[2024-12-05T12:02:08.416Z] Running test renaissance-movie-lens_0 ... [2024-12-05T12:02:08.731Z] =============================================== [2024-12-05T12:02:08.731Z] renaissance-movie-lens_0 Start Time: Thu Dec 5 12:02:08 2024 Epoch Time (ms): 1733400128524 [2024-12-05T12:02:08.731Z] variation: NoOptions [2024-12-05T12:02:08.731Z] JVM_OPTIONS: [2024-12-05T12:02:08.731Z] { \ [2024-12-05T12:02:08.731Z] echo ""; echo "TEST SETUP:"; \ [2024-12-05T12:02:08.731Z] echo "Nothing to be done for setup."; \ [2024-12-05T12:02:08.731Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/aqa-tests/\\TKG\\output_17333993696917\\renaissance-movie-lens_0"; \ [2024-12-05T12:02:08.731Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/aqa-tests/\\TKG\\output_17333993696917\\renaissance-movie-lens_0"; \ [2024-12-05T12:02:08.731Z] echo ""; echo "TESTING:"; \ [2024-12-05T12:02:08.731Z] "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_17333993696917\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-12-05T12:02:08.731Z] 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_17333993696917\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-12-05T12:02:08.731Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-12-05T12:02:08.731Z] echo "Nothing to be done for teardown."; \ [2024-12-05T12:02:08.731Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_rerun/aqa-tests/\\TKG\\output_17333993696917\\TestTargetResult"; [2024-12-05T12:02:09.061Z] [2024-12-05T12:02:09.061Z] TEST SETUP: [2024-12-05T12:02:09.061Z] Nothing to be done for setup. [2024-12-05T12:02:09.061Z] [2024-12-05T12:02:09.061Z] TESTING: [2024-12-05T12:02:19.813Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-12-05T12:02:22.019Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-12-05T12:02:24.933Z] Got 100004 ratings from 671 users on 9066 movies. [2024-12-05T12:02:25.311Z] Training: 60056, validation: 20285, test: 19854 [2024-12-05T12:02:25.311Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-12-05T12:02:25.311Z] GC before operation: completed in 63.181 ms, heap usage 139.708 MB -> 37.618 MB. [2024-12-05T12:02:36.107Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:02:44.942Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:02:53.723Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:02:59.556Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:03:04.251Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:03:07.972Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:03:12.682Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:03:16.453Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:03:16.790Z] 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. [2024-12-05T12:03:16.790Z] The best model improves the baseline by 14.52%. [2024-12-05T12:03:17.126Z] Movies recommended for you: [2024-12-05T12:03:17.126Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:03:17.126Z] There is no way to check that no silent failure occurred. [2024-12-05T12:03:17.126Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (51786.282 ms) ====== [2024-12-05T12:03:17.126Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-12-05T12:03:17.126Z] GC before operation: completed in 69.015 ms, heap usage 239.906 MB -> 58.532 MB. [2024-12-05T12:03:24.294Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:03:31.493Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:03:38.659Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:03:45.830Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:03:48.735Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:03:53.421Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:03:57.161Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:04:00.901Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:04:01.610Z] 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. [2024-12-05T12:04:01.610Z] The best model improves the baseline by 14.52%. [2024-12-05T12:04:01.610Z] Movies recommended for you: [2024-12-05T12:04:01.610Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:04:01.610Z] There is no way to check that no silent failure occurred. [2024-12-05T12:04:01.610Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (44419.275 ms) ====== [2024-12-05T12:04:01.610Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-12-05T12:04:01.610Z] GC before operation: completed in 63.794 ms, heap usage 72.867 MB -> 50.163 MB. [2024-12-05T12:04:08.768Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:04:15.929Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:04:23.101Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:04:28.941Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:04:32.718Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:04:36.432Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:04:40.161Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:04:43.907Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:04:44.236Z] 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. [2024-12-05T12:04:44.236Z] The best model improves the baseline by 14.52%. [2024-12-05T12:04:44.567Z] Movies recommended for you: [2024-12-05T12:04:44.567Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:04:44.567Z] There is no way to check that no silent failure occurred. [2024-12-05T12:04:44.567Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (42773.993 ms) ====== [2024-12-05T12:04:44.567Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-12-05T12:04:44.567Z] GC before operation: completed in 61.227 ms, heap usage 183.000 MB -> 50.401 MB. [2024-12-05T12:04:51.771Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:04:57.602Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:05:04.787Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:05:11.956Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:05:15.676Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:05:19.394Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:05:23.147Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:05:27.838Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:05:27.838Z] 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. [2024-12-05T12:05:27.838Z] The best model improves the baseline by 14.52%. [2024-12-05T12:05:27.838Z] Movies recommended for you: [2024-12-05T12:05:27.838Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:05:27.838Z] There