[2025-11-06T02:39:20.352Z] Running test renaissance-movie-lens_0 ... [2025-11-06T02:39:20.352Z] =============================================== [2025-11-06T02:39:20.352Z] renaissance-movie-lens_0 Start Time: Thu Nov 6 02:39:19 2025 Epoch Time (ms): 1762396759394 [2025-11-06T02:39:20.352Z] variation: NoOptions [2025-11-06T02:39:20.352Z] JVM_OPTIONS: [2025-11-06T02:39:20.352Z] { \ [2025-11-06T02:39:20.352Z] echo ""; echo "TEST SETUP:"; \ [2025-11-06T02:39:20.352Z] echo "Nothing to be done for setup."; \ [2025-11-06T02:39:20.352Z] mkdir -p "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17623950765061/renaissance-movie-lens_0"; \ [2025-11-06T02:39:20.352Z] cd "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17623950765061/renaissance-movie-lens_0"; \ [2025-11-06T02:39:20.352Z] echo ""; echo "TESTING:"; \ [2025-11-06T02:39:20.352Z] "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/jdkbinary/j2sdk-image/Contents/Home/bin/..//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 "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17623950765061/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-06T02:39:20.352Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/..; rm -f -r "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17623950765061/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-06T02:39:20.352Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-06T02:39:20.352Z] echo "Nothing to be done for teardown."; \ [2025-11-06T02:39:20.352Z] } 2>&1 | tee -a "/Users/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17623950765061/TestTargetResult"; [2025-11-06T02:39:20.352Z] [2025-11-06T02:39:20.352Z] TEST SETUP: [2025-11-06T02:39:20.352Z] Nothing to be done for setup. [2025-11-06T02:39:20.352Z] [2025-11-06T02:39:20.352Z] TESTING: [2025-11-06T02:39:26.473Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads. [2025-11-06T02:39:37.707Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-06T02:39:38.082Z] Training: 60056, validation: 20285, test: 19854 [2025-11-06T02:39:38.082Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-06T02:39:38.082Z] GC before operation: completed in 123.247 ms, heap usage 510.038 MB -> 75.149 MB. [2025-11-06T02:40:06.284Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:40:25.793Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:40:49.245Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:41:05.508Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:41:16.639Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:41:25.826Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:41:39.304Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:41:48.572Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:41:48.572Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T02:41:48.572Z] The best model improves the baseline by 14.43%. [2025-11-06T02:41:48.959Z] Top recommended movies for user id 72: [2025-11-06T02:41:48.959Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T02:41:48.959Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T02:41:48.959Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T02:41:48.959Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T02:41:48.959Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T02:41:48.959Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (130793.855 ms) ====== [2025-11-06T02:41:48.959Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-06T02:41:49.323Z] GC before operation: completed in 183.322 ms, heap usage 862.285 MB -> 90.942 MB. [2025-11-06T02:42:08.868Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:42:28.385Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:42:51.841Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:43:08.062Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:43:19.177Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:43:28.340Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:43:41.774Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:43:49.293Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:43:49.293Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T02:43:49.293Z] The best model improves the baseline by 14.43%. [2025-11-06T02:43:49.645Z] Top recommended movies for user id 72: [2025-11-06T02:43:49.645Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T02:43:49.645Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T02:43:49.645Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T02:43:49.645Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T02:43:49.645Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T02:43:49.645Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (120464.586 ms) ====== [2025-11-06T02:43:49.645Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-06T02:43:49.999Z] GC before operation: completed in 279.487 ms, heap usage 855.067 MB -> 109.361 MB. [2025-11-06T02:44:09.615Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:44:29.183Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:44:52.650Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:45:12.222Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:45:21.389Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:45:30.560Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:45:44.021Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:45:53.294Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:45:53.294Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T02:45:53.294Z] The best model improves the baseline by 14.43%. [2025-11-06T02:45:53.294Z] Top recommended movies for user id 72: [2025-11-06T02:45:53.294Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T02:45:53.294Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T02:45:53.294Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T02:45:53.294Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T02:45:53.294Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T02:45:53.294Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (122745.441 ms) ====== [2025-11-06T02:45:53.294Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-06T02:45:53.294Z] GC before operation: completed in 188.201 ms, heap usage 158.764 MB -> 95.946 MB. [2025-11-06T02:46:12.850Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:46:36.329Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:46:55.849Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:47:15.405Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:47:24.593Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:47:33.880Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:47:47.318Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:47:56.492Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:47:56.492Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T02:47:56.492Z] The best model improves the baseline by 14.43%. [2025-11-06T02:47:56.492Z] Top recommended movies for user id 72: [2025-11-06T02:47:56.492Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T02:47:56.492Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T02:47:56.492Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T02:47:56.492Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T02:47:56.492Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T02:47:56.492Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (123354.293 