[2025-11-19T22:47:00.879Z] Running test renaissance-movie-lens_0 ... [2025-11-19T22:47:00.879Z] =============================================== [2025-11-19T22:47:00.879Z] renaissance-movie-lens_0 Start Time: Wed Nov 19 22:47:00 2025 Epoch Time (ms): 1763592420602 [2025-11-19T22:47:00.879Z] variation: NoOptions [2025-11-19T22:47:00.879Z] JVM_OPTIONS: [2025-11-19T22:47:00.879Z] { \ [2025-11-19T22:47:00.879Z] echo ""; echo "TEST SETUP:"; \ [2025-11-19T22:47:00.879Z] echo "Nothing to be done for setup."; \ [2025-11-19T22:47:00.879Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17635903824609/renaissance-movie-lens_0"; \ [2025-11-19T22:47:00.879Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17635903824609/renaissance-movie-lens_0"; \ [2025-11-19T22:47:00.879Z] echo ""; echo "TESTING:"; \ [2025-11-19T22:47:00.879Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17635903824609/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-19T22:47:00.879Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17635903824609/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-19T22:47:00.879Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-19T22:47:00.879Z] echo "Nothing to be done for teardown."; \ [2025-11-19T22:47:00.879Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17635903824609/TestTargetResult"; [2025-11-19T22:47:00.879Z] [2025-11-19T22:47:00.879Z] TEST SETUP: [2025-11-19T22:47:00.879Z] Nothing to be done for setup. [2025-11-19T22:47:00.879Z] [2025-11-19T22:47:00.879Z] TESTING: [2025-11-19T22:47:06.636Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-11-19T22:47:15.478Z] 22:47:14.213 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. [2025-11-19T22:47:17.646Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-19T22:47:18.365Z] Training: 60056, validation: 20285, test: 19854 [2025-11-19T22:47:18.365Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-19T22:47:18.676Z] GC before operation: completed in 211.325 ms, heap usage 269.939 MB -> 75.346 MB. [2025-11-19T22:47:27.449Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:47:34.560Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:47:39.232Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:47:43.941Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:47:46.804Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:47:48.980Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:47:51.838Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:47:54.057Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:47:54.368Z] 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. [2025-11-19T22:47:54.681Z] The best model improves the baseline by 14.34%. [2025-11-19T22:47:54.992Z] Top recommended movies for user id 72: [2025-11-19T22:47:54.992Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:47:54.992Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:47:54.992Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:47:54.992Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:47:54.992Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:47:54.992Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (36281.976 ms) ====== [2025-11-19T22:47:54.992Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-19T22:47:54.992Z] GC before operation: completed in 175.429 ms, heap usage 185.800 MB -> 92.441 MB. [2025-11-19T22:47:58.667Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:48:02.370Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:48:06.164Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:48:08.416Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:48:10.595Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:48:12.784Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:48:14.964Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:48:16.556Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:48:17.230Z] 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. [2025-11-19T22:48:17.230Z] The best model improves the baseline by 14.34%. [2025-11-19T22:48:17.230Z] Top recommended movies for user id 72: [2025-11-19T22:48:17.230Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:48:17.230Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:48:17.230Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:48:17.230Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:48:17.230Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:48:17.230Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (22311.985 ms) ====== [2025-11-19T22:48:17.230Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-19T22:48:17.541Z] GC before operation: completed in 144.205 ms, heap usage 125.779 MB -> 90.613 MB. [2025-11-19T22:48:22.205Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:48:25.890Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:48:28.857Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:48:32.537Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:48:34.126Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:48:35.722Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:48:37.944Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:48:40.117Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:48:40.117Z] 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. [2025-11-19T22:48:40.117Z] The best model improves the baseline by 14.34%. [2025-11-19T22:48:40.430Z] Top recommended movies for user id 72: [2025-11-19T22:48:40.430Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:48:40.430Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:48:40.430Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:48:40.430Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:48:40.430Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:48:40.430Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (22839.049 ms) ====== [2025-11-19T22:48:40.430Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-19T22:48:40.430Z] GC before operation: completed in 146.095 ms, heap usage 194.761 MB -> 91.448 MB. [2025-11-19T22:48:43.282Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:48:46.145Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:48:49.804Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:48:52.033Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:48:54.203Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:48:55.793Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:48:57.382Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:48:58.969Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:48:59.281Z] 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. [2025-11-19T22:48:59.281Z] The best model improves the baseline by 14.34%. [2025-11-19T22:48:59.591Z] Top recommended movies for user id 72: [2025-11-19T22:48:59.591Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:48:59.591Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:48:59.591Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:48:59.591Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:48:59.591Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:48:59.591Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19160.172 ms) ====== [2025-11-19T22:48:59.591Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-19T22:48:59.905Z] GC