[2025-11-27T02:15:42.866Z] Running test renaissance-movie-lens_0 ... [2025-11-27T02:15:42.866Z] =============================================== [2025-11-27T02:15:42.866Z] renaissance-movie-lens_0 Start Time: Thu Nov 27 02:15:42 2025 Epoch Time (ms): 1764209742180 [2025-11-27T02:15:42.866Z] variation: NoOptions [2025-11-27T02:15:42.866Z] JVM_OPTIONS: [2025-11-27T02:15:42.866Z] { \ [2025-11-27T02:15:42.866Z] echo ""; echo "TEST SETUP:"; \ [2025-11-27T02:15:42.866Z] echo "Nothing to be done for setup."; \ [2025-11-27T02:15:42.866Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17642080018362/renaissance-movie-lens_0"; \ [2025-11-27T02:15:42.866Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17642080018362/renaissance-movie-lens_0"; \ [2025-11-27T02:15:42.866Z] echo ""; echo "TESTING:"; \ [2025-11-27T02:15:42.866Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_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_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17642080018362/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-27T02:15:42.866Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17642080018362/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-27T02:15:42.866Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-27T02:15:42.866Z] echo "Nothing to be done for teardown."; \ [2025-11-27T02:15:42.866Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17642080018362/TestTargetResult"; [2025-11-27T02:15:42.866Z] [2025-11-27T02:15:42.866Z] TEST SETUP: [2025-11-27T02:15:42.866Z] Nothing to be done for setup. [2025-11-27T02:15:42.866Z] [2025-11-27T02:15:42.866Z] TESTING: [2025-11-27T02:15:48.228Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-27T02:15:54.903Z] 02:15:54.002 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-11-27T02:15:56.851Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-27T02:15:56.851Z] Training: 60056, validation: 20285, test: 19854 [2025-11-27T02:15:56.851Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-27T02:15:57.800Z] GC before operation: completed in 156.250 ms, heap usage 178.642 MB -> 75.727 MB. [2025-11-27T02:16:04.515Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:16:07.526Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:16:12.380Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:16:15.390Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:16:16.338Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:16:18.286Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:16:20.258Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:16:22.213Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:16:22.213Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:16:22.213Z] The best model improves the baseline by 14.52%. [2025-11-27T02:16:22.213Z] Top recommended movies for user id 72: [2025-11-27T02:16:22.213Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:16:22.213Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:16:22.213Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:16:22.213Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:16:22.213Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:16:22.213Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25144.296 ms) ====== [2025-11-27T02:16:22.213Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-27T02:16:23.164Z] GC before operation: completed in 145.712 ms, heap usage 741.480 MB -> 97.689 MB. [2025-11-27T02:16:26.175Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:16:28.122Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:16:31.163Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:16:33.116Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:16:35.070Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:16:37.019Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:16:38.965Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:16:39.914Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:16:39.914Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:16:39.914Z] The best model improves the baseline by 14.52%. [2025-11-27T02:16:40.863Z] Top recommended movies for user id 72: [2025-11-27T02:16:40.863Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:16:40.863Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:16:40.863Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:16:40.863Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:16:40.863Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:16:40.863Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17790.114 ms) ====== [2025-11-27T02:16:40.863Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-27T02:16:40.863Z] GC before operation: completed in 160.290 ms, heap usage 729.450 MB -> 92.512 MB. [2025-11-27T02:16:43.874Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:16:45.996Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:16:49.004Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:16:52.009Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:16:52.959Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:16:54.908Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:16:56.854Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:16:57.803Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:16:58.753Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:16:58.753Z] The best model improves the baseline by 14.52%. [2025-11-27T02:16:58.753Z] Top recommended movies for user id 72: [2025-11-27T02:16:58.753Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:16:58.753Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:16:58.753Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:16:58.753Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:16:58.753Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:16:58.753Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18057.766 ms) ====== [2025-11-27T02:16:58.753Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-27T02:16:58.753Z] GC before operation: completed in 135.464 ms, heap usage 444.187 MB -> 89.769 MB. [2025-11-27T02:17:01.769Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:17:05.224Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:17:08.246Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:17:10.195Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:17:12.154Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:17:13.105Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:17:15.066Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:17:17.014Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:17:17.014Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:17:17.014Z] The best model improves the baseline by 14.52%. [2025-11-27T02:17:17.014Z] Top recommended movies for user id 72: [2025-11-27T02:17:17.014Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:17:17.014Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:17:17.014Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:17:17.014Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:17:17.014Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:17:17.014Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (18292.244 