[2024-08-08T00:48:17.063Z] Running test renaissance-movie-lens_0 ... [2024-08-08T00:48:17.063Z] =============================================== [2024-08-08T00:48:17.378Z] renaissance-movie-lens_0 Start Time: Thu Aug 8 00:48:17 2024 Epoch Time (ms): 1723078097171 [2024-08-08T00:48:17.378Z] variation: NoOptions [2024-08-08T00:48:17.378Z] JVM_OPTIONS: [2024-08-08T00:48:17.378Z] { \ [2024-08-08T00:48:17.378Z] echo ""; echo "TEST SETUP:"; \ [2024-08-08T00:48:17.378Z] echo "Nothing to be done for setup."; \ [2024-08-08T00:48:17.379Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17230771406735\\renaissance-movie-lens_0"; \ [2024-08-08T00:48:17.379Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17230771406735\\renaissance-movie-lens_0"; \ [2024-08-08T00:48:17.379Z] echo ""; echo "TESTING:"; \ [2024-08-08T00:48:17.379Z] "c:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/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_testList_0/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17230771406735\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-08T00:48:17.379Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17230771406735\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-08T00:48:17.379Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-08T00:48:17.379Z] echo "Nothing to be done for teardown."; \ [2024-08-08T00:48:17.379Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17230771406735\\TestTargetResult"; [2024-08-08T00:48:17.708Z] [2024-08-08T00:48:17.708Z] TEST SETUP: [2024-08-08T00:48:17.708Z] Nothing to be done for setup. [2024-08-08T00:48:17.708Z] [2024-08-08T00:48:17.708Z] TESTING: [2024-08-08T00:48:28.369Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-08T00:48:29.493Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-08T00:48:32.445Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-08T00:48:32.445Z] Training: 60056, validation: 20285, test: 19854 [2024-08-08T00:48:32.445Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-08T00:48:32.445Z] GC before operation: completed in 47.249 ms, heap usage 103.942 MB -> 37.553 MB. [2024-08-08T00:48:45.507Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:48:51.313Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:49:00.102Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:49:05.899Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:49:09.598Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:49:14.257Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:49:18.100Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:49:21.802Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:49:22.148Z] 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. [2024-08-08T00:49:22.148Z] The best model improves the baseline by 14.52%. [2024-08-08T00:49:22.148Z] Movies recommended for you: [2024-08-08T00:49:22.148Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:49:22.148Z] There is no way to check that no silent failure occurred. [2024-08-08T00:49:22.148Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (49643.594 ms) ====== [2024-08-08T00:49:22.148Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-08T00:49:22.148Z] GC before operation: completed in 62.225 ms, heap usage 171.895 MB -> 57.975 MB. [2024-08-08T00:49:29.317Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:49:36.463Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:49:42.262Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:49:49.408Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:49:52.316Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:49:56.010Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:49:59.741Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:50:03.461Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:50:03.461Z] 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. [2024-08-08T00:50:03.461Z] The best model improves the baseline by 14.52%. [2024-08-08T00:50:03.794Z] Movies recommended for you: [2024-08-08T00:50:03.794Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:50:03.794Z] There is no way to check that no silent failure occurred. [2024-08-08T00:50:03.794Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (41491.778 ms) ====== [2024-08-08T00:50:03.794Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-08T00:50:03.794Z] GC before operation: completed in 56.794 ms, heap usage 108.056 MB -> 50.087 MB. [2024-08-08T00:50:10.971Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:50:16.849Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:50:24.002Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:50:29.803Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:50:33.493Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:50:36.376Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:50:40.075Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:50:43.776Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:50:44.103Z] 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. [2024-08-08T00:50:44.103Z] The best model improves the baseline by 14.52%. [2024-08-08T00:50:44.422Z] Movies recommended for you: [2024-08-08T00:50:44.422Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:50:44.422Z] There is no way to check that no silent failure occurred. [2024-08-08T00:50:44.422Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (40521.027 ms) ====== [2024-08-08T00:50:44.422Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-08T00:50:44.422Z] GC before operation: completed in 57.355 ms, heap usage 189.148 MB -> 50.469 MB. [2024-08-08T00:50:50.243Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:50:57.385Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:51:03.163Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:51:10.294Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:51:13.185Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:51:16.879Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:51:20.596Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:51:24.302Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:51:24.302Z] 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. [2024-08-08T00:51:24.302Z] The best model improves the baseline by 14.52%. [2024-08-08T00:51:24.302Z] Movies recommended for you: [2024-08-08T00:51:24.302Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:51:24.302Z] There