[2025-06-12T13:44:51.217Z] Running test renaissance-movie-lens_0 ... [2025-06-12T13:44:51.217Z] =============================================== [2025-06-12T13:44:51.527Z] renaissance-movie-lens_0 Start Time: Thu Jun 12 13:44:51 2025 Epoch Time (ms): 1749735891307 [2025-06-12T13:44:51.528Z] variation: NoOptions [2025-06-12T13:44:51.528Z] JVM_OPTIONS: [2025-06-12T13:44:51.528Z] { \ [2025-06-12T13:44:51.528Z] echo ""; echo "TEST SETUP:"; \ [2025-06-12T13:44:51.528Z] echo "Nothing to be done for setup."; \ [2025-06-12T13:44:51.528Z] mkdir -p "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17497346318379\\renaissance-movie-lens_0"; \ [2025-06-12T13:44:51.528Z] cd "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17497346318379\\renaissance-movie-lens_0"; \ [2025-06-12T13:44:51.528Z] echo ""; echo "TESTING:"; \ [2025-06-12T13:44:51.528Z] "c:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/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_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17497346318379\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-06-12T13:44:51.528Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17497346318379\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-12T13:44:51.528Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-12T13:44:51.528Z] echo "Nothing to be done for teardown."; \ [2025-06-12T13:44:51.528Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17497346318379\\TestTargetResult"; [2025-06-12T13:44:51.854Z] [2025-06-12T13:44:51.854Z] TEST SETUP: [2025-06-12T13:44:51.854Z] Nothing to be done for setup. [2025-06-12T13:44:51.854Z] [2025-06-12T13:44:51.854Z] TESTING: [2025-06-12T13:45:04.755Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-12T13:45:10.586Z] 13:45:10.166 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-06-12T13:45:12.774Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-12T13:45:13.114Z] Training: 60056, validation: 20285, test: 19854 [2025-06-12T13:45:13.114Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-12T13:45:13.114Z] GC before operation: completed in 138.324 ms, heap usage 309.159 MB -> 76.325 MB. [2025-06-12T13:45:26.144Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:45:33.312Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:45:42.117Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:45:49.247Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:45:53.905Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:45:57.576Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:46:03.346Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:46:07.096Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:46:07.526Z] 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. [2025-06-12T13:46:07.526Z] The best model improves the baseline by 14.52%. [2025-06-12T13:46:07.526Z] Top recommended movies for user id 72: [2025-06-12T13:46:07.526Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:46:07.526Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:46:07.526Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:46:07.526Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:46:07.526Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:46:07.850Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (54421.240 ms) ====== [2025-06-12T13:46:07.850Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-12T13:46:07.850Z] GC before operation: completed in 116.514 ms, heap usage 319.529 MB -> 87.174 MB. [2025-06-12T13:46:14.953Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:46:22.067Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:46:29.181Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:46:36.312Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:46:39.999Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:46:43.706Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:46:48.330Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:46:52.033Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:46:52.358Z] 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. [2025-06-12T13:46:52.358Z] The best model improves the baseline by 14.52%. [2025-06-12T13:46:52.688Z] Top recommended movies for user id 72: [2025-06-12T13:46:52.688Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:46:52.688Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:46:52.688Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:46:52.688Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:46:52.688Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:46:52.688Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (44979.770 ms) ====== [2025-06-12T13:46:52.688Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-12T13:46:52.688Z] GC before operation: completed in 112.880 ms, heap usage 175.172 MB -> 89.128 MB. [2025-06-12T13:46:59.797Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:47:06.912Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:47:14.027Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:47:21.173Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:47:24.034Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:47:28.662Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:47:32.324Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:47:35.989Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:47:36.321Z] 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. [2025-06-12T13:47:36.322Z] The best model improves the baseline by 14.52%. [2025-06-12T13:47:36.656Z] Top recommended movies for user id 72: [2025-06-12T13:47:36.656Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:47:36.656Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:47:36.656Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:47:36.656Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:47:36.656Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:47:36.656Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (43873.049 ms) ====== [2025-06-12T13:47:36.656Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-12T13:47:36.656Z] GC before operation: completed in 112.130 ms, heap usage 117.958 MB -> 89.706 MB. [2025-06-12T13:47:43.828Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:47:49.601Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:47:58.306Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:48:04.108Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:48:07.798Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:48:11.477Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:48:16.090Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:48:19.757Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:48:19.757Z] 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. [2025-06-12T13:48:19.757Z] The best model improves the baseline by 14.52%. [2025-06-12T13:48:20.085Z] Top recommended movies for user id 72: [2025-06-12T13:48:20.085Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:48:20.085Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:48:20.085Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:48:20.085Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:48:20.085Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:48:20.085Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (43307.394 