[2025-11-13T06:03:53.580Z] Running test renaissance-movie-lens_0 ... [2025-11-13T06:03:53.580Z] =============================================== [2025-11-13T06:03:53.580Z] renaissance-movie-lens_0 Start Time: Thu Nov 13 06:03:53 2025 Epoch Time (ms): 1763013833461 [2025-11-13T06:03:53.580Z] variation: NoOptions [2025-11-13T06:03:53.580Z] JVM_OPTIONS: [2025-11-13T06:03:53.580Z] { \ [2025-11-13T06:03:53.580Z] echo ""; echo "TEST SETUP:"; \ [2025-11-13T06:03:53.580Z] echo "Nothing to be done for setup."; \ [2025-11-13T06:03:53.580Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17630128781253/renaissance-movie-lens_0"; \ [2025-11-13T06:03:53.580Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17630128781253/renaissance-movie-lens_0"; \ [2025-11-13T06:03:53.580Z] echo ""; echo "TESTING:"; \ [2025-11-13T06:03:53.580Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17630128781253/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-13T06:03:53.581Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17630128781253/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-13T06:03:53.581Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-13T06:03:53.581Z] echo "Nothing to be done for teardown."; \ [2025-11-13T06:03:53.581Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17630128781253/TestTargetResult"; [2025-11-13T06:03:53.581Z] [2025-11-13T06:03:53.581Z] TEST SETUP: [2025-11-13T06:03:53.581Z] Nothing to be done for setup. [2025-11-13T06:03:53.581Z] [2025-11-13T06:03:53.581Z] TESTING: [2025-11-13T06:03:58.851Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-13T06:04:05.333Z] 06:04:05.126 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. [2025-11-13T06:04:07.652Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-13T06:04:08.373Z] Training: 60056, validation: 20285, test: 19854 [2025-11-13T06:04:08.373Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-13T06:04:08.373Z] GC before operation: completed in 123.884 ms, heap usage 409.054 MB -> 75.821 MB. [2025-11-13T06:04:16.255Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:04:19.474Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:04:22.696Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:04:25.913Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:04:28.227Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:04:29.721Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:04:31.208Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:04:33.532Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:04:33.532Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:04:33.532Z] The best model improves the baseline by 14.52%. [2025-11-13T06:04:33.532Z] Top recommended movies for user id 72: [2025-11-13T06:04:33.532Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:04:33.532Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:04:33.532Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:04:33.532Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:04:33.532Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:04:33.532Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25164.832 ms) ====== [2025-11-13T06:04:33.532Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-13T06:04:33.532Z] GC before operation: completed in 114.732 ms, heap usage 278.454 MB -> 95.136 MB. [2025-11-13T06:04:37.212Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:04:39.529Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:04:42.740Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:04:46.027Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:04:46.751Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:04:49.069Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:04:50.554Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:04:52.045Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:04:52.045Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:04:52.045Z] The best model improves the baseline by 14.52%. [2025-11-13T06:04:52.045Z] Top recommended movies for user id 72: [2025-11-13T06:04:52.045Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:04:52.045Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:04:52.045Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:04:52.045Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:04:52.045Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:04:52.045Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18370.762 ms) ====== [2025-11-13T06:04:52.045Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-13T06:04:52.045Z] GC before operation: completed in 108.077 ms, heap usage 261.364 MB -> 89.985 MB. [2025-11-13T06:04:55.254Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:04:57.565Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:05:00.779Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:05:03.089Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:05:04.576Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:05:06.060Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:05:08.376Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:05:09.863Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:05:09.863Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:05:09.863Z] The best model improves the baseline by 14.52%. [2025-11-13T06:05:09.863Z] Top recommended movies for user id 72: [2025-11-13T06:05:09.863Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:05:09.863Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:05:09.863Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:05:09.863Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:05:09.863Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:05:09.863Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17744.752 ms) ====== [2025-11-13T06:05:09.863Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-13T06:05:09.863Z] GC before operation: completed in 105.472 ms, heap usage 172.211 MB -> 91.173 MB. [2025-11-13T06:05:13.091Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:05:15.399Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:05:17.714Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:05:20.923Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:05:22.401Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:05:23.886Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:05:25.367Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:05:26.858Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:05:26.858Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:05:26.858Z] The best model improves the baseline by 14.52%. [2025-11-13T06:05:26.858Z] Top recommended movies for user id 72: [2025-11-13T06:05:26.858Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:05:26.858Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:05:26.858Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:05:26.858Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:05:26.858Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:05:26.858Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16753.151 ms) ====== [2025-11-13T06:05:26.858Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-13T06:05:26.858Z] GC