[2024-08-01T03:35:57.077Z] Running test renaissance-movie-lens_0 ... [2024-08-01T03:35:57.395Z] =============================================== [2024-08-01T03:35:57.396Z] renaissance-movie-lens_0 Start Time: Thu Aug 1 03:35:57 2024 Epoch Time (ms): 1722483357356 [2024-08-01T03:35:57.716Z] variation: NoOptions [2024-08-01T03:35:57.716Z] JVM_OPTIONS: [2024-08-01T03:35:57.716Z] { \ [2024-08-01T03:35:57.716Z] echo ""; echo "TEST SETUP:"; \ [2024-08-01T03:35:57.716Z] echo "Nothing to be done for setup."; \ [2024-08-01T03:35:57.716Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17224823655998\\renaissance-movie-lens_0"; \ [2024-08-01T03:35:57.716Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17224823655998\\renaissance-movie-lens_0"; \ [2024-08-01T03:35:57.716Z] echo ""; echo "TESTING:"; \ [2024-08-01T03:35:57.716Z] "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_17224823655998\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-01T03:35:57.716Z] 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_17224823655998\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-01T03:35:57.716Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-01T03:35:57.716Z] echo "Nothing to be done for teardown."; \ [2024-08-01T03:35:57.716Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17224823655998\\TestTargetResult"; [2024-08-01T03:35:58.039Z] [2024-08-01T03:35:58.039Z] TEST SETUP: [2024-08-01T03:35:58.039Z] Nothing to be done for setup. [2024-08-01T03:35:58.039Z] [2024-08-01T03:35:58.039Z] TESTING: [2024-08-01T03:36:08.628Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-01T03:36:10.223Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-01T03:36:13.910Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-01T03:36:13.910Z] Training: 60056, validation: 20285, test: 19854 [2024-08-01T03:36:13.910Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-01T03:36:13.910Z] GC before operation: completed in 48.316 ms, heap usage 92.352 MB -> 37.396 MB. [2024-08-01T03:36:26.824Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:36:34.062Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:36:41.185Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:36:48.274Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:36:52.920Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:36:56.595Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:37:01.219Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:37:04.885Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:37:04.885Z] 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. [2024-08-01T03:37:04.885Z] The best model improves the baseline by 14.52%. [2024-08-01T03:37:05.227Z] Movies recommended for you: [2024-08-01T03:37:05.227Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:37:05.227Z] There is no way to check that no silent failure occurred. [2024-08-01T03:37:05.227Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (51232.216 ms) ====== [2024-08-01T03:37:05.227Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-01T03:37:05.227Z] GC before operation: completed in 63.252 ms, heap usage 178.593 MB -> 57.877 MB. [2024-08-01T03:37:12.331Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:37:19.414Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:37:26.567Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:37:33.666Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:37:37.331Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:37:40.976Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:37:44.645Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:37:48.304Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:37:48.678Z] 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. [2024-08-01T03:37:49.046Z] The best model improves the baseline by 14.52%. [2024-08-01T03:37:49.046Z] Movies recommended for you: [2024-08-01T03:37:49.046Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:37:49.046Z] There is no way to check that no silent failure occurred. [2024-08-01T03:37:49.046Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (43719.618 ms) ====== [2024-08-01T03:37:49.046Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-01T03:37:49.046Z] GC before operation: completed in 61.194 ms, heap usage 181.186 MB -> 50.019 MB. [2024-08-01T03:37:56.156Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:38:01.908Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:38:09.042Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:38:16.160Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:38:19.025Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:38:22.689Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:38:27.305Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:38:30.148Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:38:30.829Z] 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. [2024-08-01T03:38:30.829Z] The best model improves the baseline by 14.52%. [2024-08-01T03:38:30.829Z] Movies recommended for you: [2024-08-01T03:38:30.829Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:38:30.829Z] There is no way to check that no silent failure occurred. [2024-08-01T03:38:30.829Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (41858.689 ms) ====== [2024-08-01T03:38:30.829Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-01T03:38:30.829Z] GC before operation: completed in 60.865 ms, heap usage 205.160 MB -> 50.348 MB. [2024-08-01T03:38:37.912Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:38:43.760Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:38:50.884Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:38:57.990Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:39:00.875Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:39:04.532Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:39:08.199Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:39:11.858Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:39:12.540Z] 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. [2024-08-01T03:39:12.540Z] The best model improves the baseline by 14.52%. [2024-08-01T03:39:12.540Z] Movies recommended for you: [2024-08-01T03:39:12.540Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:39:12.540Z] There is no way to check that no silent failure