[2025-01-14T10:20:43.218Z] Running test renaissance-movie-lens_0 ... [2025-01-14T10:20:43.218Z] =============================================== [2025-01-14T10:20:43.218Z] renaissance-movie-lens_0 Start Time: Tue Jan 14 10:20:43 2025 Epoch Time (ms): 1736850043165 [2025-01-14T10:20:43.556Z] variation: NoOptions [2025-01-14T10:20:43.556Z] JVM_OPTIONS: [2025-01-14T10:20:43.556Z] { \ [2025-01-14T10:20:43.556Z] echo ""; echo "TEST SETUP:"; \ [2025-01-14T10:20:43.556Z] echo "Nothing to be done for setup."; \ [2025-01-14T10:20:43.556Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/aqa-tests/\\TKG\\output_17368492198530\\renaissance-movie-lens_0"; \ [2025-01-14T10:20:43.556Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/aqa-tests/\\TKG\\output_17368492198530\\renaissance-movie-lens_0"; \ [2025-01-14T10:20:43.556Z] echo ""; echo "TESTING:"; \ [2025-01-14T10:20:43.556Z] "c:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/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 "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/aqa-tests/\\TKG\\output_17368492198530\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-01-14T10:20:43.556Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/aqa-tests/\\TKG\\output_17368492198530\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-01-14T10:20:43.556Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-01-14T10:20:43.556Z] echo "Nothing to be done for teardown."; \ [2025-01-14T10:20:43.556Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/aqa-tests/\\TKG\\output_17368492198530\\TestTargetResult"; [2025-01-14T10:20:43.556Z] [2025-01-14T10:20:43.556Z] TEST SETUP: [2025-01-14T10:20:43.556Z] Nothing to be done for setup. [2025-01-14T10:20:43.556Z] [2025-01-14T10:20:43.556Z] TESTING: [2025-01-14T10:20:59.281Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2025-01-14T10:20:59.281Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-01-14T10:21:03.103Z] Got 100004 ratings from 671 users on 9066 movies. [2025-01-14T10:21:03.103Z] Training: 60056, validation: 20285, test: 19854 [2025-01-14T10:21:03.103Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-01-14T10:21:03.103Z] GC before operation: completed in 68.435 ms, heap usage 44.482 MB -> 37.515 MB. [2025-01-14T10:21:16.687Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:21:25.494Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:21:36.223Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:21:43.426Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:21:48.177Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:21:52.857Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:21:57.548Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:22:02.295Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:22:03.075Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:22:03.075Z] The best model improves the baseline by 14.52%. [2025-01-14T10:22:03.075Z] Movies recommended for you: [2025-01-14T10:22:03.075Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:22:03.075Z] There is no way to check that no silent failure occurred. [2025-01-14T10:22:03.075Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (60156.885 ms) ====== [2025-01-14T10:22:03.075Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-01-14T10:22:03.468Z] GC before operation: completed in 75.201 ms, heap usage 79.120 MB -> 52.745 MB. [2025-01-14T10:22:12.235Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:22:21.048Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:22:28.251Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:22:35.446Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:22:40.136Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:22:44.873Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:22:49.559Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:22:54.281Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:22:54.281Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:22:54.281Z] The best model improves the baseline by 14.52%. [2025-01-14T10:22:54.281Z] Movies recommended for you: [2025-01-14T10:22:54.281Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:22:54.281Z] There is no way to check that no silent failure occurred. [2025-01-14T10:22:54.281Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (51135.895 ms) ====== [2025-01-14T10:22:54.281Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-01-14T10:22:54.622Z] GC before operation: completed in 70.753 ms, heap usage 390.423 MB -> 53.435 MB. [2025-01-14T10:23:01.814Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:23:10.616Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:23:17.822Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:23:26.640Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:23:30.386Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:23:35.083Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:23:39.761Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:23:43.486Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:23:44.194Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:23:44.194Z] The best model improves the baseline by 14.52%. [2025-01-14T10:23:44.194Z] Movies recommended for you: [2025-01-14T10:23:44.194Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:23:44.194Z] There is no way to check that no silent failure occurred. [2025-01-14T10:23:44.195Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (49825.713 ms) ====== [2025-01-14T10:23:44.195Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-01-14T10:23:44.195Z] GC before operation: completed in 67.476 ms, heap usage 318.895 MB -> 50.471 MB. [2025-01-14T10:23:53.016Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:24:00.217Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:24:09.013Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:24:16.196Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:24:19.927Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:24:23.636Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:24:28.324Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:24:33.012Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:24:33.012Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:24:33.012Z] The best model improves the baseline by 