[2025-05-08T08:01:49.195Z] Running test renaissance-movie-lens_0 ... [2025-05-08T08:01:49.195Z] =============================================== [2025-05-08T08:01:49.195Z] renaissance-movie-lens_0 Start Time: Thu May 8 08:01:47 2025 Epoch Time (ms): 1746691307927 [2025-05-08T08:01:49.195Z] variation: NoOptions [2025-05-08T08:01:49.195Z] JVM_OPTIONS: [2025-05-08T08:01:49.195Z] { \ [2025-05-08T08:01:49.195Z] echo ""; echo "TEST SETUP:"; \ [2025-05-08T08:01:49.195Z] echo "Nothing to be done for setup."; \ [2025-05-08T08:01:49.195Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1746689949764/renaissance-movie-lens_0"; \ [2025-05-08T08:01:49.195Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1746689949764/renaissance-movie-lens_0"; \ [2025-05-08T08:01:49.195Z] echo ""; echo "TESTING:"; \ [2025-05-08T08:01:49.195Z] "/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_1746689949764/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-05-08T08:01:49.195Z] 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_1746689949764/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-05-08T08:01:49.195Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-05-08T08:01:49.195Z] echo "Nothing to be done for teardown."; \ [2025-05-08T08:01:49.195Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_1746689949764/TestTargetResult"; [2025-05-08T08:01:49.195Z] [2025-05-08T08:01:49.195Z] TEST SETUP: [2025-05-08T08:01:49.195Z] Nothing to be done for setup. [2025-05-08T08:01:49.195Z] [2025-05-08T08:01:49.195Z] TESTING: [2025-05-08T08:01:53.346Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-05-08T08:02:00.036Z] 08:01:59.474 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. [2025-05-08T08:02:01.989Z] Got 100004 ratings from 671 users on 9066 movies. [2025-05-08T08:02:02.939Z] Training: 60056, validation: 20285, test: 19854 [2025-05-08T08:02:02.939Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-05-08T08:02:02.939Z] GC before operation: completed in 137.650 ms, heap usage 233.245 MB -> 75.623 MB. [2025-05-08T08:02:08.317Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:02:11.342Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:02:14.364Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:02:17.380Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:02:19.339Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:02:21.295Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:02:22.247Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:02:24.206Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:02:24.206Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-08T08:02:25.158Z] The best model improves the baseline by 14.52%. [2025-05-08T08:02:25.158Z] Top recommended movies for user id 72: [2025-05-08T08:02:25.158Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:02:25.158Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:02:25.158Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:02:25.158Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:02:25.158Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:02:25.158Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22313.180 ms) ====== [2025-05-08T08:02:25.158Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-05-08T08:02:25.158Z] GC before operation: completed in 140.889 ms, heap usage 524.785 MB -> 91.861 MB. [2025-05-08T08:02:28.191Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:02:31.228Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:02:33.185Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:02:36.209Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:02:37.162Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:02:39.117Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:02:41.075Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:02:42.029Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:02:42.029Z] 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. [2025-05-08T08:02:42.029Z] The best model improves the baseline by 14.52%. [2025-05-08T08:02:42.995Z] Top recommended movies for user id 72: [2025-05-08T08:02:42.995Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:02:42.995Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:02:42.995Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:02:42.995Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:02:42.995Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:02:42.995Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17477.926 ms) ====== [2025-05-08T08:02:42.995Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-05-08T08:02:42.995Z] GC before operation: completed in 130.086 ms, heap usage 610.906 MB -> 95.933 MB. [2025-05-08T08:02:44.955Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:02:47.978Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:02:49.932Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:02:52.948Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:02:53.901Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:02:56.942Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:02:57.895Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:02:58.847Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:02:59.798Z] 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. [2025-05-08T08:02:59.798Z] The best model improves the baseline by 14.52%. [2025-05-08T08:02:59.798Z] Top recommended movies for user id 72: [2025-05-08T08:02:59.798Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:02:59.798Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:02:59.798Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:02:59.798Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:02:59.798Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:02:59.798Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17089.644 ms) ====== [2025-05-08T08:02:59.798Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-05-08T08:02:59.798Z] GC before operation: completed in 144.346 ms, heap usage 371.147 MB -> 90.559 MB. [2025-05-08T08:03:02.824Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:03:05.845Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:03:07.803Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:03:10.822Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:03:11.774Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:03:13.