occurred. [2024-08-01T03:39:12.540Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (41625.935 ms) ====== [2024-08-01T03:39:12.540Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-01T03:39:12.540Z] GC before operation: completed in 58.565 ms, heap usage 159.800 MB -> 50.609 MB. [2024-08-01T03:39:19.627Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:39:25.375Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:39:32.493Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:39:39.577Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:39:42.467Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:39:46.126Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:39:49.786Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:39:53.449Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:39:53.770Z] 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. [2024-08-01T03:39:53.771Z] The best model improves the baseline by 14.52%. [2024-08-01T03:39:53.771Z] Movies recommended for you: [2024-08-01T03:39:53.771Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:39:53.771Z] There is no way to check that no silent failure occurred. [2024-08-01T03:39:53.771Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (41197.423 ms) ====== [2024-08-01T03:39:53.771Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-01T03:39:53.771Z] GC before operation: completed in 59.266 ms, heap usage 78.033 MB -> 50.833 MB. [2024-08-01T03:40:00.930Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:40:06.686Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:40:13.794Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:40:19.543Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:40:24.153Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:40:27.001Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:40:31.624Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:40:34.468Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:40:34.802Z] 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. [2024-08-01T03:40:34.802Z] The best model improves the baseline by 14.52%. [2024-08-01T03:40:35.132Z] Movies recommended for you: [2024-08-01T03:40:35.132Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:40:35.132Z] There is no way to check that no silent failure occurred. [2024-08-01T03:40:35.132Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (41207.120 ms) ====== [2024-08-01T03:40:35.132Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-01T03:40:35.132Z] GC before operation: completed in 58.670 ms, heap usage 194.980 MB -> 50.814 MB. [2024-08-01T03:40:42.218Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:40:47.975Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:40:55.072Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:41:00.830Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:41:04.489Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:41:08.140Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:41:11.807Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:41:15.486Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:41:15.486Z] 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. [2024-08-01T03:41:15.486Z] The best model improves the baseline by 14.52%. [2024-08-01T03:41:15.486Z] Movies recommended for you: [2024-08-01T03:41:15.486Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:41:15.486Z] There is no way to check that no silent failure occurred. [2024-08-01T03:41:15.486Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (40370.568 ms) ====== [2024-08-01T03:41:15.486Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-01T03:41:15.486Z] GC before operation: completed in 61.125 ms, heap usage 187.048 MB -> 50.990 MB. [2024-08-01T03:41:22.594Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:41:28.355Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:41:35.446Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:41:41.190Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:41:44.861Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:41:48.517Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:41:52.181Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:41:55.844Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:41:56.224Z] 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. [2024-08-01T03:41:56.224Z] The best model improves the baseline by 14.52%. [2024-08-01T03:41:56.552Z] Movies recommended for you: [2024-08-01T03:41:56.552Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:41:56.552Z] There is no way to check that no silent failure occurred. [2024-08-01T03:41:56.552Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (40773.241 ms) ====== [2024-08-01T03:41:56.552Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-01T03:41:56.552Z] GC before operation: completed in 59.302 ms, heap usage 162.898 MB -> 51.260 MB. [2024-08-01T03:42:03.662Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:42:09.420Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:42:16.514Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:42:22.265Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:42:25.121Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:42:28.867Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:42:32.523Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:42:36.212Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:42:36.543Z] 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. [2024-08-01T03:42:36.543Z] The best model improves the baseline by 14.52%. [2024-08-01T03:42:36.876Z] Movies recommended for you: [2024-08-01T03:42:36.876Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:42:36.876Z] There is no way to check that no silent failure occurred. [2024-08-01T03:42:36.876Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (40344.048 ms) ====== [2024-08-01T03:42:36.876Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-01T03:42:36.876Z] GC before operation: completed in 59.634 ms, heap usage 335.118 MB -> 51.298 MB. [2024-08-01T03:42:43.972Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:42:49.777Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:42:56.868Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:43:02.617Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:43:06.280Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:43:09.945Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:43:13.613Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:43:17.274Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:43:17.594Z] 