[2025-10-22T22:33:06.652Z] Running test renaissance-movie-lens_0 ... [2025-10-22T22:33:06.652Z] =============================================== [2025-10-22T22:33:06.652Z] renaissance-movie-lens_0 Start Time: Wed Oct 22 22:33:05 2025 Epoch Time (ms): 1761172385713 [2025-10-22T22:33:06.652Z] variation: NoOptions [2025-10-22T22:33:06.652Z] JVM_OPTIONS: [2025-10-22T22:33:06.652Z] { \ [2025-10-22T22:33:06.652Z] echo ""; echo "TEST SETUP:"; \ [2025-10-22T22:33:06.652Z] echo "Nothing to be done for setup."; \ [2025-10-22T22:33:06.652Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17611709275715/renaissance-movie-lens_0"; \ [2025-10-22T22:33:06.652Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17611709275715/renaissance-movie-lens_0"; \ [2025-10-22T22:33:06.652Z] echo ""; echo "TESTING:"; \ [2025-10-22T22:33:06.652Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/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/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17611709275715/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-10-22T22:33:06.652Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17611709275715/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-10-22T22:33:06.652Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-10-22T22:33:06.652Z] echo "Nothing to be done for teardown."; \ [2025-10-22T22:33:06.652Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17611709275715/TestTargetResult"; [2025-10-22T22:33:06.652Z] [2025-10-22T22:33:06.652Z] TEST SETUP: [2025-10-22T22:33:06.652Z] Nothing to be done for setup. [2025-10-22T22:33:06.652Z] [2025-10-22T22:33:06.652Z] TESTING: [2025-10-22T22:33:06.652Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-10-22T22:33:06.652Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/output_17611709275715/renaissance-movie-lens_0/launcher-223305-15080376729640313357/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-10-22T22:33:06.652Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-10-22T22:33:06.652Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-10-22T22:33:12.032Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-10-22T22:33:18.748Z] 22:33:17.577 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. [2025-10-22T22:33:20.713Z] Got 100004 ratings from 671 users on 9066 movies. [2025-10-22T22:33:20.713Z] Training: 60056, validation: 20285, test: 19854 [2025-10-22T22:33:20.713Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-10-22T22:33:20.713Z] GC before operation: completed in 173.046 ms, heap usage 226.963 MB -> 75.655 MB. [2025-10-22T22:33:27.474Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:33:30.505Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:33:33.553Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:33:36.580Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:33:38.537Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:33:40.519Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:33:42.483Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:33:44.597Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:33:44.597Z] 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. [2025-10-22T22:33:44.597Z] The best model improves the baseline by 14.52%. [2025-10-22T22:33:44.597Z] Top recommended movies for user id 72: [2025-10-22T22:33:44.597Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:33:44.597Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:33:44.597Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:33:44.597Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:33:44.597Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:33:44.597Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24076.429 ms) ====== [2025-10-22T22:33:44.597Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-10-22T22:33:45.549Z] GC before operation: completed in 160.263 ms, heap usage 418.024 MB -> 87.611 MB. [2025-10-22T22:33:47.508Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:33:50.534Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:33:54.047Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:33:56.004Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:33:57.966Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:34:08.862Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:34:11.240Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:34:11.240Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:34:11.240Z] 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. [2025-10-22T22:34:11.240Z] The best model improves the baseline by 14.52%. [2025-10-22T22:34:11.240Z] Top recommended movies for user id 72: [2025-10-22T22:34:11.240Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:34:11.240Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:34:11.240Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:34:11.240Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:34:11.240Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:34:11.240Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18481.362 ms) ====== [2025-10-22T22:34:11.240Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-10-22T22:34:11.240Z] GC before operation: completed in 137.909 ms, heap usage 291.392 MB -> 88.515 MB. [2025-10-22T22:34:11.240Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:34:11.240Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:34:11.240Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:34:13.212Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:34:15.170Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:34:16.127Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:34:18.094Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:34:19.051Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:34:19.051Z] 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. [2025-10-22T22:34:19.051Z] The best model improves the baseline by 14.52%. [2025-10-22T22:34:20.016Z] Top recommended movies for user id 72: [2025-10-22T22:34:20.016Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:34:20.016Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:34:20.016Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:34:20.016Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:34:20.016Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:34:20.016Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16028.102 ms) ====== [2025-10-22T22:34:20.016Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-10-22T22:34:20.016Z] GC before operation: completed in 139.436 ms, heap usage 216.027 MB -> 89.048 MB. [2025-10-22T22:34:21.976Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:34:25.002Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:34:26.961Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:34:28.919Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:34:30.878Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:34:31.832Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:34:33.790Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:34:35.745Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:34:35.745Z] 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. [2025-10-22T22:34:35.745Z] The best model improves the baseline by 14.52%. [2025-10-22T22:34:35.745Z] Top recommended movies for user id 72: [2025-10-22T22:34:35.745Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:34:35.745Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:34:35.745Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:34:35.745Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:34:35.745Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:34:35.745Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16074.184 ms) ====== [2025-10-22T22:34:35.745Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-10-22T22:34:35.745Z] GC before operation: completed in 193.442 ms, heap usage 128.422 MB -> 89.180 MB. [2025-10-22T22:34:38.771Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:34:41.801Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:34:43.764Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:34:46.846Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:34:47.800Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:34:49.759Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:34:51.723Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:34:52.680Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:34:52.680Z] 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. [2025-10-22T22:34:52.680Z] The best model improves the baseline by 14.52%. [2025-10-22T22:34:53.634Z] Top recommended movies for user id 72: [2025-10-22T22:34:53.634Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:34:53.634Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:34:53.634Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:34:53.634Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:34:53.634Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:34:53.634Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17123.047 ms) ====== [2025-10-22T22:34:53.634Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-10-22T22:34:53.634Z] GC before operation: completed in 143.251 ms, heap usage 456.126 MB -> 90.079 MB. [2025-10-22T22:34:55.594Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:34:58.616Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:35:00.577Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:35:02.553Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:35:04.509Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:35:05.464Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:35:07.427Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:35:09.383Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:35:09.384Z] 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. [2025-10-22T22:35:09.384Z] The best model improves the baseline by 14.52%. [2025-10-22T22:35:09.384Z] Top recommended movies for user id 72: [2025-10-22T22:35:09.384Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:35:09.384Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:35:09.384Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:35:09.384Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:35:09.384Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:35:09.384Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15934.887 ms) ====== [2025-10-22T22:35:09.384Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-10-22T22:35:09.384Z] GC before operation: completed in 151.857 ms, heap usage 453.349 MB -> 89.908 MB. [2025-10-22T22:35:11.341Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:35:14.375Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:35:16.335Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:35:18.303Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:35:20.262Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:35:21.217Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:35:23.185Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:35:24.139Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:35:25.098Z] 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. [2025-10-22T22:35:25.098Z] The best model improves the baseline by 14.52%. [2025-10-22T22:35:25.098Z] Top recommended movies for user id 72: [2025-10-22T22:35:25.098Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:35:25.098Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:35:25.098Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:35:25.098Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:35:25.098Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:35:25.098Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15613.993 ms) ====== [2025-10-22T22:35:25.098Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-10-22T22:35:25.098Z] GC before operation: completed in 135.549 ms, heap usage 368.318 MB -> 89.751 MB. [2025-10-22T22:35:27.138Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:35:30.162Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:35:32.124Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:35:53.563Z] test-osuosl-centos74-ppc64le-1 seems to be removed or offline (java.lang.InterruptedException); will wait for 5 min 0 sec for it to come back online [2025-10-22T22:35:53.864Z] test-osuosl-centos74-ppc64le-1 is back online [2025-10-22T22:36:13.870Z] test-osuosl-centos74-ppc64le-1 seems to be removed or offline (java.lang.InterruptedException); will wait for 5 min 0 sec for it to come back online [2025-10-22T22:36:14.171Z] test-osuosl-centos74-ppc64le-1 is back online [2025-10-22T22:36:20.565Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:36:20.565Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:36:20.565Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:36:20.565Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:36:20.565Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:36:20.565Z] 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. [2025-10-22T22:36:20.565Z] The best model improves the baseline by 14.52%. [2025-10-22T22:36:20.565Z] Top recommended movies for user id 72: [2025-10-22T22:36:20.565Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:36:20.565Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:36:20.565Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:36:20.565Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:36:20.565Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:36:20.565Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15683.853 ms) ====== [2025-10-22T22:36:20.565Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-10-22T22:36:20.565Z] GC before operation: completed in 158.189 ms, heap usage 429.465 MB -> 90.113 MB. [2025-10-22T22:36:20.565Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:36:20.565Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:36:20.565Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:36:20.565Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:36:20.565Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:36:20.565Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:36:20.565Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:36:20.565Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:36:20.565Z] 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. [2025-10-22T22:36:20.565Z] The best model improves the baseline by 14.52%. [2025-10-22T22:36:20.565Z] Top recommended movies for user id 72: [2025-10-22T22:36:20.566Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:36:20.566Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:36:20.566Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:36:20.566Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:36:20.566Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:36:20.566Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15493.143 ms) ====== [2025-10-22T22:36:20.566Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-10-22T22:36:20.566Z] GC before operation: completed