before operation: completed in 149.108 ms, heap usage 174.817 MB -> 89.572 MB. [2025-11-19T22:49:02.761Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:49:05.618Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:49:09.275Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:49:11.444Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:49:13.039Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:49:14.705Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:49:16.877Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:49:18.472Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:49:18.784Z] 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. [2025-11-19T22:49:18.784Z] The best model improves the baseline by 14.34%. [2025-11-19T22:49:18.784Z] Top recommended movies for user id 72: [2025-11-19T22:49:18.784Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:49:18.784Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:49:18.784Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:49:18.784Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:49:18.784Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:49:18.784Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19093.683 ms) ====== [2025-11-19T22:49:18.784Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-19T22:49:19.096Z] GC before operation: completed in 146.683 ms, heap usage 198.989 MB -> 93.030 MB. [2025-11-19T22:49:22.007Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:49:24.861Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:49:27.722Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:49:29.905Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:49:32.077Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:49:33.703Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:49:35.375Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:49:36.969Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:49:37.284Z] 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. [2025-11-19T22:49:37.597Z] The best model improves the baseline by 14.34%. [2025-11-19T22:49:37.597Z] Top recommended movies for user id 72: [2025-11-19T22:49:37.597Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:49:37.597Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:49:37.597Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:49:37.597Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:49:37.597Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:49:37.597Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18628.465 ms) ====== [2025-11-19T22:49:37.597Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-19T22:49:37.910Z] GC before operation: completed in 155.011 ms, heap usage 214.408 MB -> 88.763 MB. [2025-11-19T22:49:40.775Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:49:44.449Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:49:49.081Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:49:52.755Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:49:54.951Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:49:57.137Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:49:58.766Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:50:00.974Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:50:01.285Z] 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. [2025-11-19T22:50:01.285Z] The best model improves the baseline by 14.34%. [2025-11-19T22:50:01.285Z] Top recommended movies for user id 72: [2025-11-19T22:50:01.285Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:50:01.285Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:50:01.285Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:50:01.285Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:50:01.285Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:50:01.285Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (23559.502 ms) ====== [2025-11-19T22:50:01.285Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-19T22:50:01.597Z] GC before operation: completed in 154.917 ms, heap usage 192.368 MB -> 93.140 MB. [2025-11-19T22:50:05.287Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:50:08.152Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:50:10.374Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:50:13.242Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:50:14.833Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:50:16.423Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:50:18.611Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:50:20.198Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:50:20.198Z] 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. [2025-11-19T22:50:20.198Z] The best model improves the baseline by 14.34%. [2025-11-19T22:50:20.510Z] Top recommended movies for user id 72: [2025-11-19T22:50:20.510Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:50:20.510Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:50:20.510Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:50:20.510Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:50:20.510Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:50:20.510Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18941.099 ms) ====== [2025-11-19T22:50:20.510Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-19T22:50:20.510Z] GC before operation: completed in 138.325 ms, heap usage 174.082 MB -> 91.098 MB. [2025-11-19T22:50:23.414Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:50:26.277Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:50:29.176Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:50:32.104Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:50:33.735Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:50:35.358Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:50:36.963Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:50:39.157Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:50:39.157Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-19T22:50:39.157Z] The best model improves the baseline by 14.34%. [2025-11-19T22:50:39.157Z] Top recommended movies for user id 72: [2025-11-19T22:50:39.157Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:50:39.157Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:50:39.157Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:50:39.157Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:50:39.157Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:50:39.157Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18697.966 ms) ====== [2025-11-19T22:50:39.157Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-19T22:50:39.473Z] GC before operation: completed in 142.063 ms, heap usage 206.851 MB -> 89.971 MB. [2025-11-19T22:50:42.329Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:50:45.299Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:50:48.150Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:50:50.346Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:50:52.535Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:50:54.146Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:50:55.818Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:50:57.424Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:50:57.741Z] 