Test Results Summary Service

renaissance-movie-lens_0

[2025-12-06T14:17:55.106Z] Running test renaissance-movie-lens_0 ... [2025-12-06T14:17:55.106Z] =============================================== [2025-12-06T14:17:55.507Z] renaissance-movie-lens_0 Start Time: Sat Dec 6 06:17:54 2025 Epoch Time (ms): 1765030674979 [2025-12-06T14:17:55.507Z] variation: NoOptions [2025-12-06T14:17:55.507Z] JVM_OPTIONS: [2025-12-06T14:17:55.507Z] { \ [2025-12-06T14:17:55.508Z] echo ""; echo "TEST SETUP:"; \ [2025-12-06T14:17:55.508Z] echo "Nothing to be done for setup."; \ [2025-12-06T14:17:55.508Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17650287207940/renaissance-movie-lens_0"; \ [2025-12-06T14:17:55.508Z] cd "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17650287207940/renaissance-movie-lens_0"; \ [2025-12-06T14:17:55.508Z] echo ""; echo "TESTING:"; \ [2025-12-06T14:17:55.508Z] "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//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 "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17650287207940/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-06T14:17:55.508Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17650287207940/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-06T14:17:55.508Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-06T14:17:55.508Z] echo "Nothing to be done for teardown."; \ [2025-12-06T14:17:55.508Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17650287207940/TestTargetResult"; [2025-12-06T14:17:55.508Z] [2025-12-06T14:17:55.508Z] TEST SETUP: [2025-12-06T14:17:55.508Z] Nothing to be done for setup. [2025-12-06T14:17:55.508Z] [2025-12-06T14:17:55.508Z] TESTING: [2025-12-06T14:17:56.428Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-06T14:17:56.428Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/output_17650287207940/renaissance-movie-lens_0/launcher-061755-2773090128292757617/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-06T14:17:56.428Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-06T14:17:56.428Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-06T14:18:11.088Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-06T14:18:25.635Z] 06:18:23.835 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. [2025-12-06T14:18:30.465Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-06T14:18:30.465Z] Training: 60056, validation: 20285, test: 19854 [2025-12-06T14:18:30.465Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-06T14:18:30.849Z] GC before operation: completed in 235.215 ms, heap usage 442.513 MB -> 75.223 MB. [2025-12-06T14:18:46.117Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:18:56.543Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:19:05.428Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:19:14.196Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:19:20.474Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:19:26.560Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:19:32.465Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:19:38.674Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:19:39.195Z] 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. [2025-12-06T14:19:39.770Z] The best model improves the baseline by 14.52%. [2025-12-06T14:19:40.313Z] Top recommended movies for user id 72: [2025-12-06T14:19:40.313Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:19:40.313Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:19:40.313Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:19:40.313Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:19:40.313Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:19:40.713Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (69785.849 ms) ====== [2025-12-06T14:19:40.713Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-06T14:19:40.713Z] GC before operation: completed in 239.946 ms, heap usage 156.849 MB -> 87.498 MB. [2025-12-06T14:19:53.143Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:20:03.169Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:20:11.883Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:20:17.505Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:20:20.139Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:20:23.681Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:20:27.183Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:20:30.634Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:20:30.634Z] 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. [2025-12-06T14:20:30.634Z] The best model improves the baseline by 14.52%. [2025-12-06T14:20:30.634Z] Top recommended movies for user id 72: [2025-12-06T14:20:30.634Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:20:30.634Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:20:30.634Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:20:30.634Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:20:30.634Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:20:30.634Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (49848.852 ms) ====== [2025-12-06T14:20:30.634Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-06T14:20:30.634Z] GC before operation: completed in 164.076 ms, heap usage 1.808 GB -> 94.439 MB. [2025-12-06T14:20:37.326Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:20:43.037Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:20:49.945Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:20:55.458Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:20:57.495Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:21:00.875Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:21:03.530Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:21:08.052Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:21:08.052Z] 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. [2025-12-06T14:21:08.052Z] The best model improves the baseline by 14.52%. [2025-12-06T14:21:08.558Z] Top recommended movies for user id 72: [2025-12-06T14:21:08.558Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:21:08.558Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:21:08.558Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:21:08.558Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:21:08.558Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:21:08.558Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (37879.189 ms) ====== [2025-12-06T14:21:08.558Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-06T14:21:08.967Z] GC before operation: completed in 465.106 ms, heap usage 783.638 MB -> 92.326 MB. [2025-12-06T14:21:14.337Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:21:19.703Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:21:25.038Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:21:30.470Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:21:33.281Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:21:36.789Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:21:38.786Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:21:41.386Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:21:41.386Z] 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. [2025-12-06T14:21:41.386Z] The best model improves the baseline by 14.52%. [2025-12-06T14:21:41.769Z] Top recommended movies for user id 72: [2025-12-06T14:21:41.769Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:21:41.769Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:21:41.769Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:21:41.769Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:21:41.769Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:21:41.769Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (32599.300 ms) ====== [2025-12-06T14:21:41.769Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-06T14:21:41.769Z] GC before operation: completed in 134.408 ms, heap usage 356.394 MB -> 88.804 MB. [2025-12-06T14:21:45.981Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:21:49.323Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:21:53.756Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:21:57.168Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:21:59.964Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:22:02.604Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:22:05.996Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:22:08.638Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:22:08.638Z] 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. [2025-12-06T14:22:08.638Z] The best model improves the baseline by 14.52%. [2025-12-06T14:22:09.014Z] Top recommended movies for user id 72: [2025-12-06T14:22:09.014Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:22:09.014Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:22:09.014Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:22:09.014Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:22:09.014Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:22:09.014Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (27015.751 ms) ====== [2025-12-06T14:22:09.014Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-06T14:22:09.014Z] GC before operation: completed in 115.924 ms, heap usage 103.810 MB -> 94.007 MB. [2025-12-06T14:22:15.474Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:22:19.945Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:22:23.252Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:22:26.502Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:22:29.094Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:22:30.415Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:22:33.141Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:22:35.863Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:22:35.863Z] 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. [2025-12-06T14:22:35.863Z] The best model improves the baseline by 14.52%. [2025-12-06T14:22:36.253Z] Top recommended movies for user id 72: [2025-12-06T14:22:36.254Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:22:36.254Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:22:36.254Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:22:36.254Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:22:36.254Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:22:36.254Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (27286.959 ms) ====== [2025-12-06T14:22:36.254Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-06T14:22:36.254Z] GC before operation: completed in 164.886 ms, heap usage 913.942 MB -> 93.608 MB. [2025-12-06T14:22:42.809Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:22:45.478Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:22:50.800Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:22:56.217Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:22:58.868Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:23:00.227Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:23:03.009Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:23:06.482Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:23:07.390Z] 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. [2025-12-06T14:23:07.827Z] The best model improves the baseline by 14.52%. [2025-12-06T14:23:07.827Z] Top recommended movies for user id 72: [2025-12-06T14:23:07.827Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:23:07.827Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:23:07.827Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:23:07.827Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:23:07.827Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:23:07.827Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (31490.793 ms) ====== [2025-12-06T14:23:07.827Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-06T14:23:08.233Z] GC before operation: completed in 270.565 ms, heap usage 742.785 MB -> 92.825 MB. [2025-12-06T14:23:14.890Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:23:19.212Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:23:24.925Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:23:28.441Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:23:31.282Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:23:33.975Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:23:35.277Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:23:37.841Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:23:38.211Z] 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. [2025-12-06T14:23:38.211Z] The best model improves the baseline by 14.52%. [2025-12-06T14:23:38.211Z] Top recommended movies for user id 72: [2025-12-06T14:23:38.211Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:23:38.211Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:23:38.211Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:23:38.211Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:23:38.211Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:23:38.211Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (29983.652 ms) ====== [2025-12-06T14:23:38.211Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-06T14:23:38.211Z] GC before operation: completed in 108.992 ms, heap usage 869.557 MB -> 93.553 MB. [2025-12-06T14:23:44.908Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:23:50.179Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:23:56.809Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:24:01.319Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:24:05.733Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:24:10.293Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:24:14.476Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:24:17.891Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:24:17.891Z] 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. [2025-12-06T14:24:17.891Z] The best model improves the baseline by 14.52%. [2025-12-06T14:24:19.404Z] Top recommended movies for user id 72: [2025-12-06T14:24:19.404Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:24:19.404Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:24:19.404Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:24:19.404Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:24:19.404Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:24:19.404Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (40788.685 ms) ====== [2025-12-06T14:24:19.404Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-06T14:24:19.404Z] GC before operation: completed in 185.205 ms, heap usage 152.959 MB -> 92.442 