in 149.484 ms, heap usage 468.710 MB -> 89.945 MB. [2025-10-22T22:36:20.566Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:36:20.566Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:36:20.566Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:36:20.566Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:36:20.566Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:36:20.566Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:36:20.566Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:36:20.566Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:36:20.566Z] 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. [2025-10-22T22:36:20.566Z] The best model improves the baseline by 14.52%. [2025-10-22T22:36:20.566Z] Top recommended movies for user id 72: [2025-10-22T22:36:20.566Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:36:20.566Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:36:20.566Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:36:20.566Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:36:20.566Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:36:20.566Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15426.195 ms) ====== [2025-10-22T22:36:20.566Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-10-22T22:36:20.566Z] GC before operation: completed in 154.789 ms, heap usage 295.707 MB -> 90.012 MB. [2025-10-22T22:36:20.566Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:36:20.566Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:36:20.566Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:36:21.530Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:36:23.502Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:36:24.456Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:36:26.442Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:36:27.400Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:36:29.008Z] 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. [2025-10-22T22:36:29.008Z] The best model improves the baseline by 14.52%. [2025-10-22T22:36:29.008Z] Top recommended movies for user id 72: [2025-10-22T22:36:29.008Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:36:29.008Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:36:29.008Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:36:29.008Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:36:29.008Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:36:29.008Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15876.084 ms) ====== [2025-10-22T22:36:29.008Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-10-22T22:36:29.008Z] GC before operation: completed in 131.167 ms, heap usage 426.123 MB -> 89.755 MB. [2025-10-22T22:36:30.990Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:36:32.950Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:36:34.910Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:36:36.868Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:36:37.820Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:36:39.777Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:36:40.731Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:36:42.691Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:36:42.691Z] 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. [2025-10-22T22:36:42.691Z] The best model improves the baseline by 14.52%. [2025-10-22T22:36:42.691Z] Top recommended movies for user id 72: [2025-10-22T22:36:42.692Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:36:42.692Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:36:42.692Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:36:42.692Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:36:42.692Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:36:42.692Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14356.625 ms) ====== [2025-10-22T22:36:42.692Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-10-22T22:36:42.692Z] GC before operation: completed in 164.621 ms, heap usage 264.828 MB -> 89.879 MB. [2025-10-22T22:36:45.718Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:36:47.732Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:36:49.691Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:36:51.652Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:36:52.609Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:36:54.569Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:36:55.521Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:36:56.474Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:36:57.428Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-10-22T22:36:57.428Z] The best model improves the baseline by 14.52%. [2025-10-22T22:36:57.428Z] Top recommended movies for user id 72: [2025-10-22T22:36:57.428Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:36:57.428Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:36:57.428Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:36:57.428Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:36:57.428Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:36:57.428Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14453.711 ms) ====== [2025-10-22T22:36:57.428Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-10-22T22:36:57.428Z] GC before operation: completed in 131.418 ms, heap usage 447.789 MB -> 90.207 MB. [2025-10-22T22:36:59.386Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:37:01.343Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:37:04.364Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:37:06.325Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:37:07.277Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:37:08.232Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:37:10.194Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:37:11.146Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:37:11.146Z] 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. [2025-10-22T22:37:11.146Z] The best model improves the baseline by 14.52%. [2025-10-22T22:37:11.146Z] Top recommended movies for user id 72: [2025-10-22T22:37:11.146Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:37:11.146Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:37:11.146Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:37:11.146Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:37:11.146Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:37:11.146Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14056.885 ms) ====== [2025-10-22T22:37:11.147Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-10-22T22:37:12.102Z] GC before operation: completed in 143.865 ms, heap usage 200.340 MB -> 89.715 MB. [2025-10-22T22:37:14.059Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:37:16.018Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:37:17.975Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:37:20.013Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:37:20.966Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:37:23.107Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:37:24.061Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:37:25.015Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:37:25.015Z] 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. [2025-10-22T22:37:25.983Z] The best model improves the baseline by 14.52%. [2025-10-22T22:37:25.983Z] Top recommended movies for user id 72: [2025-10-22T22:37:25.983Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:37:25.983Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:37:25.983Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:37:25.983Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:37:25.983Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:37:25.983Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14067.862 ms) ====== [2025-10-22T22:37:25.983Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-10-22T22:37:25.983Z] GC before operation: completed in 154.960 ms, heap usage 261.634 MB -> 90.084 MB. [2025-10-22T22:37:27.954Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:37:29.917Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:37:31.878Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:37:34.904Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:37:35.858Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:37:36.811Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:38:03.