[2025-12-13T14:21:55.509Z] Running test renaissance-movie-lens_0 ... [2025-12-13T14:21:55.509Z] =============================================== [2025-12-13T14:21:55.509Z] renaissance-movie-lens_0 Start Time: Sat Dec 13 14:21:55 2025 Epoch Time (ms): 1765635715158 [2025-12-13T14:21:55.509Z] variation: NoOptions [2025-12-13T14:21:55.509Z] JVM_OPTIONS: [2025-12-13T14:21:55.509Z] { \ [2025-12-13T14:21:55.509Z] echo ""; echo "TEST SETUP:"; \ [2025-12-13T14:21:55.509Z] echo "Nothing to be done for setup."; \ [2025-12-13T14:21:55.509Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17656332036224/renaissance-movie-lens_0"; \ [2025-12-13T14:21:55.509Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17656332036224/renaissance-movie-lens_0"; \ [2025-12-13T14:21:55.509Z] echo ""; echo "TESTING:"; \ [2025-12-13T14:21:55.509Z] "/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_17656332036224/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-13T14:21:55.509Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17656332036224/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-13T14:21:55.509Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-13T14:21:55.509Z] echo "Nothing to be done for teardown."; \ [2025-12-13T14:21:55.509Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17656332036224/TestTargetResult"; [2025-12-13T14:21:55.509Z] [2025-12-13T14:21:55.509Z] TEST SETUP: [2025-12-13T14:21:55.509Z] Nothing to be done for setup. [2025-12-13T14:21:55.509Z] [2025-12-13T14:21:55.509Z] TESTING: [2025-12-13T14:21:55.841Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-13T14:21:55.841Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/output_17656332036224/renaissance-movie-lens_0/launcher-142155-6157724139406900670/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-13T14:21:55.841Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-13T14:21:55.841Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-13T14:22:00.599Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-13T14:22:09.710Z] 14:22:08.104 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-12-13T14:22:11.385Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-13T14:22:12.604Z] Training: 60056, validation: 20285, test: 19854 [2025-12-13T14:22:12.604Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-13T14:22:12.604Z] GC before operation: completed in 163.931 ms, heap usage 188.314 MB -> 75.408 MB. [2025-12-13T14:22:21.608Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:22:27.516Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:22:32.295Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:22:35.257Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:22:37.546Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:22:39.895Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:22:42.151Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:22:44.400Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:22:44.400Z] 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. [2025-12-13T14:22:44.400Z] The best model improves the baseline by 14.34%. [2025-12-13T14:22:44.727Z] Top recommended movies for user id 72: [2025-12-13T14:22:44.727Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:22:44.727Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:22:44.727Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:22:44.727Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:22:44.727Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:22:44.727Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (32211.552 ms) ====== [2025-12-13T14:22:44.727Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-13T14:22:45.057Z] GC before operation: completed in 178.928 ms, heap usage 218.699 MB -> 94.380 MB. [2025-12-13T14:22:48.858Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:22:51.814Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:22:54.774Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:22:57.766Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:22:59.428Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:23:01.097Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:23:02.844Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:23:04.497Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:23:04.825Z] 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. [2025-12-13T14:23:04.825Z] The best model improves the baseline by 14.34%. [2025-12-13T14:23:05.152Z] Top recommended movies for user id 72: [2025-12-13T14:23:05.152Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:23:05.152Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:23:05.152Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:23:05.152Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:23:05.152Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:23:05.152Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20255.821 ms) ====== [2025-12-13T14:23:05.152Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-13T14:23:05.480Z] GC before operation: completed in 165.140 ms, heap usage 192.868 MB -> 88.668 MB. [2025-12-13T14:23:08.457Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:23:11.441Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:23:14.405Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:23:17.363Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:23:18.512Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:23:20.173Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:23:22.426Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:23:23.674Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:23:24.001Z] 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. [2025-12-13T14:23:24.001Z] The best model improves the baseline by 14.34%. [2025-12-13T14:23:24.328Z] Top recommended movies for user id 72: [2025-12-13T14:23:24.328Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:23:24.328Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:23:24.328Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:23:24.328Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:23:24.328Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:23:24.328Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18889.005 ms) ====== [2025-12-13T14:23:24.328Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-13T14:23:24.328Z] GC before operation: completed in 168.676 ms, heap usage 210.106 MB -> 88.209 MB. [2025-12-13T14:23:27.288Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:23:30.237Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:23:33.191Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:23:35.479Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:23:37.136Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:23:38.799Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:23:40.465Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:23:42.721Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:23:42.721Z] 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. [2025-12-13T14:23:42.721Z] The best model improves the baseline by 14.34%. [2025-12-13T14:23:43.049Z] Top recommended movies for user id 72: [2025-12-13T14:23:43.049Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:23:43.049Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:23:43.049Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:23:43.049Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:23:43.049Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:23:43.049Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (18522.273 ms) ====== [2025-12-13T14:23:43.049Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-13T14:23:43.049Z] GC before operation: completed in 176.107 ms, heap usage 216.182 MB -> 88.528 MB. [2025-12-13T14:23:46.004Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:23:48.981Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:23:51.935Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:23:54.893Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:23:56.547Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:23:58.799Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:24:00.463Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:24:02.122Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:24:02.459Z] 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. [2025-12-13T14:24:02.459Z] The best model improves the baseline by 14.34%. [2025-12-13T14:24:02.795Z] Top recommended movies for user id 72: [2025-12-13T14:24:02.795Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:24:02.795Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:24:02.795Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:24:02.795Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:24:02.795Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:24:02.795Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19574.800 ms) ====== [2025-12-13T14:24:02.795Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-13T14:24:02.795Z] GC before operation: completed in 187.330 ms, heap usage 220.129 MB -> 88.543 MB. [2025-12-13T14:24:05.755Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:24:09.583Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:24:12.599Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:24:15.562Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:24:17.214Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:24:18.363Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:24:20.642Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:24:22.303Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:24:22.303Z] 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. [2025-12-13T14:24:22.642Z] The best model improves the baseline by 14.34%. [2025-12-13T14:24:22.642Z] Top recommended movies for user id 72: [2025-12-13T14:24:22.642Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:24:22.642Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:24:22.642Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:24:22.642Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:24:22.642Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:24:22.642Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19935.980 ms) ====== [2025-12-13T14:24:22.642Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-13T14:24:22.973Z] GC before operation: completed in 158.457 ms, heap usage 247.529 MB -> 88.980 MB. [2025-12-13T14:24:25.968Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:24:28.973Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:24:32.025Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:24:34.981Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:24:36.129Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:24:37.783Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:24:39.441Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:24:41.105Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:24:41.439Z] 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. [2025-12-13T14:24:41.439Z] The best model improves the baseline by 14.34%. [2025-12-13T14:24:41.440Z] Top recommended movies for user id 72: [2025-12-13T14:24:41.440Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:24:41.440Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:24:41.440Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:24:41.440Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:24:41.440Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:24:41.440Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18611.082 ms) ====== [2025-12-13T14:24:41.440Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-13T14:24:41.775Z] GC before operation: completed in 170.063 ms, heap usage 240.647 MB -> 88.869 MB. [2025-12-13T14:24:44.747Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:24:47.014Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:24:49.999Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:24:52.293Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:24:53.438Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:24:55.196Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:24:56.871Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:24:58.574Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:24:58.574Z] 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. [2025-12-13T14:24:58.902Z] The best model improves the baseline by 14.34%. [2025-12-13T14:24:58.902Z] Top recommended movies for user id 72: [2025-12-13T14:24:58.902Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:24:58.902Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:24:58.902Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:24:58.902Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:24:58.902Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:24:58.902Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17172.998 ms) ====== [2025-12-13T14:24:58.902Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-13T14:24:59.242Z] GC before operation: completed in 171.379 ms, heap usage 208.393 MB -> 88.976 MB. [2025-12-13T14:25:02.216Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:25:04.478Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:25:07.428Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:25:09.701Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:25:11.359Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:25:12.504Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:25:14.165Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:25:15.927Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:25:15.927Z] 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. [2025-12-13T14:25:15.927Z] The best model improves the baseline by 14.34%. [2025-12-13T14:25:16.266Z] Top recommended movies for user id 72: [2025-12-13T14:25:16.266Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:25:16.266Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:25:16.266Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:25:16.266Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:25:16.266Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:25:16.266Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17135.666 ms) ====== [2025-12-13T14:25:16.266Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-13T14:25:16.266Z] GC before operation: completed in 159.119 ms, heap usage 160.641 MB -> 88.876 MB. [2025-12-13T14:25:19.236Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:25:22.248Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:25:24.507Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:25:26.761Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:25:28.417Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:25:29.565Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:25:31.225Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:25:32.920Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:25:33.250Z] 