before operation: completed in 104.845 ms, heap usage 129.859 MB -> 90.304 MB. [2025-11-13T06:05:29.174Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:05:32.383Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:05:34.694Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:05:37.015Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:05:38.496Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:05:40.147Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:05:41.627Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:05:43.118Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:05:43.118Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:05:43.836Z] The best model improves the baseline by 14.52%. [2025-11-13T06:05:43.836Z] Top recommended movies for user id 72: [2025-11-13T06:05:43.836Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:05:43.836Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:05:43.836Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:05:43.836Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:05:43.836Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:05:43.836Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16581.290 ms) ====== [2025-11-13T06:05:43.836Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-13T06:05:43.836Z] GC before operation: completed in 117.331 ms, heap usage 574.479 MB -> 93.242 MB. [2025-11-13T06:05:46.157Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:05:48.468Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:05:51.682Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:05:53.987Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:05:54.704Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:05:56.192Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:05:57.674Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:05:59.156Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:05:59.869Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:05:59.869Z] The best model improves the baseline by 14.52%. [2025-11-13T06:05:59.869Z] Top recommended movies for user id 72: [2025-11-13T06:05:59.869Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:05:59.869Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:05:59.869Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:05:59.869Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:05:59.869Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:05:59.869Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16112.498 ms) ====== [2025-11-13T06:05:59.869Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-13T06:05:59.869Z] GC before operation: completed in 105.543 ms, heap usage 286.077 MB -> 90.071 MB. [2025-11-13T06:06:02.184Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:06:05.399Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:06:07.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:06:10.034Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:06:11.521Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:06:13.015Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:06:13.733Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:06:15.222Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:06:15.942Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:06:15.942Z] The best model improves the baseline by 14.52%. [2025-11-13T06:06:15.942Z] Top recommended movies for user id 72: [2025-11-13T06:06:15.942Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:06:15.942Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:06:15.942Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:06:15.942Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:06:15.942Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:06:15.942Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15878.240 ms) ====== [2025-11-13T06:06:15.942Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-13T06:06:15.942Z] GC before operation: completed in 110.364 ms, heap usage 193.538 MB -> 89.917 MB. [2025-11-13T06:06:18.257Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:06:20.575Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:06:23.796Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:06:25.280Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:06:26.765Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:06:28.254Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:06:29.741Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:06:31.224Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:06:31.224Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:06:31.224Z] The best model improves the baseline by 14.52%. [2025-11-13T06:06:31.937Z] Top recommended movies for user id 72: [2025-11-13T06:06:31.937Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:06:31.937Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:06:31.937Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:06:31.937Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:06:31.937Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:06:31.937Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15759.609 ms) ====== [2025-11-13T06:06:31.937Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-13T06:06:31.937Z] GC before operation: completed in 108.146 ms, heap usage 257.621 MB -> 90.183 MB. [2025-11-13T06:06:34.249Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:06:36.560Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:06:38.873Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:06:41.184Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:06:42.665Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:06:44.387Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:06:45.345Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:06:46.830Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:06:46.830Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:06:46.830Z] The best model improves the baseline by 14.52%. [2025-11-13T06:06:46.830Z] Top recommended movies for user id 72: [2025-11-13T06:06:46.830Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:06:46.830Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:06:46.830Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:06:46.830Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:06:46.830Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:06:46.830Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15269.101 ms) ====== [2025-11-13T06:06:46.830Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-13T06:06:47.543Z] GC before operation: completed in 114.982 ms, heap usage 496.462 MB -> 90.404 MB. [2025-11-13T06:06:49.862Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:06:52.171Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:06:54.485Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:06:56.793Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:06:58.277Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:06:59.762Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:07:01.243Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:07:02.729Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:07:02.729Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:07:02.729Z] The