[2025-06-27T21:03:37.081Z] Running test renaissance-movie-lens_0 ... [2025-06-27T21:03:37.081Z] =============================================== [2025-06-27T21:03:37.081Z] renaissance-movie-lens_0 Start Time: Fri Jun 27 21:03:36 2025 Epoch Time (ms): 1751058216118 [2025-06-27T21:03:37.081Z] variation: NoOptions [2025-06-27T21:03:37.081Z] JVM_OPTIONS: [2025-06-27T21:03:37.081Z] { \ [2025-06-27T21:03:37.081Z] echo ""; echo "TEST SETUP:"; \ [2025-06-27T21:03:37.081Z] echo "Nothing to be done for setup."; \ [2025-06-27T21:03:37.081Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17510568032680/renaissance-movie-lens_0"; \ [2025-06-27T21:03:37.081Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17510568032680/renaissance-movie-lens_0"; \ [2025-06-27T21:03:37.081Z] echo ""; echo "TESTING:"; \ [2025-06-27T21:03:37.081Z] "/home/jenkins/workspace/Test_openjdk21_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_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17510568032680/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-27T21:03:37.081Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17510568032680/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-27T21:03:37.081Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-27T21:03:37.081Z] echo "Nothing to be done for teardown."; \ [2025-06-27T21:03:37.081Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17510568032680/TestTargetResult"; [2025-06-27T21:03:37.081Z] [2025-06-27T21:03:37.081Z] TEST SETUP: [2025-06-27T21:03:37.081Z] Nothing to be done for setup. [2025-06-27T21:03:37.081Z] [2025-06-27T21:03:37.081Z] TESTING: [2025-06-27T21:03:42.489Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-27T21:03:49.091Z] 21:03:47.859 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-06-27T21:03:51.017Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-27T21:03:51.017Z] Training: 60056, validation: 20285, test: 19854 [2025-06-27T21:03:51.017Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-27T21:03:51.017Z] GC before operation: completed in 141.702 ms, heap usage 285.886 MB -> 75.759 MB. [2025-06-27T21:03:56.350Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:04:00.436Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:04:03.126Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:04:06.096Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:04:08.017Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:04:08.956Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:04:10.886Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:04:12.806Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:04:12.807Z] 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. [2025-06-27T21:04:12.807Z] The best model improves the baseline by 14.52%. [2025-06-27T21:04:12.807Z] Top recommended movies for user id 72: [2025-06-27T21:04:12.807Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:04:12.807Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:04:12.807Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:04:12.807Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:04:12.807Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:04:12.807Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22009.718 ms) ====== [2025-06-27T21:04:12.807Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-27T21:04:13.741Z] GC before operation: completed in 150.834 ms, heap usage 248.334 MB -> 91.918 MB. [2025-06-27T21:04:15.679Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:04:18.670Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:04:20.622Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:04:23.604Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:04:24.541Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:04:26.466Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:04:28.391Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:04:29.326Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:04:30.260Z] 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. [2025-06-27T21:04:30.260Z] The best model improves the baseline by 14.52%. [2025-06-27T21:04:30.260Z] Top recommended movies for user id 72: [2025-06-27T21:04:30.260Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:04:30.260Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:04:30.260Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:04:30.260Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:04:30.260Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:04:30.260Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16762.278 ms) ====== [2025-06-27T21:04:30.260Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-27T21:04:30.260Z] GC before operation: completed in 117.481 ms, heap usage 178.649 MB -> 88.463 MB. [2025-06-27T21:04:32.185Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:04:35.148Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:04:37.071Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:04:40.037Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:04:40.971Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:04:41.907Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:04:43.827Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:04:45.748Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:04:45.748Z] 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. [2025-06-27T21:04:45.748Z] The best model improves the baseline by 14.52%. [2025-06-27T21:04:45.748Z] Top recommended movies for user id 72: [2025-06-27T21:04:45.748Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:04:45.748Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:04:45.748Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:04:45.748Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:04:45.748Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:04:45.748Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15592.128 ms) ====== [2025-06-27T21:04:45.748Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-27T21:04:45.748Z] GC before operation: completed in 131.917 ms, heap usage 268.052 MB -> 89.257 MB. [2025-06-27T21:04:47.671Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:04:50.649Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:04:52.573Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:04:55.222Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:04:56.162Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:04:58.081Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:04:59.015Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:05:00.934Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:05:00.934Z] 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. [2025-06-27T21:05:00.934Z] The best model improves the baseline by 14.52%. [2025-06-27T21:05:00.934Z] Top recommended movies for user id 72: [2025-06-27T21:05:00.934Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:05:00.934Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:05:00.934Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:05:00.934Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:05:00.934Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:05:00.935Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15353.083 