[2024-08-10T10:07:21.543Z] Running test renaissance-movie-lens_0 ... [2024-08-10T10:07:21.866Z] =============================================== [2024-08-10T10:07:22.173Z] renaissance-movie-lens_0 Start Time: Sat Aug 10 10:07:21 2024 Epoch Time (ms): 1723284441878 [2024-08-10T10:07:22.173Z] variation: NoOptions [2024-08-10T10:07:22.490Z] JVM_OPTIONS: [2024-08-10T10:07:22.490Z] { \ [2024-08-10T10:07:22.490Z] echo ""; echo "TEST SETUP:"; \ [2024-08-10T10:07:22.490Z] echo "Nothing to be done for setup."; \ [2024-08-10T10:07:22.490Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17232831628287\\renaissance-movie-lens_0"; \ [2024-08-10T10:07:22.490Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17232831628287\\renaissance-movie-lens_0"; \ [2024-08-10T10:07:22.490Z] echo ""; echo "TESTING:"; \ [2024-08-10T10:07:22.490Z] "c:/jenkins/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17232831628287\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-08-10T10:07:22.490Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17232831628287\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-08-10T10:07:22.491Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-08-10T10:07:22.491Z] echo "Nothing to be done for teardown."; \ [2024-08-10T10:07:22.491Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows_testList_0/aqa-tests/\\TKG\\output_17232831628287\\TestTargetResult"; [2024-08-10T10:07:22.491Z] [2024-08-10T10:07:22.491Z] TEST SETUP: [2024-08-10T10:07:22.491Z] Nothing to be done for setup. [2024-08-10T10:07:22.491Z] [2024-08-10T10:07:22.491Z] TESTING: [2024-08-10T10:07:33.019Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-08-10T10:07:35.166Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-08-10T10:07:37.997Z] Got 100004 ratings from 671 users on 9066 movies. [2024-08-10T10:07:38.346Z] Training: 60056, validation: 20285, test: 19854 [2024-08-10T10:07:38.346Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-08-10T10:07:38.346Z] GC before operation: completed in 83.353 ms, heap usage 92.271 MB -> 36.942 MB. [2024-08-10T10:07:51.233Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:07:59.858Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:08:06.912Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:08:13.949Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:08:18.528Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:08:23.126Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:08:27.774Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:08:31.382Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:08:31.719Z] 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. [2024-08-10T10:08:31.719Z] The best model improves the baseline by 14.52%. [2024-08-10T10:08:32.036Z] Movies recommended for you: [2024-08-10T10:08:32.036Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:08:32.036Z] There is no way to check that no silent failure occurred. [2024-08-10T10:08:32.036Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (53577.403 ms) ====== [2024-08-10T10:08:32.036Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-08-10T10:08:32.036Z] GC before operation: completed in 98.291 ms, heap usage 292.055 MB -> 47.423 MB. [2024-08-10T10:08:39.110Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:08:47.755Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:08:54.809Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:09:01.851Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:09:05.464Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:09:09.156Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:09:13.732Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:09:17.347Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:09:17.693Z] 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. [2024-08-10T10:09:17.693Z] The best model improves the baseline by 14.52%. [2024-08-10T10:09:17.693Z] Movies recommended for you: [2024-08-10T10:09:17.693Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:09:17.693Z] There is no way to check that no silent failure occurred. [2024-08-10T10:09:17.693Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (45700.302 ms) ====== [2024-08-10T10:09:17.693Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-08-10T10:09:18.017Z] GC before operation: completed in 84.168 ms, heap usage 249.515 MB -> 49.633 MB. [2024-08-10T10:09:26.643Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:09:33.663Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:09:40.752Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:09:47.794Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:09:51.484Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:09:56.040Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:09:59.660Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:10:03.264Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:10:03.942Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-08-10T10:10:03.942Z] The best model improves the baseline by 14.52%. [2024-08-10T10:10:03.942Z] Movies recommended for you: [2024-08-10T10:10:03.942Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:10:03.942Z] There is no way to check that no silent failure occurred. [2024-08-10T10:10:03.942Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (46157.906 ms) ====== [2024-08-10T10:10:03.942Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-08-10T10:10:04.258Z] GC before operation: completed in 87.179 ms, heap usage 82.871 MB -> 49.683 MB. [2024-08-10T10:10:11.273Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:10:18.322Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:10:25.470Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:10:32.538Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:10:37.128Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:10:40.766Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:10:45.371Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:10:49.009Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:10:49.331Z] 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. [2024-08-10T10:10:49.673Z] The best model improves the baseline by 14.52%. [2024-08-10T10:10:49.673Z] Movies recommended for you: [2024-08-10T10:10:49.673Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:10:49.673Z] There is no way to check that no