[2025-12-06T13:41:56.643Z] Running test renaissance-movie-lens_0 ... [2025-12-06T13:41:56.643Z] =============================================== [2025-12-06T13:41:56.643Z] renaissance-movie-lens_0 Start Time: Sat Dec 6 13:41:55 2025 Epoch Time (ms): 1765028515696 [2025-12-06T13:41:56.643Z] variation: NoOptions [2025-12-06T13:41:56.643Z] JVM_OPTIONS: [2025-12-06T13:41:56.643Z] { \ [2025-12-06T13:41:56.643Z] echo ""; echo "TEST SETUP:"; \ [2025-12-06T13:41:56.643Z] echo "Nothing to be done for setup."; \ [2025-12-06T13:41:56.643Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1765026547681/renaissance-movie-lens_0"; \ [2025-12-06T13:41:56.643Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1765026547681/renaissance-movie-lens_0"; \ [2025-12-06T13:41:56.643Z] echo ""; echo "TESTING:"; \ [2025-12-06T13:41:56.643Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_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_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1765026547681/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-06T13:41:56.643Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1765026547681/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-06T13:41:56.643Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-06T13:41:56.643Z] echo "Nothing to be done for teardown."; \ [2025-12-06T13:41:56.643Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_1765026547681/TestTargetResult"; [2025-12-06T13:41:56.643Z] [2025-12-06T13:41:56.643Z] TEST SETUP: [2025-12-06T13:41:56.643Z] Nothing to be done for setup. [2025-12-06T13:41:56.643Z] [2025-12-06T13:41:56.643Z] TESTING: [2025-12-06T13:41:56.643Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-06T13:41:56.643Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux/aqa-tests/TKG/output_1765026547681/renaissance-movie-lens_0/launcher-134156-2275327214960748029/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-06T13:41:56.643Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-06T13:41:56.643Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-06T13:42:01.476Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-06T13:42:07.449Z] 13:42:07.109 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-12-06T13:42:09.575Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-06T13:42:10.220Z] Training: 60056, validation: 20285, test: 19854 [2025-12-06T13:42:10.220Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-06T13:42:10.885Z] GC before operation: completed in 186.402 ms, heap usage 298.832 MB -> 75.566 MB. [2025-12-06T13:42:18.310Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:42:23.664Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:42:27.456Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:42:31.248Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:42:34.166Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:42:36.440Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:42:38.524Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:42:40.601Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:42:41.293Z] 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. [2025-12-06T13:42:41.293Z] The best model improves the baseline by 14.34%. [2025-12-06T13:42:41.293Z] Top recommended movies for user id 72: [2025-12-06T13:42:41.293Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:42:41.293Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:42:41.293Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:42:41.293Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:42:41.293Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:42:41.293Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (30795.253 ms) ====== [2025-12-06T13:42:41.293Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-06T13:42:41.293Z] GC before operation: completed in 245.833 ms, heap usage 114.959 MB -> 90.155 MB. [2025-12-06T13:42:45.074Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:42:47.962Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:42:50.853Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:42:53.744Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:42:55.880Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:42:57.973Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:42:59.301Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:43:01.825Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:43:01.825Z] 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. [2025-12-06T13:43:01.825Z] The best model improves the baseline by 14.34%. [2025-12-06T13:43:01.825Z] Top recommended movies for user id 72: [2025-12-06T13:43:01.825Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:43:01.825Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:43:01.825Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:43:01.825Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:43:01.825Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:43:01.825Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20201.247 ms) ====== [2025-12-06T13:43:01.825Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-06T13:43:01.825Z] GC before operation: completed in 192.660 ms, heap usage 240.698 MB -> 87.817 MB. [2025-12-06T13:43:04.708Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:43:07.585Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:43:10.505Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:43:13.447Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:43:14.767Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:43:16.104Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:43:17.453Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:43:18.765Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:43:19.424Z] 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. [2025-12-06T13:43:19.424Z] The best model improves the baseline by 14.34%. [2025-12-06T13:43:19.424Z] Top recommended movies for user id 72: [2025-12-06T13:43:19.424Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:43:19.424Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:43:19.424Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:43:19.424Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:43:19.424Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:43:19.424Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17456.126 ms) ====== [2025-12-06T13:43:19.424Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-06T13:43:19.424Z] GC before operation: completed in 164.941 ms, heap usage 231.985 MB -> 90.052 MB. [2025-12-06T13:43:22.296Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:43:25.263Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:43:28.236Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:43:30.309Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:43:31.648Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:43:32.971Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:43:34.322Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:43:35.751Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:43:35.751Z] 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. [2025-12-06T13:43:36.410Z] The best model improves the baseline by 14.34%. [2025-12-06T13:43:36.410Z] Top recommended movies for user id 72: [2025-12-06T13:43:36.410Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:43:36.410Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:43:36.410Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:43:36.410Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:43:36.410Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:43:36.410Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16623.669 ms) ====== [2025-12-06T13:43:36.410Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-06T13:43:36.410Z] GC before operation: completed in 172.306 ms, heap usage 114.390 MB -> 88.354 MB. [2025-12-06T13:43:39.320Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:43:41.964Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:43:44.931Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:43:47.078Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:43:49.180Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:43:49.843Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:43:52.006Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:43:53.400Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:43:53.400Z] 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. [2025-12-06T13:43:53.400Z] The best model improves the baseline by 14.34%. [2025-12-06T13:43:54.038Z] Top recommended movies for user id 72: [2025-12-06T13:43:54.038Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:43:54.038Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:43:54.038Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:43:54.038Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:43:54.038Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:43:54.038Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17326.744 ms) ====== [2025-12-06T13:43:54.038Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-06T13:43:54.038Z] GC before operation: completed in 166.258 ms, heap usage 351.670 MB -> 88.757 MB. [2025-12-06T13:43:56.917Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:43:58.997Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:44:01.907Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:44:03.956Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:44:05.287Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:44:06.652Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:44:08.715Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:44:10.133Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:44:10.770Z] 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. [2025-12-06T13:44:10.770Z] The best model improves the baseline by 14.34%. [2025-12-06T13:44:10.770Z] Top recommended movies for user id 72: [2025-12-06T13:44:10.770Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:44:10.770Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:44:10.770Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:44:10.770Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:44:10.770Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:44:10.770Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16936.263 ms) ====== [2025-12-06T13:44:10.770Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-06T13:44:10.770Z] GC before operation: completed in 176.498 ms, heap usage 115.865 MB -> 88.721 MB. [2025-12-06T13:44:13.653Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:44:17.510Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:44:20.465Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:44:22.925Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:44:24.988Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:44:27.116Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:44:28.445Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:44:30.519Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:44:30.519Z] 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. [2025-12-06T13:44:30.519Z] The best model improves the baseline by 14.34%. [2025-12-06T13:44:30.519Z] Top recommended movies for user id 72: [2025-12-06T13:44:30.519Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:44:30.519Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:44:30.519Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:44:30.519Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:44:30.519Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:44:30.519Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19573.468 ms) ====== [2025-12-06T13:44:30.519Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-06T13:44:31.148Z] GC before operation: completed in 239.758 ms, heap usage 104.236 MB -> 92.620 MB. [2025-12-06T13:44:34.038Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:44:36.229Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:44:39.090Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:44:41.950Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:44:43.973Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:44:45.263Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:44:48.111Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:44:49.402Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:44:49.402Z] 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. [2025-12-06T13:44:49.402Z] The best model improves the baseline by 14.34%. [2025-12-06T13:44:49.402Z] Top recommended movies for user id 72: [2025-12-06T13:44:49.402Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:44:49.402Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:44:49.402Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:44:49.402Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:44:49.402Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:44:49.402Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18802.683 ms) ====== [2025-12-06T13:44:49.402Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-06T13:44:50.024Z] GC before operation: completed in 200.551 ms, heap usage 97.250 MB -> 91.809 MB. [2025-12-06T13:44:52.867Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:44:55.717Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:44:58.570Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:45:00.727Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:45:02.020Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:45:03.338Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:45:04.629Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:45:05.934Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:45:06.552Z] 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. [2025-12-06T13:45:06.552Z] The best model improves the baseline by 14.34%. [2025-12-06T13:45:06.552Z] Top recommended movies for user id 72: [2025-12-06T13:45:06.552Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:45:06.552Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:45:06.552Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:45:06.552Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:45:06.552Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:45:06.552Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16638.912 ms) ====== [2025-12-06T13:45:06.552Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-06T13:45:06.552Z] GC before operation: completed in 161.078 ms, heap usage 194.410 MB -> 88.864 