[2025-09-05T15:15:46.827Z] Running test renaissance-movie-lens_0 ... [2025-09-05T15:15:46.827Z] =============================================== [2025-09-05T15:15:46.827Z] renaissance-movie-lens_0 Start Time: Fri Sep 5 15:15:46 2025 Epoch Time (ms): 1757085346141 [2025-09-05T15:15:46.827Z] variation: NoOptions [2025-09-05T15:15:46.827Z] JVM_OPTIONS: [2025-09-05T15:15:46.827Z] { \ [2025-09-05T15:15:46.827Z] echo ""; echo "TEST SETUP:"; \ [2025-09-05T15:15:46.827Z] echo "Nothing to be done for setup."; \ [2025-09-05T15:15:46.827Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17570841288023/renaissance-movie-lens_0"; \ [2025-09-05T15:15:46.827Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17570841288023/renaissance-movie-lens_0"; \ [2025-09-05T15:15:46.827Z] echo ""; echo "TESTING:"; \ [2025-09-05T15:15:46.827Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_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_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17570841288023/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-05T15:15:46.827Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17570841288023/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-05T15:15:46.827Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-05T15:15:46.827Z] echo "Nothing to be done for teardown."; \ [2025-09-05T15:15:46.827Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17570841288023/TestTargetResult"; [2025-09-05T15:15:46.827Z] [2025-09-05T15:15:46.827Z] TEST SETUP: [2025-09-05T15:15:46.827Z] Nothing to be done for setup. [2025-09-05T15:15:46.827Z] [2025-09-05T15:15:46.827Z] TESTING: [2025-09-05T15:15:46.827Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-09-05T15:15:46.827Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/output_17570841288023/renaissance-movie-lens_0/launcher-151546-7909039768711003178/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-09-05T15:15:46.827Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-09-05T15:15:46.827Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-09-05T15:15:50.648Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-09-05T15:15:57.920Z] 15:15:56.832 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-09-05T15:16:00.013Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-05T15:16:00.652Z] Training: 60056, validation: 20285, test: 19854 [2025-09-05T15:16:00.652Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-05T15:16:00.652Z] GC before operation: completed in 132.192 ms, heap usage 298.300 MB -> 75.726 MB. [2025-09-05T15:16:07.928Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:16:11.858Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:16:15.967Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:16:18.063Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:16:20.154Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:16:21.492Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:16:23.579Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:16:24.918Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:16:24.918Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:16:24.918Z] The best model improves the baseline by 14.34%. [2025-09-05T15:16:25.557Z] Top recommended movies for user id 72: [2025-09-05T15:16:25.557Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:16:25.557Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:16:25.557Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:16:25.557Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:16:25.557Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:16:25.557Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24516.577 ms) ====== [2025-09-05T15:16:25.557Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-05T15:16:25.557Z] GC before operation: completed in 127.347 ms, heap usage 249.108 MB -> 89.624 MB. [2025-09-05T15:16:28.467Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:16:30.555Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:16:32.643Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:16:34.738Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:16:36.073Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:16:37.406Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:16:38.742Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:16:40.080Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:16:40.080Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:16:40.722Z] The best model improves the baseline by 14.34%. [2025-09-05T15:16:40.722Z] Top recommended movies for user id 72: [2025-09-05T15:16:40.722Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:16:40.722Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:16:40.722Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:16:40.722Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:16:40.722Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:16:40.722Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15131.755 ms) ====== [2025-09-05T15:16:40.722Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-05T15:16:40.722Z] GC before operation: completed in 133.453 ms, heap usage 197.016 MB -> 87.703 MB. [2025-09-05T15:16:42.809Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:16:44.900Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:16:46.992Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:16:49.086Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:16:50.530Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:16:51.485Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:16:52.819Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:16:54.157Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:16:54.157Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:16:54.157Z] The best model improves the baseline by 14.34%. [2025-09-05T15:16:54.157Z] Top recommended movies for user id 72: [2025-09-05T15:16:54.157Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:16:54.157Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:16:54.157Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:16:54.157Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:16:54.157Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:16:54.157Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (13501.937 ms) ====== [2025-09-05T15:16:54.157Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-05T15:16:54.157Z] GC before operation: completed in 127.435 ms, heap usage 241.932 MB -> 88.464 MB. [2025-09-05T15:16:57.068Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:16:59.187Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:17:01.275Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:17:02.673Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:17:04.053Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:17:05.391Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:17:06.725Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:17:08.061Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:17:08.061Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:17:08.061Z] The best model improves the baseline by 14.34%. [2025-09-05T15:17:08.061Z] Top recommended movies for user id 72: [2025-09-05T15:17:08.061Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:17:08.061Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:17:08.061Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:17:08.061Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:17:08.061Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:17:08.061Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13832.553 ms) ====== [2025-09-05T15:17:08.061Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-05T15:17:08.703Z] GC before operation: completed in 122.449 ms, heap usage 153.199 MB -> 88.620 MB. [2025-09-05T15:17:10.792Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:17:12.873Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:17:14.955Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:17:17.088Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:17:18.421Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:17:19.756Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:17:21.089Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:17:22.430Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:17:22.430Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:17:22.430Z] The best model improves the baseline by 14.34%. [2025-09-05T15:17:22.430Z] Top recommended movies for user id 72: [2025-09-05T15:17:22.431Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:17:22.431Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:17:22.431Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:17:22.431Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:17:22.431Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:17:22.431Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14120.511 ms) ====== [2025-09-05T15:17:22.431Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-05T15:17:22.431Z] GC before operation: completed in 119.828 ms, heap usage 335.541 MB -> 88.871 MB. [2025-09-05T15:17:25.340Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:17:27.119Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:17:29.213Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:17:30.547Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:17:31.884Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:17:33.219Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:17:34.555Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:17:35.893Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:17:35.893Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:17:35.893Z] The best model improves the baseline by 14.34%. [2025-09-05T15:17:36.543Z] Top recommended movies for user id 72: [2025-09-05T15:17:36.543Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:17:36.543Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:17:36.543Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:17:36.543Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:17:36.543Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:17:36.543Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13634.895 ms) ====== [2025-09-05T15:17:36.543Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-05T15:17:36.543Z] GC before operation: completed in 125.941 ms, heap usage 418.080 MB -> 89.365 MB. [2025-09-05T15:17:38.661Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:17:39.996Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:17:42.084Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:17:44.172Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:17:45.507Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:17:46.841Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:17:48.177Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:17:48.818Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:17:48.818Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:17:48.818Z] The best model improves the baseline by 14.34%. [2025-09-05T15:17:49.461Z] Top recommended movies for user id 72: [2025-09-05T15:17:49.461Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:17:49.461Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:17:49.461Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:17:49.461Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:17:49.461Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:17:49.461Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12805.688 ms) ====== [2025-09-05T15:17:49.461Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-05T15:17:49.461Z] GC before operation: completed in 127.180 ms, heap usage 242.199 MB -> 89.082 MB. [2025-09-05T15:17:51.550Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:17:53.637Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:17:54.969Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:17:57.061Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:17:58.397Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:17:59.728Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:18:00.371Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:18:01.700Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:18:01.700Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:18:01.700Z] The best model improves the baseline by 14.34%. [2025-09-05T15:18:01.700Z] Top recommended movies for user id 72: [2025-09-05T15:18:01.700Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:18:01.700Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:18:01.700Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:18:01.700Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:18:01.700Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:18:01.700Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (12614.952 ms) ====== [2025-09-05T15:18:01.700Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-05T15:18:02.347Z] GC before operation: completed in 127.467 ms, heap usage 240.845 MB -> 89.359 MB. [2025-09-05T15:18:03.683Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:18:05.911Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:18:07.250Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:18:09.346Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:18:10.701Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:18:11.347Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:18:12.685Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:18:13.327Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:18:13.970Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:18:13.970Z] The best model improves the baseline by 14.34%. [2025-09-05T15:18:13.970Z] Top recommended movies for user id 72: [2025-09-05T15:18:13.970Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:18:13.970Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:18:13.970Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:18:13.970Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:18:13.970Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:18:13.970Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (11839.235 ms) ====== [2025-09-05T15:18:13.970Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-05T15:18:13.970Z] GC before operation: completed in 133.441 ms, heap usage 598.630 MB -> 93.076 