[2025-06-13T10:46:36.248Z] Running test renaissance-movie-lens_0 ... [2025-06-13T10:46:36.248Z] =============================================== [2025-06-13T10:46:36.248Z] renaissance-movie-lens_0 Start Time: Fri Jun 13 10:46:33 2025 Epoch Time (ms): 1749811593625 [2025-06-13T10:46:36.248Z] variation: NoOptions [2025-06-13T10:46:36.248Z] JVM_OPTIONS: [2025-06-13T10:46:36.248Z] { \ [2025-06-13T10:46:36.248Z] echo ""; echo "TEST SETUP:"; \ [2025-06-13T10:46:36.248Z] echo "Nothing to be done for setup."; \ [2025-06-13T10:46:36.248Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17498083843889/renaissance-movie-lens_0"; \ [2025-06-13T10:46:36.248Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17498083843889/renaissance-movie-lens_0"; \ [2025-06-13T10:46:36.248Z] echo ""; echo "TESTING:"; \ [2025-06-13T10:46:36.248Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_1/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 "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17498083843889/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-13T10:46:36.248Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17498083843889/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-13T10:46:36.248Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-13T10:46:36.248Z] echo "Nothing to be done for teardown."; \ [2025-06-13T10:46:36.248Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17498083843889/TestTargetResult"; [2025-06-13T10:46:36.248Z] [2025-06-13T10:46:36.248Z] TEST SETUP: [2025-06-13T10:46:36.248Z] Nothing to be done for setup. [2025-06-13T10:46:36.248Z] [2025-06-13T10:46:36.248Z] TESTING: [2025-06-13T10:46:55.306Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-13T10:47:31.524Z] 10:47:28.314 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-06-13T10:47:38.535Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-13T10:47:40.162Z] Training: 60056, validation: 20285, test: 19854 [2025-06-13T10:47:40.162Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-13T10:47:40.939Z] GC before operation: completed in 364.788 ms, heap usage 102.192 MB -> 74.539 MB. [2025-06-13T10:48:06.972Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T10:48:21.578Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T10:48:40.688Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T10:48:52.540Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T10:49:00.928Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T10:49:07.896Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T10:49:14.834Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T10:49:21.872Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T10:49:23.540Z] 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. [2025-06-13T10:49:23.540Z] The best model improves the baseline by 14.52%. [2025-06-13T10:49:24.307Z] Top recommended movies for user id 72: [2025-06-13T10:49:24.307Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T10:49:24.307Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T10:49:24.307Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T10:49:24.307Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T10:49:24.307Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T10:49:24.307Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (103737.490 ms) ====== [2025-06-13T10:49:24.307Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-13T10:49:25.068Z] GC before operation: completed in 562.622 ms, heap usage 400.775 MB -> 85.587 MB. [2025-06-13T10:49:36.714Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T10:49:46.555Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T10:50:00.360Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T10:50:08.640Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T10:50:14.237Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T10:50:22.997Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T10:50:31.296Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T10:50:38.135Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T10:50:38.935Z] 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. [2025-06-13T10:50:39.701Z] The best model improves the baseline by 14.52%. [2025-06-13T10:50:40.479Z] Top recommended movies for user id 72: [2025-06-13T10:50:40.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T10:50:40.479Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T10:50:40.479Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T10:50:40.479Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T10:50:40.480Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T10:50:40.480Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (75197.953 ms) ====== [2025-06-13T10:50:40.480Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-13T10:50:40.480Z] GC before operation: completed in 549.977 ms, heap usage 134.934 MB -> 87.369 MB. [2025-06-13T10:50:56.575Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T10:51:07.085Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T10:51:21.373Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T10:51:31.301Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T10:51:38.146Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T10:51:46.506Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T10:51:56.501Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T10:52:04.946Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T10:52:05.722Z] 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. [2025-06-13T10:52:06.507Z] The best model improves the baseline by 14.52%. [2025-06-13T10:52:06.507Z] Top recommended movies for user id 72: [2025-06-13T10:52:06.507Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T10:52:06.507Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T10:52:06.507Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T10:52:06.507Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T10:52:06.507Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T10:52:06.507Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (86198.974 ms) ====== [2025-06-13T10:52:06.507Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-13T10:52:07.427Z] GC before operation: completed in 777.298 ms, heap usage 303.752 MB -> 88.195 MB. [2025-06-13T10:52:23.955Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T10:52:35.711Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T10:52:51.890Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T10:53:05.727Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T10:53:13.006Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T10:53:21.431Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T10:53:31.297Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T10:53:39.577Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T10:53:39.577Z] 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. [2025-06-13T10:53:40.342Z] The best model improves the baseline by 14.52%. [2025-06-13T10:53:40.342Z] Top recommended movies for user id 72: [2025-06-13T10:53:40.342Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T10:53:40.342Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T10:53:40.342Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T10:53:40.342Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T10:53:40.342Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T10:53:40.342Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (92791.298 