ms) ====== [2025-06-27T21:05:00.935Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-27T21:05:00.935Z] GC before operation: completed in 143.020 ms, heap usage 380.104 MB -> 89.665 MB. [2025-06-27T21:05:03.940Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:05:05.860Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:05:09.002Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:05:10.922Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:05:12.841Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:05:13.778Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:05:15.698Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:05:16.646Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:05:17.585Z] 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. [2025-06-27T21:05:17.585Z] The best model improves the baseline by 14.52%. [2025-06-27T21:05:17.585Z] Top recommended movies for user id 72: [2025-06-27T21:05:17.585Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:05:17.585Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:05:17.585Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:05:17.585Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:05:17.585Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:05:17.585Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16076.337 ms) ====== [2025-06-27T21:05:17.585Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-27T21:05:17.586Z] GC before operation: completed in 127.013 ms, heap usage 396.516 MB -> 89.649 MB. [2025-06-27T21:05:19.510Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:05:22.476Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:05:24.400Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:05:26.324Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:05:28.246Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:05:29.185Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:05:31.107Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:05:32.041Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:05:32.977Z] 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. [2025-06-27T21:05:32.977Z] The best model improves the baseline by 14.52%. [2025-06-27T21:05:32.978Z] Top recommended movies for user id 72: [2025-06-27T21:05:32.978Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:05:32.978Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:05:32.978Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:05:32.978Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:05:32.978Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:05:32.978Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15263.662 ms) ====== [2025-06-27T21:05:32.978Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-27T21:05:32.978Z] GC before operation: completed in 201.287 ms, heap usage 285.714 MB -> 89.921 MB. [2025-06-27T21:05:34.925Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:05:37.890Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:05:39.814Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:05:41.735Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:05:43.658Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:05:44.594Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:05:46.572Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:05:48.533Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:05:48.533Z] 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. [2025-06-27T21:05:48.533Z] The best model improves the baseline by 14.52%. [2025-06-27T21:05:48.533Z] Top recommended movies for user id 72: [2025-06-27T21:05:48.533Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:05:48.533Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:05:48.533Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:05:48.533Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:05:48.533Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:05:48.533Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15347.265 ms) ====== [2025-06-27T21:05:48.533Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-27T21:05:48.533Z] GC before operation: completed in 142.614 ms, heap usage 375.607 MB -> 89.968 MB. [2025-06-27T21:05:50.460Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:05:53.428Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:05:55.362Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:05:58.332Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:05:59.268Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:06:00.206Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:06:02.137Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:06:03.075Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:06:04.009Z] 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. [2025-06-27T21:06:04.009Z] The best model improves the baseline by 14.52%. [2025-06-27T21:06:04.009Z] Top recommended movies for user id 72: [2025-06-27T21:06:04.009Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:06:04.009Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:06:04.009Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:06:04.009Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:06:04.009Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:06:04.009Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15253.520 ms) ====== [2025-06-27T21:06:04.009Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-27T21:06:04.009Z] GC before operation: completed in 139.431 ms, heap usage 435.555 MB -> 90.251 MB. [2025-06-27T21:06:05.945Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:06:09.952Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:06:10.898Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:06:12.824Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:06:13.758Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:06:15.682Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:06:16.624Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:06:17.570Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:06:18.510Z] 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. [2025-06-27T21:06:18.510Z] The best model improves the baseline by 14.52%. [2025-06-27T21:06:18.510Z] Top recommended movies for user id 72: [2025-06-27T21:06:18.510Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:06:18.510Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:06:18.510Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:06:18.510Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:06:18.510Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:06:18.510Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14552.793 ms) ====== [2025-06-27T21:06:18.510Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-27T21:06:18.510Z] GC before operation: completed in 137.338 ms, heap usage 212.034 MB -> 89.803 MB. [2025-06-27T21:06:21.484Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:06:23.425Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:06:25.349Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:06:28.320Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:06:29.255Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:06:31.187Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:06:32.120Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:06:34.040Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:06:34.040Z] 