MB. [2025-09-05T15:18:16.054Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:18:17.389Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:18:19.484Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:18:20.814Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:18:22.148Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:18:22.793Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:18:24.128Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:18:24.771Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:18:25.415Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:18:25.415Z] The best model improves the baseline by 14.34%. [2025-09-05T15:18:25.415Z] Top recommended movies for user id 72: [2025-09-05T15:18:25.415Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:18:25.415Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:18:25.415Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:18:25.415Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:18:25.415Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:18:25.415Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (11257.893 ms) ====== [2025-09-05T15:18:25.415Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-05T15:18:25.415Z] GC before operation: completed in 126.714 ms, heap usage 579.818 MB -> 93.131 MB. [2025-09-05T15:18:27.500Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:18:28.834Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:18:30.923Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:18:32.258Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:18:32.898Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:18:34.235Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:18:35.567Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:18:36.208Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:18:36.848Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:18:36.848Z] The best model improves the baseline by 14.34%. [2025-09-05T15:18:36.848Z] Top recommended movies for user id 72: [2025-09-05T15:18:36.848Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:18:36.848Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:18:36.848Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:18:36.848Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:18:36.848Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:18:36.848Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (11350.957 ms) ====== [2025-09-05T15:18:36.848Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-05T15:18:36.848Z] GC before operation: completed in 122.964 ms, heap usage 184.589 MB -> 88.938 MB. [2025-09-05T15:18:38.931Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:18:40.369Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:18:42.457Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:18:43.792Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:18:44.433Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:18:45.770Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:18:47.103Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:18:47.746Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:18:47.747Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:18:47.747Z] The best model improves the baseline by 14.34%. [2025-09-05T15:18:47.747Z] Top recommended movies for user id 72: [2025-09-05T15:18:47.747Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:18:47.747Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:18:47.747Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:18:47.747Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:18:47.747Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:18:47.747Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (11068.641 ms) ====== [2025-09-05T15:18:47.747Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-05T15:18:48.392Z] GC before operation: completed in 117.324 ms, heap usage 155.396 MB -> 89.155 MB. [2025-09-05T15:18:49.729Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:18:51.815Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:18:53.147Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:18:55.231Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:18:55.872Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:18:57.209Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:18:57.853Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:18:59.192Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:18:59.192Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:18:59.192Z] The best model improves the baseline by 14.34%. [2025-09-05T15:18:59.192Z] Top recommended movies for user id 72: [2025-09-05T15:18:59.192Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:18:59.192Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:18:59.192Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:18:59.192Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:18:59.192Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:18:59.192Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (11291.890 ms) ====== [2025-09-05T15:18:59.192Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-05T15:18:59.836Z] GC before operation: completed in 128.672 ms, heap usage 490.613 MB -> 93.071 MB. [2025-09-05T15:19:01.169Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:19:03.255Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:19:04.652Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:19:06.740Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:19:07.380Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:19:08.715Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:19:09.355Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:19:10.690Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:19:10.690Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:19:10.690Z] The best model improves the baseline by 14.34%. [2025-09-05T15:19:10.690Z] Top recommended movies for user id 72: [2025-09-05T15:19:10.690Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:19:10.690Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:19:10.690Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:19:10.690Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:19:10.690Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:19:10.690Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (11111.982 ms) ====== [2025-09-05T15:19:10.690Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-05T15:19:10.690Z] GC before operation: completed in 123.438 ms, heap usage 393.711 MB -> 89.541 MB. [2025-09-05T15:19:12.777Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:19:14.113Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:19:16.594Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:19:17.238Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:19:18.573Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:19:19.212Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:19:20.545Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:19:21.204Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:19:21.204Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:19:21.204Z] The best model improves the baseline by 14.34%. [2025-09-05T15:19:21.852Z] Top recommended movies for user id 72: [2025-09-05T15:19:21.852Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:19:21.852Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:19:21.852Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:19:21.852Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:19:21.852Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:19:21.852Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (10831.384 