14.52%. [2025-01-14T10:24:33.345Z] Movies recommended for you: [2025-01-14T10:24:33.345Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:24:33.345Z] There is no way to check that no silent failure occurred. [2025-01-14T10:24:33.345Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (48951.369 ms) ====== [2025-01-14T10:24:33.345Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-01-14T10:24:33.345Z] GC before operation: completed in 65.112 ms, heap usage 126.841 MB -> 50.608 MB. [2025-01-14T10:24:42.130Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:24:49.278Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:24:56.459Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:25:03.645Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:25:08.327Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:25:13.021Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:25:17.708Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:25:21.419Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:25:22.151Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:25:22.151Z] The best model improves the baseline by 14.52%. [2025-01-14T10:25:22.151Z] Movies recommended for you: [2025-01-14T10:25:22.151Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:25:22.151Z] There is no way to check that no silent failure occurred. [2025-01-14T10:25:22.151Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (48881.636 ms) ====== [2025-01-14T10:25:22.151Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-01-14T10:25:22.486Z] GC before operation: completed in 71.511 ms, heap usage 190.829 MB -> 50.936 MB. [2025-01-14T10:25:29.664Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:25:38.445Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:25:45.639Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:25:52.833Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:25:57.551Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:26:02.236Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:26:06.956Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:26:10.696Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:26:11.406Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:26:11.406Z] The best model improves the baseline by 14.52%. [2025-01-14T10:26:11.406Z] Movies recommended for you: [2025-01-14T10:26:11.406Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:26:11.406Z] There is no way to check that no silent failure occurred. [2025-01-14T10:26:11.406Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (49085.156 ms) ====== [2025-01-14T10:26:11.406Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-01-14T10:26:11.406Z] GC before operation: completed in 64.641 ms, heap usage 312.326 MB -> 50.965 MB. [2025-01-14T10:26:18.590Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:26:27.387Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:26:34.574Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:26:43.377Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:26:47.080Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:26:50.798Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:26:55.489Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:27:00.228Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:27:00.228Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:27:00.228Z] The best model improves the baseline by 14.52%. [2025-01-14T10:27:00.228Z] Movies recommended for you: [2025-01-14T10:27:00.228Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:27:00.228Z] There is no way to check that no silent failure occurred. [2025-01-14T10:27:00.228Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (48703.002 ms) ====== [2025-01-14T10:27:00.228Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-01-14T10:27:00.228Z] GC before operation: completed in 67.082 ms, heap usage 133.821 MB -> 50.979 MB. [2025-01-14T10:27:07.415Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:27:16.209Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:27:23.428Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:27:30.602Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:27:35.302Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:27:39.024Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:27:43.735Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:27:48.417Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:27:48.417Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:27:48.417Z] The best model improves the baseline by 14.52%. [2025-01-14T10:27:48.417Z] Movies recommended for you: [2025-01-14T10:27:48.417Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:27:48.417Z] There is no way to check that no silent failure occurred. [2025-01-14T10:27:48.417Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (48188.556 ms) ====== [2025-01-14T10:27:48.417Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-01-14T10:27:48.417Z] GC before operation: completed in 67.755 ms, heap usage 77.027 MB -> 51.246 MB. [2025-01-14T10:27:57.223Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:28:04.450Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:28:11.635Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:28:18.806Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:28:22.537Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:28:27.238Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:28:31.915Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:28:35.647Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:28:36.508Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:28:36.508Z] The best model improves the baseline by 14.52%. [2025-01-14T10:28:36.508Z] Movies recommended for you: [2025-01-14T10:28:36.508Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:28:36.508Z] There is no way to check that no silent failure occurred. [2025-01-14T10:28:36.508Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (47986.763 ms) ====== [2025-01-14T10:28:36.508Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-01-14T10:28:36.842Z] GC before operation: completed in 70.788 ms, heap usage 415.562 MB -> 54.638 