MB. [2025-12-06T13:45:08.572Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:45:11.387Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:45:13.415Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:45:15.434Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:45:16.724Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:45:18.740Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:45:19.362Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:45:20.648Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:45:21.277Z] 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. [2025-12-06T13:45:21.277Z] The best model improves the baseline by 14.34%. [2025-12-06T13:45:21.277Z] Top recommended movies for user id 72: [2025-12-06T13:45:21.277Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:45:21.277Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:45:21.277Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:45:21.277Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:45:21.277Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:45:21.277Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14497.492 ms) ====== [2025-12-06T13:45:21.277Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-06T13:45:21.277Z] GC before operation: completed in 158.869 ms, heap usage 217.836 MB -> 89.135 MB. [2025-12-06T13:45:24.103Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:45:26.132Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:45:28.174Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:45:31.015Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:45:32.316Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:45:33.603Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:45:36.169Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:45:36.791Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:45:36.791Z] 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. [2025-12-06T13:45:36.791Z] The best model improves the baseline by 14.34%. [2025-12-06T13:45:37.433Z] Top recommended movies for user id 72: [2025-12-06T13:45:37.433Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:45:37.433Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:45:37.433Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:45:37.433Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:45:37.433Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:45:37.433Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15901.317 ms) ====== [2025-12-06T13:45:37.433Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-06T13:45:37.433Z] GC before operation: completed in 152.213 ms, heap usage 149.941 MB -> 88.748 MB. [2025-12-06T13:45:39.454Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:45:41.486Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:45:44.306Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:45:46.335Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:45:47.625Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:45:49.659Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:45:50.962Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:45:52.251Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:45:52.251Z] 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. [2025-12-06T13:45:52.251Z] The best model improves the baseline by 14.34%. [2025-12-06T13:45:52.251Z] Top recommended movies for user id 72: [2025-12-06T13:45:52.251Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:45:52.251Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:45:52.251Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:45:52.251Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:45:52.251Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:45:52.251Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15124.525 ms) ====== [2025-12-06T13:45:52.251Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-06T13:45:52.869Z] GC before operation: completed in 223.799 ms, heap usage 109.257 MB -> 88.973 MB. [2025-12-06T13:45:54.890Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:45:56.919Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:45:59.734Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:46:01.787Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:46:02.433Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:46:04.487Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:46:05.790Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:46:06.407Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:46:07.028Z] 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. [2025-12-06T13:46:07.028Z] The best model improves the baseline by 14.34%. [2025-12-06T13:46:07.028Z] Top recommended movies for user id 72: [2025-12-06T13:46:07.028Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:46:07.028Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:46:07.028Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:46:07.028Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:46:07.028Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:46:07.028Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14330.138 ms) ====== [2025-12-06T13:46:07.028Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-06T13:46:07.028Z] GC before operation: completed in 166.275 ms, heap usage 406.218 MB -> 89.512 MB. [2025-12-06T13:46:09.876Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:46:11.909Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:46:13.932Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:46:16.088Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:46:17.383Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:46:18.674Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:46:20.702Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:46:21.994Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:46:21.994Z] 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. [2025-12-06T13:46:21.994Z] The best model improves the baseline by 14.34%. [2025-12-06T13:46:21.994Z] Top recommended movies for user id 72: [2025-12-06T13:46:21.994Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:46:21.994Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:46:21.994Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:46:21.994Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:46:21.994Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:46:21.994Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14867.611 ms) ====== [2025-12-06T13:46:21.994Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-06T13:46:21.994Z] GC before operation: completed in 142.295 ms, heap usage 166.084 MB -> 88.927 MB. [2025-12-06T13:46:24.829Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:46:26.864Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:46:28.886Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:46:30.914Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:46:32.938Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:46:33.568Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:46:35.075Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:46:36.401Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:46:37.024Z] 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. [2025-12-06T13:46:37.024Z] The best model improves the baseline by 14.34%. [2025-12-06T13:46:37.024Z] Top recommended movies for user id 72: [2025-12-06T13:46:37.024Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:46:37.024Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:46:37.024Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:46:37.024Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:46:37.024Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:46:37.024Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14781.197 ms) ====== [2025-12-06T13:46:37.024Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-06T13:46:37.024Z] GC before operation: completed in 214.687 ms, heap usage 140.320 MB -> 89.111 MB. [2025-12-06T13:46:39.919Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:46:41.240Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:46:43.276Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:46:45.316Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:46:46.624Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:46:47.943Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:46:50.096Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:46:50.994Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:46:50.994Z] 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. [2025-12-06T13:46:50.994Z] The best model improves the baseline by 14.34%. [2025-12-06T13:46:50.994Z] Top recommended movies for user id 72: [2025-12-06T13:46:50.994Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:46:50.994Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:46:50.994Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:46:50.994Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:46:50.994Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:46:50.994Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13789.133 ms) ====== [2025-12-06T13:46:50.994Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-06T13:46:50.994Z] GC before operation: completed in 122.655 ms, heap usage 179.926 MB -> 89.020 MB. [2025-12-06T13:46:53.021Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:46:55.122Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:46:57.165Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:46:58.472Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:46:59.768Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:47:01.056Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:47:03.101Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:47:03.721Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:47:04.344Z] 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. [2025-12-06T13:47:04.344Z] The best model improves the baseline by 14.34%. [2025-12-06T13:47:04.344Z] Top recommended movies for user id 72: [2025-12-06T13:47:04.344Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:47:04.344Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:47:04.344Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:47:04.344Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:47:04.344Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:47:04.344Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13077.398 ms) ====== [2025-12-06T13:47:04.344Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-06T13:47:04.344Z] GC before operation: completed in 102.446 ms, heap usage 169.201 MB -> 89.055 MB. [2025-12-06T13:47:06.379Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:47:08.425Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:47:10.511Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:47:12.572Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:47:13.877Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:47:14.530Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:47:16.572Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:47:17.192Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:47:17.813Z] 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. [2025-12-06T13:47:17.813Z] The best model improves the baseline by 14.34%. [2025-12-06T13:47:17.813Z] Top recommended movies for user id 72: [2025-12-06T13:47:17.813Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:47:17.813Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:47:17.813Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:47:17.813Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:47:17.813Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:47:17.813Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13535.459 ms) ====== [2025-12-06T13:47:17.813Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-06T13:47:17.813Z] GC before operation: completed in 154.763 ms, heap usage 243.643 MB -> 89.007 MB. [2025-12-06T13:47:19.848Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:47:22.094Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:47:24.113Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:47:26.145Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:47:27.430Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:47:28.723Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:47:30.127Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:47:32.016Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:47:32.016Z] 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. [2025-12-06T13:47:32.016Z] The best model improves the baseline by 14.34%. [2025-12-06T13:47:32.016Z] Top recommended movies for user id 72: [2025-12-06T13:47:32.016Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:47:32.016Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:47:32.016Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:47:32.016Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:47:32.016Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:47:32.016Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13492.487 ms) ====== [2025-12-06T13:47:32.016Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-06T13:47:32.016Z] GC before operation: completed in 180.763 ms, heap usage 148.021 MB -> 96.511 MB. [2025-12-06T13:47:34.062Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:47:36.230Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:47:38.269Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:47:40.302Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:47:41.607Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:47:42.241Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:47:43.561Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:47:44.869Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:47:44.869Z] 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. [2025-12-06T13:47:44.869Z] The best model improves the baseline by 14.34%. [2025-12-06T13:47:44.869Z] Top recommended movies for user id 72: [2025-12-06T13:47:44.869Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:47:44.869Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:47:44.869Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:47:44.869Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:47:44.869Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:47:44.869Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13508.053 ms) ====== [2025-12-06T13:47:45.497Z] ----------------------------------- [2025-12-06T13:47:45.498Z] renaissance-movie-lens_0_PASSED [2025-12-06T13:47:45.498Z] ----------------------------------- [2025-12-06T13:47:45.498Z] [2025-12-06T13:47:45.498Z] TEST TEARDOWN: [2025-12-06T13:47:45.498Z] Nothing to be done for teardown. [2025-12-06T13:47:45.498Z] renaissance-movie-lens_0 Finish Time: Sat Dec 6 13:47:45 2025 Epoch Time (ms): 1765028865074