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. [2025-06-27T21:06:34.040Z] The best model improves the baseline by 14.52%. [2025-06-27T21:06:34.040Z] Top recommended movies for user id 72: [2025-06-27T21:06:34.040Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:06:34.040Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:06:34.040Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:06:34.040Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:06:34.040Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:06:34.040Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15652.280 ms) ====== [2025-06-27T21:06:34.040Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-27T21:06:34.040Z] GC before operation: completed in 130.014 ms, heap usage 125.525 MB -> 89.875 MB. [2025-06-27T21:06:37.002Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:06:38.920Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:06:40.842Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:06:43.688Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:06:44.626Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:06:45.559Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:06:46.494Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:06:48.416Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:06:48.416Z] 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. [2025-06-27T21:06:48.416Z] The best model improves the baseline by 14.52%. [2025-06-27T21:06:48.416Z] Top recommended movies for user id 72: [2025-06-27T21:06:48.416Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:06:48.416Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:06:48.416Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:06:48.416Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:06:48.416Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:06:48.416Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14221.774 ms) ====== [2025-06-27T21:06:48.416Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-27T21:06:48.416Z] GC before operation: completed in 136.760 ms, heap usage 123.746 MB -> 89.880 MB. [2025-06-27T21:06:51.384Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:06:53.307Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:06:55.226Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:06:57.147Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:06:58.085Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:06:59.032Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:07:00.955Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:07:01.897Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:07:01.897Z] 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. [2025-06-27T21:07:01.897Z] The best model improves the baseline by 14.52%. [2025-06-27T21:07:02.839Z] Top recommended movies for user id 72: [2025-06-27T21:07:02.839Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:07:02.839Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:07:02.839Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:07:02.839Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:07:02.839Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:07:02.839Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13609.580 ms) ====== [2025-06-27T21:07:02.839Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-27T21:07:02.839Z] GC before operation: completed in 159.512 ms, heap usage 237.605 MB -> 89.965 MB. [2025-06-27T21:07:04.791Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:07:06.734Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:07:08.668Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:07:11.641Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:07:12.583Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:07:14.574Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:07:15.506Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:07:17.427Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:07:17.427Z] 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. [2025-06-27T21:07:17.427Z] The best model improves the baseline by 14.52%. [2025-06-27T21:07:17.427Z] Top recommended movies for user id 72: [2025-06-27T21:07:17.427Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:07:17.427Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:07:17.427Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:07:17.427Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:07:17.427Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:07:17.427Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14816.542 ms) ====== [2025-06-27T21:07:17.427Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-27T21:07:17.427Z] GC before operation: completed in 135.076 ms, heap usage 400.966 MB -> 90.351 MB. [2025-06-27T21:07:20.391Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:07:22.344Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:07:24.271Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:07:27.237Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:07:28.170Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:07:30.093Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:07:31.029Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:07:32.949Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:07:32.949Z] 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. [2025-06-27T21:07:32.949Z] The best model improves the baseline by 14.52%. [2025-06-27T21:07:32.949Z] Top recommended movies for user id 72: [2025-06-27T21:07:32.949Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:07:32.949Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:07:32.949Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:07:32.949Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:07:32.949Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:07:32.949Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15479.364 ms) ====== [2025-06-27T21:07:32.949Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-27T21:07:32.949Z] GC before operation: completed in 143.901 ms, heap usage 365.745 MB -> 90.157 MB. [2025-06-27T21:07:34.890Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:07:37.872Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:07:40.543Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:07:42.500Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:07:43.434Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:07:45.356Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:07:46.296Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:07:47.229Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:07:48.164Z] 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. [2025-06-27T21:07:48.164Z] The best model improves the baseline by 14.52%. [2025-06-27T21:07:48.164Z] Top recommended movies for user id 72: [2025-06-27T21:07:48.164Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:07:48.164Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:07:48.164Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:07:48.164Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:07:48.164Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:07:48.164Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14928.558 