01-10T21:39:54.367Z] echo ""; echo "TEST SETUP:"; \ [2025-01-10T21:39:54.367Z] echo "Nothing to be done for setup."; \ [2025-01-10T21:39:54.367Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17365445999324/renaissance-movie-lens_0"; \ [2025-01-10T21:39:54.367Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17365445999324/renaissance-movie-lens_0"; \ [2025-01-10T21:39:54.367Z] echo ""; echo "TESTING:"; \ [2025-01-10T21:39:54.367Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17365445999324/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-01-10T21:39:54.367Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17365445999324/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-01-10T21:39:54.367Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-01-10T21:39:54.367Z] echo "Nothing to be done for teardown."; \ [2025-01-10T21:39:54.367Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17365445999324/TestTargetResult"; [2025-01-10T21:39:54.367Z] [2025-01-10T21:39:54.367Z] TEST SETUP: [2025-01-10T21:39:54.367Z] Nothing to be done for setup. [2025-01-10T21:39:54.367Z] [2025-01-10T21:39:54.367Z] TESTING: [2025-01-10T21:39:57.419Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-01-10T21:39:58.825Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2025-01-10T21:40:01.161Z] Got 100004 ratings from 671 users on 9066 movies. [2025-01-10T21:40:01.843Z] Training: 60056, validation: 20285, test: 19854 [2025-01-10T21:40:01.843Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-01-10T21:40:01.843Z] GC before operation: completed in 99.448 ms, heap usage 99.596 MB -> 37.867 MB. [2025-01-10T21:40:08.121Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:40:12.161Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:40:15.663Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:40:17.917Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:40:19.355Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:40:20.763Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:40:22.178Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:40:23.611Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:40:24.289Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:40:24.289Z] The best model improves the baseline by 14.43%. [2025-01-10T21:40:24.289Z] Movies recommended for you: [2025-01-10T21:40:24.289Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:40:24.289Z] There is no way to check that no silent failure occurred. [2025-01-10T21:40:24.289Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22496.589 ms) ====== [2025-01-10T21:40:24.289Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-01-10T21:40:24.289Z] GC before operation: completed in 111.809 ms, heap usage 196.220 MB -> 50.734 MB. [2025-01-10T21:40:27.384Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:40:30.454Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:40:32.661Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:40:34.860Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:40:36.276Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:40:37.704Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:40:39.118Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:40:40.548Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:40:40.548Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:40:40.548Z] The best model improves the baseline by 14.43%. [2025-01-10T21:40:41.223Z] Movies recommended for you: [2025-01-10T21:40:41.223Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:40:41.223Z] There is no way to check that no silent failure occurred. [2025-01-10T21:40:41.223Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16660.773 ms) ====== [2025-01-10T21:40:41.223Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-01-10T21:40:41.223Z] GC before operation: completed in 51.218 ms, heap usage 278.957 MB -> 51.637 MB. [2025-01-10T21:40:44.279Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:40:46.506Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:40:48.732Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:40:51.818Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:40:52.525Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:40:53.944Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:40:55.347Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:40:56.754Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:40:56.754Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:40:56.754Z] The best model improves the baseline by 14.43%. [2025-01-10T21:40:56.754Z] Movies recommended for you: [2025-01-10T21:40:56.754Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:40:56.754Z] There is no way to check that no silent failure occurred. [2025-01-10T21:40:56.754Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15951.960 ms) ====== [2025-01-10T21:40:56.754Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-01-10T21:40:56.754Z] GC before operation: completed in 69.886 ms, heap usage 335.974 MB -> 52.179 MB. [2025-01-10T21:40:59.804Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:41:02.036Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:41:04.265Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:41:05.681Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:41:07.092Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:41:08.502Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:41:09.908Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:41:11.334Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:41:11.334Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:41:11.334Z] The best model improves the baseline by 14.43%. [2025-01-10T21:41:11.334Z] Movies recommended for you: [2025-01-10T21:41:11.334Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:41:11.334Z] There is no way to check that no silent failure occurred. [2025-01-10T21:41:11.334Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14533.731 ms) ====== [2025-01-10T21:41:11.334Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-01-10T21:41:11.334Z] GC before operation: completed in 47.946 ms, heap usage 76.674 MB -> 56.271 