silent failure occurred. [2024-08-10T10:10:49.673Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (45526.680 ms) ====== [2024-08-10T10:10:49.673Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-08-10T10:10:49.673Z] GC before operation: completed in 89.025 ms, heap usage 183.011 MB -> 50.152 MB. [2024-08-10T10:10:56.721Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:11:03.796Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:11:12.477Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:11:18.189Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:11:22.817Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:11:26.465Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:11:31.053Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:11:34.693Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:11:34.693Z] 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. [2024-08-10T10:11:34.693Z] The best model improves the baseline by 14.52%. [2024-08-10T10:11:35.014Z] Movies recommended for you: [2024-08-10T10:11:35.014Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:11:35.014Z] There is no way to check that no silent failure occurred. [2024-08-10T10:11:35.014Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (45213.724 ms) ====== [2024-08-10T10:11:35.014Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-08-10T10:11:35.014Z] GC before operation: completed in 83.756 ms, heap usage 134.366 MB -> 53.586 MB. [2024-08-10T10:11:42.052Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:11:49.087Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:11:56.150Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:12:03.195Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:12:06.830Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:12:10.478Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:12:14.134Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:12:17.767Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:12:18.143Z] 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. [2024-08-10T10:12:18.143Z] The best model improves the baseline by 14.52%. [2024-08-10T10:12:18.143Z] Movies recommended for you: [2024-08-10T10:12:18.143Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:12:18.143Z] There is no way to check that no silent failure occurred. [2024-08-10T10:12:18.143Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (43210.369 ms) ====== [2024-08-10T10:12:18.143Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-08-10T10:12:18.498Z] GC before operation: completed in 94.272 ms, heap usage 221.088 MB -> 53.530 MB. [2024-08-10T10:12:25.579Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:12:32.632Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:12:39.676Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:12:46.737Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:12:50.380Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:12:53.997Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:12:58.587Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:13:02.219Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:13:02.540Z] 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. [2024-08-10T10:13:02.540Z] The best model improves the baseline by 14.52%. [2024-08-10T10:13:02.858Z] Movies recommended for you: [2024-08-10T10:13:02.858Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:13:02.858Z] There is no way to check that no silent failure occurred. [2024-08-10T10:13:02.858Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (44426.058 ms) ====== [2024-08-10T10:13:02.858Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-08-10T10:13:02.858Z] GC before operation: completed in 86.515 ms, heap usage 82.585 MB -> 50.291 MB. [2024-08-10T10:13:09.904Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:13:16.934Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:13:23.959Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:13:30.993Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:13:33.842Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:13:38.402Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:13:42.040Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:13:45.673Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:13:46.351Z] 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. [2024-08-10T10:13:46.351Z] The best model improves the baseline by 14.52%. [2024-08-10T10:13:46.351Z] Movies recommended for you: [2024-08-10T10:13:46.351Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:13:46.351Z] There is no way to check that no silent failure occurred. [2024-08-10T10:13:46.351Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (43464.452 ms) ====== [2024-08-10T10:13:46.351Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-08-10T10:13:46.351Z] GC before operation: completed in 79.919 ms, heap usage 195.477 MB -> 50.714 MB. [2024-08-10T10:13:53.409Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:14:00.524Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:14:07.619Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:14:14.660Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:14:18.288Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:14:21.912Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:14:26.467Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:14:30.102Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:14:30.102Z] 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. [2024-08-10T10:14:30.102Z] The best model improves the baseline by 14.52%. [2024-08-10T10:14:30.432Z] Movies recommended for you: [2024-08-10T10:14:30.432Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:14:30.432Z] There is no way to check that no silent failure occurred. [2024-08-10T10:14:30.432Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (43991.634 ms) ====== [2024-08-10T10:14:30.432Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-08-10T10:14:30.432Z] GC before operation: completed in 78.915 ms, heap usage 122.271 MB -> 50.451 MB. [2024-08-10T10:14:37.472Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:14:44.507Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:14:51.550Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:14:58.582Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:15:02.220Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:15:05.843Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:15:10.407Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:15:14.087Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:15:14.428Z] 