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. [2025-11-19T22:50:57.741Z] The best model improves the baseline by 14.34%. [2025-11-19T22:50:58.060Z] Top recommended movies for user id 72: [2025-11-19T22:50:58.060Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:50:58.060Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:50:58.060Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:50:58.060Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:50:58.060Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:50:58.060Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18500.489 ms) ====== [2025-11-19T22:50:58.060Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-19T22:50:58.060Z] GC before operation: completed in 139.935 ms, heap usage 151.490 MB -> 93.663 MB. [2025-11-19T22:51:00.920Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:51:03.792Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:51:06.657Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:51:08.954Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:51:10.558Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:51:12.749Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:51:14.347Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:51:15.986Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:51:16.300Z] 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. [2025-11-19T22:51:16.300Z] The best model improves the baseline by 14.34%. [2025-11-19T22:51:16.300Z] Top recommended movies for user id 72: [2025-11-19T22:51:16.300Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:51:16.300Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:51:16.300Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:51:16.300Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:51:16.300Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:51:16.300Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18258.383 ms) ====== [2025-11-19T22:51:16.300Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-19T22:51:16.612Z] GC before operation: completed in 144.942 ms, heap usage 194.079 MB -> 97.162 MB. [2025-11-19T22:51:19.530Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:51:22.399Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:51:25.254Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:51:28.106Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:51:29.306Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:51:30.902Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:51:32.503Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:51:34.110Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:51:34.421Z] 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. [2025-11-19T22:51:34.421Z] The best model improves the baseline by 14.34%. [2025-11-19T22:51:34.733Z] Top recommended movies for user id 72: [2025-11-19T22:51:34.733Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:51:34.733Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:51:34.733Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:51:34.733Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:51:34.733Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:51:34.733Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18187.523 ms) ====== [2025-11-19T22:51:34.733Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-19T22:51:34.733Z] GC before operation: completed in 144.253 ms, heap usage 179.996 MB -> 94.252 MB. [2025-11-19T22:51:37.589Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:51:40.455Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:51:42.906Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:51:45.189Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:51:47.403Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:51:48.540Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:51:50.740Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:51:51.931Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:51:52.242Z] 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. [2025-11-19T22:51:52.242Z] The best model improves the baseline by 14.34%. [2025-11-19T22:51:52.559Z] Top recommended movies for user id 72: [2025-11-19T22:51:52.559Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:51:52.559Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:51:52.559Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:51:52.559Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:51:52.559Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:51:52.559Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (17649.094 ms) ====== [2025-11-19T22:51:52.559Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-19T22:51:52.559Z] GC before operation: completed in 144.569 ms, heap usage 150.864 MB -> 91.344 MB. [2025-11-19T22:51:55.410Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:51:58.262Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:52:01.115Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:52:03.290Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:52:05.457Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:52:06.553Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:52:08.733Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:52:10.340Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:52:10.340Z] 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. [2025-11-19T22:52:10.340Z] The best model improves the baseline by 14.34%. [2025-11-19T22:52:10.653Z] Top recommended movies for user id 72: [2025-11-19T22:52:10.653Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:52:10.653Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:52:10.653Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:52:10.653Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:52:10.653Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:52:10.653Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17949.022 ms) ====== [2025-11-19T22:52:10.653Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-19T22:52:10.653Z] GC before operation: completed in 139.647 ms, heap usage 145.109 MB -> 88.919 MB. [2025-11-19T22:52:13.568Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:52:16.418Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:52:19.287Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:52:21.499Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:52:23.088Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:52:24.675Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:52:26.262Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:52:27.850Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:52:28.160Z] 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. [2025-11-19T22:52:28.160Z] The best model improves the baseline by 14.34%. [2025-11-19T22:52:28.160Z] Top recommended movies for user id 72: [2025-11-19T22:52:28.160Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:52:28.160Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:52:28.160Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:52:28.160Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:52:28.160Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:52:28.160Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17509.957 