MB. [2025-12-06T14:24:26.178Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:24:31.406Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:24:39.508Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:24:44.824Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:24:46.805Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:24:50.432Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:24:53.900Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:24:57.426Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:24:57.426Z] 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. [2025-12-06T14:24:57.426Z] The best model improves the baseline by 14.52%. [2025-12-06T14:24:57.840Z] Top recommended movies for user id 72: [2025-12-06T14:24:57.840Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:24:57.840Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:24:57.840Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:24:57.840Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:24:57.840Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:24:57.840Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (38372.893 ms) ====== [2025-12-06T14:24:57.840Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-06T14:24:57.840Z] GC before operation: completed in 121.152 ms, heap usage 827.445 MB -> 93.511 MB. [2025-12-06T14:25:04.733Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:25:10.204Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:25:15.555Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:25:19.891Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:25:22.775Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:25:26.261Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:25:28.948Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:25:33.283Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:25:34.531Z] 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. [2025-12-06T14:25:34.531Z] The best model improves the baseline by 14.52%. [2025-12-06T14:25:35.066Z] Top recommended movies for user id 72: [2025-12-06T14:25:35.066Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:25:35.066Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:25:35.066Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:25:35.066Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:25:35.066Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:25:35.066Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (37063.990 ms) ====== [2025-12-06T14:25:35.066Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-06T14:25:35.066Z] GC before operation: completed in 121.744 ms, heap usage 180.736 MB -> 89.022 MB. [2025-12-06T14:25:45.184Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:25:55.200Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:26:05.571Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:26:18.395Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:26:24.082Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:26:29.153Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:26:36.594Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:26:41.556Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:26:41.996Z] 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. [2025-12-06T14:26:41.996Z] The best model improves the baseline by 14.52%. [2025-12-06T14:26:41.996Z] Top recommended movies for user id 72: [2025-12-06T14:26:41.996Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:26:41.996Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:26:41.996Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:26:41.996Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:26:41.996Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:26:41.996Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (67105.290 ms) ====== [2025-12-06T14:26:41.996Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-06T14:26:42.566Z] GC before operation: completed in 307.857 ms, heap usage 753.245 MB -> 93.281 MB. [2025-12-06T14:26:54.947Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:27:02.160Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:27:12.870Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:27:21.485Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:27:26.264Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:27:32.344Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:27:39.440Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:27:42.448Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:27:42.874Z] 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. [2025-12-06T14:27:42.874Z] The best model improves the baseline by 14.52%. [2025-12-06T14:27:43.270Z] Top recommended movies for user id 72: [2025-12-06T14:27:43.270Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:27:43.270Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:27:43.270Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:27:43.270Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:27:43.270Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:27:43.270Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (60731.988 ms) ====== [2025-12-06T14:27:43.270Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-06T14:27:43.270Z] GC before operation: completed in 185.264 ms, heap usage 140.900 MB -> 97.003 MB. [2025-12-06T14:27:50.099Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:27:54.631Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:27:58.806Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:28:03.103Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:28:05.779Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:28:08.424Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:28:11.821Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:28:12.659Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:28:13.580Z] 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. [2025-12-06T14:28:13.580Z] The best model improves the baseline by 14.52%. [2025-12-06T14:28:14.042Z] Top recommended movies for user id 72: [2025-12-06T14:28:14.042Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:28:14.042Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:28:14.042Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:28:14.042Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:28:14.042Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:28:14.043Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (30835.348 ms) ====== [2025-12-06T14:28:14.043Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-06T14:28:14.422Z] GC before operation: completed in 213.542 ms, heap usage 397.126 MB -> 89.439 MB. [2025-12-06T14:28:18.725Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:28:23.120Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:28:27.502Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:28:30.952Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:28:33.583Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:28:36.309Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:28:39.042Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:28:41.649Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:28:41.649Z] 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. [2025-12-06T14:28:41.649Z] The best model improves the baseline by 14.52%. [2025-12-06T14:28:42.013Z] Top recommended movies for user id 72: [2025-12-06T14:28:42.013Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:28:42.013Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:28:42.013Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:28:42.013Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:28:42.013Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:28:42.013Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (27580.436 ms) ====== [2025-12-06T14:28:42.013Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-06T14:28:42.013Z] GC before operation: completed in 137.242 ms, heap usage 648.819 MB -> 93.189 MB. [2025-12-06T14:28:45.379Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:28:48.737Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:28:52.