[2024-09-26T21:03:59.760Z] Running test renaissance-movie-lens_0 ... [2024-09-26T21:03:59.760Z] =============================================== [2024-09-26T21:03:59.760Z] renaissance-movie-lens_0 Start Time: Thu Sep 26 21:03:58 2024 Epoch Time (ms): 1727384638495 [2024-09-26T21:03:59.760Z] variation: NoOptions [2024-09-26T21:03:59.760Z] JVM_OPTIONS: [2024-09-26T21:03:59.761Z] { \ [2024-09-26T21:03:59.761Z] echo ""; echo "TEST SETUP:"; \ [2024-09-26T21:03:59.761Z] echo "Nothing to be done for setup."; \ [2024-09-26T21:03:59.761Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17273835137937/renaissance-movie-lens_0"; \ [2024-09-26T21:03:59.761Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17273835137937/renaissance-movie-lens_0"; \ [2024-09-26T21:03:59.761Z] echo ""; echo "TESTING:"; \ [2024-09-26T21:03:59.761Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17273835137937/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2024-09-26T21:03:59.761Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17273835137937/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-09-26T21:03:59.761Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-09-26T21:03:59.761Z] echo "Nothing to be done for teardown."; \ [2024-09-26T21:03:59.761Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64_aix/aqa-tests/TKG/../TKG/output_17273835137937/TestTargetResult"; [2024-09-26T21:03:59.761Z] [2024-09-26T21:03:59.761Z] TEST SETUP: [2024-09-26T21:03:59.761Z] Nothing to be done for setup. [2024-09-26T21:03:59.761Z] [2024-09-26T21:03:59.761Z] TESTING: [2024-09-26T21:04:04.314Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-09-26T21:04:07.712Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads. [2024-09-26T21:04:14.545Z] Got 100004 ratings from 671 users on 9066 movies. [2024-09-26T21:04:14.545Z] Training: 60056, validation: 20285, test: 19854 [2024-09-26T21:04:14.545Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-09-26T21:04:14.545Z] GC before operation: completed in 306.075 ms, heap usage 232.999 MB -> 26.632 MB. [2024-09-26T21:04:22.791Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:04:28.356Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:04:33.956Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:04:38.388Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:04:40.850Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:04:43.297Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:04:45.749Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:04:49.161Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:04:49.161Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2024-09-26T21:04:49.161Z] The best model improves the baseline by 14.43%. [2024-09-26T21:04:49.161Z] Movies recommended for you: [2024-09-26T21:04:49.161Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:04:49.161Z] There is no way to check that no silent failure occurred. [2024-09-26T21:04:49.161Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (35014.086 ms) ====== [2024-09-26T21:04:49.161Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-09-26T21:04:49.920Z] GC before operation: completed in 304.858 ms, heap usage 277.100 MB -> 42.788 MB. [2024-09-26T21:04:54.378Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:04:58.813Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:05:03.237Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:05:07.656Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:05:10.114Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:05:12.559Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:05:15.019Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:05:17.641Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:05:17.641Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:05:17.641Z] The best model improves the baseline by 14.43%. [2024-09-26T21:05:18.417Z] Movies recommended for you: [2024-09-26T21:05:18.417Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:05:18.417Z] There is no way to check that no silent failure occurred. [2024-09-26T21:05:18.417Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (28391.338 ms) ====== [2024-09-26T21:05:18.417Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-09-26T21:05:18.417Z] GC before operation: completed in 268.812 ms, heap usage 72.867 MB -> 45.257 MB. [2024-09-26T21:05:22.839Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:05:27.273Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:05:31.819Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:05:36.256Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:05:37.839Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:05:40.297Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:05:42.745Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:05:46.142Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:05:46.142Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2024-09-26T21:05:46.142Z] The best model improves the baseline by 14.43%. [2024-09-26T21:05:46.142Z] Movies recommended for you: [2024-09-26T21:05:46.142Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:05:46.142Z] There is no way to check that no silent failure occurred. [2024-09-26T21:05:46.142Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (27755.621 ms) ====== [2024-09-26T21:05:46.142Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-09-26T21:05:46.142Z] GC before operation: completed in 255.639 ms, heap usage 334.360 MB -> 47.270 MB. [2024-09-26T21:05:50.598Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:05:55.025Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:05:59.457Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:06:03.888Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:06:05.466Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:06:07.910Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:06:10.358Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:06:12.821Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:06:13.582Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:06:13.582Z] The best model improves the baseline by 14.43%. [2024-09-26T21:06:13.582Z] Movies recommended for you: [2024-09-26T21:06:13.582Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:06:13.582Z] There is no way to check