[2025-12-27T14:28:53.960Z] Running test renaissance-movie-lens_0 ... [2025-12-27T14:28:53.960Z] =============================================== [2025-12-27T14:28:53.960Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 14:28:53 2025 Epoch Time (ms): 1766845733829 [2025-12-27T14:28:53.960Z] variation: NoOptions [2025-12-27T14:28:53.960Z] JVM_OPTIONS: [2025-12-27T14:28:53.960Z] { \ [2025-12-27T14:28:53.960Z] echo ""; echo "TEST SETUP:"; \ [2025-12-27T14:28:53.960Z] echo "Nothing to be done for setup."; \ [2025-12-27T14:28:53.960Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17668437595934/renaissance-movie-lens_0"; \ [2025-12-27T14:28:53.960Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17668437595934/renaissance-movie-lens_0"; \ [2025-12-27T14:28:53.960Z] echo ""; echo "TESTING:"; \ [2025-12-27T14:28:53.960Z] "/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_17668437595934/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-27T14:28:53.960Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17668437595934/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-27T14:28:53.960Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-27T14:28:53.960Z] echo "Nothing to be done for teardown."; \ [2025-12-27T14:28:53.960Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17668437595934/TestTargetResult"; [2025-12-27T14:28:53.960Z] [2025-12-27T14:28:53.960Z] TEST SETUP: [2025-12-27T14:28:53.960Z] Nothing to be done for setup. [2025-12-27T14:28:53.960Z] [2025-12-27T14:28:53.960Z] TESTING: [2025-12-27T14:28:54.604Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-27T14:28:54.604Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/output_17668437595934/renaissance-movie-lens_0/launcher-142853-17701541619829173074/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-27T14:28:54.604Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-27T14:28:54.604Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-27T14:28:59.478Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-27T14:29:06.840Z] 14:29:06.242 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. [2025-12-27T14:29:09.242Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-27T14:29:10.611Z] Training: 60056, validation: 20285, test: 19854 [2025-12-27T14:29:10.611Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-27T14:29:10.611Z] GC before operation: completed in 167.520 ms, heap usage 230.942 MB -> 75.488 MB. [2025-12-27T14:29:17.902Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:29:23.894Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:29:27.729Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:29:31.600Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:29:33.689Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:29:35.781Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:29:37.875Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:29:39.970Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:29:39.970Z] 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. [2025-12-27T14:29:39.970Z] The best model improves the baseline by 14.34%. [2025-12-27T14:29:40.622Z] Top recommended movies for user id 72: [2025-12-27T14:29:40.622Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:29:40.622Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:29:40.622Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:29:40.622Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:29:40.622Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:29:40.622Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29700.992 ms) ====== [2025-12-27T14:29:40.622Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-27T14:29:40.622Z] GC before operation: completed in 185.649 ms, heap usage 181.388 MB -> 102.489 MB. [2025-12-27T14:29:44.450Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:29:47.370Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:29:50.340Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:29:52.433Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:29:54.523Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:29:56.617Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:29:57.959Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:30:00.059Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:30:00.059Z] 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. [2025-12-27T14:30:00.059Z] The best model improves the baseline by 14.34%. [2025-12-27T14:30:00.059Z] Top recommended movies for user id 72: [2025-12-27T14:30:00.059Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:30:00.059Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:30:00.059Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:30:00.059Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:30:00.059Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:30:00.059Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (19747.943 ms) ====== [2025-12-27T14:30:00.059Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-27T14:30:00.703Z] GC before operation: completed in 170.662 ms, heap usage 217.361 MB -> 96.578 MB. [2025-12-27T14:30:04.036Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:30:06.124Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:30:09.044Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:30:11.963Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:30:13.306Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:30:14.646Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:30:16.737Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:30:18.834Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:30:18.834Z] 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. [2025-12-27T14:30:18.834Z] The best model improves the baseline by 14.34%. [2025-12-27T14:30:18.834Z] Top recommended movies for user id 72: [2025-12-27T14:30:18.834Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:30:18.834Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:30:18.834Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:30:18.834Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:30:18.834Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:30:18.834Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18694.607 ms) ====== [2025-12-27T14:30:18.834Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-27T14:30:19.477Z] GC before operation: completed in 161.631 ms, heap usage 194.971 MB -> 88.134 MB. [2025-12-27T14:30:22.393Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:30:24.492Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:30:27.415Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:30:30.331Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:30:31.676Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:30:33.768Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:30:35.106Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:30:37.205Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:30:37.205Z] 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. [2025-12-27T14:30:37.205Z] The best model improves the baseline by 14.34%. [2025-12-27T14:30:37.851Z] Top recommended movies for user id 72: [2025-12-27T14:30:37.851Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:30:37.851Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:30:37.851Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:30:37.851Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:30:37.851Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:30:37.851Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (18250.501 ms) ====== [2025-12-27T14:30:37.851Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-27T14:30:37.851Z] GC before operation: completed in 155.638 ms, heap usage 244.284 MB -> 88.643 MB. [2025-12-27T14:30:40.780Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:30:43.698Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:30:46.615Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:30:49.536Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:30:50.879Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:30:52.214Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:30:54.305Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:30:55.641Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:30:56.284Z] 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. [2025-12-27T14:30:56.284Z] The best model improves the baseline by 14.34%. [2025-12-27T14:30:56.284Z] Top recommended movies for user id 72: [2025-12-27T14:30:56.284Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:30:56.284Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:30:56.284Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:30:56.284Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:30:56.284Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:30:56.284Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18510.166 ms) ====== [2025-12-27T14:30:56.284Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-27T14:30:56.284Z] GC before operation: completed in 157.589 ms, heap usage 220.764 MB -> 88.505 MB. [2025-12-27T14:30:59.603Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:31:01.789Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:31:04.710Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:31:06.854Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:31:08.193Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:31:09.535Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:31:11.627Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:31:12.966Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:31:12.966Z] 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. [2025-12-27T14:31:12.966Z] The best model improves the baseline by 14.34%. [2025-12-27T14:31:12.966Z] Top recommended movies for user id 72: [2025-12-27T14:31:12.966Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:31:12.966Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:31:12.966Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:31:12.966Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:31:12.966Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:31:12.966Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16838.869 ms) ====== [2025-12-27T14:31:12.966Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-27T14:31:13.608Z] GC before operation: completed in 165.264 ms, heap usage 214.803 MB -> 88.780 MB. [2025-12-27T14:31:15.698Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:31:18.617Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:31:21.544Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:31:23.637Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:31:25.729Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:31:27.067Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:31:28.404Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:31:30.496Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:31:30.496Z] 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. [2025-12-27T14:31:30.496Z] The best model improves the baseline by 14.34%. [2025-12-27T14:31:30.496Z] Top recommended movies for user id 72: [2025-12-27T14:31:30.496Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:31:30.496Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:31:30.496Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:31:30.496Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:31:30.496Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:31:30.496Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17115.749 ms) ====== [2025-12-27T14:31:30.496Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-27T14:31:30.496Z] GC before operation: completed in 158.558 ms, heap usage 220.223 MB -> 88.828 MB. [2025-12-27T14:31:33.405Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:31:35.497Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:31:38.410Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:31:40.502Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:31:41.842Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:31:43.180Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:31:45.363Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:31:47.092Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:31:47.092Z] 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. [2025-12-27T14:31:47.092Z] The best model improves the baseline by 14.34%. [2025-12-27T14:31:47.092Z] Top recommended movies for user id 72: [2025-12-27T14:31:47.092Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:31:47.092Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:31:47.092Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:31:47.092Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:31:47.092Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:31:47.092Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16220.360 ms) ====== [2025-12-27T14:31:47.092Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-27T14:31:47.092Z] GC before operation: completed in 159.257 ms, heap usage 233.793 MB -> 89.064 MB. [2025-12-27T14:31:49.185Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:31:52.104Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:31:55.018Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:31:57.155Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:31:58.493Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:31:59.833Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:32:01.951Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:32:03.287Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:32:03.287Z] 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. [2025-12-27T14:32:03.287Z] The best model improves the baseline by 14.34%. [2025-12-27T14:32:03.287Z] Top recommended movies for user id 72: [2025-12-27T14:32:03.287Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:32:03.287Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:32:03.287Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:32:03.287Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:32:03.287Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:32:03.287Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16491.371 ms) ====== [2025-12-27T14:32:03.287Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-27T14:32:03.927Z] GC before operation: completed in 155.424 ms, heap usage 175.735 MB -> 88.786 