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:28:55.506Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:28:58.167Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:29:01.651Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:29:04.592Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:29:08.974Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:29:09.339Z] 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. [2025-12-06T14:29:09.777Z] The best model improves the baseline by 14.52%. [2025-12-06T14:29:09.777Z] Top recommended movies for user id 72: [2025-12-06T14:29:09.777Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:29:09.777Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:29:09.777Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:29:09.777Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:29:09.777Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:29:09.777Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (27838.321 ms) ====== [2025-12-06T14:29:09.777Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-06T14:29:10.147Z] GC before operation: completed in 135.493 ms, heap usage 186.895 MB -> 91.971 MB. [2025-12-06T14:29:15.523Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:29:19.043Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:29:24.653Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:29:29.004Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:29:32.504Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:29:36.771Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:29:41.197Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:29:45.742Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:29:46.122Z] 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. [2025-12-06T14:29:46.526Z] The best model improves the baseline by 14.52%. [2025-12-06T14:29:46.526Z] Top recommended movies for user id 72: [2025-12-06T14:29:46.526Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:29:46.526Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:29:46.526Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:29:46.526Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:29:46.526Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:29:46.526Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (36559.809 ms) ====== [2025-12-06T14:29:46.526Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-06T14:29:46.892Z] GC before operation: completed in 137.895 ms, heap usage 374.549 MB -> 89.629 MB. [2025-12-06T14:29:54.916Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:29:59.195Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:30:06.031Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:30:11.471Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:30:14.147Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:30:16.761Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:30:19.405Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:30:22.138Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:30:22.697Z] 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. [2025-12-06T14:30:22.697Z] The best model improves the baseline by 14.52%. [2025-12-06T14:30:23.594Z] Top recommended movies for user id 72: [2025-12-06T14:30:23.594Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:30:23.594Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:30:23.594Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:30:23.594Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:30:23.594Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:30:23.594Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (36763.204 ms) ====== [2025-12-06T14:30:23.594Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-06T14:30:23.594Z] GC before operation: completed in 108.350 ms, heap usage 202.605 MB -> 89.192 MB. [2025-12-06T14:30:29.123Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:30:35.730Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:30:41.263Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:30:45.584Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:30:48.308Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:30:52.748Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:30:55.313Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:30:58.733Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:30:58.733Z] 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. [2025-12-06T14:30:58.733Z] The best model improves the baseline by 14.52%. [2025-12-06T14:30:58.733Z] Top recommended movies for user id 72: [2025-12-06T14:30:58.733Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:30:58.733Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:30:58.733Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:30:58.733Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:30:58.733Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:30:58.733Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (35258.247 ms) ====== [2025-12-06T14:30:58.733Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-06T14:30:59.133Z] GC before operation: completed in 88.495 ms, heap usage 249.282 MB -> 89.379 MB. [2025-12-06T14:31:04.961Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T14:31:15.175Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T14:31:25.719Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T14:31:36.127Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T14:31:41.006Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T14:31:45.566Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T14:31:51.152Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T14:31:53.977Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T14:31:54.361Z] 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. [2025-12-06T14:31:54.361Z] The best model improves the baseline by 14.52%. [2025-12-06T14:31:54.361Z] Top recommended movies for user id 72: [2025-12-06T14:31:54.361Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-06T14:31:54.361Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-06T14:31:54.361Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-06T14:31:54.361Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-06T14:31:54.361Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-06T14:31:54.361Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (55478.878 ms) ====== [2025-12-06T14:31:56.276Z] ----------------------------------- [2025-12-06T14:31:56.276Z] renaissance-movie-lens_0_PASSED [2025-12-06T14:31:56.276Z] ----------------------------------- [2025-12-06T14:31:56.276Z] [2025-12-06T14:31:56.276Z] TEST TEARDOWN: [2025-12-06T14:31:56.276Z] Nothing to be done for teardown. [2025-12-06T14:31:56.690Z] renaissance-movie-lens_0 Finish Time: Sat Dec 6 06:31:56 2025 Epoch Time (ms): 1765031516073