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. [2024-08-10T10:15:14.428Z] The best model improves the baseline by 14.52%. [2024-08-10T10:15:14.428Z] Movies recommended for you: [2024-08-10T10:15:14.428Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:15:14.428Z] There is no way to check that no silent failure occurred. [2024-08-10T10:15:14.428Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (44062.523 ms) ====== [2024-08-10T10:15:14.428Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-08-10T10:15:14.748Z] GC before operation: completed in 84.646 ms, heap usage 78.036 MB -> 50.508 MB. [2024-08-10T10:15:21.765Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:15:28.780Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:15:35.822Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:15:42.892Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:15:45.707Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:15:50.251Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:15:53.872Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:15:57.486Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:15:57.798Z] 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. [2024-08-10T10:15:57.798Z] The best model improves the baseline by 14.52%. [2024-08-10T10:15:58.119Z] Movies recommended for you: [2024-08-10T10:15:58.119Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:15:58.119Z] There is no way to check that no silent failure occurred. [2024-08-10T10:15:58.119Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (43380.331 ms) ====== [2024-08-10T10:15:58.119Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-08-10T10:15:58.119Z] GC before operation: completed in 85.896 ms, heap usage 132.366 MB -> 53.638 MB. [2024-08-10T10:16:05.167Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:16:12.203Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:16:19.281Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:16:26.310Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:16:29.933Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:16:33.564Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:16:38.163Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:16:41.801Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:16:42.117Z] 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. [2024-08-10T10:16:42.117Z] The best model improves the baseline by 14.52%. [2024-08-10T10:16:42.117Z] Movies recommended for you: [2024-08-10T10:16:42.117Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:16:42.117Z] There is no way to check that no silent failure occurred. [2024-08-10T10:16:42.117Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (44093.935 ms) ====== [2024-08-10T10:16:42.117Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-08-10T10:16:42.117Z] GC before operation: completed in 81.696 ms, heap usage 94.755 MB -> 50.471 MB. [2024-08-10T10:16:49.177Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:16:56.251Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:17:03.333Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:17:10.385Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:17:14.031Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:17:18.615Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:17:22.292Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:17:25.925Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:17:26.624Z] 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. [2024-08-10T10:17:26.624Z] The best model improves the baseline by 14.52%. [2024-08-10T10:17:26.624Z] Movies recommended for you: [2024-08-10T10:17:26.624Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:17:26.624Z] There is no way to check that no silent failure occurred. [2024-08-10T10:17:26.624Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (44452.090 ms) ====== [2024-08-10T10:17:26.624Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-08-10T10:17:26.940Z] GC before operation: completed in 84.587 ms, heap usage 94.298 MB -> 50.654 MB. [2024-08-10T10:17:34.025Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:17:41.084Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:17:48.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:17:55.169Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:17:58.796Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:18:02.415Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:18:06.982Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:18:10.627Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:18:10.627Z] 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. [2024-08-10T10:18:10.627Z] The best model improves the baseline by 14.52%. [2024-08-10T10:18:10.961Z] Movies recommended for you: [2024-08-10T10:18:10.961Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:18:10.961Z] There is no way to check that no silent failure occurred. [2024-08-10T10:18:10.961Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (44044.594 ms) ====== [2024-08-10T10:18:10.961Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-08-10T10:18:10.961Z] GC before operation: completed in 82.106 ms, heap usage 97.343 MB -> 50.383 MB. [2024-08-10T10:18:18.055Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:18:25.091Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:18:32.140Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:18:37.837Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:18:41.447Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:18:46.026Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:18:49.664Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:18:53.296Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:18:53.999Z] 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. [2024-08-10T10:18:53.999Z] The best model improves the baseline by 14.52%. [2024-08-10T10:18:53.999Z] Movies recommended for you: [2024-08-10T10:18:53.999Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:18:53.999Z] There is no way to check that no silent failure