[2025-12-27T15:31:59.392Z] Running test renaissance-movie-lens_0 ... [2025-12-27T15:31:59.392Z] =============================================== [2025-12-27T15:31:59.392Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 15:31:58 2025 Epoch Time (ms): 1766849518118 [2025-12-27T15:31:59.392Z] variation: NoOptions [2025-12-27T15:31:59.392Z] JVM_OPTIONS: [2025-12-27T15:31:59.392Z] { \ [2025-12-27T15:31:59.392Z] echo ""; echo "TEST SETUP:"; \ [2025-12-27T15:31:59.392Z] echo "Nothing to be done for setup."; \ [2025-12-27T15:31:59.392Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17668484518974/renaissance-movie-lens_0"; \ [2025-12-27T15:31:59.392Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17668484518974/renaissance-movie-lens_0"; \ [2025-12-27T15:31:59.392Z] echo ""; echo "TESTING:"; \ [2025-12-27T15:31:59.392Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17668484518974/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-27T15:31:59.392Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17668484518974/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-27T15:31:59.392Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-27T15:31:59.392Z] echo "Nothing to be done for teardown."; \ [2025-12-27T15:31:59.392Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17668484518974/TestTargetResult"; [2025-12-27T15:31:59.392Z] [2025-12-27T15:31:59.392Z] TEST SETUP: [2025-12-27T15:31:59.392Z] Nothing to be done for setup. [2025-12-27T15:31:59.392Z] [2025-12-27T15:31:59.392Z] TESTING: [2025-12-27T15:31:59.392Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-27T15:31:59.392Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/output_17668484518974/renaissance-movie-lens_0/launcher-153158-11018929235800105318/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-27T15:31:59.392Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-27T15:31:59.392Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-27T15:32:03.610Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-27T15:32:10.123Z] 15:32:09.756 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. [2025-12-27T15:32:12.110Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-27T15:32:13.080Z] Training: 60056, validation: 20285, test: 19854 [2025-12-27T15:32:13.080Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-27T15:32:13.080Z] GC before operation: completed in 147.651 ms, heap usage 296.765 MB -> 75.754 MB. [2025-12-27T15:32:18.535Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:32:21.612Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:32:24.680Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:32:27.748Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:32:28.718Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:32:30.705Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:32:32.703Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:32:33.672Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:32:33.672Z] 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. [2025-12-27T15:32:34.642Z] The best model improves the baseline by 14.52%. [2025-12-27T15:32:34.642Z] Top recommended movies for user id 72: [2025-12-27T15:32:34.642Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:32:34.642Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:32:34.642Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:32:34.642Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:32:34.642Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:32:34.642Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21475.642 ms) ====== [2025-12-27T15:32:34.642Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-27T15:32:34.642Z] GC before operation: completed in 161.014 ms, heap usage 254.514 MB -> 95.187 MB. [2025-12-27T15:32:37.709Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:32:39.697Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:32:42.762Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:32:44.755Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:32:46.744Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:32:48.732Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:32:49.701Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:32:51.689Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:32:51.689Z] 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. [2025-12-27T15:32:51.689Z] The best model improves the baseline by 14.52%. [2025-12-27T15:32:52.658Z] Top recommended movies for user id 72: [2025-12-27T15:32:52.658Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:32:52.658Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:32:52.658Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:32:52.658Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:32:52.658Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:32:52.658Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17789.719 ms) ====== [2025-12-27T15:32:52.658Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-27T15:32:52.658Z] GC before operation: completed in 129.518 ms, heap usage 149.524 MB -> 88.566 MB. [2025-12-27T15:32:54.648Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:32:57.717Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:33:00.784Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:33:02.783Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:33:04.780Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:33:05.749Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:33:07.736Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:33:08.708Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:33:09.677Z] 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. [2025-12-27T15:33:09.677Z] The best model improves the baseline by 14.52%. [2025-12-27T15:33:09.677Z] Top recommended movies for user id 72: [2025-12-27T15:33:09.677Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:33:09.677Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:33:09.677Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:33:09.677Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:33:09.677Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:33:09.677Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17297.208 ms) ====== [2025-12-27T15:33:09.677Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-27T15:33:09.677Z] GC before operation: completed in 150.837 ms, heap usage 147.717 MB -> 89.200 MB. [2025-12-27T15:33:12.745Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:33:14.734Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:33:17.803Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:33:19.792Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:33:21.783Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:33:22.752Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:33:24.741Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:33:26.628Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:33:26.628Z] 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. [2025-12-27T15:33:26.628Z] The best model improves the baseline by 14.52%. [2025-12-27T15:33:26.628Z] Top recommended movies for user id 72: [2025-12-27T15:33:26.628Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:33:26.628Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:33:26.628Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:33:26.628Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:33:26.628Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:33:26.629Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16970.093 ms) ====== [2025-12-27T15:33:26.629Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-27T15:33:26.629Z] GC before operation: completed in 136.371 ms, heap usage 167.527 MB -> 89.508 MB. [2025-12-27T15:33:29.877Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:33:31.864Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:33:33.852Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:33:36.931Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:33:37.900Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:33:38.869Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:33:40.855Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:33:41.833Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:33:42.800Z] 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. [2025-12-27T15:33:42.800Z] The best model improves the baseline by 14.52%. [2025-12-27T15:33:42.800Z] Top recommended movies for user id 72: [2025-12-27T15:33:42.800Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:33:42.800Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:33:42.800Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:33:42.800Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:33:42.800Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:33:42.800Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15479.508 ms) ====== [2025-12-27T15:33:42.800Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-27T15:33:42.800Z] GC before operation: completed in 149.800 ms, heap usage 510.857 MB -> 89.945 MB. [2025-12-27T15:33:44.785Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:33:46.773Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:33:49.840Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:33:51.831Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:33:52.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:33:53.779Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:33:55.765Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:33:56.737Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:33:57.706Z] 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. [2025-12-27T15:33:57.706Z] The best model improves the baseline by 14.52%. [2025-12-27T15:33:57.706Z] Top recommended movies for user id 72: [2025-12-27T15:33:57.706Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:33:57.706Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:33:57.706Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:33:57.706Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:33:57.706Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:33:57.706Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14831.501 ms) ====== [2025-12-27T15:33:57.706Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-27T15:33:57.706Z] GC before operation: completed in 171.953 ms, heap usage 530.319 MB -> 90.303 MB. [2025-12-27T15:33:59.691Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:34:02.757Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:34:04.742Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:34:06.729Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:34:08.731Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:34:09.700Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:34:11.690Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:34:12.657Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:34:13.806Z] 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. [2025-12-27T15:34:13.806Z] The best model improves the baseline by 14.52%. [2025-12-27T15:34:13.806Z] Top recommended movies for user id 72: [2025-12-27T15:34:13.806Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:34:13.806Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:34:13.806Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:34:13.806Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:34:13.806Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:34:13.806Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15832.269 ms) ====== [2025-12-27T15:34:13.806Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-27T15:34:13.806Z] GC before operation: completed in 172.829 ms, heap usage 297.679 MB -> 89.907 MB. [2025-12-27T15:34:15.793Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:34:18.866Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:34:20.856Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:34:22.941Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:34:24.928Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:34:25.899Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:34:27.885Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:34:28.862Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:34:29.832Z] 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. [2025-12-27T15:34:29.832Z] The best model improves the baseline by 14.52%. [2025-12-27T15:34:29.832Z] Top recommended movies for user id 72: [2025-12-27T15:34:29.832Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:34:29.832Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:34:29.832Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:34:29.832Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:34:29.832Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:34:29.832Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15974.757 ms) ====== [2025-12-27T15:34:29.832Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-27T15:34:29.832Z] GC before operation: completed in 159.471 ms, heap usage 131.302 MB -> 89.952 MB. [2025-12-27T15:34:31.831Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:34:33.821Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:34:36.887Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:34:38.875Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:34:39.845Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:34:40.814Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:34:42.803Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:34:43.773Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:34:45.660Z] 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. [2025-12-27T15:34:45.660Z] The best model improves the baseline by 14.52%. [2025-12-27T15:34:45.660Z] Top recommended movies for user id 72: [2025-12-27T15:34:45.660Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:34:45.660Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:34:45.660Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:34:45.660Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:34:45.660Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:34:45.660Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14900.619 ms) ====== [2025-12-27T15:34:45.660Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-27T15:34:45.660Z] GC before operation: completed in 155.664 ms, heap usage 119.608 MB -> 89.756 