MB. [2025-01-10T21:41:13.596Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:41:15.828Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:41:18.054Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:41:20.256Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:41:20.936Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:41:22.353Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:41:23.756Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:41:25.187Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:41:25.187Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:41:25.187Z] The best model improves the baseline by 14.43%. [2025-01-10T21:41:25.187Z] Movies recommended for you: [2025-01-10T21:41:25.187Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:41:25.187Z] There is no way to check that no silent failure occurred. [2025-01-10T21:41:25.187Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (13704.609 ms) ====== [2025-01-10T21:41:25.187Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-01-10T21:41:25.187Z] GC before operation: completed in 64.465 ms, heap usage 150.972 MB -> 52.581 MB. [2025-01-10T21:41:27.850Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:41:30.047Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:41:32.262Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:41:34.510Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:41:35.186Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:41:36.612Z] RMSE (validation) = 1.117495376637101 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:41:38.023Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:41:39.448Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:41:39.448Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:41:39.448Z] The best model improves the baseline by 14.43%. [2025-01-10T21:41:39.448Z] Movies recommended for you: [2025-01-10T21:41:39.448Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:41:39.448Z] There is no way to check that no silent failure occurred. [2025-01-10T21:41:39.448Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14099.521 ms) ====== [2025-01-10T21:41:39.448Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-01-10T21:41:39.448Z] GC before operation: completed in 53.341 ms, heap usage 241.073 MB -> 52.591 MB. [2025-01-10T21:41:41.656Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:41:43.880Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:41:46.098Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:41:47.516Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:41:48.919Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:41:50.348Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:41:51.806Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:41:52.496Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:41:53.180Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:41:53.180Z] The best model improves the baseline by 14.43%. [2025-01-10T21:41:53.180Z] Movies recommended for you: [2025-01-10T21:41:53.180Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:41:53.180Z] There is no way to check that no silent failure occurred. [2025-01-10T21:41:53.180Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13658.196 ms) ====== [2025-01-10T21:41:53.180Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-01-10T21:41:53.180Z] GC before operation: completed in 59.702 ms, heap usage 203.710 MB -> 55.902 MB. [2025-01-10T21:41:55.382Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:41:57.597Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:41:59.814Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:42:02.025Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:42:03.455Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:42:04.134Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:42:05.551Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:42:07.006Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:42:07.006Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:42:07.006Z] The best model improves the baseline by 14.43%. [2025-01-10T21:42:07.684Z] Movies recommended for you: [2025-01-10T21:42:07.684Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:42:07.684Z] There is no way to check that no silent failure occurred. [2025-01-10T21:42:07.684Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14127.501 ms) ====== [2025-01-10T21:42:07.684Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-01-10T21:42:07.684Z] GC before operation: completed in 84.108 ms, heap usage 795.594 MB -> 58.603 MB. [2025-01-10T21:42:09.960Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:42:12.162Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:42:14.364Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:42:15.792Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:42:17.204Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:42:18.620Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:42:20.049Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:42:20.746Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:42:21.430Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:42:21.430Z] The best model improves the baseline by 14.43%. [2025-01-10T21:42:21.430Z] Movies recommended for you: [2025-01-10T21:42:21.430Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:42:21.430Z] There is no way to check that no silent failure occurred. [2025-01-10T21:42:21.430Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13937.971 ms) ====== [2025-01-10T21:42:21.430Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-01-10T21:42:21.430Z] GC before operation: completed in 56.270 ms, heap usage 243.708 MB -> 52.666 MB. [2025-01-10T21:42:23.626Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:42:25.833Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:42:28.029Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:42:29.444Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:42:31.297Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:42:31.974Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:42:33.383Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:42:34.815Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:42:34.815Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:42:34.815Z] The