MB. [2025-01-14T10:28:44.026Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:28:51.216Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:28:59.983Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:29:05.837Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:29:10.535Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:29:14.269Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:29:18.001Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:29:22.707Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:29:22.707Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:29:22.707Z] The best model improves the baseline by 14.52%. [2025-01-14T10:29:22.707Z] Movies recommended for you: [2025-01-14T10:29:22.707Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:29:22.707Z] There is no way to check that no silent failure occurred. [2025-01-14T10:29:22.707Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (46239.921 ms) ====== [2025-01-14T10:29:22.707Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-01-14T10:29:23.049Z] GC before operation: completed in 71.851 ms, heap usage 253.381 MB -> 51.361 MB. [2025-01-14T10:29:30.225Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:29:37.380Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:29:44.579Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:29:51.783Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:29:55.495Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:29:59.207Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:30:03.889Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:30:07.629Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:30:08.315Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:30:08.315Z] The best model improves the baseline by 14.52%. [2025-01-14T10:30:08.654Z] Movies recommended for you: [2025-01-14T10:30:08.654Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:30:08.654Z] There is no way to check that no silent failure occurred. [2025-01-14T10:30:08.654Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (45697.682 ms) ====== [2025-01-14T10:30:08.654Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-01-14T10:30:08.654Z] GC before operation: completed in 68.162 ms, heap usage 251.968 MB -> 51.146 MB. [2025-01-14T10:30:15.834Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:30:23.013Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:30:31.806Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:30:37.646Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:30:42.355Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:30:46.074Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:30:50.772Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:30:54.501Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:30:55.205Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:30:55.205Z] The best model improves the baseline by 14.52%. [2025-01-14T10:30:55.205Z] Movies recommended for you: [2025-01-14T10:30:55.205Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:30:55.205Z] There is no way to check that no silent failure occurred. [2025-01-14T10:30:55.205Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (46609.742 ms) ====== [2025-01-14T10:30:55.205Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-01-14T10:30:55.205Z] GC before operation: completed in 68.954 ms, heap usage 182.371 MB -> 51.231 MB. [2025-01-14T10:31:02.436Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:31:09.611Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:31:18.436Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:31:24.261Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:31:28.942Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:31:32.666Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:31:37.362Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:31:41.105Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:31:41.105Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:31:41.105Z] The best model improves the baseline by 14.52%. [2025-01-14T10:31:41.473Z] Movies recommended for you: [2025-01-14T10:31:41.473Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:31:41.473Z] There is no way to check that no silent failure occurred. [2025-01-14T10:31:41.473Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (46054.942 ms) ====== [2025-01-14T10:31:41.473Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-01-14T10:31:41.473Z] GC before operation: completed in 69.853 ms, heap usage 249.776 MB -> 51.465 MB. [2025-01-14T10:31:48.647Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:31:57.451Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:32:04.679Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:32:11.860Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:32:15.614Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:32:19.361Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:32:24.047Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:32:27.789Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:32:28.136Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:32:28.136Z] The best model improves the baseline by 14.52%. [2025-01-14T10:32:28.477Z] Movies recommended for you: [2025-01-14T10:32:28.477Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:32:28.477Z] There is no way to check that no silent failure occurred. [2025-01-14T10:32:28.477Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (46931.498 ms) ====== [2025-01-14T10:32:28.477Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-01-14T10:32:28.477Z] GC before operation: completed in 65.394 ms, heap usage 299.303 MB -> 51.346 MB. [2025-01-14T10:32:35.652Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:32:44.436Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:32:50.279Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:32:57.453Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:33:02.130Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:33:05.865Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:33:10.575Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:33:14.294Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:33:14.619Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:33:14.619Z] The best model improves the baseline by 14.52%. [2025-01-14T10:33:14.971Z] Movies recommended for you: [2025-01-14T10:33:14.971Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:33:14.971Z] There is no way to check that no silent failure