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:03:15.690Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:03:16.643Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:03:16.644Z] 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. [2025-05-08T08:03:16.644Z] The best model improves the baseline by 14.52%. [2025-05-08T08:03:16.644Z] Top recommended movies for user id 72: [2025-05-08T08:03:16.644Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:03:16.644Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:03:16.644Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:03:16.644Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:03:16.644Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:03:16.644Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17098.213 ms) ====== [2025-05-08T08:03:16.644Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-05-08T08:03:17.596Z] GC before operation: completed in 136.672 ms, heap usage 525.407 MB -> 89.936 MB. [2025-05-08T08:03:19.553Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:03:22.572Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:03:24.541Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:03:27.555Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:03:28.510Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:03:30.470Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:03:31.421Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:03:33.384Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:03:33.384Z] 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. [2025-05-08T08:03:33.384Z] The best model improves the baseline by 14.52%. [2025-05-08T08:03:33.385Z] Top recommended movies for user id 72: [2025-05-08T08:03:33.385Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:03:33.385Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:03:33.385Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:03:33.385Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:03:33.385Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:03:33.385Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16229.326 ms) ====== [2025-05-08T08:03:33.385Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-05-08T08:03:33.385Z] GC before operation: completed in 144.071 ms, heap usage 716.331 MB -> 93.289 MB. [2025-05-08T08:03:36.402Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:03:39.422Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:03:41.375Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:03:44.391Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:03:45.344Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:03:47.297Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:03:48.253Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:03:50.207Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:03:50.207Z] 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. [2025-05-08T08:03:50.207Z] The best model improves the baseline by 14.52%. [2025-05-08T08:03:50.207Z] Top recommended movies for user id 72: [2025-05-08T08:03:50.207Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:03:50.207Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:03:50.207Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:03:50.207Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:03:50.207Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:03:50.207Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16667.573 ms) ====== [2025-05-08T08:03:50.207Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-05-08T08:03:50.207Z] GC before operation: completed in 142.101 ms, heap usage 371.445 MB -> 93.752 MB. [2025-05-08T08:03:52.162Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:03:55.182Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:03:57.139Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:03:59.093Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:04:00.048Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:04:02.436Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:04:03.389Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:04:04.342Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:04:04.342Z] 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. [2025-05-08T08:04:04.342Z] The best model improves the baseline by 14.52%. [2025-05-08T08:04:04.342Z] Top recommended movies for user id 72: [2025-05-08T08:04:04.342Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:04:04.342Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:04:04.342Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:04:04.342Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:04:04.342Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:04:04.342Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14159.253 ms) ====== [2025-05-08T08:04:04.342Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-05-08T08:04:04.342Z] GC before operation: completed in 139.343 ms, heap usage 182.929 MB -> 93.135 MB. [2025-05-08T08:04:07.358Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:04:09.312Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:04:11.263Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:04:13.394Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:04:14.347Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:04:15.299Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:04:17.254Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:04:18.206Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:04:18.206Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-08T08:04:18.206Z] The best model improves the baseline by 14.52%. [2025-05-08T08:04:19.156Z] Top recommended movies for user id 72: [2025-05-08T08:04:19.156Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:04:19.156Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:04:19.156Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:04:19.156Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:04:19.156Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:04:19.156Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13976.916 ms) ====== [2025-05-08T08:04:19.156Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-05-08T08:04:19.156Z] GC before operation: completed in 128.397 ms, heap usage 430.381 MB -> 90.332 MB. [2025-05-08T08:04:21.110Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:04:23.069Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:04:25.031Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:04:26.987Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:04:28.993Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:04:30.618Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:04:31.569Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:04:32.525Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:04:32.525Z] 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. [2025-05-08T08:04:32.525Z] The best model improves the baseline by 14.52%. [2025-05-08T08:04:32.525Z] Top recommended movies for user id 72: [2025-05-08T08:04:32.525Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:04:32.525Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:04:32.525Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:04:32.525Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:04:32.525Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:04:32.525Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13948.684 ms) ====== [2025-05-08T08:04:32.525Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-05-08T08:04:32.525Z] GC before operation: completed in 122.789 ms, heap usage 118.707 MB -> 93.402 MB. [2025-05-08T08:04:35.628Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:04:37.580Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:04:39.538Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:04:41.491Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:04:42.448Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:04:44.401Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:04:45.358Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:04:46.311Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:04:47.261Z] 