MB. [2025-12-27T14:32:06.017Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:32:08.932Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:32:11.019Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:32:13.109Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:32:14.444Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:32:15.779Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:32:17.872Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:32:19.209Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:32:19.209Z] 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. [2025-12-27T14:32:19.209Z] The best model improves the baseline by 14.34%. [2025-12-27T14:32:19.851Z] Top recommended movies for user id 72: [2025-12-27T14:32:19.851Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:32:19.851Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:32:19.851Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:32:19.851Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:32:19.851Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:32:19.851Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15962.273 ms) ====== [2025-12-27T14:32:19.851Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-27T14:32:19.851Z] GC before operation: completed in 151.917 ms, heap usage 139.631 MB -> 89.082 MB. [2025-12-27T14:32:21.940Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:32:24.860Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:32:26.949Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:32:29.867Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:32:31.204Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:32:32.545Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:32:33.884Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:32:35.973Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:32:35.973Z] 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. [2025-12-27T14:32:35.973Z] The best model improves the baseline by 14.34%. [2025-12-27T14:32:35.973Z] Top recommended movies for user id 72: [2025-12-27T14:32:35.973Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:32:35.973Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:32:35.973Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:32:35.973Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:32:35.973Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:32:35.973Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16300.852 ms) ====== [2025-12-27T14:32:35.973Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-27T14:32:35.973Z] GC before operation: completed in 158.545 ms, heap usage 216.248 MB -> 88.808 MB. [2025-12-27T14:32:39.300Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:32:41.391Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:32:44.307Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:32:46.394Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:32:47.729Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:32:49.063Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:32:51.156Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:32:52.493Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:32:52.493Z] 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. [2025-12-27T14:32:52.493Z] The best model improves the baseline by 14.34%. [2025-12-27T14:32:52.493Z] Top recommended movies for user id 72: [2025-12-27T14:32:52.493Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:32:52.493Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:32:52.493Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:32:52.493Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:32:52.493Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:32:52.493Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16303.971 ms) ====== [2025-12-27T14:32:52.493Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-27T14:32:52.493Z] GC before operation: completed in 154.760 ms, heap usage 168.296 MB -> 96.427 MB. [2025-12-27T14:32:55.403Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:32:57.491Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:33:00.480Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:33:02.569Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:33:03.903Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:33:05.240Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:33:06.578Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:33:07.927Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:33:08.572Z] 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. [2025-12-27T14:33:08.572Z] The best model improves the baseline by 14.34%. [2025-12-27T14:33:08.572Z] Top recommended movies for user id 72: [2025-12-27T14:33:08.572Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:33:08.572Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:33:08.572Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:33:08.572Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:33:08.572Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:33:08.573Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15937.726 ms) ====== [2025-12-27T14:33:08.573Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-27T14:33:08.573Z] GC before operation: completed in 153.391 ms, heap usage 213.512 MB -> 89.143 MB. [2025-12-27T14:33:11.488Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:33:13.581Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:33:16.500Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:33:18.656Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:33:20.746Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:33:22.096Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:33:23.437Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:33:24.775Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:33:25.420Z] 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. [2025-12-27T14:33:25.420Z] The best model improves the baseline by 14.34%. [2025-12-27T14:33:25.420Z] Top recommended movies for user id 72: [2025-12-27T14:33:25.420Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:33:25.420Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:33:25.420Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:33:25.420Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:33:25.420Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:33:25.420Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16898.927 ms) ====== [2025-12-27T14:33:25.420Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-27T14:33:26.064Z] GC before operation: completed in 156.221 ms, heap usage 147.843 MB -> 94.229 MB. [2025-12-27T14:33:28.568Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:33:30.658Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:33:33.577Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:33:35.666Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:33:37.008Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:33:38.348Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:33:40.441Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:33:41.780Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:33:41.780Z] 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. [2025-12-27T14:33:41.780Z] The best model improves the baseline by 14.34%. [2025-12-27T14:33:41.780Z] Top recommended movies for user id 72: [2025-12-27T14:33:41.780Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:33:41.780Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:33:41.780Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:33:41.780Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:33:41.780Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:33:41.780Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16130.067 