best model improves the baseline by 14.43%. [2025-01-10T21:42:34.815Z] Movies recommended for you: [2025-01-10T21:42:34.815Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:42:34.815Z] There is no way to check that no silent failure occurred. [2025-01-10T21:42:34.815Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13553.817 ms) ====== [2025-01-10T21:42:34.815Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-01-10T21:42:34.815Z] GC before operation: completed in 61.599 ms, heap usage 634.439 MB -> 56.532 MB. [2025-01-10T21:42:37.031Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:42:39.251Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:42:41.464Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:42:43.681Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:42:44.371Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:42:45.779Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:42:47.199Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:42:48.622Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:42:48.622Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:42:48.622Z] The best model improves the baseline by 14.43%. [2025-01-10T21:42:48.622Z] Movies recommended for you: [2025-01-10T21:42:48.622Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:42:48.622Z] There is no way to check that no silent failure occurred. [2025-01-10T21:42:48.622Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13610.375 ms) ====== [2025-01-10T21:42:48.622Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-01-10T21:42:48.622Z] GC before operation: completed in 54.942 ms, heap usage 346.111 MB -> 52.731 MB. [2025-01-10T21:42:50.831Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:42:53.044Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:42:55.247Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:42:56.662Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:42:58.076Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:42:59.488Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:43:00.902Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:43:02.337Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:43:02.337Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:43:02.337Z] The best model improves the baseline by 14.43%. [2025-01-10T21:43:02.337Z] Movies recommended for you: [2025-01-10T21:43:02.337Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:43:02.337Z] There is no way to check that no silent failure occurred. [2025-01-10T21:43:02.337Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13606.480 ms) ====== [2025-01-10T21:43:02.337Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-01-10T21:43:02.337Z] GC before operation: completed in 53.231 ms, heap usage 348.484 MB -> 52.890 MB. [2025-01-10T21:43:04.547Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:43:06.756Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:43:08.975Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:43:10.400Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:43:11.821Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:43:13.247Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:43:14.674Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:43:16.100Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:43:16.100Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:43:16.100Z] The best model improves the baseline by 14.43%. [2025-01-10T21:43:16.100Z] Movies recommended for you: [2025-01-10T21:43:16.100Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:43:16.100Z] There is no way to check that no silent failure occurred. [2025-01-10T21:43:16.100Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13874.875 ms) ====== [2025-01-10T21:43:16.100Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-01-10T21:43:16.100Z] GC before operation: completed in 77.931 ms, heap usage 252.189 MB -> 53.030 MB. [2025-01-10T21:43:18.331Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:43:20.555Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:43:22.771Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:43:24.987Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:43:25.686Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:43:27.098Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:43:28.505Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:43:29.940Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:43:29.940Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:43:29.940Z] The best model improves the baseline by 14.43%. [2025-01-10T21:43:29.940Z] Movies recommended for you: [2025-01-10T21:43:29.940Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:43:29.940Z] There is no way to check that no silent failure occurred. [2025-01-10T21:43:29.940Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13562.487 ms) ====== [2025-01-10T21:43:29.940Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-01-10T21:43:29.940Z] GC before operation: completed in 59.362 ms, heap usage 557.668 MB -> 56.295 MB. [2025-01-10T21:43:32.136Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:43:34.846Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:43:36.271Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:43:38.495Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:43:39.907Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:43:40.600Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:43:42.028Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:43:43.446Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:43:43.446Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:43:43.446Z] The best model improves the baseline by 14.43%. [2025-01-10T21:43:43.446Z] Movies recommended for you: [2025-01-10T21:43:43.446Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:43:43.446Z] There is no way to check that no silent failure occurred. [2025-01-10T21:43:43.446Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13617.029 