MB. [2025-12-27T15:34:46.822Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:34:49.895Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:34:51.883Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:34:54.952Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:34:55.922Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:34:56.890Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:34:58.878Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:34:59.848Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:34:59.848Z] 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. [2025-12-27T15:34:59.848Z] The best model improves the baseline by 14.52%. [2025-12-27T15:35:00.817Z] Top recommended movies for user id 72: [2025-12-27T15:35:00.817Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:35:00.817Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:35:00.817Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:35:00.817Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:35:00.817Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:35:00.817Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15536.093 ms) ====== [2025-12-27T15:35:00.817Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-27T15:35:00.817Z] GC before operation: completed in 155.180 ms, heap usage 249.608 MB -> 90.223 MB. [2025-12-27T15:35:02.806Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:35:04.795Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:35:06.787Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:35:08.775Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:35:10.763Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:35:11.731Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:35:12.700Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:35:14.692Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:35:14.692Z] 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. [2025-12-27T15:35:14.692Z] The best model improves the baseline by 14.52%. [2025-12-27T15:35:14.692Z] Top recommended movies for user id 72: [2025-12-27T15:35:14.692Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:35:14.692Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:35:14.692Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:35:14.692Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:35:14.692Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:35:14.692Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14235.152 ms) ====== [2025-12-27T15:35:14.692Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-27T15:35:14.692Z] GC before operation: completed in 144.453 ms, heap usage 114.250 MB -> 91.605 MB. [2025-12-27T15:35:16.681Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:35:18.673Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:35:21.746Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:35:23.737Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:35:25.732Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:35:26.704Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:35:28.704Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:35:29.673Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:35:29.673Z] 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. [2025-12-27T15:35:29.673Z] The best model improves the baseline by 14.52%. [2025-12-27T15:35:30.645Z] Top recommended movies for user id 72: [2025-12-27T15:35:30.645Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:35:30.645Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:35:30.645Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:35:30.645Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:35:30.645Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:35:30.645Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15363.281 ms) ====== [2025-12-27T15:35:30.645Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-27T15:35:30.645Z] GC before operation: completed in 152.752 ms, heap usage 153.756 MB -> 90.023 MB. [2025-12-27T15:35:32.634Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:35:34.623Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:35:37.689Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:35:39.678Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:35:41.672Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:35:42.646Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:35:44.638Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:35:45.610Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:35:45.610Z] 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. [2025-12-27T15:35:45.610Z] The best model improves the baseline by 14.52%. [2025-12-27T15:35:45.610Z] Top recommended movies for user id 72: [2025-12-27T15:35:45.610Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:35:45.610Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:35:45.610Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:35:45.610Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:35:45.610Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:35:45.610Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15619.073 ms) ====== [2025-12-27T15:35:45.610Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-27T15:35:46.579Z] GC before operation: completed in 158.360 ms, heap usage 371.972 MB -> 90.448 MB. [2025-12-27T15:35:48.570Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:35:50.556Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:35:52.545Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:35:54.531Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:35:56.520Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:35:57.491Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:35:58.460Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:36:00.448Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:36:00.449Z] 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. [2025-12-27T15:36:00.449Z] The best model improves the baseline by 14.52%. [2025-12-27T15:36:00.449Z] Top recommended movies for user id 72: [2025-12-27T15:36:00.449Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:36:00.449Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:36:00.449Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:36:00.449Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:36:00.449Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:36:00.449Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14350.042 ms) ====== [2025-12-27T15:36:00.449Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-27T15:36:00.449Z] GC before operation: completed in 159.809 ms, heap usage 234.027 MB -> 90.080 MB. [2025-12-27T15:36:03.517Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:36:05.507Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:36:08.432Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:36:09.585Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:36:11.579Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:36:12.547Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:36:14.535Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:36:15.505Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:36:15.505Z] 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. [2025-12-27T15:36:15.505Z] The best model improves the baseline by 14.52%. [2025-12-27T15:36:16.475Z] Top recommended movies for user id 72: [2025-12-27T15:36:16.475Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:36:16.475Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:36:16.475Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:36:16.475Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:36:16.475Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:36:16.475Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15345.380 