[2025-11-26T23:14:48.647Z] Running test renaissance-movie-lens_0 ... [2025-11-26T23:14:48.647Z] =============================================== [2025-11-26T23:14:48.647Z] renaissance-movie-lens_0 Start Time: Wed Nov 26 23:14:48 2025 Epoch Time (ms): 1764198888324 [2025-11-26T23:14:48.647Z] variation: NoOptions [2025-11-26T23:14:48.647Z] JVM_OPTIONS: [2025-11-26T23:14:48.647Z] { \ [2025-11-26T23:14:48.647Z] echo ""; echo "TEST SETUP:"; \ [2025-11-26T23:14:48.647Z] echo "Nothing to be done for setup."; \ [2025-11-26T23:14:48.647Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17641970042591/renaissance-movie-lens_0"; \ [2025-11-26T23:14:48.647Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17641970042591/renaissance-movie-lens_0"; \ [2025-11-26T23:14:48.647Z] echo ""; echo "TESTING:"; \ [2025-11-26T23:14:48.647Z] "/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_17641970042591/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-26T23:14:48.647Z] 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_17641970042591/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-26T23:14:48.647Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-26T23:14:48.647Z] echo "Nothing to be done for teardown."; \ [2025-11-26T23:14:48.647Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17641970042591/TestTargetResult"; [2025-11-26T23:14:48.647Z] [2025-11-26T23:14:48.647Z] TEST SETUP: [2025-11-26T23:14:48.647Z] Nothing to be done for setup. [2025-11-26T23:14:48.647Z] [2025-11-26T23:14:48.647Z] TESTING: [2025-11-26T23:14:55.197Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-11-26T23:15:01.219Z] 23:15:00.723 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. [2025-11-26T23:15:05.546Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-26T23:15:05.546Z] Training: 60056, validation: 20285, test: 19854 [2025-11-26T23:15:05.546Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-26T23:15:05.546Z] GC before operation: completed in 131.319 ms, heap usage 307.403 MB -> 75.274 MB. [2025-11-26T23:15:12.309Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:15:18.659Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:15:21.644Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:15:25.309Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:15:28.283Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:15:29.940Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:15:32.721Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:15:34.392Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:15:34.786Z] 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. [2025-11-26T23:15:34.786Z] The best model improves the baseline by 14.34%. [2025-11-26T23:15:34.786Z] Top recommended movies for user id 72: [2025-11-26T23:15:34.786Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:15:34.786Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:15:34.786Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:15:34.786Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:15:34.786Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:15:34.786Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29962.181 ms) ====== [2025-11-26T23:15:34.786Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-26T23:15:35.114Z] GC before operation: completed in 129.916 ms, heap usage 358.028 MB -> 96.704 MB. [2025-11-26T23:15:38.074Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:15:41.027Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:15:43.980Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:15:46.237Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:15:47.895Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:15:49.427Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:15:51.082Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:15:52.224Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:15:52.552Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-26T23:15:52.552Z] The best model improves the baseline by 14.34%. [2025-11-26T23:15:52.880Z] Top recommended movies for user id 72: [2025-11-26T23:15:52.880Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:15:52.880Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:15:52.880Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:15:52.880Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:15:52.880Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:15:52.880Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17760.463 ms) ====== [2025-11-26T23:15:52.880Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-26T23:15:52.880Z] GC before operation: completed in 115.598 ms, heap usage 431.514 MB -> 87.852 MB. [2025-11-26T23:15:55.129Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:15:57.377Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:15:59.758Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:16:02.011Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:16:03.666Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:16:04.817Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:16:07.068Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:16:08.309Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:16:08.309Z] 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. [2025-11-26T23:16:08.644Z] The best model improves the baseline by 14.34%. [2025-11-26T23:16:08.644Z] Top recommended movies for user id 72: [2025-11-26T23:16:08.644Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:16:08.644Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:16:08.644Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:16:08.644Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:16:08.644Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:16:08.644Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15633.664 ms) ====== [2025-11-26T23:16:08.644Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-26T23:16:08.644Z] GC before operation: completed in 114.557 ms, heap usage 108.567 MB -> 87.893 MB. [2025-11-26T23:16:10.899Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:16:13.175Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:16:15.434Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:16:17.172Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:16:18.851Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:16:19.997Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:16:21.657Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:16:22.834Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:16:23.162Z] 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. [2025-11-26T23:16:23.162Z] The best model improves the baseline by 14.34%. [2025-11-26T23:16:23.162Z] Top recommended movies for user id 72: [2025-11-26T23:16:23.162Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:16:23.162Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:16:23.162Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:16:23.162Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:16:23.162Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:16:23.162Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14527.634 ms) ====== [2025-11-26T23:16:23.162Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-26T23:16:23.492Z] GC