is no way to check that no silent failure occurred. [2024-12-05T12:05:27.838Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (43167.321 ms) ====== [2024-12-05T12:05:27.838Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-12-05T12:05:27.838Z] GC before operation: completed in 58.640 ms, heap usage 224.757 MB -> 50.838 MB. [2024-12-05T12:05:35.018Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:05:40.841Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:05:48.016Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:05:55.196Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:05:58.168Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:06:01.904Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:06:06.569Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:06:09.506Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:06:09.833Z] 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. [2024-12-05T12:06:09.833Z] The best model improves the baseline by 14.52%. [2024-12-05T12:06:10.164Z] Movies recommended for you: [2024-12-05T12:06:10.164Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:06:10.164Z] There is no way to check that no silent failure occurred. [2024-12-05T12:06:10.164Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (42353.815 ms) ====== [2024-12-05T12:06:10.164Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-12-05T12:06:10.164Z] GC before operation: completed in 59.613 ms, heap usage 220.396 MB -> 50.974 MB. [2024-12-05T12:06:17.339Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:06:24.511Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:06:30.344Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:06:37.532Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:06:41.248Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:06:44.985Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:06:48.679Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:06:52.406Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:06:52.734Z] 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. [2024-12-05T12:06:52.734Z] The best model improves the baseline by 14.52%. [2024-12-05T12:06:52.734Z] Movies recommended for you: [2024-12-05T12:06:52.734Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:06:52.734Z] There is no way to check that no silent failure occurred. [2024-12-05T12:06:52.734Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (42608.117 ms) ====== [2024-12-05T12:06:52.734Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-12-05T12:06:52.734Z] GC before operation: completed in 60.091 ms, heap usage 185.593 MB -> 50.932 MB. [2024-12-05T12:06:59.923Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:07:05.750Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:07:12.927Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:07:20.093Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:07:23.001Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:07:26.716Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:07:31.407Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:07:35.197Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:07:35.197Z] 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. [2024-12-05T12:07:35.197Z] The best model improves the baseline by 14.52%. [2024-12-05T12:07:35.197Z] Movies recommended for you: [2024-12-05T12:07:35.197Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:07:35.197Z] There is no way to check that no silent failure occurred. [2024-12-05T12:07:35.197Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (42482.400 ms) ====== [2024-12-05T12:07:35.197Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-12-05T12:07:35.514Z] GC before operation: completed in 58.006 ms, heap usage 196.385 MB -> 51.161 MB. [2024-12-05T12:07:42.676Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:07:48.514Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:07:55.675Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:08:02.870Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:08:05.767Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:08:09.473Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:08:14.161Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:08:17.087Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:08:17.792Z] 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. [2024-12-05T12:08:17.792Z] The best model improves the baseline by 14.52%. [2024-12-05T12:08:17.792Z] Movies recommended for you: [2024-12-05T12:08:17.792Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:08:17.792Z] There is no way to check that no silent failure occurred. [2024-12-05T12:08:17.792Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (42390.447 ms) ====== [2024-12-05T12:08:17.792Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-12-05T12:08:17.792Z] GC before operation: completed in 60.365 ms, heap usage 214.256 MB -> 51.405 MB. [2024-12-05T12:08:24.958Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:08:30.776Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:08:37.952Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:08:43.776Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:08:47.491Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:08:51.261Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:08:54.992Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:08:58.704Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:08:59.049Z] 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. [2024-12-05T12:08:59.049Z] The best model improves the baseline by 14.52%. [2024-12-05T12:08:59.049Z] Movies recommended for you: [2024-12-05T12:08:59.049Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:08:59.049Z] There is no way to check that no silent failure occurred. [2024-12-05T12:08:59.049Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (41356.594 ms) ====== [2024-12-05T12:08:59.049Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-12-05T12:08:59.374Z] GC before operation: completed in 64.118 ms, heap usage 183.617 MB -> 51.227 MB. [2024-12-05T12:09:06.525Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:09:12.336Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:09:19.489Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:09:26.641Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:09:29.538Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:09:33.259Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:09:36.974Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:09:40.685Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:09:40.685Z] 