ms) ====== [2025-12-27T15:36:16.475Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-27T15:36:16.475Z] GC before operation: completed in 139.766 ms, heap usage 294.259 MB -> 90.406 MB. [2025-12-27T15:36:18.462Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:36:20.451Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:36:23.522Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:36:25.512Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:36:27.505Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:36:28.475Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:36:30.465Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:36:31.434Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:36:31.434Z] 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. [2025-12-27T15:36:32.404Z] The best model improves the baseline by 14.52%. [2025-12-27T15:36:32.404Z] Top recommended movies for user id 72: [2025-12-27T15:36:32.404Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:36:32.404Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:36:32.404Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:36:32.404Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:36:32.404Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:36:32.404Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15840.537 ms) ====== [2025-12-27T15:36:32.404Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-27T15:36:32.404Z] GC before operation: completed in 137.075 ms, heap usage 445.722 MB -> 90.497 MB. [2025-12-27T15:36:34.390Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:36:36.374Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:36:38.359Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:36:40.344Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:36:42.328Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:36:43.295Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:36:45.279Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:36:46.246Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:36:46.246Z] 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. [2025-12-27T15:36:46.246Z] The best model improves the baseline by 14.52%. [2025-12-27T15:36:47.213Z] Top recommended movies for user id 72: [2025-12-27T15:36:47.213Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:36:47.213Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:36:47.213Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:36:47.213Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:36:47.213Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:36:47.213Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14571.066 ms) ====== [2025-12-27T15:36:47.213Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-27T15:36:47.213Z] GC before operation: completed in 135.969 ms, heap usage 397.920 MB -> 90.502 MB. [2025-12-27T15:36:49.198Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:36:51.187Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:36:54.250Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:36:56.237Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:36:57.219Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:36:59.203Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:37:00.169Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:37:01.138Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:37:02.106Z] 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. [2025-12-27T15:37:02.106Z] The best model improves the baseline by 14.52%. [2025-12-27T15:37:02.106Z] Top recommended movies for user id 72: [2025-12-27T15:37:02.106Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:37:02.106Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:37:02.106Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:37:02.106Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:37:02.106Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:37:02.106Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15197.494 ms) ====== [2025-12-27T15:37:02.106Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-27T15:37:02.106Z] GC before operation: completed in 141.641 ms, heap usage 171.087 MB -> 90.087 MB. [2025-12-27T15:37:04.089Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:37:07.158Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:37:09.147Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:37:11.131Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:37:13.115Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:37:14.081Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:37:16.066Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:37:17.033Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:37:17.033Z] 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. [2025-12-27T15:37:17.033Z] The best model improves the baseline by 14.52%. [2025-12-27T15:37:17.033Z] Top recommended movies for user id 72: [2025-12-27T15:37:17.033Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:37:17.033Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:37:17.033Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:37:17.033Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:37:17.033Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:37:17.033Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15207.125 ms) ====== [2025-12-27T15:37:17.033Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-27T15:37:17.999Z] GC before operation: completed in 172.781 ms, heap usage 107.242 MB -> 90.280 MB. [2025-12-27T15:37:19.982Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T15:37:21.967Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T15:37:25.034Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T15:37:27.024Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T15:37:27.995Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T15:37:30.923Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T15:37:30.923Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T15:37:32.911Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T15:37:32.911Z] 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. [2025-12-27T15:37:32.911Z] The best model improves the baseline by 14.52%. [2025-12-27T15:37:32.911Z] Top recommended movies for user id 72: [2025-12-27T15:37:32.911Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T15:37:32.911Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T15:37:32.911Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T15:37:32.911Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T15:37:32.911Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T15:37:32.911Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15348.399 ms) ====== [2025-12-27T15:37:33.881Z] ----------------------------------- [2025-12-27T15:37:33.881Z] renaissance-movie-lens_0_PASSED [2025-12-27T15:37:33.881Z] ----------------------------------- [2025-12-27T15:37:33.881Z] [2025-12-27T15:37:33.881Z] TEST TEARDOWN: [2025-12-27T15:37:33.881Z] Nothing to be done for teardown. [2025-12-27T15:37:33.881Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 15:37:32 2025 Epoch Time (ms): 1766849852975