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. [2025-05-08T08:04:47.261Z] The best model improves the baseline by 14.52%. [2025-05-08T08:04:47.261Z] Top recommended movies for user id 72: [2025-05-08T08:04:47.261Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:04:47.261Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:04:47.261Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:04:47.261Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:04:47.261Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:04:47.261Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14212.087 ms) ====== [2025-05-08T08:04:47.261Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-05-08T08:04:47.261Z] GC before operation: completed in 138.898 ms, heap usage 297.200 MB -> 94.547 MB. [2025-05-08T08:04:49.213Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:04:51.165Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:04:53.147Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:04:56.202Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:04:57.153Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:04:58.103Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:05:00.053Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:05:01.011Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:05:01.011Z] 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. [2025-05-08T08:05:01.011Z] The best model improves the baseline by 14.52%. [2025-05-08T08:05:01.011Z] Top recommended movies for user id 72: [2025-05-08T08:05:01.011Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:05:01.011Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:05:01.011Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:05:01.011Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:05:01.011Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:05:01.011Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14140.989 ms) ====== [2025-05-08T08:05:01.011Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-05-08T08:05:01.962Z] GC before operation: completed in 141.619 ms, heap usage 218.457 MB -> 91.592 MB. [2025-05-08T08:05:03.911Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:05:05.864Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:05:08.859Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:05:09.978Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:05:11.936Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:05:12.889Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:05:14.842Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:05:15.791Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:05:15.791Z] 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. [2025-05-08T08:05:15.791Z] The best model improves the baseline by 14.52%. [2025-05-08T08:05:15.791Z] Top recommended movies for user id 72: [2025-05-08T08:05:15.791Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:05:15.792Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:05:15.792Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:05:15.792Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:05:15.792Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:05:15.792Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14681.190 ms) ====== [2025-05-08T08:05:15.792Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-05-08T08:05:16.744Z] GC before operation: completed in 138.198 ms, heap usage 498.927 MB -> 92.361 MB. [2025-05-08T08:05:18.697Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:05:20.648Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:05:22.601Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:05:24.554Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:05:26.504Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:05:27.455Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:05:28.407Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:05:30.357Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:05:30.357Z] 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. [2025-05-08T08:05:30.357Z] The best model improves the baseline by 14.52%. [2025-05-08T08:05:30.357Z] Top recommended movies for user id 72: [2025-05-08T08:05:30.357Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:05:30.357Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:05:30.357Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:05:30.357Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:05:30.357Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:05:30.357Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14460.602 ms) ====== [2025-05-08T08:05:30.357Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-05-08T08:05:31.307Z] GC before operation: completed in 182.754 ms, heap usage 187.514 MB -> 93.479 MB. [2025-05-08T08:05:33.256Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:05:35.211Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:05:38.231Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:05:40.216Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:05:41.169Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:05:43.125Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:05:44.076Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:05:46.029Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:05:46.029Z] 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. [2025-05-08T08:05:46.029Z] The best model improves the baseline by 14.52%. [2025-05-08T08:05:46.029Z] Top recommended movies for user id 72: [2025-05-08T08:05:46.029Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:05:46.029Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:05:46.029Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:05:46.029Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:05:46.029Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:05:46.029Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15048.999 ms) ====== [2025-05-08T08:05:46.029Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-05-08T08:05:46.029Z] GC before operation: completed in 145.584 ms, heap usage 309.771 MB -> 93.670 MB. [2025-05-08T08:05:47.984Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:05:51.014Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:05:52.964Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:05:54.915Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:05:55.866Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:05:56.819Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:05:58.777Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:05:59.739Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:05:59.739Z] 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. [2025-05-08T08:05:59.739Z] The best model improves the baseline by 14.52%. [2025-05-08T08:06:00.693Z] Top recommended movies for user id 72: [2025-05-08T08:06:00.693Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:06:00.693Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:06:00.693Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:06:00.693Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:06:00.693Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:06:00.693Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14117.657 