occurred. [2025-01-14T10:33:14.971Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (46358.887 ms) ====== [2025-01-14T10:33:14.971Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-01-14T10:33:14.971Z] GC before operation: completed in 66.630 ms, heap usage 347.707 MB -> 51.548 MB. [2025-01-14T10:33:22.141Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:33:29.320Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:33:38.130Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:33:43.960Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:33:48.620Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:33:52.327Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:33:57.020Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:34:01.709Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:34:01.710Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:34:01.710Z] The best model improves the baseline by 14.52%. [2025-01-14T10:34:02.101Z] Movies recommended for you: [2025-01-14T10:34:02.101Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:34:02.101Z] There is no way to check that no silent failure occurred. [2025-01-14T10:34:02.101Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (47040.416 ms) ====== [2025-01-14T10:34:02.101Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-01-14T10:34:02.101Z] GC before operation: completed in 74.842 ms, heap usage 101.251 MB -> 51.393 MB. [2025-01-14T10:34:09.293Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:34:18.053Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:34:25.233Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:34:32.407Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:34:36.139Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:34:39.869Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:34:44.536Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:34:48.256Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:34:48.972Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:34:48.973Z] The best model improves the baseline by 14.52%. [2025-01-14T10:34:48.973Z] Movies recommended for you: [2025-01-14T10:34:48.973Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:34:48.973Z] There is no way to check that no silent failure occurred. [2025-01-14T10:34:48.973Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (47029.498 ms) ====== [2025-01-14T10:34:48.973Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-01-14T10:34:48.973Z] GC before operation: completed in 69.370 ms, heap usage 179.800 MB -> 51.280 MB. [2025-01-14T10:34:56.156Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:35:04.960Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:35:12.162Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:35:17.998Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:35:22.706Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:35:26.440Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:35:31.137Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:35:35.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:35:35.836Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:35:35.836Z] The best model improves the baseline by 14.52%. [2025-01-14T10:35:35.836Z] Movies recommended for you: [2025-01-14T10:35:35.836Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:35:35.836Z] There is no way to check that no silent failure occurred. [2025-01-14T10:35:35.836Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (46599.513 ms) ====== [2025-01-14T10:35:35.836Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-01-14T10:35:35.836Z] GC before operation: completed in 68.352 ms, heap usage 400.873 MB -> 54.785 MB. [2025-01-14T10:35:43.037Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:35:50.233Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:35:59.037Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:36:04.877Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:36:09.594Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:36:13.313Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:36:17.986Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:36:21.723Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:36:21.723Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:36:22.057Z] The best model improves the baseline by 14.52%. [2025-01-14T10:36:22.057Z] Movies recommended for you: [2025-01-14T10:36:22.057Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:36:22.057Z] There is no way to check that no silent failure occurred. [2025-01-14T10:36:22.057Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (46278.037 ms) ====== [2025-01-14T10:36:22.058Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-01-14T10:36:22.058Z] GC before operation: completed in 66.304 ms, heap usage 316.031 MB -> 51.697 MB. [2025-01-14T10:36:29.245Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-01-14T10:36:36.428Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-01-14T10:36:45.243Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-01-14T10:36:52.421Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-01-14T10:36:56.128Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-01-14T10:36:59.854Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-01-14T10:37:04.592Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-01-14T10:37:08.316Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-01-14T10:37:09.028Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-01-14T10:37:09.028Z] The best model improves the baseline by 14.52%. [2025-01-14T10:37:09.028Z] Movies recommended for you: [2025-01-14T10:37:09.028Z] WARNING: This benchmark provides no result that can be validated. [2025-01-14T10:37:09.028Z] There is no way to check that no silent failure occurred. [2025-01-14T10:37:09.028Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (46961.662 ms) ====== [2025-01-14T10:37:09.814Z] ----------------------------------- [2025-01-14T10:37:09.814Z] renaissance-movie-lens_0_PASSED [2025-01-14T10:37:09.814Z] ----------------------------------- [2025-01-14T10:37:10.168Z] [2025-01-14T10:37:10.168Z] TEST TEARDOWN: [2025-01-14T10:37:10.168Z] Nothing to be done for teardown. [2025-01-14T10:37:10.486Z] renaissance-movie-lens_0 Finish Time: Tue Jan 14 10:37:10 2025 Epoch Time (ms): 1736851030213