that no silent failure occurred. [2024-09-26T21:06:13.582Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (26953.374 ms) ====== [2024-09-26T21:06:13.582Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-09-26T21:06:13.582Z] GC before operation: completed in 197.299 ms, heap usage 334.138 MB -> 43.350 MB. [2024-09-26T21:06:18.026Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:06:21.440Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:06:25.861Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:06:30.334Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:06:32.782Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:06:35.236Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:06:37.696Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:06:40.139Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:06:40.139Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:06:40.139Z] The best model improves the baseline by 14.43%. [2024-09-26T21:06:40.139Z] Movies recommended for you: [2024-09-26T21:06:40.139Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:06:40.139Z] There is no way to check that no silent failure occurred. [2024-09-26T21:06:40.139Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (26746.103 ms) ====== [2024-09-26T21:06:40.139Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-09-26T21:06:40.908Z] GC before operation: completed in 293.813 ms, heap usage 287.257 MB -> 45.472 MB. [2024-09-26T21:06:45.344Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:06:48.734Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:06:53.169Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:06:57.613Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:07:00.066Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:07:02.521Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:07:04.975Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:07:07.434Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:07:07.434Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2024-09-26T21:07:07.434Z] The best model improves the baseline by 14.43%. [2024-09-26T21:07:07.434Z] Movies recommended for you: [2024-09-26T21:07:07.434Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:07:07.434Z] There is no way to check that no silent failure occurred. [2024-09-26T21:07:07.434Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (26834.217 ms) ====== [2024-09-26T21:07:07.434Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-09-26T21:07:07.434Z] GC before operation: completed in 158.954 ms, heap usage 249.388 MB -> 47.109 MB. [2024-09-26T21:07:11.881Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:07:16.324Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:07:20.806Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:07:24.204Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:07:26.652Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:07:29.134Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:07:31.605Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:07:34.073Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:07:34.073Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2024-09-26T21:07:34.073Z] The best model improves the baseline by 14.43%. [2024-09-26T21:07:34.073Z] Movies recommended for you: [2024-09-26T21:07:34.073Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:07:34.073Z] There is no way to check that no silent failure occurred. [2024-09-26T21:07:34.073Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (26576.983 ms) ====== [2024-09-26T21:07:34.073Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-09-26T21:07:34.073Z] GC before operation: completed in 179.102 ms, heap usage 359.304 MB -> 45.717 MB. [2024-09-26T21:07:38.503Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:07:42.933Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:07:47.368Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:07:50.766Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:07:53.215Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:07:55.665Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:07:58.122Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:08:00.585Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:08:00.585Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:08:00.585Z] The best model improves the baseline by 14.43%. [2024-09-26T21:08:01.347Z] Movies recommended for you: [2024-09-26T21:08:01.348Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:08:01.348Z] There is no way to check that no silent failure occurred. [2024-09-26T21:08:01.348Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (26576.106 ms) ====== [2024-09-26T21:08:01.348Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-09-26T21:08:01.348Z] GC before operation: completed in 150.339 ms, heap usage 138.280 MB -> 44.669 MB. [2024-09-26T21:08:05.781Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:08:09.178Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:08:13.602Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:08:18.040Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:08:20.521Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:08:22.971Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:08:25.452Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:08:27.905Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:08:27.905Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2024-09-26T21:08:27.905Z] The best model improves the baseline by 14.43%. [2024-09-26T21:08:27.905Z] Movies recommended for you: [2024-09-26T21:08:27.905Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:08:27.905Z] There is no way to check that no silent failure occurred. [2024-09-26T21:08:27.905Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (27063.883 ms) ====== [2024-09-26T21:08:27.905Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-09-26T21:08:28.672Z] GC before operation: completed in 186.172 ms, heap usage 230.005 MB -> 45.664 