before operation: completed in 124.209 ms, heap usage 296.601 MB -> 88.476 MB. [2025-11-26T23:16:25.744Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:16:27.993Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:16:30.244Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:16:31.900Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:16:33.564Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:16:34.708Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:16:35.973Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:16:37.115Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:16:37.445Z] 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. [2025-11-26T23:16:37.445Z] The best model improves the baseline by 14.34%. [2025-11-26T23:16:37.445Z] Top recommended movies for user id 72: [2025-11-26T23:16:37.445Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:16:37.445Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:16:37.445Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:16:37.445Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:16:37.445Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:16:37.445Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14238.252 ms) ====== [2025-11-26T23:16:37.445Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-26T23:16:37.774Z] GC before operation: completed in 118.528 ms, heap usage 310.748 MB -> 88.552 MB. [2025-11-26T23:16:40.052Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:16:41.714Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:16:43.965Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:16:46.216Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:16:47.359Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:16:48.502Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:16:50.157Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:16:51.306Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:16:51.634Z] 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. [2025-11-26T23:16:51.634Z] The best model improves the baseline by 14.34%. [2025-11-26T23:16:51.634Z] Top recommended movies for user id 72: [2025-11-26T23:16:51.634Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:16:51.634Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:16:51.634Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:16:51.634Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:16:51.634Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:16:51.635Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14022.290 ms) ====== [2025-11-26T23:16:51.635Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-26T23:16:51.962Z] GC before operation: completed in 118.254 ms, heap usage 311.155 MB -> 88.907 MB. [2025-11-26T23:16:54.300Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:16:55.954Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:16:58.209Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:17:00.462Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:17:01.700Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:17:02.926Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:17:04.088Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:17:05.741Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:17:05.741Z] 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. [2025-11-26T23:17:05.741Z] The best model improves the baseline by 14.34%. [2025-11-26T23:17:06.069Z] Top recommended movies for user id 72: [2025-11-26T23:17:06.069Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:17:06.069Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:17:06.069Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:17:06.069Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:17:06.069Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:17:06.069Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14070.734 ms) ====== [2025-11-26T23:17:06.069Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-26T23:17:06.069Z] GC before operation: completed in 117.255 ms, heap usage 312.012 MB -> 88.786 MB. [2025-11-26T23:17:08.326Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:17:10.628Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:17:12.284Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:17:14.537Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:17:15.775Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:17:16.946Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:17:18.092Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:17:19.233Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:17:19.566Z] 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. [2025-11-26T23:17:19.566Z] The best model improves the baseline by 14.34%. [2025-11-26T23:17:19.896Z] Top recommended movies for user id 72: [2025-11-26T23:17:19.896Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:17:19.896Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:17:19.896Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:17:19.896Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:17:19.897Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:17:19.897Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13708.075 ms) ====== [2025-11-26T23:17:19.897Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-26T23:17:19.897Z] GC before operation: completed in 133.510 ms, heap usage 184.807 MB -> 88.839 MB. [2025-11-26T23:17:22.157Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:17:23.810Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:17:26.106Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:17:28.358Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:17:29.509Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:17:30.652Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:17:32.309Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:17:33.458Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:17:33.458Z] 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. [2025-11-26T23:17:33.458Z] The best model improves the baseline by 14.34%. [2025-11-26T23:17:33.790Z] Top recommended movies for user id 72: [2025-11-26T23:17:33.790Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:17:33.790Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:17:33.790Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:17:33.790Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:17:33.790Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:17:33.790Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13835.189 ms) ====== [2025-11-26T23:17:33.790Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-26T23:17:33.790Z] GC before operation: completed in 120.199 ms, heap usage 643.575 MB -> 92.611 MB. [2025-11-26T23:17:36.039Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:17:37.695Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:17:39.947Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:17:41.606Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:17:42.978Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:17:44.128Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:17:45.781Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:17:46.932Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:17:46.932Z] 