ms) ====== [2025-11-19T22:52:28.160Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-19T22:52:28.473Z] GC before operation: completed in 139.315 ms, heap usage 180.565 MB -> 90.364 MB. [2025-11-19T22:52:31.330Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:52:34.184Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:52:36.385Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:52:39.233Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:52:40.819Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:52:41.929Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:52:44.108Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:52:45.217Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:52:45.530Z] 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. [2025-11-19T22:52:45.530Z] The best model improves the baseline by 14.34%. [2025-11-19T22:52:45.843Z] Top recommended movies for user id 72: [2025-11-19T22:52:45.843Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:52:45.843Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:52:45.843Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:52:45.843Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:52:45.843Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:52:45.843Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17473.991 ms) ====== [2025-11-19T22:52:45.843Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-19T22:52:45.843Z] GC before operation: completed in 138.031 ms, heap usage 169.677 MB -> 89.065 MB. [2025-11-19T22:52:48.716Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:52:51.566Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:52:54.413Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:52:56.591Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:52:58.216Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:52:59.818Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:53:01.422Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:53:03.043Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:53:03.043Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-19T22:53:03.365Z] The best model improves the baseline by 14.34%. [2025-11-19T22:53:03.365Z] Top recommended movies for user id 72: [2025-11-19T22:53:03.365Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:53:03.365Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:53:03.365Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:53:03.365Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:53:03.365Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:53:03.365Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17394.891 ms) ====== [2025-11-19T22:53:03.365Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-19T22:53:03.365Z] GC before operation: completed in 142.281 ms, heap usage 203.179 MB -> 90.248 MB. [2025-11-19T22:53:06.256Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:53:09.209Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:53:12.122Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:53:14.307Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:53:15.899Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:53:17.486Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:53:19.677Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:53:20.791Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:53:21.105Z] 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. [2025-11-19T22:53:21.105Z] The best model improves the baseline by 14.34%. [2025-11-19T22:53:21.418Z] Top recommended movies for user id 72: [2025-11-19T22:53:21.418Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:53:21.418Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:53:21.418Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:53:21.418Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:53:21.418Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:53:21.418Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17860.761 ms) ====== [2025-11-19T22:53:21.418Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-19T22:53:21.418Z] GC before operation: completed in 141.607 ms, heap usage 170.446 MB -> 88.913 MB. [2025-11-19T22:53:24.280Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:53:27.129Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:53:29.302Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:53:32.158Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:53:33.744Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:53:34.839Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:53:37.025Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:53:38.121Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:53:38.435Z] 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. [2025-11-19T22:53:38.746Z] The best model improves the baseline by 14.34%. [2025-11-19T22:53:38.746Z] Top recommended movies for user id 72: [2025-11-19T22:53:38.746Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:53:38.746Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:53:38.746Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:53:38.746Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:53:38.746Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:53:38.746Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17236.437 ms) ====== [2025-11-19T22:53:38.747Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-19T22:53:38.747Z] GC before operation: completed in 143.636 ms, heap usage 179.391 MB -> 89.106 MB. [2025-11-19T22:53:41.671Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-19T22:53:44.528Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-19T22:53:46.702Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-19T22:53:49.560Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-19T22:53:51.151Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-19T22:53:52.741Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-19T22:53:54.372Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-19T22:53:55.971Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-19T22:53:55.971Z] 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. [2025-11-19T22:53:55.971Z] The best model improves the baseline by 14.34%. [2025-11-19T22:53:56.287Z] Top recommended movies for user id 72: [2025-11-19T22:53:56.287Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-19T22:53:56.287Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-19T22:53:56.287Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-19T22:53:56.287Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-19T22:53:56.287Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-19T22:53:56.287Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17366.226 ms) ====== [2025-11-19T22:53:56.599Z] ----------------------------------- [2025-11-19T22:53:56.599Z] renaissance-movie-lens_0_PASSED [2025-11-19T22:53:56.599Z] ----------------------------------- [2025-11-19T22:53:56.599Z] [2025-11-19T22:53:56.599Z] TEST TEARDOWN: [2025-11-19T22:53:56.599Z] Nothing to be done for teardown. [2025-11-19T22:53:56.599Z] renaissance-movie-lens_0 Finish Time: Wed Nov 19 22:53:56 2025 Epoch Time (ms): 1763592836488