is no way to check that no silent failure occurred. [2024-08-08T00:51:24.302Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (39971.127 ms) ====== [2024-08-08T00:51:24.302Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-08T00:51:24.302Z] GC before operation: completed in 57.916 ms, heap usage 206.321 MB -> 50.843 MB. [2024-08-08T00:51:31.488Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:51:37.299Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:51:44.448Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:51:50.302Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:51:53.207Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:51:56.912Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:52:00.639Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:52:04.368Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:52:04.368Z] 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. [2024-08-08T00:52:04.368Z] The best model improves the baseline by 14.52%. [2024-08-08T00:52:04.368Z] Movies recommended for you: [2024-08-08T00:52:04.368Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:52:04.368Z] There is no way to check that no silent failure occurred. [2024-08-08T00:52:04.368Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (39981.580 ms) ====== [2024-08-08T00:52:04.368Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-08T00:52:04.368Z] GC before operation: completed in 59.199 ms, heap usage 291.923 MB -> 51.060 MB. [2024-08-08T00:52:11.545Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:52:17.350Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:52:23.212Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:52:30.368Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:52:33.273Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:52:36.977Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:52:40.679Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:52:43.570Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:52:44.266Z] 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. [2024-08-08T00:52:44.266Z] The best model improves the baseline by 14.52%. [2024-08-08T00:52:44.266Z] Movies recommended for you: [2024-08-08T00:52:44.266Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:52:44.266Z] There is no way to check that no silent failure occurred. [2024-08-08T00:52:44.266Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (39766.059 ms) ====== [2024-08-08T00:52:44.266Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-08T00:52:44.266Z] GC before operation: completed in 56.008 ms, heap usage 139.302 MB -> 50.890 MB. [2024-08-08T00:52:51.420Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:52:57.228Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:53:03.057Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:53:08.869Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:53:12.587Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:53:16.346Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:53:20.084Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:53:22.975Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:53:23.300Z] 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. [2024-08-08T00:53:23.640Z] The best model improves the baseline by 14.52%. [2024-08-08T00:53:23.640Z] Movies recommended for you: [2024-08-08T00:53:23.640Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:53:23.640Z] There is no way to check that no silent failure occurred. [2024-08-08T00:53:23.640Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (39286.812 ms) ====== [2024-08-08T00:53:23.640Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-08T00:53:23.640Z] GC before operation: completed in 57.415 ms, heap usage 191.726 MB -> 51.151 MB. [2024-08-08T00:53:29.439Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:53:36.592Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:53:42.403Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:53:48.205Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:53:51.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:53:55.580Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:53:59.304Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:54:02.210Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:54:02.596Z] 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. [2024-08-08T00:54:02.596Z] The best model improves the baseline by 14.52%. [2024-08-08T00:54:02.924Z] Movies recommended for you: [2024-08-08T00:54:02.924Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:54:02.924Z] There is no way to check that no silent failure occurred. [2024-08-08T00:54:02.924Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (39058.131 ms) ====== [2024-08-08T00:54:02.924Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-08T00:54:02.924Z] GC before operation: completed in 58.781 ms, heap usage 194.307 MB -> 51.397 MB. [2024-08-08T00:54:10.106Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:54:15.913Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:54:21.724Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:54:27.538Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:54:31.305Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:54:35.019Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:54:38.744Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:54:41.638Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:54:42.381Z] 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. [2024-08-08T00:54:42.381Z] The best model improves the baseline by 14.52%. [2024-08-08T00:54:42.381Z] Movies recommended for you: [2024-08-08T00:54:42.381Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:54:42.381Z] There is no way to check that no silent failure occurred. [2024-08-08T00:54:42.381Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (39554.267 ms) ====== [2024-08-08T00:54:42.381Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-08T00:54:42.381Z] GC before operation: completed in 56.713 ms, heap usage 169.532 MB -> 51.289 MB. [2024-08-08T00:54:48.178Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:54:55.317Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:55:01.140Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:55:06.934Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:55:10.691Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:55:13.585Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:55:17.274Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:55:20.969Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:55:20.969Z] 