occurred. [2024-08-10T10:18:53.999Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (43068.469 ms) ====== [2024-08-10T10:18:53.999Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-08-10T10:18:53.999Z] GC before operation: completed in 90.580 ms, heap usage 71.653 MB -> 50.616 MB. [2024-08-10T10:19:01.036Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:19:08.092Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:19:15.146Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:19:22.190Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:19:25.046Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:19:28.669Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:19:33.245Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:19:36.886Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:19:37.202Z] 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. [2024-08-10T10:19:37.202Z] The best model improves the baseline by 14.52%. [2024-08-10T10:19:37.202Z] Movies recommended for you: [2024-08-10T10:19:37.202Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:19:37.202Z] There is no way to check that no silent failure occurred. [2024-08-10T10:19:37.202Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (43158.994 ms) ====== [2024-08-10T10:19:37.202Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-08-10T10:19:37.202Z] GC before operation: completed in 93.363 ms, heap usage 319.602 MB -> 50.867 MB. [2024-08-10T10:19:44.236Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:19:51.279Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:19:58.333Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:20:05.374Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:20:08.992Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:20:12.689Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:20:16.387Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:20:20.013Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:20:20.783Z] 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. [2024-08-10T10:20:20.783Z] The best model improves the baseline by 14.52%. [2024-08-10T10:20:20.783Z] Movies recommended for you: [2024-08-10T10:20:20.783Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:20:20.783Z] There is no way to check that no silent failure occurred. [2024-08-10T10:20:20.784Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (43407.318 ms) ====== [2024-08-10T10:20:20.784Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-08-10T10:20:21.100Z] GC before operation: completed in 91.205 ms, heap usage 216.665 MB -> 52.850 MB. [2024-08-10T10:20:28.142Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:20:35.207Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:20:42.291Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:20:49.315Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:20:52.958Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:20:56.592Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:21:01.176Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:21:04.867Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:21:04.867Z] 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. [2024-08-10T10:21:04.867Z] The best model improves the baseline by 14.52%. [2024-08-10T10:21:05.192Z] Movies recommended for you: [2024-08-10T10:21:05.192Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:21:05.192Z] There is no way to check that no silent failure occurred. [2024-08-10T10:21:05.192Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (44310.871 ms) ====== [2024-08-10T10:21:05.192Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-08-10T10:21:05.192Z] GC before operation: completed in 83.169 ms, heap usage 108.650 MB -> 50.553 MB. [2024-08-10T10:21:12.261Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:21:19.295Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:21:26.369Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:21:33.397Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:21:37.011Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:21:40.626Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:21:45.191Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:21:48.821Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:21:49.181Z] 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. [2024-08-10T10:21:49.181Z] The best model improves the baseline by 14.52%. [2024-08-10T10:21:49.181Z] Movies recommended for you: [2024-08-10T10:21:49.181Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:21:49.181Z] There is no way to check that no silent failure occurred. [2024-08-10T10:21:49.181Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (44048.459 ms) ====== [2024-08-10T10:21:49.181Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-08-10T10:21:49.486Z] GC before operation: completed in 85.047 ms, heap usage 124.994 MB -> 53.930 MB. [2024-08-10T10:21:58.131Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-08-10T10:22:05.198Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-08-10T10:22:12.230Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-08-10T10:22:17.931Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-08-10T10:22:22.496Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-08-10T10:22:26.124Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-08-10T10:22:30.686Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-08-10T10:22:34.321Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-08-10T10:22:34.321Z] 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. [2024-08-10T10:22:34.321Z] The best model improves the baseline by 14.52%. [2024-08-10T10:22:34.321Z] Movies recommended for you: [2024-08-10T10:22:34.321Z] WARNING: This benchmark provides no result that can be validated. [2024-08-10T10:22:34.321Z] There is no way to check that no silent failure occurred. [2024-08-10T10:22:34.321Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (45094.919 ms) ====== [2024-08-10T10:22:34.988Z] ----------------------------------- [2024-08-10T10:22:34.988Z] renaissance-movie-lens_0_PASSED [2024-08-10T10:22:34.988Z] ----------------------------------- [2024-08-10T10:22:35.290Z] [2024-08-10T10:22:35.290Z] TEST TEARDOWN: [2024-08-10T10:22:35.290Z] Nothing to be done for teardown. [2024-08-10T10:22:35.290Z] renaissance-movie-lens_0 Finish Time: Sat Aug 10 10:22:35 2024 Epoch Time (ms): 1723285355250