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:38:03.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:38:03.836Z] 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. [2025-10-22T22:38:03.836Z] The best model improves the baseline by 14.52%. [2025-10-22T22:38:03.836Z] Top recommended movies for user id 72: [2025-10-22T22:38:03.836Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:38:03.836Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:38:03.836Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:38:03.836Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:38:03.836Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:38:03.836Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14148.325 ms) ====== [2025-10-22T22:38:03.836Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-10-22T22:38:03.836Z] GC before operation: completed in 135.658 ms, heap usage 549.747 MB -> 93.495 MB. [2025-10-22T22:38:03.836Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:38:03.836Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:38:03.836Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:38:03.836Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:38:03.836Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:38:03.836Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:38:03.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:38:03.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:38:03.836Z] 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. [2025-10-22T22:38:03.836Z] The best model improves the baseline by 14.52%. [2025-10-22T22:38:03.836Z] Top recommended movies for user id 72: [2025-10-22T22:38:03.836Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:38:03.836Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:38:03.836Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:38:03.836Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:38:03.836Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:38:03.836Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14553.292 ms) ====== [2025-10-22T22:38:03.836Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-10-22T22:38:03.836Z] GC before operation: completed in 122.907 ms, heap usage 374.596 MB -> 90.105 MB. [2025-10-22T22:38:03.836Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:38:03.836Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:38:03.836Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:38:03.836Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:38:04.794Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:38:05.750Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:38:06.703Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:38:08.663Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:38:08.663Z] 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. [2025-10-22T22:38:08.663Z] The best model improves the baseline by 14.52%. [2025-10-22T22:38:08.663Z] Top recommended movies for user id 72: [2025-10-22T22:38:08.663Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:38:08.663Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:38:08.663Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:38:08.663Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:38:08.663Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:38:08.663Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14019.511 ms) ====== [2025-10-22T22:38:08.663Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-10-22T22:38:08.663Z] GC before operation: completed in 149.821 ms, heap usage 758.505 MB -> 93.739 MB. [2025-10-22T22:38:10.626Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:38:13.649Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:38:15.607Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:38:17.583Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:38:18.538Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:38:19.499Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:38:21.456Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:38:22.409Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:38:22.409Z] 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. [2025-10-22T22:38:22.409Z] The best model improves the baseline by 14.52%. [2025-10-22T22:38:23.363Z] Top recommended movies for user id 72: [2025-10-22T22:38:23.363Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:38:23.363Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:38:23.363Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:38:23.363Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:38:23.363Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:38:23.363Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13908.428 ms) ====== [2025-10-22T22:38:23.363Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-10-22T22:38:23.363Z] GC before operation: completed in 140.770 ms, heap usage 208.017 MB -> 89.899 MB. [2025-10-22T22:38:25.321Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-22T22:38:27.281Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-22T22:38:29.240Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-22T22:38:31.199Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-22T22:38:32.152Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-22T22:38:34.109Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-22T22:38:35.064Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-22T22:38:37.043Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-22T22:38:37.043Z] 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. [2025-10-22T22:38:37.043Z] The best model improves the baseline by 14.52%. [2025-10-22T22:38:37.043Z] Top recommended movies for user id 72: [2025-10-22T22:38:37.043Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-22T22:38:37.043Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-22T22:38:37.043Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-22T22:38:37.043Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-22T22:38:37.043Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-22T22:38:37.043Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14209.370 ms) ====== [2025-10-22T22:38:37.998Z] ----------------------------------- [2025-10-22T22:38:37.998Z] renaissance-movie-lens_0_PASSED [2025-10-22T22:38:37.998Z] ----------------------------------- [2025-10-22T22:38:37.998Z] [2025-10-22T22:38:37.998Z] TEST TEARDOWN: [2025-10-22T22:38:37.998Z] Nothing to be done for teardown. [2025-10-22T22:38:37.998Z] renaissance-movie-lens_0 Finish Time: Wed Oct 22 22:38:37 2025 Epoch Time (ms): 1761172717231