ms) ====== [2025-06-12T13:48:20.085Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-12T13:48:20.085Z] GC before operation: completed in 109.727 ms, heap usage 307.770 MB -> 90.302 MB. [2025-06-12T13:48:27.233Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:48:34.396Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:48:41.516Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:48:47.313Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:48:50.987Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:48:54.658Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:48:58.340Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:49:02.006Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:49:02.338Z] 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. [2025-06-12T13:49:02.338Z] The best model improves the baseline by 14.52%. [2025-06-12T13:49:02.659Z] Top recommended movies for user id 72: [2025-06-12T13:49:02.659Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:49:02.659Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:49:02.659Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:49:02.659Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:49:02.659Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:49:02.659Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (42371.207 ms) ====== [2025-06-12T13:49:02.659Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-12T13:49:02.659Z] GC before operation: completed in 117.229 ms, heap usage 366.886 MB -> 90.381 MB. [2025-06-12T13:49:09.763Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:49:15.585Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:49:22.678Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:49:29.797Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:49:32.655Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:49:36.334Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:49:40.971Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:49:44.635Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:49:44.635Z] 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. [2025-06-12T13:49:44.635Z] The best model improves the baseline by 14.52%. [2025-06-12T13:49:44.973Z] Top recommended movies for user id 72: [2025-06-12T13:49:44.973Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:49:44.973Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:49:44.973Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:49:44.973Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:49:44.973Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:49:44.973Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (42332.614 ms) ====== [2025-06-12T13:49:44.973Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-12T13:49:45.310Z] GC before operation: completed in 110.454 ms, heap usage 233.002 MB -> 90.448 MB. [2025-06-12T13:49:52.489Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:49:58.262Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:50:05.420Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:50:12.502Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:50:15.359Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:50:19.993Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:50:23.671Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:50:27.336Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:50:27.659Z] 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. [2025-06-12T13:50:27.659Z] The best model improves the baseline by 14.52%. [2025-06-12T13:50:27.987Z] Top recommended movies for user id 72: [2025-06-12T13:50:27.987Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:50:27.987Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:50:27.987Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:50:27.987Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:50:27.987Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:50:27.987Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (42817.813 ms) ====== [2025-06-12T13:50:27.987Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-12T13:50:27.987Z] GC before operation: completed in 113.627 ms, heap usage 211.766 MB -> 90.407 MB. [2025-06-12T13:50:35.133Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:50:42.248Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:50:49.342Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:50:55.096Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:50:58.794Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:51:02.475Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:51:06.156Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:51:09.828Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:51:10.176Z] 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. [2025-06-12T13:51:10.510Z] The best model improves the baseline by 14.52%. [2025-06-12T13:51:10.511Z] Top recommended movies for user id 72: [2025-06-12T13:51:10.511Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:51:10.511Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:51:10.511Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:51:10.511Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:51:10.511Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:51:10.511Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (42477.956 ms) ====== [2025-06-12T13:51:10.511Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-12T13:51:10.833Z] GC before operation: completed in 119.715 ms, heap usage 494.776 MB -> 94.236 MB. [2025-06-12T13:51:17.940Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:51:23.686Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:51:30.804Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:51:36.558Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:51:41.176Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:51:44.068Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:51:48.678Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:51:52.353Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:51:52.697Z] 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. [2025-06-12T13:51:52.697Z] The best model improves the baseline by 14.52%. [2025-06-12T13:51:53.073Z] Top recommended movies for user id 72: [2025-06-12T13:51:53.073Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:51:53.073Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:51:53.073Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:51:53.073Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:51:53.073Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:51:53.073Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (42206.940 ms) ====== [2025-06-12T13:51:53.073Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-12T13:51:53.073Z] GC before operation: completed in 112.309 ms, heap usage 212.900 MB -> 90.439 MB. [2025-06-12T13:52:00.201Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:52:05.972Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:52:13.074Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:52:20.203Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:52:23.884Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:52:27.624Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:52:31.306Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:52:34.985Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:52:35.313Z] 