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. [2025-11-26T23:17:46.932Z] The best model improves the baseline by 14.34%. [2025-11-26T23:17:47.259Z] Top recommended movies for user id 72: [2025-11-26T23:17:47.259Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:17:47.259Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:17:47.259Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:17:47.259Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:17:47.259Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:17:47.259Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13386.496 ms) ====== [2025-11-26T23:17:47.259Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-26T23:17:47.259Z] GC before operation: completed in 112.678 ms, heap usage 228.635 MB -> 88.898 MB. [2025-11-26T23:17:49.510Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:17:51.163Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:17:53.415Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:17:55.068Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:17:56.212Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:17:57.358Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:17:59.010Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:18:00.155Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:18:00.155Z] 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. [2025-11-26T23:18:00.155Z] The best model improves the baseline by 14.34%. [2025-11-26T23:18:00.483Z] Top recommended movies for user id 72: [2025-11-26T23:18:00.483Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:18:00.483Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:18:00.483Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:18:00.483Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:18:00.483Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:18:00.483Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13088.387 ms) ====== [2025-11-26T23:18:00.483Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-26T23:18:00.483Z] GC before operation: completed in 115.508 ms, heap usage 280.903 MB -> 88.756 MB. [2025-11-26T23:18:02.746Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:18:04.490Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:18:06.804Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:18:08.472Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:18:09.616Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:18:10.760Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:18:11.906Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:18:13.052Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:18:13.380Z] 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. [2025-11-26T23:18:13.380Z] The best model improves the baseline by 14.34%. [2025-11-26T23:18:13.708Z] Top recommended movies for user id 72: [2025-11-26T23:18:13.708Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:18:13.708Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:18:13.708Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:18:13.708Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:18:13.708Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:18:13.708Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13032.802 ms) ====== [2025-11-26T23:18:13.708Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-26T23:18:13.708Z] GC before operation: completed in 115.039 ms, heap usage 305.454 MB -> 88.941 MB. [2025-11-26T23:18:15.972Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:18:17.626Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:18:19.880Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:18:21.533Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:18:22.746Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:18:23.896Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:18:25.560Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:18:26.724Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:18:26.724Z] 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. [2025-11-26T23:18:26.724Z] The best model improves the baseline by 14.34%. [2025-11-26T23:18:26.724Z] Top recommended movies for user id 72: [2025-11-26T23:18:26.724Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:18:26.724Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:18:26.724Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:18:26.724Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:18:26.724Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:18:26.724Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13166.629 ms) ====== [2025-11-26T23:18:26.724Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-26T23:18:27.096Z] GC before operation: completed in 119.687 ms, heap usage 310.650 MB -> 89.170 MB. [2025-11-26T23:18:29.415Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:18:31.069Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:18:33.340Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:18:34.995Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:18:36.141Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:18:37.794Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:18:38.935Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:18:40.078Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:18:40.078Z] 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. [2025-11-26T23:18:40.078Z] The best model improves the baseline by 14.34%. [2025-11-26T23:18:40.078Z] Top recommended movies for user id 72: [2025-11-26T23:18:40.078Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:18:40.078Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:18:40.078Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:18:40.078Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:18:40.078Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:18:40.078Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13266.694 ms) ====== [2025-11-26T23:18:40.078Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-26T23:18:40.407Z] GC before operation: completed in 117.280 ms, heap usage 311.174 MB -> 89.024 MB. [2025-11-26T23:18:42.135Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:18:44.385Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:18:46.661Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:18:47.961Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:18:49.374Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:18:50.550Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:18:51.723Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:18:52.887Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:18:53.223Z] 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. [2025-11-26T23:18:53.223Z] The best model improves the baseline by 14.34%. [2025-11-26T23:18:53.223Z] Top recommended movies for user id 72: [2025-11-26T23:18:53.223Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:18:53.223Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:18:53.223Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:18:53.223Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:18:53.223Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:18:53.223Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12842.744 