best model improves the baseline by 14.52%. [2025-11-13T06:07:02.729Z] Top recommended movies for user id 72: [2025-11-13T06:07:02.729Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:07:02.729Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:07:02.729Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:07:02.729Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:07:02.729Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:07:02.729Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15507.006 ms) ====== [2025-11-13T06:07:02.729Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-13T06:07:02.729Z] GC before operation: completed in 113.509 ms, heap usage 497.754 MB -> 90.691 MB. [2025-11-13T06:07:05.050Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:07:07.360Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:07:09.679Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:07:11.992Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:07:13.474Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:07:14.958Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:07:16.440Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:07:17.925Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:07:17.925Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:07:17.925Z] The best model improves the baseline by 14.52%. [2025-11-13T06:07:17.925Z] Top recommended movies for user id 72: [2025-11-13T06:07:17.925Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:07:17.925Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:07:17.925Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:07:17.925Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:07:17.925Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:07:17.925Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15423.515 ms) ====== [2025-11-13T06:07:17.925Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-13T06:07:18.640Z] GC before operation: completed in 107.398 ms, heap usage 381.122 MB -> 92.549 MB. [2025-11-13T06:07:21.859Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:07:24.160Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:07:27.371Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:07:28.854Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:07:30.335Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:07:31.823Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:07:33.321Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:07:34.811Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:07:34.811Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:07:34.811Z] The best model improves the baseline by 14.52%. [2025-11-13T06:07:34.811Z] Top recommended movies for user id 72: [2025-11-13T06:07:34.811Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:07:34.811Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:07:34.811Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:07:34.811Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:07:34.811Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:07:34.811Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16808.695 ms) ====== [2025-11-13T06:07:34.811Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-13T06:07:35.524Z] GC before operation: completed in 115.216 ms, heap usage 265.095 MB -> 92.660 MB. [2025-11-13T06:07:37.852Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:07:40.244Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:07:42.591Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:07:44.957Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:07:46.125Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:07:47.636Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:07:49.146Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:07:50.655Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:07:50.655Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:07:50.655Z] The best model improves the baseline by 14.52%. [2025-11-13T06:07:50.655Z] Top recommended movies for user id 72: [2025-11-13T06:07:50.655Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:07:50.655Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:07:50.655Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:07:50.655Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:07:50.655Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:07:50.655Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15363.937 ms) ====== [2025-11-13T06:07:50.655Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-13T06:07:50.655Z] GC before operation: completed in 109.156 ms, heap usage 510.478 MB -> 93.173 MB. [2025-11-13T06:07:53.006Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:07:55.361Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:07:57.713Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:08:00.062Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:08:01.685Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:08:03.209Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:08:04.727Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:08:05.472Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:08:06.201Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:08:06.201Z] The best model improves the baseline by 14.52%. [2025-11-13T06:08:06.201Z] Top recommended movies for user id 72: [2025-11-13T06:08:06.201Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:08:06.201Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:08:06.201Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:08:06.201Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:08:06.201Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:08:06.201Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15307.874 ms) ====== [2025-11-13T06:08:06.201Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-13T06:08:06.201Z] GC before operation: completed in 107.590 ms, heap usage 204.739 MB -> 92.350 MB. [2025-11-13T06:08:08.556Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:08:10.906Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:08:13.257Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:08:15.690Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:08:17.211Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:08:17.939Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:08:19.447Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:08:20.968Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:08:20.969Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:08:20.969Z] The best model improves the baseline by 14.52%. [2025-11-13T06:08:20.969Z] Top recommended movies for user id 72: [2025-11-13T06:08:20.969Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:08:20.969Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:08:20.969Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:08:20.969Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:08:20.969Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:08:20.969Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15128.015 