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. [2025-06-12T13:52:35.313Z] The best model improves the baseline by 14.52%. [2025-06-12T13:52:35.640Z] Top recommended movies for user id 72: [2025-06-12T13:52:35.640Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:52:35.640Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:52:35.640Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:52:35.640Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:52:35.641Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:52:35.641Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (42635.624 ms) ====== [2025-06-12T13:52:35.641Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-12T13:52:35.641Z] GC before operation: completed in 110.512 ms, heap usage 179.060 MB -> 90.601 MB. [2025-06-12T13:52:42.755Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:52:48.520Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:52:55.618Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:53:02.708Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:53:06.424Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:53:10.099Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:53:13.776Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:53:17.430Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:53:17.771Z] 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. [2025-06-12T13:53:17.771Z] The best model improves the baseline by 14.52%. [2025-06-12T13:53:18.103Z] Top recommended movies for user id 72: [2025-06-12T13:53:18.103Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:53:18.103Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:53:18.103Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:53:18.103Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:53:18.103Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:53:18.103Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (42397.305 ms) ====== [2025-06-12T13:53:18.103Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-12T13:53:18.103Z] GC before operation: completed in 112.995 ms, heap usage 119.135 MB -> 90.304 MB. [2025-06-12T13:53:25.204Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:53:30.967Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:53:39.684Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:53:45.432Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:53:48.295Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:53:52.936Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:53:56.654Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:54:00.320Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:54:00.642Z] 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. [2025-06-12T13:54:00.642Z] The best model improves the baseline by 14.52%. [2025-06-12T13:54:00.988Z] Top recommended movies for user id 72: [2025-06-12T13:54:00.988Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:54:00.988Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:54:00.988Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:54:00.988Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:54:00.988Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:54:00.988Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (42594.945 ms) ====== [2025-06-12T13:54:00.988Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-12T13:54:00.988Z] GC before operation: completed in 111.531 ms, heap usage 221.612 MB -> 90.623 MB. [2025-06-12T13:54:08.084Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:54:13.894Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:54:21.611Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:54:27.376Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:54:31.054Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:54:35.666Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:54:39.419Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:54:43.079Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:54:43.398Z] 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. [2025-06-12T13:54:43.398Z] The best model improves the baseline by 14.52%. [2025-06-12T13:54:43.724Z] Top recommended movies for user id 72: [2025-06-12T13:54:43.724Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:54:43.724Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:54:43.724Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:54:43.724Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:54:43.724Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:54:43.724Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (42664.642 ms) ====== [2025-06-12T13:54:43.724Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-12T13:54:43.724Z] GC before operation: completed in 112.983 ms, heap usage 308.110 MB -> 90.918 MB. [2025-06-12T13:54:50.822Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:54:56.571Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:55:03.667Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:55:10.804Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:55:13.697Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:55:17.361Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:55:21.985Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:55:25.649Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:55:25.649Z] 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. [2025-06-12T13:55:25.649Z] The best model improves the baseline by 14.52%. [2025-06-12T13:55:25.991Z] Top recommended movies for user id 72: [2025-06-12T13:55:25.991Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:55:25.991Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:55:25.991Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:55:25.991Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:55:25.991Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:55:25.991Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (42299.018 ms) ====== [2025-06-12T13:55:25.991Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-12T13:55:26.315Z] GC before operation: completed in 116.348 ms, heap usage 290.107 MB -> 90.678 MB. [2025-06-12T13:55:33.413Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:55:39.168Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:55:46.300Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:55:53.392Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:55:57.063Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:56:00.733Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:56:04.608Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:56:08.293Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:56:08.625Z] 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. [2025-06-12T13:56:08.625Z] The best model improves the baseline by 14.52%. [2025-06-12T13:56:08.960Z] Top recommended movies for user id 72: [2025-06-12T13:56:08.960Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:56:08.960Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:56:08.960Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:56:08.960Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:56:08.960Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:56:08.960Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (42757.662 