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. [2025-12-13T14:25:33.250Z] The best model improves the baseline by 14.34%. [2025-12-13T14:25:33.580Z] Top recommended movies for user id 72: [2025-12-13T14:25:33.580Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:25:33.580Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:25:33.580Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:25:33.580Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:25:33.580Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:25:33.580Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17094.400 ms) ====== [2025-12-13T14:25:33.580Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-13T14:25:33.580Z] GC before operation: completed in 157.723 ms, heap usage 174.842 MB -> 89.082 MB. [2025-12-13T14:25:36.550Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:25:38.965Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:25:41.940Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:25:43.622Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:25:45.280Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:25:46.934Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:25:48.595Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:25:50.264Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:25:50.264Z] 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. [2025-12-13T14:25:50.264Z] The best model improves the baseline by 14.34%. [2025-12-13T14:25:50.595Z] Top recommended movies for user id 72: [2025-12-13T14:25:50.595Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:25:50.595Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:25:50.595Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:25:50.595Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:25:50.595Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:25:50.595Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16907.113 ms) ====== [2025-12-13T14:25:50.595Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-13T14:25:50.595Z] GC before operation: completed in 157.681 ms, heap usage 246.607 MB -> 88.902 MB. [2025-12-13T14:25:53.566Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:25:55.821Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:25:58.785Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:26:01.058Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:26:02.235Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:26:03.890Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:26:05.561Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:26:07.220Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:26:07.220Z] 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. [2025-12-13T14:26:07.220Z] The best model improves the baseline by 14.34%. [2025-12-13T14:26:07.548Z] Top recommended movies for user id 72: [2025-12-13T14:26:07.549Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:26:07.549Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:26:07.549Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:26:07.549Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:26:07.549Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:26:07.549Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16697.362 ms) ====== [2025-12-13T14:26:07.549Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-13T14:26:07.549Z] GC before operation: completed in 155.826 ms, heap usage 150.027 MB -> 89.012 MB. [2025-12-13T14:26:10.524Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:26:12.779Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:26:15.751Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:26:17.418Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:26:19.080Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:26:20.772Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:26:22.048Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:26:23.710Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:26:24.045Z] 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. [2025-12-13T14:26:24.045Z] The best model improves the baseline by 14.34%. [2025-12-13T14:26:24.045Z] Top recommended movies for user id 72: [2025-12-13T14:26:24.045Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:26:24.045Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:26:24.045Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:26:24.045Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:26:24.045Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:26:24.045Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16558.794 ms) ====== [2025-12-13T14:26:24.045Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-13T14:26:24.379Z] GC before operation: completed in 166.905 ms, heap usage 383.271 MB -> 89.452 MB. [2025-12-13T14:26:27.331Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:26:29.605Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:26:35.655Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:26:35.655Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:26:36.808Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:26:38.479Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:26:40.732Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:26:41.878Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:26:42.206Z] 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. [2025-12-13T14:26:42.206Z] The best model improves the baseline by 14.34%. [2025-12-13T14:26:42.535Z] Top recommended movies for user id 72: [2025-12-13T14:26:42.535Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:26:42.535Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:26:42.535Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:26:42.535Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:26:42.535Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:26:42.535Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18155.596 ms) ====== [2025-12-13T14:26:42.535Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-13T14:26:42.535Z] GC before operation: completed in 159.804 ms, heap usage 177.332 MB -> 88.964 MB. [2025-12-13T14:26:45.494Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:26:49.320Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:26:52.381Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:26:54.634Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:26:56.292Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:26:57.948Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:26:59.612Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:27:01.285Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:27:01.285Z] 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. [2025-12-13T14:27:01.285Z] The best model improves the baseline by 14.34%. [2025-12-13T14:27:01.613Z] Top recommended movies for user id 72: [2025-12-13T14:27:01.613Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:27:01.613Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:27:01.613Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:27:01.613Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:27:01.613Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:27:01.613Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18889.824 