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. [2024-12-05T12:09:40.685Z] The best model improves the baseline by 14.52%. [2024-12-05T12:09:41.009Z] Movies recommended for you: [2024-12-05T12:09:41.009Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:09:41.009Z] There is no way to check that no silent failure occurred. [2024-12-05T12:09:41.009Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (41736.245 ms) ====== [2024-12-05T12:09:41.009Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-12-05T12:09:41.009Z] GC before operation: completed in 60.725 ms, heap usage 191.670 MB -> 51.335 MB. [2024-12-05T12:09:48.176Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:09:53.988Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:10:01.140Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:10:06.956Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:10:10.661Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:10:14.365Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:10:19.057Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:10:22.802Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:10:22.803Z] 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. [2024-12-05T12:10:22.803Z] The best model improves the baseline by 14.52%. [2024-12-05T12:10:22.803Z] Movies recommended for you: [2024-12-05T12:10:22.803Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:10:22.803Z] There is no way to check that no silent failure occurred. [2024-12-05T12:10:22.803Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (41872.730 ms) ====== [2024-12-05T12:10:22.803Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-12-05T12:10:22.803Z] GC before operation: completed in 61.555 ms, heap usage 199.650 MB -> 51.071 MB. [2024-12-05T12:10:29.979Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:10:37.173Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:10:42.998Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:10:50.173Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:10:53.088Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:10:56.803Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:11:00.526Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:11:04.262Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:11:04.589Z] 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. [2024-12-05T12:11:04.589Z] The best model improves the baseline by 14.52%. [2024-12-05T12:11:04.928Z] Movies recommended for you: [2024-12-05T12:11:04.928Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:11:04.928Z] There is no way to check that no silent failure occurred. [2024-12-05T12:11:04.928Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (41837.673 ms) ====== [2024-12-05T12:11:04.928Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-12-05T12:11:04.928Z] GC before operation: completed in 62.128 ms, heap usage 183.865 MB -> 51.232 MB. [2024-12-05T12:11:12.085Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:11:17.925Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:11:25.111Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:11:32.272Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:11:35.174Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:11:38.901Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:11:43.586Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:11:46.518Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:11:47.215Z] 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. [2024-12-05T12:11:47.215Z] The best model improves the baseline by 14.52%. [2024-12-05T12:11:47.215Z] Movies recommended for you: [2024-12-05T12:11:47.215Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:11:47.215Z] There is no way to check that no silent failure occurred. [2024-12-05T12:11:47.215Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (42343.364 ms) ====== [2024-12-05T12:11:47.215Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-12-05T12:11:47.215Z] GC before operation: completed in 60.751 ms, heap usage 129.402 MB -> 51.386 MB. [2024-12-05T12:11:54.394Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:12:00.202Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:12:07.367Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:12:14.509Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:12:17.400Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:12:21.104Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:12:25.791Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:12:28.718Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:12:29.045Z] 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. [2024-12-05T12:12:29.045Z] The best model improves the baseline by 14.52%. [2024-12-05T12:12:29.360Z] Movies recommended for you: [2024-12-05T12:12:29.360Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:12:29.360Z] There is no way to check that no silent failure occurred. [2024-12-05T12:12:29.360Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (42070.674 ms) ====== [2024-12-05T12:12:29.360Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-12-05T12:12:29.360Z] GC before operation: completed in 68.026 ms, heap usage 212.189 MB -> 51.178 MB. [2024-12-05T12:12:36.518Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:12:42.347Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:12:49.518Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:12:55.334Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:13:00.033Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:13:02.934Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:13:07.616Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:13:11.349Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:13:11.349Z] 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. [2024-12-05T12:13:11.349Z] The best model improves the baseline by 14.52%. [2024-12-05T12:13:11.349Z] Movies recommended for you: [2024-12-05T12:13:11.349Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:13:11.349Z] There is no way to check that no silent failure