ms) ====== [2025-06-12T13:56:08.960Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-12T13:56:08.960Z] GC before operation: completed in 110.706 ms, heap usage 212.708 MB -> 90.800 MB. [2025-06-12T13:56:16.074Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:56:21.850Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:56:28.988Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:56:36.095Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:56:39.002Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:56:42.666Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:56:47.301Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:56:50.959Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:56:50.959Z] 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. [2025-06-12T13:56:50.959Z] The best model improves the baseline by 14.52%. [2025-06-12T13:56:51.290Z] Top recommended movies for user id 72: [2025-06-12T13:56:51.290Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:56:51.290Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:56:51.290Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:56:51.290Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:56:51.291Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:56:51.291Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (42213.066 ms) ====== [2025-06-12T13:56:51.291Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-12T13:56:51.291Z] GC before operation: completed in 111.732 ms, heap usage 232.098 MB -> 90.632 MB. [2025-06-12T13:56:58.379Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:57:04.136Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:57:11.277Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:57:18.400Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:57:21.257Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:57:24.937Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:57:29.546Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:57:32.457Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:57:33.144Z] 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. [2025-06-12T13:57:33.144Z] The best model improves the baseline by 14.52%. [2025-06-12T13:57:33.475Z] Top recommended movies for user id 72: [2025-06-12T13:57:33.475Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:57:33.475Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:57:33.475Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:57:33.475Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:57:33.475Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:57:33.475Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (41989.484 ms) ====== [2025-06-12T13:57:33.475Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-12T13:57:33.475Z] GC before operation: completed in 113.320 ms, heap usage 298.710 MB -> 90.891 MB. [2025-06-12T13:57:40.631Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:57:47.741Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:57:54.896Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:58:00.654Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:58:04.327Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:58:08.054Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:58:11.742Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:58:15.446Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:58:15.769Z] 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. [2025-06-12T13:58:15.769Z] The best model improves the baseline by 14.52%. [2025-06-12T13:58:16.093Z] Top recommended movies for user id 72: [2025-06-12T13:58:16.093Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:58:16.093Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:58:16.093Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:58:16.093Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:58:16.093Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:58:16.093Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (42591.705 ms) ====== [2025-06-12T13:58:16.093Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-12T13:58:16.093Z] GC before operation: completed in 109.596 ms, heap usage 233.650 MB -> 90.546 MB. [2025-06-12T13:58:23.210Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:58:28.982Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:58:36.081Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:58:43.217Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:58:46.105Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:58:49.781Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:58:54.452Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:58:58.128Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:58:58.446Z] 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. [2025-06-12T13:58:58.446Z] The best model improves the baseline by 14.52%. [2025-06-12T13:58:58.768Z] Top recommended movies for user id 72: [2025-06-12T13:58:58.768Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:58:58.769Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:58:58.769Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:58:58.769Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:58:58.769Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:58:58.769Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (42513.669 ms) ====== [2025-06-12T13:58:58.769Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-12T13:58:58.769Z] GC before operation: completed in 114.553 ms, heap usage 211.850 MB -> 90.677 MB. [2025-06-12T13:59:05.892Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T13:59:11.679Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T13:59:20.460Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T13:59:25.075Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T13:59:28.777Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T13:59:32.446Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T13:59:37.088Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T13:59:40.136Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T13:59:40.832Z] 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. [2025-06-12T13:59:40.832Z] The best model improves the baseline by 14.52%. [2025-06-12T13:59:40.832Z] Top recommended movies for user id 72: [2025-06-12T13:59:40.832Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-12T13:59:40.832Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-12T13:59:40.832Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-12T13:59:40.832Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-12T13:59:40.832Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-12T13:59:40.832Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (42164.283 ms) ====== [2025-06-12T13:59:41.521Z] ----------------------------------- [2025-06-12T13:59:41.521Z] renaissance-movie-lens_0_PASSED [2025-06-12T13:59:41.521Z] ----------------------------------- [2025-06-12T13:59:41.832Z] [2025-06-12T13:59:41.832Z] TEST TEARDOWN: [2025-06-12T13:59:41.832Z] Nothing to be done for teardown. [2025-06-12T13:59:41.832Z] renaissance-movie-lens_0 Finish Time: Thu Jun 12 13:59:41 2025 Epoch Time (ms): 1749736781767