ms) ====== [2025-11-27T02:17:17.014Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-27T02:17:17.014Z] GC before operation: completed in 148.105 ms, heap usage 214.422 MB -> 95.251 MB. [2025-11-27T02:17:20.073Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:17:22.021Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:17:25.030Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:17:26.978Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:17:28.935Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:17:30.887Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:17:31.835Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:17:33.789Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:17:33.789Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:17:33.789Z] The best model improves the baseline by 14.52%. [2025-11-27T02:17:33.789Z] Top recommended movies for user id 72: [2025-11-27T02:17:33.789Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:17:33.789Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:17:33.789Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:17:33.789Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:17:33.789Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:17:33.789Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16603.771 ms) ====== [2025-11-27T02:17:33.789Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-27T02:17:33.789Z] GC before operation: completed in 139.201 ms, heap usage 721.194 MB -> 93.456 MB. [2025-11-27T02:17:36.797Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:17:38.741Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:17:41.751Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:17:43.706Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:17:45.653Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:17:46.600Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:17:48.546Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:17:49.496Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:17:49.496Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:17:49.496Z] The best model improves the baseline by 14.52%. [2025-11-27T02:17:50.446Z] Top recommended movies for user id 72: [2025-11-27T02:17:50.446Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:17:50.446Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:17:50.446Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:17:50.446Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:17:50.446Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:17:50.446Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16088.953 ms) ====== [2025-11-27T02:17:50.446Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-27T02:17:50.446Z] GC before operation: completed in 140.775 ms, heap usage 140.424 MB -> 94.249 MB. [2025-11-27T02:17:52.392Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:17:54.342Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:17:57.366Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:18:00.017Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:18:00.966Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:18:01.917Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:18:03.872Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:18:04.821Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:18:05.771Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:18:05.771Z] The best model improves the baseline by 14.52%. [2025-11-27T02:18:05.771Z] Top recommended movies for user id 72: [2025-11-27T02:18:05.771Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:18:05.771Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:18:05.771Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:18:05.771Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:18:05.771Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:18:05.771Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15438.130 ms) ====== [2025-11-27T02:18:05.771Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-27T02:18:05.771Z] GC before operation: completed in 133.386 ms, heap usage 499.697 MB -> 93.444 MB. [2025-11-27T02:18:08.793Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:18:11.801Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:18:13.748Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:18:15.694Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:18:17.640Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:18:18.669Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:18:20.622Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:18:21.570Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:18:21.570Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:18:21.570Z] The best model improves the baseline by 14.52%. [2025-11-27T02:18:22.534Z] Top recommended movies for user id 72: [2025-11-27T02:18:22.534Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:18:22.534Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:18:22.534Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:18:22.534Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:18:22.534Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:18:22.534Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16288.855 ms) ====== [2025-11-27T02:18:22.534Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-27T02:18:22.534Z] GC before operation: completed in 136.836 ms, heap usage 731.923 MB -> 98.718 MB. [2025-11-27T02:18:24.483Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:18:26.433Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:18:29.454Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:18:31.406Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:18:33.354Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:18:34.325Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:18:36.284Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:18:37.233Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:18:37.233Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:18:37.233Z] The best model improves the baseline by 14.52%. [2025-11-27T02:18:38.183Z] Top recommended movies for user id 72: [2025-11-27T02:18:38.183Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:18:38.183Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:18:38.183Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:18:38.183Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:18:38.183Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:18:38.183Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15515.498 ms) ====== [2025-11-27T02:18:38.183Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-27T02:18:38.183Z] GC before operation: completed in 132.503 ms, heap usage 212.030 MB -> 91.092 MB. [2025-11-27T02:18:41.226Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:18:43.179Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:18:46.183Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:18:48.132Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:18:50.098Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:18:51.047Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:18:53.872Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:18:53.872Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:18:53.872Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:18:53.872Z] The