occurred. [2024-12-05T12:13:11.349Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (42026.034 ms) ====== [2024-12-05T12:13:11.349Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-12-05T12:13:11.349Z] GC before operation: completed in 60.237 ms, heap usage 192.130 MB -> 51.423 MB. [2024-12-05T12:13:18.530Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:13:25.692Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:13:31.535Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:13:38.710Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:13:41.636Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:13:45.359Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:13:50.045Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:13:52.970Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:13:53.664Z] 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. [2024-12-05T12:13:53.664Z] The best model improves the baseline by 14.52%. [2024-12-05T12:13:53.664Z] Movies recommended for you: [2024-12-05T12:13:53.664Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:13:53.664Z] There is no way to check that no silent failure occurred. [2024-12-05T12:13:53.664Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (42196.414 ms) ====== [2024-12-05T12:13:53.664Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-12-05T12:13:53.664Z] GC before operation: completed in 60.599 ms, heap usage 165.646 MB -> 51.461 MB. [2024-12-05T12:14:00.839Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:14:06.645Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:14:13.811Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:14:19.632Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:14:24.303Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:14:28.025Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:14:31.797Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:14:35.521Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:14:35.521Z] 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. [2024-12-05T12:14:35.521Z] The best model improves the baseline by 14.52%. [2024-12-05T12:14:35.521Z] Movies recommended for you: [2024-12-05T12:14:35.521Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:14:35.521Z] There is no way to check that no silent failure occurred. [2024-12-05T12:14:35.521Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (41777.331 ms) ====== [2024-12-05T12:14:35.521Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-12-05T12:14:35.521Z] GC before operation: completed in 59.118 ms, heap usage 208.367 MB -> 51.353 MB. [2024-12-05T12:14:42.699Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:14:48.525Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:14:55.705Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:15:01.530Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:15:06.216Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:15:09.122Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:15:13.797Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:15:17.533Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:15:17.533Z] 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. [2024-12-05T12:15:17.533Z] The best model improves the baseline by 14.52%. [2024-12-05T12:15:17.533Z] Movies recommended for you: [2024-12-05T12:15:17.533Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:15:17.533Z] There is no way to check that no silent failure occurred. [2024-12-05T12:15:17.533Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (41965.229 ms) ====== [2024-12-05T12:15:17.534Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-12-05T12:15:17.534Z] GC before operation: completed in 60.726 ms, heap usage 209.509 MB -> 51.363 MB. [2024-12-05T12:15:24.722Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:15:31.902Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:15:37.727Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:15:44.895Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:15:48.624Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:15:51.533Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:15:56.230Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:15:59.159Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:15:59.858Z] 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. [2024-12-05T12:15:59.858Z] The best model improves the baseline by 14.52%. [2024-12-05T12:15:59.858Z] Movies recommended for you: [2024-12-05T12:15:59.858Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:15:59.858Z] There is no way to check that no silent failure occurred. [2024-12-05T12:15:59.858Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (42292.272 ms) ====== [2024-12-05T12:15:59.858Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-12-05T12:15:59.858Z] GC before operation: completed in 60.610 ms, heap usage 206.983 MB -> 51.564 MB. [2024-12-05T12:16:07.032Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-12-05T12:16:12.829Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-12-05T12:16:20.016Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-12-05T12:16:25.845Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-12-05T12:16:29.584Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-12-05T12:16:33.329Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-12-05T12:16:37.993Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-12-05T12:16:40.918Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-12-05T12:16:41.246Z] 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. [2024-12-05T12:16:41.246Z] The best model improves the baseline by 14.52%. [2024-12-05T12:16:41.593Z] Movies recommended for you: [2024-12-05T12:16:41.593Z] WARNING: This benchmark provides no result that can be validated. [2024-12-05T12:16:41.593Z] There is no way to check that no silent failure occurred. [2024-12-05T12:16:41.593Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (41489.063 ms) ====== [2024-12-05T12:16:41.923Z] ----------------------------------- [2024-12-05T12:16:41.923Z] renaissance-movie-lens_0_PASSED [2024-12-05T12:16:41.923Z] ----------------------------------- [2024-12-05T12:16:42.627Z] [2024-12-05T12:16:42.627Z] TEST TEARDOWN: [2024-12-05T12:16:42.627Z] Nothing to be done for teardown. [2024-12-05T12:16:42.627Z] renaissance-movie-lens_0 Finish Time: Thu Dec 5 12:16:42 2024 Epoch Time (ms): 1733401002433