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. [2024-08-01T03:43:17.594Z] The best model improves the baseline by 14.52%. [2024-08-01T03:43:17.594Z] Movies recommended for you: [2024-08-01T03:43:17.594Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:43:17.594Z] There is no way to check that no silent failure occurred. [2024-08-01T03:43:17.594Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (40793.307 ms) ====== [2024-08-01T03:43:17.594Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-01T03:43:17.594Z] GC before operation: completed in 57.826 ms, heap usage 279.748 MB -> 51.343 MB. [2024-08-01T03:43:24.699Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:43:30.450Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:43:37.579Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:43:43.343Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:43:47.042Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:43:49.902Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:43:54.505Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:43:57.394Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:43:57.720Z] 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. [2024-08-01T03:43:57.720Z] The best model improves the baseline by 14.52%. [2024-08-01T03:43:58.068Z] Movies recommended for you: [2024-08-01T03:43:58.068Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:43:58.068Z] There is no way to check that no silent failure occurred. [2024-08-01T03:43:58.068Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (40293.052 ms) ====== [2024-08-01T03:43:58.068Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-01T03:43:58.068Z] GC before operation: completed in 64.775 ms, heap usage 227.472 MB -> 50.981 MB. [2024-08-01T03:44:05.185Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:44:11.010Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:44:18.115Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:44:23.874Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:44:27.555Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:44:31.216Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:44:34.877Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:44:38.555Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:44:38.555Z] 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. [2024-08-01T03:44:38.555Z] The best model improves the baseline by 14.52%. [2024-08-01T03:44:38.555Z] Movies recommended for you: [2024-08-01T03:44:38.555Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:44:38.555Z] There is no way to check that no silent failure occurred. [2024-08-01T03:44:38.555Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (40631.193 ms) ====== [2024-08-01T03:44:38.555Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-01T03:44:38.884Z] GC before operation: completed in 59.186 ms, heap usage 178.577 MB -> 51.217 MB. [2024-08-01T03:44:45.979Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:44:51.726Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:44:58.830Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:45:04.584Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:45:08.255Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:45:11.931Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:45:15.611Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:45:19.269Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:45:19.593Z] 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. [2024-08-01T03:45:19.593Z] The best model improves the baseline by 14.52%. [2024-08-01T03:45:19.593Z] Movies recommended for you: [2024-08-01T03:45:19.593Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:45:19.593Z] There is no way to check that no silent failure occurred. [2024-08-01T03:45:19.593Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (40924.298 ms) ====== [2024-08-01T03:45:19.593Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-01T03:45:19.593Z] GC before operation: completed in 64.164 ms, heap usage 74.104 MB -> 51.250 MB. [2024-08-01T03:45:26.703Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:45:32.457Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:45:39.556Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:45:45.292Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:45:48.952Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:45:52.622Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:45:56.288Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:45:59.951Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:46:00.309Z] 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. [2024-08-01T03:46:00.309Z] The best model improves the baseline by 14.52%. [2024-08-01T03:46:00.309Z] Movies recommended for you: [2024-08-01T03:46:00.309Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:46:00.309Z] There is no way to check that no silent failure occurred. [2024-08-01T03:46:00.309Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (40704.519 ms) ====== [2024-08-01T03:46:00.309Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-01T03:46:00.309Z] GC before operation: completed in 59.776 ms, heap usage 183.369 MB -> 51.123 MB. [2024-08-01T03:46:07.388Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:46:13.149Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:46:20.266Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:46:26.030Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:46:29.688Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:46:32.621Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:46:37.227Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:46:40.080Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:46:40.763Z] 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. [2024-08-01T03:46:40.763Z] The best model improves the baseline by 14.52%. [2024-08-01T03:46:40.763Z] Movies recommended for you: [2024-08-01T03:46:40.763Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:46:40.763Z] There is no way to check that no silent failure