ms) ====== [2025-01-10T21:43:43.446Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-01-10T21:43:43.446Z] GC before operation: completed in 58.420 ms, heap usage 380.002 MB -> 53.167 MB. [2025-01-10T21:43:45.682Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:43:47.901Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:43:50.097Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:43:52.297Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:43:53.736Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:43:54.413Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:43:55.874Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:43:57.295Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:43:57.295Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:43:57.982Z] The best model improves the baseline by 14.43%. [2025-01-10T21:43:57.982Z] Movies recommended for you: [2025-01-10T21:43:57.982Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:43:57.982Z] There is no way to check that no silent failure occurred. [2025-01-10T21:43:57.982Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14123.605 ms) ====== [2025-01-10T21:43:57.982Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-01-10T21:43:57.982Z] GC before operation: completed in 66.605 ms, heap usage 778.577 MB -> 56.920 MB. [2025-01-10T21:44:00.175Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:44:02.394Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:44:04.621Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:44:06.037Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:44:07.494Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:44:08.913Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:44:09.612Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:44:11.019Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:44:11.019Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:44:11.019Z] The best model improves the baseline by 14.43%. [2025-01-10T21:44:11.020Z] Movies recommended for you: [2025-01-10T21:44:11.020Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:44:11.020Z] There is no way to check that no silent failure occurred. [2025-01-10T21:44:11.020Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13409.540 ms) ====== [2025-01-10T21:44:11.020Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-01-10T21:44:11.020Z] GC before operation: completed in 50.569 ms, heap usage 132.047 MB -> 52.791 MB. [2025-01-10T21:44:13.238Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:44:15.437Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:44:17.637Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:44:19.861Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:44:20.549Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:44:21.959Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:44:23.408Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:44:24.810Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:44:24.810Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:44:24.810Z] The best model improves the baseline by 14.43%. [2025-01-10T21:44:24.810Z] Movies recommended for you: [2025-01-10T21:44:24.810Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:44:24.810Z] There is no way to check that no silent failure occurred. [2025-01-10T21:44:24.810Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13570.109 ms) ====== [2025-01-10T21:44:24.810Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-01-10T21:44:24.810Z] GC before operation: completed in 51.816 ms, heap usage 444.940 MB -> 53.077 MB. [2025-01-10T21:44:27.005Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:44:29.192Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:44:31.386Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:44:32.795Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:44:34.201Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:44:35.628Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:44:37.060Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:44:37.744Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:44:38.651Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:44:38.651Z] The best model improves the baseline by 14.43%. [2025-01-10T21:44:38.651Z] Movies recommended for you: [2025-01-10T21:44:38.651Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:44:38.651Z] There is no way to check that no silent failure occurred. [2025-01-10T21:44:38.651Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13391.575 ms) ====== [2025-01-10T21:44:38.651Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-01-10T21:44:38.651Z] GC before operation: completed in 49.789 ms, heap usage 352.758 MB -> 53.347 MB. [2025-01-10T21:44:40.887Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-10T21:44:42.349Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-10T21:44:44.647Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-10T21:44:46.074Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-10T21:44:47.488Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-10T21:44:48.907Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-10T21:44:50.335Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-10T21:44:51.017Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-10T21:44:51.694Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-01-10T21:44:51.694Z] The best model improves the baseline by 14.43%. [2025-01-10T21:44:51.694Z] Movies recommended for you: [2025-01-10T21:44:51.694Z] WARNING: This benchmark provides no result that can be validated. [2025-01-10T21:44:51.694Z] There is no way to check that no silent failure occurred. [2025-01-10T21:44:51.694Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13249.130 ms) ====== [2025-01-10T21:44:52.372Z] ----------------------------------- [2025-01-10T21:44:52.372Z] renaissance-movie-lens_0_PASSED [2025-01-10T21:44:52.372Z] ----------------------------------- [2025-01-10T21:44:52.372Z] [2025-01-10T21:44:52.372Z] TEST TEARDOWN: [2025-01-10T21:44:52.372Z] Nothing to be done for teardown. [2025-01-10T21:44:52.372Z] renaissance-movie-lens_0 Finish Time: Fri Jan 10 15:44:52 2025 Epoch Time (ms): 1736545492324