ms) ====== [2025-06-13T10:53:40.342Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-13T10:53:41.114Z] GC before operation: completed in 713.359 ms, heap usage 472.081 MB -> 88.662 MB. [2025-06-13T10:53:54.836Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T10:54:07.108Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T10:54:20.940Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T10:54:37.228Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T10:54:44.232Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T10:54:54.168Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T10:55:04.070Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T10:55:12.438Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T10:55:14.104Z] 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. [2025-06-13T10:55:14.104Z] The best model improves the baseline by 14.52%. [2025-06-13T10:55:14.880Z] Top recommended movies for user id 72: [2025-06-13T10:55:14.880Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T10:55:14.880Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T10:55:14.880Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T10:55:14.880Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T10:55:14.880Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T10:55:14.880Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (94035.285 ms) ====== [2025-06-13T10:55:14.880Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-13T10:55:15.651Z] GC before operation: completed in 783.489 ms, heap usage 203.121 MB -> 88.257 MB. [2025-06-13T10:55:29.918Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T10:55:39.829Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T10:55:49.759Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T10:56:00.446Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T10:56:08.860Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T10:56:17.164Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T10:56:25.463Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T10:56:32.486Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T10:56:34.055Z] 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. [2025-06-13T10:56:34.055Z] The best model improves the baseline by 14.52%. [2025-06-13T10:56:34.814Z] Top recommended movies for user id 72: [2025-06-13T10:56:34.814Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T10:56:34.814Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T10:56:34.814Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T10:56:34.814Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T10:56:34.814Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T10:56:34.814Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (78758.243 ms) ====== [2025-06-13T10:56:34.814Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-13T10:56:35.576Z] GC before operation: completed in 782.180 ms, heap usage 517.837 MB -> 89.014 MB. [2025-06-13T10:56:49.296Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T10:57:05.695Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T10:57:19.292Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T10:57:35.409Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T10:57:45.276Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T10:57:52.667Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T10:58:00.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T10:58:10.516Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T10:58:10.516Z] 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. [2025-06-13T10:58:11.260Z] The best model improves the baseline by 14.52%. [2025-06-13T10:58:11.260Z] Top recommended movies for user id 72: [2025-06-13T10:58:11.260Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T10:58:11.260Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T10:58:11.260Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T10:58:11.260Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T10:58:11.260Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T10:58:11.260Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (95917.259 ms) ====== [2025-06-13T10:58:11.260Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-13T10:58:11.999Z] GC before operation: completed in 719.877 ms, heap usage 205.964 MB -> 88.535 MB. [2025-06-13T10:58:25.667Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T10:58:41.669Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T10:58:53.632Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T10:59:07.195Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T10:59:18.622Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T10:59:26.763Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T10:59:36.440Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T10:59:44.515Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T10:59:46.576Z] 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. [2025-06-13T10:59:46.576Z] The best model improves the baseline by 14.52%. [2025-06-13T10:59:47.322Z] Top recommended movies for user id 72: [2025-06-13T10:59:47.323Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T10:59:47.323Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T10:59:47.323Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T10:59:47.323Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T10:59:47.323Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T10:59:47.323Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (95124.171 ms) ====== [2025-06-13T10:59:47.323Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-13T10:59:48.069Z] GC before operation: completed in 730.067 ms, heap usage 229.746 MB -> 88.751 MB. [2025-06-13T11:00:06.741Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:00:20.321Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:00:36.377Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:00:50.268Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:01:00.064Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:01:09.968Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:01:19.885Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:01:28.098Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:01:28.853Z] 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. [2025-06-13T11:01:29.622Z] The best model improves the baseline by 14.52%. [2025-06-13T11:01:30.384Z] Top recommended movies for user id 72: [2025-06-13T11:01:30.384Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:01:30.384Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:01:30.384Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:01:30.384Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:01:30.384Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:01:30.384Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (102141.659 ms) ====== [2025-06-13T11:01:30.384Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-13T11:01:31.148Z] GC before operation: completed in 768.514 ms, heap usage 160.915 MB -> 88.535 MB. [2025-06-13T11:01:47.823Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:02:01.735Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:02:18.046Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:02:34.176Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:02:42.429Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:02:50.