ms) ====== [2025-12-13T14:27:01.613Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-13T14:27:01.613Z] GC before operation: completed in 156.246 ms, heap usage 110.827 MB -> 89.025 MB. [2025-12-13T14:27:04.568Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:27:07.535Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:27:10.510Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:27:12.867Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:27:14.549Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:27:16.201Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:27:17.865Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:27:19.537Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:27:19.537Z] 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. [2025-12-13T14:27:19.866Z] The best model improves the baseline by 14.34%. [2025-12-13T14:27:19.866Z] Top recommended movies for user id 72: [2025-12-13T14:27:19.866Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:27:19.866Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:27:19.866Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:27:19.866Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:27:19.866Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:27:19.866Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18211.907 ms) ====== [2025-12-13T14:27:19.866Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-13T14:27:19.866Z] GC before operation: completed in 162.341 ms, heap usage 195.884 MB -> 88.985 MB. [2025-12-13T14:27:23.645Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:27:25.913Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:27:28.864Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:27:31.111Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:27:32.316Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:27:33.475Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:27:35.131Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:27:36.796Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:27:36.796Z] 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. [2025-12-13T14:27:36.796Z] The best model improves the baseline by 14.34%. [2025-12-13T14:27:37.125Z] Top recommended movies for user id 72: [2025-12-13T14:27:37.125Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:27:37.125Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:27:37.125Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:27:37.125Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:27:37.125Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:27:37.125Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16972.918 ms) ====== [2025-12-13T14:27:37.125Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-13T14:27:37.125Z] GC before operation: completed in 159.936 ms, heap usage 299.790 MB -> 89.378 MB. [2025-12-13T14:27:40.103Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:27:42.363Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:27:44.632Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:27:46.882Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:27:48.540Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:27:49.708Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:27:51.386Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:27:53.062Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:27:53.062Z] 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. [2025-12-13T14:27:53.062Z] The best model improves the baseline by 14.34%. [2025-12-13T14:27:53.062Z] Top recommended movies for user id 72: [2025-12-13T14:27:53.062Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:27:53.062Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:27:53.062Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:27:53.062Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:27:53.062Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:27:53.062Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16047.036 ms) ====== [2025-12-13T14:27:53.062Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-13T14:27:53.392Z] GC before operation: completed in 159.556 ms, heap usage 190.301 MB -> 88.990 MB. [2025-12-13T14:27:55.767Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:27:58.732Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:28:01.023Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:28:03.313Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:28:04.467Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:28:06.126Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:28:07.812Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:28:08.962Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:28:09.296Z] 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. [2025-12-13T14:28:09.296Z] The best model improves the baseline by 14.34%. [2025-12-13T14:28:09.625Z] Top recommended movies for user id 72: [2025-12-13T14:28:09.625Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:28:09.625Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:28:09.625Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:28:09.625Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:28:09.625Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:28:09.625Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16154.074 ms) ====== [2025-12-13T14:28:09.625Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-13T14:28:09.625Z] GC before operation: completed in 159.515 ms, heap usage 220.057 MB -> 89.177 MB. [2025-12-13T14:28:12.595Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-13T14:28:14.895Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-13T14:28:17.214Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-13T14:28:19.476Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-13T14:28:21.133Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-13T14:28:22.288Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-13T14:28:23.953Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-13T14:28:25.102Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-13T14:28:25.431Z] 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. [2025-12-13T14:28:25.431Z] The best model improves the baseline by 14.34%. [2025-12-13T14:28:25.763Z] Top recommended movies for user id 72: [2025-12-13T14:28:25.763Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-13T14:28:25.763Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-13T14:28:25.764Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-13T14:28:25.764Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-13T14:28:25.764Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-13T14:28:25.764Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16001.332 ms) ====== [2025-12-13T14:28:26.097Z] ----------------------------------- [2025-12-13T14:28:26.097Z] renaissance-movie-lens_0_PASSED [2025-12-13T14:28:26.097Z] ----------------------------------- [2025-12-13T14:28:26.097Z] [2025-12-13T14:28:26.097Z] TEST TEARDOWN: [2025-12-13T14:28:26.097Z] Nothing to be done for teardown. [2025-12-13T14:28:26.097Z] renaissance-movie-lens_0 Finish Time: Sat Dec 13 14:28:25 2025 Epoch Time (ms): 1765636105865