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. [2024-08-08T00:55:20.969Z] The best model improves the baseline by 14.52%. [2024-08-08T00:55:21.301Z] Movies recommended for you: [2024-08-08T00:55:21.301Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:55:21.302Z] There is no way to check that no silent failure occurred. [2024-08-08T00:55:21.302Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (38820.674 ms) ====== [2024-08-08T00:55:21.302Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-08T00:55:21.302Z] GC before operation: completed in 58.867 ms, heap usage 170.809 MB -> 51.247 MB. [2024-08-08T00:55:27.097Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:55:34.250Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:55:40.047Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:55:45.834Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:55:49.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:55:52.463Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:55:57.128Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:56:00.089Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:56:00.416Z] 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. [2024-08-08T00:56:00.416Z] The best model improves the baseline by 14.52%. [2024-08-08T00:56:00.416Z] Movies recommended for you: [2024-08-08T00:56:00.416Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:56:00.416Z] There is no way to check that no silent failure occurred. [2024-08-08T00:56:00.416Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (39084.967 ms) ====== [2024-08-08T00:56:00.416Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-08T00:56:00.416Z] GC before operation: completed in 57.663 ms, heap usage 169.919 MB -> 51.001 MB. [2024-08-08T00:56:06.216Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:56:13.411Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:56:19.241Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:56:25.029Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:56:28.742Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:56:31.647Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:56:35.352Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:56:39.058Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:56:39.389Z] 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. [2024-08-08T00:56:39.389Z] The best model improves the baseline by 14.52%. [2024-08-08T00:56:39.389Z] Movies recommended for you: [2024-08-08T00:56:39.389Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:56:39.389Z] There is no way to check that no silent failure occurred. [2024-08-08T00:56:39.389Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (39034.362 ms) ====== [2024-08-08T00:56:39.389Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-08T00:56:39.389Z] GC before operation: completed in 57.805 ms, heap usage 195.910 MB -> 51.178 MB. [2024-08-08T00:56:46.540Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:56:52.392Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:56:58.206Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:57:04.040Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:57:07.760Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:57:10.650Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:57:15.308Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:57:18.191Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:57:18.519Z] 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. [2024-08-08T00:57:18.519Z] The best model improves the baseline by 14.52%. [2024-08-08T00:57:18.519Z] Movies recommended for you: [2024-08-08T00:57:18.519Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:57:18.519Z] There is no way to check that no silent failure occurred. [2024-08-08T00:57:18.519Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (39099.940 ms) ====== [2024-08-08T00:57:18.519Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-08T00:57:18.519Z] GC before operation: completed in 58.594 ms, heap usage 216.652 MB -> 51.375 MB. [2024-08-08T00:57:25.690Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:57:31.474Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:57:37.254Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:57:43.138Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:57:46.837Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:57:50.539Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:57:54.259Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:57:57.294Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:57:57.622Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-08T00:57:57.622Z] The best model improves the baseline by 14.52%. [2024-08-08T00:57:57.622Z] Movies recommended for you: [2024-08-08T00:57:57.622Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:57:57.622Z] There is no way to check that no silent failure occurred. [2024-08-08T00:57:57.622Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (38938.664 ms) ====== [2024-08-08T00:57:57.622Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-08T00:57:57.622Z] GC before operation: completed in 58.992 ms, heap usage 170.533 MB -> 51.142 MB. [2024-08-08T00:58:03.422Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:58:10.570Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:58:16.375Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:58:22.163Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:58:25.856Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:58:28.842Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:58:32.536Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:58:36.229Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:58:36.557Z] 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. [2024-08-08T00:58:36.557Z] The best model improves the baseline by 14.52%. [2024-08-08T00:58:36.557Z] Movies recommended for you: [2024-08-08T00:58:36.557Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:58:36.557Z] There is no way to check that no silent failure occurred. [2024-08-08T00:58:36.557Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (38944.343 