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:03:02.483Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:03:12.329Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:03:13.223Z] 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. [2025-06-13T11:03:13.223Z] The best model improves the baseline by 14.52%. [2025-06-13T11:03:13.981Z] Top recommended movies for user id 72: [2025-06-13T11:03:13.981Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:03:13.981Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:03:13.981Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:03:13.981Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:03:13.981Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:03:13.981Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (102849.923 ms) ====== [2025-06-13T11:03:13.981Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-13T11:03:14.759Z] GC before operation: completed in 748.421 ms, heap usage 419.851 MB -> 89.055 MB. [2025-06-13T11:03:33.636Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:03:49.733Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:04:03.361Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:04:17.236Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:04:28.078Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:04:36.602Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:04:46.045Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:04:53.003Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:04:53.771Z] 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. [2025-06-13T11:04:54.579Z] The best model improves the baseline by 14.52%. [2025-06-13T11:04:55.363Z] Top recommended movies for user id 72: [2025-06-13T11:04:55.364Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:04:55.364Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:04:55.364Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:04:55.364Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:04:55.364Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:04:55.364Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (100502.007 ms) ====== [2025-06-13T11:04:55.364Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-13T11:04:56.124Z] GC before operation: completed in 796.821 ms, heap usage 216.585 MB -> 88.536 MB. [2025-06-13T11:05:12.583Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:05:26.572Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:05:40.444Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:05:57.027Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:06:03.967Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:06:12.317Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:06:20.683Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:06:27.609Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:06:29.223Z] 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. [2025-06-13T11:06:29.223Z] The best model improves the baseline by 14.52%. [2025-06-13T11:06:29.223Z] Top recommended movies for user id 72: [2025-06-13T11:06:29.223Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:06:29.223Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:06:29.223Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:06:29.223Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:06:29.223Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:06:29.223Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (93530.996 ms) ====== [2025-06-13T11:06:29.223Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-13T11:06:29.986Z] GC before operation: completed in 575.255 ms, heap usage 398.743 MB -> 89.003 MB. [2025-06-13T11:06:41.667Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:06:55.995Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:07:12.253Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:07:24.097Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:07:35.839Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:07:44.178Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:07:55.460Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:08:03.795Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:08:05.388Z] 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. [2025-06-13T11:08:05.388Z] The best model improves the baseline by 14.52%. [2025-06-13T11:08:06.157Z] Top recommended movies for user id 72: [2025-06-13T11:08:06.157Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:08:06.157Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:08:06.157Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:08:06.157Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:08:06.157Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:08:06.157Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (96365.392 ms) ====== [2025-06-13T11:08:06.157Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-13T11:08:06.925Z] GC before operation: completed in 627.435 ms, heap usage 397.983 MB -> 89.100 MB. [2025-06-13T11:08:20.906Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:08:37.353Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:08:51.627Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:09:07.910Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:09:14.862Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:09:23.258Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:09:35.103Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:09:43.462Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:09:44.244Z] 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. [2025-06-13T11:09:45.045Z] The best model improves the baseline by 14.52%. [2025-06-13T11:09:45.045Z] Top recommended movies for user id 72: [2025-06-13T11:09:45.045Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:09:45.045Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:09:45.045Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:09:45.045Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:09:45.045Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:09:45.045Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (98361.588 ms) ====== [2025-06-13T11:09:45.045Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-13T11:09:45.817Z] GC before operation: completed in 831.047 ms, heap usage 274.609 MB -> 88.803 MB. [2025-06-13T11:10:02.136Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:10:16.520Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:10:32.873Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:10:46.824Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:10:55.224Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:11:02.188Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:11:10.946Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:11:19.330Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:11:21.009Z] 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. [2025-06-13T11:11:21.009Z] The best model improves the baseline by 14.52%. [2025-06-13T11:11:21.009Z] Top recommended movies for user id 72: [2025-06-13T11:11:21.009Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:11:21.009Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:11:21.009Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:11:21.009Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:11:21.009Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:11:21.009Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (95182.645 