ms) ====== [2025-06-27T21:07:48.164Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-27T21:07:48.164Z] GC before operation: completed in 119.301 ms, heap usage 152.438 MB -> 90.091 MB. [2025-06-27T21:07:50.085Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:07:53.074Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:07:54.999Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:07:56.918Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:07:58.838Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:07:59.776Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:08:01.698Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:08:03.617Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:08:03.617Z] 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. [2025-06-27T21:08:03.617Z] The best model improves the baseline by 14.52%. [2025-06-27T21:08:03.617Z] Top recommended movies for user id 72: [2025-06-27T21:08:03.617Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:08:03.617Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:08:03.617Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:08:03.617Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:08:03.617Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:08:03.617Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15474.376 ms) ====== [2025-06-27T21:08:03.617Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-27T21:08:03.617Z] GC before operation: completed in 119.130 ms, heap usage 365.242 MB -> 90.257 MB. [2025-06-27T21:08:05.550Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:08:08.522Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:08:10.442Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:08:12.374Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:08:14.329Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:08:15.265Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:08:17.184Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:08:18.126Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:08:19.061Z] 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. [2025-06-27T21:08:19.061Z] The best model improves the baseline by 14.52%. [2025-06-27T21:08:19.061Z] Top recommended movies for user id 72: [2025-06-27T21:08:19.061Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:08:19.061Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:08:19.061Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:08:19.061Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:08:19.061Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:08:19.061Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15090.623 ms) ====== [2025-06-27T21:08:19.061Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-27T21:08:19.061Z] GC before operation: completed in 135.657 ms, heap usage 154.142 MB -> 89.933 MB. [2025-06-27T21:08:20.985Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:08:22.907Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:08:25.871Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:08:27.797Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:08:28.731Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:08:29.673Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:08:32.625Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:08:32.625Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:08:32.625Z] 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. [2025-06-27T21:08:32.625Z] The best model improves the baseline by 14.52%. [2025-06-27T21:08:32.625Z] Top recommended movies for user id 72: [2025-06-27T21:08:32.625Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:08:32.625Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:08:32.625Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:08:32.625Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:08:32.625Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:08:32.625Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13822.633 ms) ====== [2025-06-27T21:08:32.625Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-27T21:08:32.625Z] GC before operation: completed in 119.571 ms, heap usage 497.726 MB -> 90.332 MB. [2025-06-27T21:08:35.591Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:08:37.513Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:08:39.444Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:08:41.366Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:08:42.331Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:08:43.267Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:08:45.193Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:08:46.129Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:08:46.129Z] 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. [2025-06-27T21:08:46.129Z] The best model improves the baseline by 14.52%. [2025-06-27T21:08:47.086Z] Top recommended movies for user id 72: [2025-06-27T21:08:47.086Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:08:47.086Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:08:47.086Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:08:47.086Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:08:47.086Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:08:47.086Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13805.590 ms) ====== [2025-06-27T21:08:47.086Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-27T21:08:47.086Z] GC before operation: completed in 140.970 ms, heap usage 221.945 MB -> 90.082 MB. [2025-06-27T21:08:49.012Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:08:50.936Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:08:52.857Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:08:55.832Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:08:56.768Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:08:57.705Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:08:59.628Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:09:00.563Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:09:00.564Z] 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. [2025-06-27T21:09:00.564Z] The best model improves the baseline by 14.52%. [2025-06-27T21:09:00.564Z] Top recommended movies for user id 72: [2025-06-27T21:09:00.564Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-27T21:09:00.564Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-27T21:09:00.564Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-27T21:09:00.564Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-27T21:09:00.564Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-27T21:09:00.564Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14087.883 ms) ====== [2025-06-27T21:09:01.499Z] ----------------------------------- [2025-06-27T21:09:01.499Z] renaissance-movie-lens_0_PASSED [2025-06-27T21:09:01.499Z] ----------------------------------- [2025-06-27T21:09:01.499Z] [2025-06-27T21:09:01.499Z] TEST TEARDOWN: [2025-06-27T21:09:01.499Z] Nothing to be done for teardown. [2025-06-27T21:09:01.499Z] renaissance-movie-lens_0 Finish Time: Fri Jun 27 21:09:00 2025 Epoch Time (ms): 1751058541000