ms) ====== [2025-05-08T08:06:00.693Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-05-08T08:06:00.693Z] GC before operation: completed in 121.810 ms, heap usage 125.335 MB -> 90.913 MB. [2025-05-08T08:06:02.651Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:06:04.607Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:06:06.559Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:06:09.573Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:06:10.524Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:06:11.476Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:06:14.489Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:06:14.489Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:06:14.489Z] 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. [2025-05-08T08:06:14.489Z] The best model improves the baseline by 14.52%. [2025-05-08T08:06:15.614Z] Top recommended movies for user id 72: [2025-05-08T08:06:15.614Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:06:15.614Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:06:15.614Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:06:15.614Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:06:15.614Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:06:15.614Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14264.316 ms) ====== [2025-05-08T08:06:15.614Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-05-08T08:06:15.614Z] GC before operation: completed in 133.398 ms, heap usage 746.545 MB -> 93.967 MB. [2025-05-08T08:06:16.566Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:06:19.587Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:06:21.542Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:06:23.498Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:06:24.450Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:06:26.405Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:06:27.358Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:06:28.311Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:06:29.263Z] 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. [2025-05-08T08:06:29.263Z] The best model improves the baseline by 14.52%. [2025-05-08T08:06:29.263Z] Top recommended movies for user id 72: [2025-05-08T08:06:29.263Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:06:29.263Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:06:29.263Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:06:29.263Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:06:29.263Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:06:29.263Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14218.600 ms) ====== [2025-05-08T08:06:29.263Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-05-08T08:06:29.263Z] GC before operation: completed in 134.293 ms, heap usage 429.968 MB -> 90.489 MB. [2025-05-08T08:06:31.219Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:06:34.246Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:06:37.264Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:06:39.221Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:06:40.173Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:06:42.128Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:06:43.084Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:06:44.036Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:06:44.988Z] 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. [2025-05-08T08:06:44.988Z] The best model improves the baseline by 14.52%. [2025-05-08T08:06:44.988Z] Top recommended movies for user id 72: [2025-05-08T08:06:44.988Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:06:44.988Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:06:44.988Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:06:44.988Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:06:44.988Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:06:44.988Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15698.057 ms) ====== [2025-05-08T08:06:44.988Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-05-08T08:06:44.988Z] GC before operation: completed in 219.293 ms, heap usage 551.960 MB -> 93.644 MB. [2025-05-08T08:06:48.007Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:06:49.961Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:06:51.924Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:06:54.039Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:06:54.993Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:06:56.948Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:06:57.902Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:06:58.854Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:06:59.806Z] 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. [2025-05-08T08:06:59.806Z] The best model improves the baseline by 14.52%. [2025-05-08T08:06:59.806Z] Top recommended movies for user id 72: [2025-05-08T08:06:59.806Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:06:59.806Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:06:59.806Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:06:59.806Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:06:59.806Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:06:59.806Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14483.329 ms) ====== [2025-05-08T08:06:59.806Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-05-08T08:06:59.806Z] GC before operation: completed in 149.479 ms, heap usage 449.466 MB -> 94.124 MB. [2025-05-08T08:07:01.762Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-08T08:07:03.721Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-08T08:07:06.737Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-08T08:07:08.692Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-08T08:07:09.645Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-08T08:07:10.597Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-08T08:07:12.550Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-08T08:07:13.503Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-08T08:07:13.503Z] 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. [2025-05-08T08:07:13.503Z] The best model improves the baseline by 14.52%. [2025-05-08T08:07:13.503Z] Top recommended movies for user id 72: [2025-05-08T08:07:13.503Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-08T08:07:13.503Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-08T08:07:13.503Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-08T08:07:13.503Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-08T08:07:13.503Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-08T08:07:13.503Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14160.834 ms) ====== [2025-05-08T08:07:14.459Z] ----------------------------------- [2025-05-08T08:07:14.459Z] renaissance-movie-lens_0_PASSED [2025-05-08T08:07:14.459Z] ----------------------------------- [2025-05-08T08:07:14.459Z] [2025-05-08T08:07:14.459Z] TEST TEARDOWN: [2025-05-08T08:07:14.459Z] Nothing to be done for teardown. [2025-05-08T08:07:14.459Z] renaissance-movie-lens_0 Finish Time: Thu May 8 08:07:13 2025 Epoch Time (ms): 1746691633901