ms) ====== [2025-09-05T15:19:21.852Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-05T15:19:21.852Z] GC before operation: completed in 120.672 ms, heap usage 223.230 MB -> 89.461 MB. [2025-09-05T15:19:23.184Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:19:25.273Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:19:26.608Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:19:28.713Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:19:29.352Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:19:30.689Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:19:31.330Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:19:32.664Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:19:32.664Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:19:32.664Z] The best model improves the baseline by 14.34%. [2025-09-05T15:19:32.664Z] Top recommended movies for user id 72: [2025-09-05T15:19:32.664Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:19:32.664Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:19:32.664Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:19:32.664Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:19:32.664Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:19:32.664Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (11027.615 ms) ====== [2025-09-05T15:19:32.664Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-05T15:19:32.664Z] GC before operation: completed in 121.675 ms, heap usage 248.782 MB -> 89.392 MB. [2025-09-05T15:19:34.749Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:19:36.082Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:19:38.170Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:19:39.509Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:19:40.152Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:19:41.482Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:19:42.131Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:19:43.465Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:19:43.465Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:19:43.465Z] The best model improves the baseline by 14.34%. [2025-09-05T15:19:43.465Z] Top recommended movies for user id 72: [2025-09-05T15:19:43.465Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:19:43.465Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:19:43.465Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:19:43.465Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:19:43.465Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:19:43.465Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (10843.175 ms) ====== [2025-09-05T15:19:43.465Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-05T15:19:44.106Z] GC before operation: completed in 123.442 ms, heap usage 216.467 MB -> 89.406 MB. [2025-09-05T15:19:45.439Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:19:47.530Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:19:48.864Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:19:50.204Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:19:51.540Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:19:52.184Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:19:53.920Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:19:54.562Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:19:54.562Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:19:54.562Z] The best model improves the baseline by 14.34%. [2025-09-05T15:19:54.562Z] Top recommended movies for user id 72: [2025-09-05T15:19:54.562Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:19:54.562Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:19:54.562Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:19:54.562Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:19:54.562Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:19:54.562Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (10892.725 ms) ====== [2025-09-05T15:19:54.562Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-05T15:19:54.562Z] GC before operation: completed in 117.050 ms, heap usage 166.106 MB -> 89.211 MB. [2025-09-05T15:19:56.649Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:19:57.985Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:20:00.070Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:20:01.405Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:20:02.741Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:20:03.384Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:20:04.735Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:20:06.069Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:20:06.069Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:20:06.069Z] The best model improves the baseline by 14.34%. [2025-09-05T15:20:06.069Z] Top recommended movies for user id 72: [2025-09-05T15:20:06.069Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:20:06.069Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:20:06.069Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:20:06.069Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:20:06.069Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:20:06.069Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (11155.683 ms) ====== [2025-09-05T15:20:06.069Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-05T15:20:06.069Z] GC before operation: completed in 120.313 ms, heap usage 229.172 MB -> 89.292 MB. [2025-09-05T15:20:08.152Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-05T15:20:09.491Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-05T15:20:11.580Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-05T15:20:12.958Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-05T15:20:13.607Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-05T15:20:14.249Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-05T15:20:15.583Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-05T15:20:16.224Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-05T15:20:16.864Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-05T15:20:16.864Z] The best model improves the baseline by 14.34%. [2025-09-05T15:20:16.864Z] Top recommended movies for user id 72: [2025-09-05T15:20:16.864Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-05T15:20:16.864Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-05T15:20:16.864Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-05T15:20:16.864Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-05T15:20:16.864Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-05T15:20:16.864Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (10623.798 ms) ====== [2025-09-05T15:20:17.507Z] ----------------------------------- [2025-09-05T15:20:17.507Z] renaissance-movie-lens_0_PASSED [2025-09-05T15:20:17.507Z] ----------------------------------- [2025-09-05T15:20:17.507Z] [2025-09-05T15:20:17.507Z] TEST TEARDOWN: [2025-09-05T15:20:17.507Z] Nothing to be done for teardown. [2025-09-05T15:20:17.507Z] renaissance-movie-lens_0 Finish Time: Fri Sep 5 15:20:16 2025 Epoch Time (ms): 1757085616838