MB. [2024-09-26T21:08:33.106Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:08:36.503Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:08:40.939Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:08:45.373Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:08:47.825Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:08:50.274Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:08:52.740Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:08:55.193Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:08:55.193Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2024-09-26T21:08:55.193Z] The best model improves the baseline by 14.43%. [2024-09-26T21:08:55.193Z] Movies recommended for you: [2024-09-26T21:08:55.193Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:08:55.193Z] There is no way to check that no silent failure occurred. [2024-09-26T21:08:55.193Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (26881.649 ms) ====== [2024-09-26T21:08:55.193Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-09-26T21:08:55.193Z] GC before operation: completed in 308.336 ms, heap usage 326.174 MB -> 70.264 MB. [2024-09-26T21:08:59.634Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:09:04.067Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:09:08.498Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:09:12.919Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:09:15.368Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:09:17.814Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:09:20.260Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:09:22.727Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:09:22.727Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:09:22.727Z] The best model improves the baseline by 14.43%. [2024-09-26T21:09:22.727Z] Movies recommended for you: [2024-09-26T21:09:22.727Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:09:22.727Z] There is no way to check that no silent failure occurred. [2024-09-26T21:09:22.727Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27305.734 ms) ====== [2024-09-26T21:09:22.727Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-09-26T21:09:22.727Z] GC before operation: completed in 180.662 ms, heap usage 334.978 MB -> 51.084 MB. [2024-09-26T21:09:27.150Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:09:31.590Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:09:36.036Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:09:39.439Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:09:41.891Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:09:44.347Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:09:47.776Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:09:49.368Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:09:50.130Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2024-09-26T21:09:50.130Z] The best model improves the baseline by 14.43%. [2024-09-26T21:09:50.130Z] Movies recommended for you: [2024-09-26T21:09:50.130Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:09:50.130Z] There is no way to check that no silent failure occurred. [2024-09-26T21:09:50.130Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (27046.570 ms) ====== [2024-09-26T21:09:50.130Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-09-26T21:09:50.130Z] GC before operation: completed in 211.762 ms, heap usage 114.923 MB -> 54.445 MB. [2024-09-26T21:09:54.563Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:09:59.015Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:10:03.462Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:10:06.862Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:10:10.300Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:10:11.876Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:10:15.278Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:10:17.037Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:10:17.037Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:10:17.037Z] The best model improves the baseline by 14.43%. [2024-09-26T21:10:17.798Z] Movies recommended for you: [2024-09-26T21:10:17.798Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:10:17.798Z] There is no way to check that no silent failure occurred. [2024-09-26T21:10:17.798Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (27198.077 ms) ====== [2024-09-26T21:10:17.798Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-09-26T21:10:17.798Z] GC before operation: completed in 201.158 ms, heap usage 275.833 MB -> 58.925 MB. [2024-09-26T21:10:22.226Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:10:26.663Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:10:31.124Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:10:34.581Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:10:37.039Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:10:39.493Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:10:41.942Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:10:44.409Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:10:45.173Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:10:45.173Z] The best model improves the baseline by 14.43%. [2024-09-26T21:10:45.173Z] Movies recommended for you: [2024-09-26T21:10:45.173Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:10:45.173Z] There is no way to check that no silent failure occurred. [2024-09-26T21:10:45.173Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (27405.620 ms) ====== [2024-09-26T21:10:45.173Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-09-26T21:10:45.173Z] GC before operation: completed in 199.851 ms, heap usage 396.796 MB -> 44.009 MB. [2024-09-26T21:10:49.606Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:10:54.048Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:10:58.482Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:11:01.879Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:11:04.329Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:11:06.781Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:11:09.235Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:11:11.699Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:11:12.464Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:11:12.464Z] The best model improves the baseline by 14.43%. [2024-09-26T21:11:12.464Z] Movies recommended for you: [2024-09-26T21:11:12.465Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:11:12.465Z] There is no way to check that no silent failure occurred. [2024-09-26T21:11:12.465Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (26986.478 