ms) ====== [2025-11-06T02:47:56.492Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-06T02:47:56.492Z] GC before operation: completed in 175.113 ms, heap usage 256.188 MB -> 93.889 MB. [2025-11-06T02:48:16.128Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:48:39.606Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:49:03.072Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:49:19.292Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:49:28.457Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:49:37.617Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:49:51.074Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:50:00.247Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:50:00.247Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T02:50:00.247Z] The best model improves the baseline by 14.43%. [2025-11-06T02:50:00.247Z] Top recommended movies for user id 72: [2025-11-06T02:50:00.247Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T02:50:00.247Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T02:50:00.247Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T02:50:00.247Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T02:50:00.247Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T02:50:00.247Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (123679.256 ms) ====== [2025-11-06T02:50:00.247Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-06T02:50:00.247Z] GC before operation: completed in 190.956 ms, heap usage 756.903 MB -> 95.377 MB. [2025-11-06T02:50:23.700Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:50:43.206Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:51:06.657Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:51:22.900Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:51:32.055Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:51:41.212Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:51:54.683Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:52:03.845Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:52:03.845Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T02:52:03.845Z] The best model improves the baseline by 14.43%. [2025-11-06T02:52:03.845Z] Top recommended movies for user id 72: [2025-11-06T02:52:03.845Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T02:52:03.845Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T02:52:03.845Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T02:52:03.845Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T02:52:03.845Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T02:52:03.845Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (123276.958 ms) ====== [2025-11-06T02:52:03.845Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-06T02:52:03.845Z] GC before operation: completed in 190.058 ms, heap usage 472.369 MB -> 96.685 MB. [2025-11-06T02:52:27.292Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:52:43.510Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:53:06.968Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:53:26.505Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:53:35.671Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:53:44.836Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:53:58.293Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:54:05.815Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:54:06.586Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T02:54:06.586Z] The best model improves the baseline by 14.43%. [2025-11-06T02:54:06.586Z] Top recommended movies for user id 72: [2025-11-06T02:54:06.586Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T02:54:06.586Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T02:54:06.586Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T02:54:06.586Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T02:54:06.586Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T02:54:06.586Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (122858.186 ms) ====== [2025-11-06T02:54:06.586Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-06T02:54:06.941Z] GC before operation: completed in 212.751 ms, heap usage 765.489 MB -> 94.474 MB. [2025-11-06T02:54:26.474Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:54:49.943Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:55:09.496Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:55:29.027Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:55:38.214Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:55:47.386Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:56:00.837Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:56:10.010Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:56:10.010Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T02:56:10.010Z] The best model improves the baseline by 14.43%. [2025-11-06T02:56:10.010Z] Top recommended movies for user id 72: [2025-11-06T02:56:10.010Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T02:56:10.010Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T02:56:10.010Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T02:56:10.010Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T02:56:10.010Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T02:56:10.010Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (122502.144 ms) ====== [2025-11-06T02:56:10.010Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-06T02:56:10.010Z] GC before operation: completed in 184.127 ms, heap usage 429.091 MB -> 96.720 MB. [2025-11-06T02:56:29.559Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:56:49.089Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:57:12.560Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:57:32.085Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:57:41.247Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:57:50.405Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T02:58:03.844Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T02:58:13.005Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T02:58:13.005Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T02:58:13.005Z] The best model improves the baseline by 14.43%. [2025-11-06T02:58:13.005Z] Top recommended movies for user id 72: [2025-11-06T02:58:13.005Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T02:58:13.005Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T02:58:13.005Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T02:58:13.005Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T02:58:13.005Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T02:58:13.005Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (123365.519 ms) ====== [2025-11-06T02:58:13.005Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-06T02:58:13.005Z] GC before operation: completed in 176.980 ms, heap usage 350.654 MB -> 94.189 MB. [2025-11-06T02:58:36.461Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T02:58:55.981Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T02:59:19.489Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T02:59:35.707Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T02:59:46.818Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T02:59:54.329Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:00:07.785Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:00:16.945Z] RMSE (validation) = 0.9001440981626696 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:00:16.945Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:00:16.945Z] The best model improves the baseline by 14.43%. [2025-11-06T03:00:17.299Z] Top recommended movies for user id 72: [2025-11-06T03:00:17.300Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:00:17.300Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:00:17.300Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:00:17.300Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:00:17.300Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:00:17.300Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (124214.572 ms) ====== [2025-11-06T03:00:17.300Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-06T03:00:17.300Z] GC before operation: completed in 177.592 ms, heap usage 315.267 MB -> 94.409 MB. [2025-11-06T03:00:40.851Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:01:00.370Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:01:23.860Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:01:40.072Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:01:49.234Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:01:58.393Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:02:11.850Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:02:21.035Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:02:21.035Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:02:21.035Z] The best model improves the baseline by 14.43%. [2025-11-06T03:02:21.035Z] Top recommended movies for user id 72: [2025-11-06T03:02:21.035Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:02:21.035Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:02:21.035Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:02:21.035Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:02:21.035Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:02:21.035Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (123584.512 ms) ====== [2025-11-06T03:02:21.035Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-06T03:02:21.387Z] GC before operation: completed in 179.298 ms, heap usage 337.204 MB -> 94.096 MB. [2025-11-06T03:02:44.866Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:03:01.103Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:03:24.573Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:03:44.158Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:03:53.337Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:04:02.539Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:04:16.043Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:04:23.581Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:04:24.334Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:04:24.334Z] The best model improves the baseline by 14.43%. [2025-11-06T03:04:24.334Z] Top recommended movies for user id 72: [2025-11-06T03:04:24.334Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:04:24.334Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:04:24.334Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:04:24.334Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:04:24.334Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:04:24.334Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (123160.655 ms) ====== [2025-11-06T03:04:24.334Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-06T03:04:24.687Z] GC before operation: completed in 267.408 ms, heap usage 1.133 GB -> 97.088 MB. [2025-11-06T03:04:44.242Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:05:07.707Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:05:31.207Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:05:44.652Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:05:55.776Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:06:04.957Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:06:18.392Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:06:27.587Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:06:27.587Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:06:27.587Z] The best model improves the baseline by 14.43%. [2025-11-06T03:06:27.587Z] Top recommended movies for user id 72: [2025-11-06T03:06:27.587Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:06:27.587Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:06:27.587Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:06:27.587Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:06:27.587Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:06:27.587Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (122873.042 ms) ====== [2025-11-06T03:06:27.587Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-06T03:06:27.587Z] GC before operation: completed in 188.871 ms, heap usage 768.907 MB -> 97.190 MB. [2025-11-06T03:06:47.128Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:07:10.603Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:07:34.078Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:07:50.304Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:07:59.480Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:08:08.677Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:08:22.131Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:08:33.262Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:08:33.262Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:08:33.262Z] The best model improves the baseline by 14.43%. [2025-11-06T03:08:33.262Z] Top recommended movies for user id 72: [2025-11-06T03:08:33.262Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:08:33.262Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:08:33.262Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:08:33.262Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:08:33.262Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:08:33.262Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (125433.277 ms) ====== [2025-11-06T03:08:33.262Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-06T03:08:33.262Z] GC before operation: completed in 189.673 ms, heap usage 856.806 MB -> 96.995 MB. [2025-11-06T03:09:06.895Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:09:26.432Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:09:54.774Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:10:14.302Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:10:23.495Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:10:34.623Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:10:48.105Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:11:07.446Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:11:07.447Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:11:07.447Z] The best model improves the baseline by 14.43%. [2025-11-06T03:11:07.447Z] Top recommended movies for user id 72: [2025-11-06T03:11:07.447Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:11:07.447Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:11:07.447Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:11:07.447Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:11:07.447Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:11:07.447Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (154097.250 