best model improves the baseline by 14.52%. [2025-11-27T02:18:53.872Z] Top recommended movies for user id 72: [2025-11-27T02:18:53.872Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:18:53.872Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:18:53.872Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:18:53.872Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:18:53.872Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:18:53.872Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16397.257 ms) ====== [2025-11-27T02:18:53.872Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-27T02:18:54.822Z] GC before operation: completed in 137.927 ms, heap usage 495.787 MB -> 93.863 MB. [2025-11-27T02:18:56.779Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:18:58.736Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:19:01.774Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:19:03.734Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:19:04.695Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:19:06.657Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:19:07.609Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:19:09.588Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:19:09.588Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:19:09.588Z] The best model improves the baseline by 14.52%. [2025-11-27T02:19:09.588Z] Top recommended movies for user id 72: [2025-11-27T02:19:09.588Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:19:09.588Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:19:09.588Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:19:09.588Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:19:09.588Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:19:09.588Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15376.925 ms) ====== [2025-11-27T02:19:09.588Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-27T02:19:09.588Z] GC before operation: completed in 139.848 ms, heap usage 202.925 MB -> 95.477 MB. [2025-11-27T02:19:12.608Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:19:14.569Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:19:16.527Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:19:18.492Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:19:20.465Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:19:21.423Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:19:23.379Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:19:24.331Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:19:24.331Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:19:25.292Z] The best model improves the baseline by 14.52%. [2025-11-27T02:19:25.292Z] Top recommended movies for user id 72: [2025-11-27T02:19:25.292Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:19:25.292Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:19:25.292Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:19:25.292Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:19:25.292Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:19:25.292Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14988.412 ms) ====== [2025-11-27T02:19:25.292Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-27T02:19:25.292Z] GC before operation: completed in 138.920 ms, heap usage 682.321 MB -> 96.441 MB. [2025-11-27T02:19:27.249Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:19:30.267Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:19:32.225Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:19:34.180Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:19:35.131Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:19:37.096Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:19:38.050Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:19:40.017Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:19:40.017Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:19:40.017Z] The best model improves the baseline by 14.52%. [2025-11-27T02:19:40.017Z] Top recommended movies for user id 72: [2025-11-27T02:19:40.017Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:19:40.017Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:19:40.017Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:19:40.017Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:19:40.017Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:19:40.017Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15140.180 ms) ====== [2025-11-27T02:19:40.017Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-27T02:19:40.017Z] GC before operation: completed in 130.606 ms, heap usage 232.156 MB -> 90.110 MB. [2025-11-27T02:19:43.044Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:19:45.002Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:19:47.900Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:19:48.854Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:19:50.820Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:19:51.773Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:19:56.530Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:19:56.531Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:19:56.531Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:19:56.531Z] The best model improves the baseline by 14.52%. [2025-11-27T02:19:56.531Z] Top recommended movies for user id 72: [2025-11-27T02:19:56.531Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:19:56.531Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:19:56.531Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:19:56.531Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:19:56.531Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:19:56.531Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14849.044 ms) ====== [2025-11-27T02:19:56.531Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-27T02:19:56.531Z] GC before operation: completed in 192.674 ms, heap usage 722.895 MB -> 93.903 MB. [2025-11-27T02:19:57.483Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:19:59.442Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:20:02.463Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:20:04.452Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:20:05.407Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:20:07.366Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:20:08.320Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:20:09.292Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:20:10.245Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:20:10.245Z] The best model improves the baseline by 14.52%. [2025-11-27T02:20:10.245Z] Top recommended movies for user id 72: [2025-11-27T02:20:10.245Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:20:10.245Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:20:10.245Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:20:10.245Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:20:10.245Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:20:10.245Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14754.140 