ms) ====== [2024-08-08T00:58:36.557Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-08T00:58:36.557Z] GC before operation: completed in 57.759 ms, heap usage 91.157 MB -> 51.251 MB. [2024-08-08T00:58:43.701Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:58:49.488Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:58:55.270Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:59:01.092Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:59:04.772Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:59:08.538Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:59:12.241Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:59:15.138Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:59:15.834Z] 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. [2024-08-08T00:59:15.834Z] The best model improves the baseline by 14.52%. [2024-08-08T00:59:15.834Z] Movies recommended for you: [2024-08-08T00:59:15.834Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:59:15.834Z] There is no way to check that no silent failure occurred. [2024-08-08T00:59:15.834Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (39200.605 ms) ====== [2024-08-08T00:59:15.834Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-08T00:59:15.834Z] GC before operation: completed in 58.659 ms, heap usage 225.605 MB -> 51.412 MB. [2024-08-08T00:59:22.986Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T00:59:28.797Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T00:59:34.604Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T00:59:40.413Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T00:59:44.136Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T00:59:47.837Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T00:59:51.551Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T00:59:54.473Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T00:59:54.799Z] 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. [2024-08-08T00:59:54.799Z] The best model improves the baseline by 14.52%. [2024-08-08T00:59:54.799Z] Movies recommended for you: [2024-08-08T00:59:54.799Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T00:59:54.799Z] There is no way to check that no silent failure occurred. [2024-08-08T00:59:54.799Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (38918.124 ms) ====== [2024-08-08T00:59:54.799Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-08T00:59:54.799Z] GC before operation: completed in 59.221 ms, heap usage 230.450 MB -> 51.226 MB. [2024-08-08T01:00:01.959Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T01:00:07.754Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T01:00:13.593Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T01:00:19.406Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T01:00:23.112Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T01:00:26.815Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T01:00:30.558Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T01:00:33.456Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T01:00:33.825Z] 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. [2024-08-08T01:00:33.825Z] The best model improves the baseline by 14.52%. [2024-08-08T01:00:34.152Z] Movies recommended for you: [2024-08-08T01:00:34.152Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T01:00:34.152Z] There is no way to check that no silent failure occurred. [2024-08-08T01:00:34.152Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (39036.571 ms) ====== [2024-08-08T01:00:34.152Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-08T01:00:34.152Z] GC before operation: completed in 60.422 ms, heap usage 174.155 MB -> 51.309 MB. [2024-08-08T01:00:39.985Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T01:00:47.233Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T01:00:53.028Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T01:00:58.833Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T01:01:02.549Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T01:01:06.249Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T01:01:09.945Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T01:01:12.837Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T01:01:13.532Z] 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. [2024-08-08T01:01:13.532Z] The best model improves the baseline by 14.52%. [2024-08-08T01:01:13.532Z] Movies recommended for you: [2024-08-08T01:01:13.532Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T01:01:13.532Z] There is no way to check that no silent failure occurred. [2024-08-08T01:01:13.532Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (39529.207 ms) ====== [2024-08-08T01:01:13.532Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-08T01:01:13.532Z] GC before operation: completed in 60.135 ms, heap usage 195.636 MB -> 51.456 MB. [2024-08-08T01:01:19.339Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-08T01:01:26.565Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-08T01:01:32.479Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-08T01:01:38.268Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-08T01:01:41.984Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-08T01:01:44.881Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-08T01:01:48.589Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-08T01:01:52.292Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-08T01:01:52.616Z] 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. [2024-08-08T01:01:52.616Z] The best model improves the baseline by 14.52%. [2024-08-08T01:01:52.616Z] Movies recommended for you: [2024-08-08T01:01:52.616Z] WARNING: This benchmark provides no result that can be validated. [2024-08-08T01:01:52.616Z] There is no way to check that no silent failure occurred. [2024-08-08T01:01:52.616Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (39101.561 ms) ====== [2024-08-08T01:01:53.308Z] ----------------------------------- [2024-08-08T01:01:53.308Z] renaissance-movie-lens_0_PASSED [2024-08-08T01:01:53.308Z] ----------------------------------- [2024-08-08T01:01:53.632Z] [2024-08-08T01:01:53.632Z] TEST TEARDOWN: [2024-08-08T01:01:53.632Z] Nothing to be done for teardown. [2024-08-08T01:01:53.946Z] renaissance-movie-lens_0 Finish Time: Thu Aug 8 01:01:53 2024 Epoch Time (ms): 1723078913664