ms) ====== [2025-12-27T14:33:41.780Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-27T14:33:42.423Z] GC before operation: completed in 159.086 ms, heap usage 222.695 MB -> 96.164 MB. [2025-12-27T14:33:44.519Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:33:46.612Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:33:49.528Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:33:51.618Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:33:52.960Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:33:54.298Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:33:56.393Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:33:57.037Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:33:57.684Z] 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. [2025-12-27T14:33:57.684Z] The best model improves the baseline by 14.34%. [2025-12-27T14:33:57.684Z] Top recommended movies for user id 72: [2025-12-27T14:33:57.684Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:33:57.684Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:33:57.684Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:33:57.684Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:33:57.684Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:33:57.684Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15604.952 ms) ====== [2025-12-27T14:33:57.684Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-27T14:33:57.684Z] GC before operation: completed in 154.700 ms, heap usage 167.520 MB -> 88.978 MB. [2025-12-27T14:34:00.603Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:34:02.716Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:34:04.806Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:34:07.721Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:34:09.058Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:34:10.393Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:34:11.726Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:34:13.067Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:34:13.067Z] 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. [2025-12-27T14:34:13.067Z] The best model improves the baseline by 14.34%. [2025-12-27T14:34:13.713Z] Top recommended movies for user id 72: [2025-12-27T14:34:13.713Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:34:13.713Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:34:13.713Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:34:13.713Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:34:13.713Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:34:13.713Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15563.656 ms) ====== [2025-12-27T14:34:13.713Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-27T14:34:13.713Z] GC before operation: completed in 155.145 ms, heap usage 302.903 MB -> 89.342 MB. [2025-12-27T14:34:15.801Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:34:18.729Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:34:21.210Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:34:23.297Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:34:24.634Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:34:25.971Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:34:27.305Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:34:28.642Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:34:29.285Z] 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. [2025-12-27T14:34:29.285Z] The best model improves the baseline by 14.34%. [2025-12-27T14:34:29.285Z] Top recommended movies for user id 72: [2025-12-27T14:34:29.285Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:34:29.285Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:34:29.285Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:34:29.285Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:34:29.285Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:34:29.285Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15651.752 ms) ====== [2025-12-27T14:34:29.286Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-27T14:34:29.286Z] GC before operation: completed in 154.052 ms, heap usage 165.020 MB -> 88.940 MB. [2025-12-27T14:34:32.197Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:34:34.287Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:34:36.376Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:34:38.465Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:34:40.555Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:34:41.198Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:34:43.288Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:34:44.626Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:34:44.626Z] 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. [2025-12-27T14:34:44.626Z] The best model improves the baseline by 14.34%. [2025-12-27T14:34:45.269Z] Top recommended movies for user id 72: [2025-12-27T14:34:45.269Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:34:45.269Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:34:45.269Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:34:45.269Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:34:45.269Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:34:45.269Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15530.168 ms) ====== [2025-12-27T14:34:45.269Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-27T14:34:45.269Z] GC before operation: completed in 151.267 ms, heap usage 139.989 MB -> 88.997 MB. [2025-12-27T14:34:47.359Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T14:34:50.271Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T14:34:52.361Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T14:34:54.447Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T14:34:55.781Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T14:34:57.117Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T14:34:58.460Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T14:34:59.813Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T14:35:00.483Z] 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. [2025-12-27T14:35:00.483Z] The best model improves the baseline by 14.34%. [2025-12-27T14:35:00.483Z] Top recommended movies for user id 72: [2025-12-27T14:35:00.483Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-27T14:35:00.483Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-27T14:35:00.483Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-27T14:35:00.483Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-27T14:35:00.483Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-27T14:35:00.483Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15322.673 ms) ====== [2025-12-27T14:35:01.130Z] ----------------------------------- [2025-12-27T14:35:01.130Z] renaissance-movie-lens_0_PASSED [2025-12-27T14:35:01.130Z] ----------------------------------- [2025-12-27T14:35:01.130Z] [2025-12-27T14:35:01.130Z] TEST TEARDOWN: [2025-12-27T14:35:01.130Z] Nothing to be done for teardown. [2025-12-27T14:35:01.130Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 14:35:00 2025 Epoch Time (ms): 1766846100473