ms) ====== [2025-11-27T02:20:10.245Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-27T02:20:10.245Z] GC before operation: completed in 136.801 ms, heap usage 249.479 MB -> 91.967 MB. [2025-11-27T02:20:12.201Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:20:14.160Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:20:17.188Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:20:19.150Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:20:20.112Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:20:22.085Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:20:23.048Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:20:25.018Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:20:25.018Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:20:25.018Z] The best model improves the baseline by 14.52%. [2025-11-27T02:20:25.018Z] Top recommended movies for user id 72: [2025-11-27T02:20:25.018Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:20:25.018Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:20:25.018Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:20:25.018Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:20:25.018Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:20:25.018Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14711.247 ms) ====== [2025-11-27T02:20:25.018Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-27T02:20:25.018Z] GC before operation: completed in 132.128 ms, heap usage 706.396 MB -> 96.297 MB. [2025-11-27T02:20:26.972Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:20:29.993Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:20:31.952Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:20:33.908Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:20:35.867Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:20:36.821Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:20:37.775Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:20:39.739Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:20:39.739Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:20:39.739Z] The best model improves the baseline by 14.52%. [2025-11-27T02:20:39.739Z] Top recommended movies for user id 72: [2025-11-27T02:20:39.739Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:20:39.739Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:20:39.739Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:20:39.739Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:20:39.739Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:20:39.739Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14681.412 ms) ====== [2025-11-27T02:20:39.739Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-27T02:20:39.739Z] GC before operation: completed in 138.913 ms, heap usage 279.813 MB -> 95.903 MB. [2025-11-27T02:20:41.699Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:20:45.073Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:20:47.027Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:20:48.989Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:20:49.946Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:20:50.898Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:20:52.892Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:20:53.845Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:20:53.845Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:20:53.845Z] The best model improves the baseline by 14.52%. [2025-11-27T02:20:54.797Z] Top recommended movies for user id 72: [2025-11-27T02:20:54.797Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:20:54.797Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:20:54.797Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:20:54.797Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:20:54.797Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:20:54.797Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14390.783 ms) ====== [2025-11-27T02:20:54.797Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-27T02:20:54.797Z] GC before operation: completed in 130.863 ms, heap usage 116.372 MB -> 93.462 MB. [2025-11-27T02:20:56.755Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:20:58.709Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:21:01.732Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:21:03.706Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:21:04.658Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:21:05.613Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:21:07.577Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:21:08.535Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:21:09.491Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:21:09.491Z] The best model improves the baseline by 14.52%. [2025-11-27T02:21:09.491Z] Top recommended movies for user id 72: [2025-11-27T02:21:09.491Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:21:09.491Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:21:09.491Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:21:09.491Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:21:09.491Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:21:09.491Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14775.920 ms) ====== [2025-11-27T02:21:09.491Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-27T02:21:09.491Z] GC before operation: completed in 141.092 ms, heap usage 490.971 MB -> 95.046 MB. [2025-11-27T02:21:11.448Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-27T02:21:13.403Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-27T02:21:16.424Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-27T02:21:18.401Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-27T02:21:19.451Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-27T02:21:21.421Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-27T02:21:22.374Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-27T02:21:24.348Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-27T02:21:24.348Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-27T02:21:24.348Z] The best model improves the baseline by 14.52%. [2025-11-27T02:21:24.348Z] Top recommended movies for user id 72: [2025-11-27T02:21:24.348Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-27T02:21:24.348Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-27T02:21:24.348Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-27T02:21:24.348Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-27T02:21:24.348Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-27T02:21:24.348Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15067.626 ms) ====== [2025-11-27T02:21:25.302Z] ----------------------------------- [2025-11-27T02:21:25.302Z] renaissance-movie-lens_0_PASSED [2025-11-27T02:21:25.302Z] ----------------------------------- [2025-11-27T02:21:25.302Z] [2025-11-27T02:21:25.302Z] TEST TEARDOWN: [2025-11-27T02:21:25.302Z] Nothing to be done for teardown. [2025-11-27T02:21:25.302Z] renaissance-movie-lens_0 Finish Time: Thu Nov 27 02:21:24 2025 Epoch Time (ms): 1764210084535