ms) ====== [2024-09-26T21:11:12.465Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-09-26T21:11:12.465Z] GC before operation: completed in 195.746 ms, heap usage 304.985 MB -> 75.076 MB. [2024-09-26T21:11:16.908Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:11:21.357Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:11:25.806Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:11:29.322Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:11:31.774Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:11:34.941Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:11:38.770Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:11:39.741Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:11:41.003Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:11:41.003Z] The best model improves the baseline by 14.43%. [2024-09-26T21:11:41.003Z] Movies recommended for you: [2024-09-26T21:11:41.003Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:11:41.003Z] There is no way to check that no silent failure occurred. [2024-09-26T21:11:41.003Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (27698.975 ms) ====== [2024-09-26T21:11:41.003Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-09-26T21:11:41.003Z] GC before operation: completed in 202.567 ms, heap usage 268.956 MB -> 51.593 MB. [2024-09-26T21:11:44.144Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:11:48.571Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:11:52.993Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:11:57.432Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:11:59.899Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:12:02.359Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:12:04.855Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:12:07.303Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:12:07.303Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:12:07.303Z] The best model improves the baseline by 14.43%. [2024-09-26T21:12:07.303Z] Movies recommended for you: [2024-09-26T21:12:07.303Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:12:07.303Z] There is no way to check that no silent failure occurred. [2024-09-26T21:12:07.303Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (27003.761 ms) ====== [2024-09-26T21:12:07.303Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-09-26T21:12:07.303Z] GC before operation: completed in 205.492 ms, heap usage 306.285 MB -> 74.137 MB. [2024-09-26T21:12:11.737Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:12:16.161Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:12:20.594Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:12:25.037Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:12:27.491Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:12:30.005Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:12:32.448Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:12:34.941Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:12:34.942Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2024-09-26T21:12:34.942Z] The best model improves the baseline by 14.43%. [2024-09-26T21:12:34.942Z] Movies recommended for you: [2024-09-26T21:12:34.942Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:12:34.942Z] There is no way to check that no silent failure occurred. [2024-09-26T21:12:34.942Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (27534.889 ms) ====== [2024-09-26T21:12:34.942Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-09-26T21:12:35.705Z] GC before operation: completed in 261.117 ms, heap usage 269.435 MB -> 74.323 MB. [2024-09-26T21:12:40.132Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:12:43.531Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:12:47.957Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:12:52.391Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:12:54.837Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:12:57.280Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:12:59.746Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:13:02.192Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:13:02.952Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711. [2024-09-26T21:13:02.952Z] The best model improves the baseline by 14.43%. [2024-09-26T21:13:02.952Z] Movies recommended for you: [2024-09-26T21:13:02.952Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:13:02.952Z] There is no way to check that no silent failure occurred. [2024-09-26T21:13:02.952Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (27343.731 ms) ====== [2024-09-26T21:13:02.952Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-09-26T21:13:02.952Z] GC before operation: completed in 229.167 ms, heap usage 411.823 MB -> 74.984 MB. [2024-09-26T21:13:07.408Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-09-26T21:13:11.840Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-09-26T21:13:16.259Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-09-26T21:13:19.664Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-09-26T21:13:22.125Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-09-26T21:13:24.581Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-09-26T21:13:27.035Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-09-26T21:13:29.487Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-09-26T21:13:30.249Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712. [2024-09-26T21:13:30.249Z] The best model improves the baseline by 14.43%. [2024-09-26T21:13:30.249Z] Movies recommended for you: [2024-09-26T21:13:30.249Z] WARNING: This benchmark provides no result that can be validated. [2024-09-26T21:13:30.249Z] There is no way to check that no silent failure occurred. [2024-09-26T21:13:30.249Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (27267.144 ms) ====== [2024-09-26T21:13:31.831Z] ----------------------------------- [2024-09-26T21:13:31.831Z] renaissance-movie-lens_0_PASSED [2024-09-26T21:13:31.831Z] ----------------------------------- [2024-09-26T21:13:31.831Z] [2024-09-26T21:13:31.831Z] TEST TEARDOWN: [2024-09-26T21:13:31.831Z] Nothing to be done for teardown. [2024-09-26T21:13:32.592Z] renaissance-movie-lens_0 Finish Time: Thu Sep 26 21:13:31 2024 Epoch Time (ms): 1727385211732