ms) ====== [2025-11-13T06:08:20.969Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-13T06:08:21.697Z] GC before operation: completed in 107.948 ms, heap usage 285.534 MB -> 90.547 MB. [2025-11-13T06:08:24.043Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:08:26.387Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:08:28.740Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:08:31.091Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:08:31.817Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:08:33.325Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:08:34.834Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:08:36.349Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:08:36.349Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:08:36.349Z] The best model improves the baseline by 14.52%. [2025-11-13T06:08:36.349Z] Top recommended movies for user id 72: [2025-11-13T06:08:36.349Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:08:36.349Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:08:36.349Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:08:36.349Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:08:36.349Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:08:36.349Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15092.749 ms) ====== [2025-11-13T06:08:36.349Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-13T06:08:36.349Z] GC before operation: completed in 110.974 ms, heap usage 258.207 MB -> 90.361 MB. [2025-11-13T06:08:38.698Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:08:41.051Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:08:44.326Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:08:46.757Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:08:48.269Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:08:49.005Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:08:50.515Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:08:52.529Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:08:53.262Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:08:53.262Z] The best model improves the baseline by 14.52%. [2025-11-13T06:08:53.262Z] Top recommended movies for user id 72: [2025-11-13T06:08:53.262Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:08:53.262Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:08:53.262Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:08:53.262Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:08:53.262Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:08:53.262Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15963.419 ms) ====== [2025-11-13T06:08:53.262Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-13T06:08:53.262Z] GC before operation: completed in 109.117 ms, heap usage 177.309 MB -> 94.995 MB. [2025-11-13T06:08:54.773Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:08:57.132Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:08:59.488Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:09:01.839Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:09:03.357Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:09:04.871Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:09:06.379Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:09:07.109Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:09:07.841Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:09:07.841Z] The best model improves the baseline by 14.52%. [2025-11-13T06:09:07.841Z] Top recommended movies for user id 72: [2025-11-13T06:09:07.841Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:09:07.841Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:09:07.841Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:09:07.841Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:09:07.841Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:09:07.841Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14993.489 ms) ====== [2025-11-13T06:09:07.841Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-13T06:09:07.842Z] GC before operation: completed in 107.790 ms, heap usage 254.359 MB -> 92.577 MB. [2025-11-13T06:09:10.197Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:09:12.545Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:09:14.902Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:09:17.250Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:09:17.981Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:09:19.487Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:09:20.998Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:09:22.510Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:09:22.510Z] 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. [2025-11-13T06:09:22.510Z] The best model improves the baseline by 14.52%. [2025-11-13T06:09:22.510Z] Top recommended movies for user id 72: [2025-11-13T06:09:22.510Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:09:22.510Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:09:22.510Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:09:22.510Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:09:22.510Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:09:22.510Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14957.878 ms) ====== [2025-11-13T06:09:22.510Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-13T06:09:22.510Z] GC before operation: completed in 115.389 ms, heap usage 494.534 MB -> 90.739 MB. [2025-11-13T06:09:24.868Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-13T06:09:27.223Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-13T06:09:29.576Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-13T06:09:31.930Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-13T06:09:33.448Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-13T06:09:34.184Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-13T06:09:35.753Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-13T06:09:37.271Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-13T06:09:37.271Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-13T06:09:37.271Z] The best model improves the baseline by 14.52%. [2025-11-13T06:09:37.998Z] Top recommended movies for user id 72: [2025-11-13T06:09:37.998Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-13T06:09:37.998Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-13T06:09:37.998Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-13T06:09:37.998Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-13T06:09:37.998Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-13T06:09:37.998Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14785.837 ms) ====== [2025-11-13T06:09:37.998Z] ----------------------------------- [2025-11-13T06:09:37.998Z] renaissance-movie-lens_0_PASSED [2025-11-13T06:09:37.998Z] ----------------------------------- [2025-11-13T06:09:37.998Z] [2025-11-13T06:09:37.998Z] TEST TEARDOWN: [2025-11-13T06:09:37.998Z] Nothing to be done for teardown. [2025-11-13T06:09:37.998Z] renaissance-movie-lens_0 Finish Time: Thu Nov 13 06:09:37 2025 Epoch Time (ms): 1763014177655