ms) ====== [2025-11-26T23:18:53.223Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-26T23:18:53.223Z] GC before operation: completed in 119.685 ms, heap usage 311.078 MB -> 89.243 MB. [2025-11-26T23:18:55.517Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:18:57.196Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:18:59.446Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:19:01.119Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:19:02.346Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:19:03.489Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:19:05.223Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:19:06.366Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:19:06.366Z] 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. [2025-11-26T23:19:06.366Z] The best model improves the baseline by 14.34%. [2025-11-26T23:19:06.693Z] Top recommended movies for user id 72: [2025-11-26T23:19:06.693Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:19:06.693Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:19:06.693Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:19:06.693Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:19:06.693Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:19:06.693Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13285.735 ms) ====== [2025-11-26T23:19:06.693Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-26T23:19:06.693Z] GC before operation: completed in 117.544 ms, heap usage 306.317 MB -> 88.964 MB. [2025-11-26T23:19:08.937Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:19:10.596Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:19:12.851Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:19:14.512Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:19:15.659Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:19:16.803Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:19:17.950Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:19:19.091Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:19:19.418Z] 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. [2025-11-26T23:19:19.418Z] The best model improves the baseline by 14.34%. [2025-11-26T23:19:19.418Z] Top recommended movies for user id 72: [2025-11-26T23:19:19.418Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:19:19.418Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:19:19.418Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:19:19.418Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:19:19.418Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:19:19.418Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12760.907 ms) ====== [2025-11-26T23:19:19.418Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-26T23:19:19.747Z] GC before operation: completed in 115.667 ms, heap usage 304.559 MB -> 89.139 MB. [2025-11-26T23:19:21.398Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:19:23.673Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:19:25.992Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:19:27.641Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:19:28.792Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:19:29.939Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:19:31.086Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:19:32.243Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:19:32.574Z] 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. [2025-11-26T23:19:32.574Z] The best model improves the baseline by 14.34%. [2025-11-26T23:19:32.574Z] Top recommended movies for user id 72: [2025-11-26T23:19:32.574Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:19:32.574Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:19:32.574Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:19:32.574Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:19:32.574Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:19:32.574Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13018.838 ms) ====== [2025-11-26T23:19:32.574Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-26T23:19:32.574Z] GC before operation: completed in 115.326 ms, heap usage 306.156 MB -> 88.959 MB. [2025-11-26T23:19:34.824Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:19:36.475Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:19:38.729Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:19:40.387Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:19:41.528Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:19:42.672Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:19:43.894Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:19:45.081Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:19:45.409Z] 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. [2025-11-26T23:19:45.409Z] The best model improves the baseline by 14.34%. [2025-11-26T23:19:45.409Z] Top recommended movies for user id 72: [2025-11-26T23:19:45.409Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:19:45.409Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:19:45.409Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:19:45.409Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:19:45.409Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:19:45.409Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12729.920 ms) ====== [2025-11-26T23:19:45.409Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-26T23:19:45.737Z] GC before operation: completed in 116.008 ms, heap usage 306.048 MB -> 89.035 MB. [2025-11-26T23:19:47.390Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:19:49.635Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:19:51.285Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:19:53.532Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:19:54.237Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:19:55.387Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:19:57.036Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:19:58.177Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:19:58.178Z] 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. [2025-11-26T23:19:58.178Z] The best model improves the baseline by 14.34%. [2025-11-26T23:19:58.178Z] Top recommended movies for user id 72: [2025-11-26T23:19:58.178Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-26T23:19:58.178Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-26T23:19:58.178Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-26T23:19:58.178Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-26T23:19:58.178Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-26T23:19:58.178Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12761.045 ms) ====== [2025-11-26T23:19:58.884Z] ----------------------------------- [2025-11-26T23:19:58.884Z] renaissance-movie-lens_0_PASSED [2025-11-26T23:19:58.884Z] ----------------------------------- [2025-11-26T23:19:58.884Z] [2025-11-26T23:19:58.884Z] TEST TEARDOWN: [2025-11-26T23:19:58.884Z] Nothing to be done for teardown. [2025-11-26T23:19:58.884Z] renaissance-movie-lens_0 Finish Time: Wed Nov 26 23:19:58 2025 Epoch Time (ms): 1764199198665