occurred. [2024-08-01T03:46:40.763Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (40328.049 ms) ====== [2024-08-01T03:46:40.763Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-01T03:46:40.763Z] GC before operation: completed in 65.721 ms, heap usage 70.959 MB -> 51.179 MB. [2024-08-01T03:46:47.856Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:46:53.665Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:47:00.815Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:47:06.574Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:47:10.266Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:47:13.127Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:47:17.751Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:47:21.420Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:47:21.420Z] 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. [2024-08-01T03:47:21.420Z] The best model improves the baseline by 14.52%. [2024-08-01T03:47:21.420Z] Movies recommended for you: [2024-08-01T03:47:21.420Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:47:21.420Z] There is no way to check that no silent failure occurred. [2024-08-01T03:47:21.420Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (40623.528 ms) ====== [2024-08-01T03:47:21.420Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-01T03:47:21.420Z] GC before operation: completed in 60.690 ms, heap usage 195.150 MB -> 51.339 MB. [2024-08-01T03:47:28.535Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:47:34.292Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:47:41.412Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:47:47.155Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:47:50.827Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:47:53.692Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:47:57.389Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:48:01.128Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:48:01.463Z] 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. [2024-08-01T03:48:01.463Z] The best model improves the baseline by 14.52%. [2024-08-01T03:48:01.463Z] Movies recommended for you: [2024-08-01T03:48:01.463Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:48:01.463Z] There is no way to check that no silent failure occurred. [2024-08-01T03:48:01.463Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (40014.228 ms) ====== [2024-08-01T03:48:01.463Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-01T03:48:01.782Z] GC before operation: completed in 58.775 ms, heap usage 98.513 MB -> 51.171 MB. [2024-08-01T03:48:08.864Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:48:14.664Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:48:21.758Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:48:27.555Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:48:31.209Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:48:34.059Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:48:38.678Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:48:41.597Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:48:41.921Z] 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. [2024-08-01T03:48:41.921Z] The best model improves the baseline by 14.52%. [2024-08-01T03:48:42.248Z] Movies recommended for you: [2024-08-01T03:48:42.248Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:48:42.248Z] There is no way to check that no silent failure occurred. [2024-08-01T03:48:42.248Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (40522.758 ms) ====== [2024-08-01T03:48:42.248Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-01T03:48:42.248Z] GC before operation: completed in 60.625 ms, heap usage 236.611 MB -> 51.210 MB. [2024-08-01T03:48:48.154Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:48:55.284Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:49:01.041Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:49:08.128Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:49:10.993Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:49:14.657Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:49:18.402Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:49:22.071Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:49:22.398Z] 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. [2024-08-01T03:49:22.398Z] The best model improves the baseline by 14.52%. [2024-08-01T03:49:22.398Z] Movies recommended for you: [2024-08-01T03:49:22.398Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:49:22.398Z] There is no way to check that no silent failure occurred. [2024-08-01T03:49:22.398Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (40211.032 ms) ====== [2024-08-01T03:49:22.398Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-01T03:49:22.398Z] GC before operation: completed in 61.297 ms, heap usage 229.560 MB -> 51.372 MB. [2024-08-01T03:49:29.520Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-01T03:49:35.271Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-01T03:49:42.374Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-01T03:49:48.115Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-01T03:49:51.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-01T03:49:55.474Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-01T03:49:59.134Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-01T03:50:02.816Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-01T03:50:02.816Z] 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. [2024-08-01T03:50:02.816Z] The best model improves the baseline by 14.52%. [2024-08-01T03:50:02.816Z] Movies recommended for you: [2024-08-01T03:50:02.816Z] WARNING: This benchmark provides no result that can be validated. [2024-08-01T03:50:02.816Z] There is no way to check that no silent failure occurred. [2024-08-01T03:50:02.816Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (40475.417 ms) ====== [2024-08-01T03:50:03.496Z] ----------------------------------- [2024-08-01T03:50:03.496Z] renaissance-movie-lens_0_PASSED [2024-08-01T03:50:03.496Z] ----------------------------------- [2024-08-01T03:50:03.806Z] [2024-08-01T03:50:03.806Z] TEST TEARDOWN: [2024-08-01T03:50:03.806Z] Nothing to be done for teardown. [2024-08-01T03:50:04.118Z] renaissance-movie-lens_0 Finish Time: Thu Aug 1 03:50:03 2024 Epoch Time (ms): 1722484203829