ms) ====== [2025-06-13T11:11:21.009Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-13T11:11:22.654Z] GC before operation: completed in 891.157 ms, heap usage 153.667 MB -> 86.236 MB. [2025-06-13T11:11:36.505Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:11:50.431Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:12:04.304Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:12:18.725Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:12:28.799Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:12:37.165Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:12:47.175Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:12:57.150Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:12:57.150Z] 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. [2025-06-13T11:12:57.150Z] The best model improves the baseline by 14.52%. [2025-06-13T11:12:57.921Z] Top recommended movies for user id 72: [2025-06-13T11:12:57.921Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:12:57.921Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:12:57.921Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:12:57.921Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:12:57.921Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:12:57.921Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (95646.251 ms) ====== [2025-06-13T11:12:57.921Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-13T11:12:58.721Z] GC before operation: completed in 739.601 ms, heap usage 439.135 MB -> 85.007 MB. [2025-06-13T11:13:13.142Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:13:27.191Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:13:43.469Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:13:55.263Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:14:02.186Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:14:11.132Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:14:21.186Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:14:29.520Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:14:31.132Z] 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. [2025-06-13T11:14:31.132Z] The best model improves the baseline by 14.52%. [2025-06-13T11:14:31.908Z] Top recommended movies for user id 72: [2025-06-13T11:14:31.908Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:14:31.908Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:14:31.908Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:14:31.908Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:14:31.908Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:14:31.908Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (93059.184 ms) ====== [2025-06-13T11:14:31.908Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-13T11:14:32.687Z] GC before operation: completed in 779.480 ms, heap usage 310.676 MB -> 84.876 MB. [2025-06-13T11:14:48.874Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:15:02.783Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:15:16.823Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:15:30.711Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:15:40.732Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:15:47.615Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:15:57.624Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:16:06.558Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:16:07.353Z] 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. [2025-06-13T11:16:07.353Z] The best model improves the baseline by 14.52%. [2025-06-13T11:16:08.130Z] Top recommended movies for user id 72: [2025-06-13T11:16:08.131Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:16:08.131Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:16:08.131Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:16:08.131Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:16:08.131Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:16:08.131Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (95880.970 ms) ====== [2025-06-13T11:16:08.131Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-13T11:16:08.901Z] GC before operation: completed in 704.561 ms, heap usage 398.140 MB -> 84.272 MB. [2025-06-13T11:16:22.764Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:16:36.674Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:16:52.919Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:17:09.949Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:17:18.235Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:17:26.557Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:17:36.571Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:17:43.475Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:17:44.258Z] 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. [2025-06-13T11:17:44.258Z] The best model improves the baseline by 14.52%. [2025-06-13T11:17:45.043Z] Top recommended movies for user id 72: [2025-06-13T11:17:45.043Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:17:45.043Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:17:45.043Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:17:45.043Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:17:45.043Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:17:45.043Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (95636.692 ms) ====== [2025-06-13T11:17:45.043Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-13T11:17:45.814Z] GC before operation: completed in 744.458 ms, heap usage 191.488 MB -> 84.126 MB. [2025-06-13T11:17:59.686Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-13T11:18:13.948Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-13T11:18:29.616Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-13T11:18:43.363Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-13T11:18:51.807Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-13T11:19:01.649Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-13T11:19:10.613Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-13T11:19:20.669Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-13T11:19:20.669Z] 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. [2025-06-13T11:19:20.669Z] The best model improves the baseline by 14.52%. [2025-06-13T11:19:21.432Z] Top recommended movies for user id 72: [2025-06-13T11:19:21.432Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-13T11:19:21.432Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-13T11:19:21.432Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-13T11:19:21.432Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-13T11:19:21.432Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-13T11:19:21.432Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (96077.392 ms) ====== [2025-06-13T11:19:23.893Z] ----------------------------------- [2025-06-13T11:19:23.893Z] renaissance-movie-lens_0_PASSED [2025-06-13T11:19:23.893Z] ----------------------------------- [2025-06-13T11:19:23.893Z] [2025-06-13T11:19:23.893Z] TEST TEARDOWN: [2025-06-13T11:19:23.893Z] Nothing to be done for teardown. [2025-06-13T11:19:23.893Z] renaissance-movie-lens_0 Finish Time: Fri Jun 13 11:19:23 2025 Epoch Time (ms): 1749813563222