ms) ====== [2025-11-06T03:11:07.447Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-06T03:11:07.447Z] GC before operation: completed in 182.409 ms, heap usage 196.225 MB -> 94.505 MB. [2025-11-06T03:11:45.715Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:12:05.234Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:12:33.405Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:12:46.873Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:13:00.320Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:13:09.484Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:13:26.172Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:13:35.494Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:13:35.494Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:13:35.494Z] The best model improves the baseline by 14.43%. [2025-11-06T03:13:35.494Z] Top recommended movies for user id 72: [2025-11-06T03:13:35.494Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:13:35.494Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:13:35.494Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:13:35.494Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:13:35.494Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:13:35.494Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (148051.155 ms) ====== [2025-11-06T03:13:35.494Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-06T03:13:35.847Z] GC before operation: completed in 202.686 ms, heap usage 166.222 MB -> 94.364 MB. [2025-11-06T03:13:59.318Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:14:22.781Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:14:46.257Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:15:02.475Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:15:11.650Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:15:20.816Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:15:37.026Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:15:46.186Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:15:46.186Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:15:46.186Z] The best model improves the baseline by 14.43%. [2025-11-06T03:15:46.186Z] Top recommended movies for user id 72: [2025-11-06T03:15:46.186Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:15:46.186Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:15:46.186Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:15:46.186Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:15:46.186Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:15:46.186Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (130160.935 ms) ====== [2025-11-06T03:15:46.186Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-06T03:15:46.186Z] GC before operation: completed in 202.086 ms, heap usage 202.416 MB -> 94.434 MB. [2025-11-06T03:16:18.362Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:16:37.924Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:17:06.080Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:17:22.293Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:17:33.500Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:17:42.677Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:17:56.230Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:18:03.810Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:18:03.810Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:18:03.810Z] The best model improves the baseline by 14.43%. [2025-11-06T03:18:04.162Z] Top recommended movies for user id 72: [2025-11-06T03:18:04.162Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:18:04.162Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:18:04.162Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:18:04.162Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:18:04.162Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:18:04.162Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (137890.757 ms) ====== [2025-11-06T03:18:04.162Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-06T03:18:04.162Z] GC before operation: completed in 196.205 ms, heap usage 774.281 MB -> 94.583 MB. [2025-11-06T03:18:27.679Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:18:47.225Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:19:10.839Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:19:27.066Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:19:38.199Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:19:49.313Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:20:08.801Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:20:18.000Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:20:18.353Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:20:18.353Z] The best model improves the baseline by 14.43%. [2025-11-06T03:20:18.353Z] Top recommended movies for user id 72: [2025-11-06T03:20:18.353Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:20:18.353Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:20:18.353Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:20:18.353Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:20:18.353Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:20:18.353Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (134188.858 ms) ====== [2025-11-06T03:20:18.353Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-06T03:20:18.706Z] GC before operation: completed in 200.421 ms, heap usage 900.755 MB -> 94.729 MB. [2025-11-06T03:20:42.210Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T03:21:06.737Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T03:21:46.119Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T03:22:05.643Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T03:22:14.821Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T03:22:25.965Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T03:22:39.415Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T03:22:46.941Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T03:22:46.941Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535. [2025-11-06T03:22:46.941Z] The best model improves the baseline by 14.43%. [2025-11-06T03:22:46.941Z] Top recommended movies for user id 72: [2025-11-06T03:22:46.941Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504) [2025-11-06T03:22:46.941Z] 2: Goat, The (1921) (rating: 4.674, id: 83318) [2025-11-06T03:22:46.941Z] 3: Play House, The (1921) (rating: 4.674, id: 83359) [2025-11-06T03:22:46.941Z] 4: Cops (1922) (rating: 4.674, id: 83411) [2025-11-06T03:22:46.941Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530) [2025-11-06T03:22:46.941Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (148241.881 ms) ====== [2025-11-06T03:22:48.164Z] ----------------------------------- [2025-11-06T03:22:48.164Z] renaissance-movie-lens_0_PASSED [2025-11-06T03:22:48.164Z] ----------------------------------- [2025-11-06T03:22:48.164Z] [2025-11-06T03:22:48.164Z] TEST TEARDOWN: [2025-11-06T03:22:48.164Z] Nothing to be done for teardown. [2025-11-06T03:22:48.164Z] renaissance-movie-lens_0 Finish Time: Thu Nov 6 03:22:47 2025 Epoch Time (ms): 1762399367819