[2025-11-26T22:41:30.300Z] Running test renaissance-movie-lens_0 ... [2025-11-26T22:41:30.300Z] =============================================== [2025-11-26T22:41:30.300Z] renaissance-movie-lens_0 Start Time: Wed Nov 26 14:41:29 2025 Epoch Time (ms): 1764196889125 [2025-11-26T22:41:30.300Z] variation: NoOptions [2025-11-26T22:41:30.300Z] JVM_OPTIONS: [2025-11-26T22:41:30.300Z] { \ [2025-11-26T22:41:30.300Z] echo ""; echo "TEST SETUP:"; \ [2025-11-26T22:41:30.300Z] echo "Nothing to be done for setup."; \ [2025-11-26T22:41:30.300Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17641940902829/renaissance-movie-lens_0"; \ [2025-11-26T22:41:30.300Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17641940902829/renaissance-movie-lens_0"; \ [2025-11-26T22:41:30.300Z] echo ""; echo "TESTING:"; \ [2025-11-26T22:41:30.300Z] "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17641940902829/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-26T22:41:30.300Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17641940902829/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-26T22:41:30.300Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-26T22:41:30.300Z] echo "Nothing to be done for teardown."; \ [2025-11-26T22:41:30.300Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17641940902829/TestTargetResult"; [2025-11-26T22:41:30.300Z] [2025-11-26T22:41:30.300Z] TEST SETUP: [2025-11-26T22:41:30.300Z] Nothing to be done for setup. [2025-11-26T22:41:30.300Z] [2025-11-26T22:41:30.300Z] TESTING: [2025-11-26T22:41:45.484Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-26T22:41:57.720Z] 14:41:55.525 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-11-26T22:42:00.488Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-26T22:42:00.921Z] Training: 60056, validation: 20285, test: 19854 [2025-11-26T22:42:00.921Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-26T22:42:01.352Z] GC before operation: completed in 252.354 ms, heap usage 372.563 MB -> 74.874 MB. [2025-11-26T22:42:23.689Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:42:42.237Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:42:57.271Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:43:08.130Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:43:18.739Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:43:26.231Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:43:36.968Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:43:44.499Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:43:45.504Z] 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. [2025-11-26T22:43:45.504Z] The best model improves the baseline by 14.52%. [2025-11-26T22:43:45.957Z] Top recommended movies for user id 72: [2025-11-26T22:43:45.957Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:43:45.957Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:43:45.957Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:43:45.957Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:43:45.957Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:43:45.957Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (104631.887 ms) ====== [2025-11-26T22:43:45.957Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-26T22:43:45.957Z] GC before operation: completed in 209.465 ms, heap usage 172.074 MB -> 86.660 MB. [2025-11-26T22:44:03.884Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:44:21.931Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:44:34.805Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:44:49.775Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:44:56.922Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:45:05.689Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:45:16.424Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:45:23.520Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:45:23.520Z] 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. [2025-11-26T22:45:23.520Z] The best model improves the baseline by 14.52%. [2025-11-26T22:45:23.520Z] Top recommended movies for user id 72: [2025-11-26T22:45:23.520Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:45:23.520Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:45:23.520Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:45:23.520Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:45:23.520Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:45:23.520Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (97506.079 ms) ====== [2025-11-26T22:45:23.520Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-26T22:45:24.124Z] GC before operation: completed in 335.327 ms, heap usage 1.009 GB -> 92.796 MB. [2025-11-26T22:45:40.019Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:45:55.328Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:46:13.092Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:46:28.226Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:46:37.149Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:46:44.354Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:46:51.945Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:47:02.838Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:47:03.945Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T22:47:03.945Z] The best model improves the baseline by 14.52%. [2025-11-26T22:47:03.945Z] Top recommended movies for user id 72: [2025-11-26T22:47:03.945Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:47:03.945Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:47:03.945Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:47:03.945Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:47:03.945Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:47:03.945Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (99850.009 ms) ====== [2025-11-26T22:47:03.945Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-26T22:47:05.762Z] GC before operation: completed in 1290.802 ms, heap usage 407.017 MB -> 88.582 MB. [2025-11-26T22:47:21.124Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:47:34.153Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:47:49.358Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:48:00.552Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:48:08.159Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:48:15.518Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:48:21.555Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:48:25.435Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:48:27.245Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T22:48:27.245Z] The best model improves the baseline by 14.52%. [2025-11-26T22:48:27.710Z] Top recommended movies for user id 72: [2025-11-26T22:48:27.710Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:48:27.710Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:48:27.710Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:48:27.710Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:48:27.710Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:48:27.710Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (82360.275 ms) ====== [2025-11-26T22:48:27.710Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-26T22:48:27.710Z] GC before operation: completed in 223.235 ms, heap usage 320.695 MB -> 88.906 MB. [2025-11-26T22:48:40.025Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:48:52.312Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:49:04.936Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:49:14.864Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:49:21.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:49:27.545Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:49:32.470Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:49:36.321Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:49:37.427Z] 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. [2025-11-26T22:49:37.902Z] The best model improves the baseline by 14.52%. [2025-11-26T22:49:37.902Z] Top recommended movies for user id 72: [2025-11-26T22:49:37.902Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:49:37.902Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:49:37.902Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:49:37.902Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:49:37.902Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:49:37.902Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (70173.559 ms) ====== [2025-11-26T22:49:37.902Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-26T22:49:38.387Z] GC before operation: completed in 379.813 ms, heap usage 1.474 GB -> 94.797 MB. [2025-11-26T22:49:50.801Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:49:58.214Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:50:08.910Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:50:19.422Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:50:25.183Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:50:29.972Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:50:34.779Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:50:39.655Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:50:40.152Z] 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. [2025-11-26T22:50:40.152Z] The best model improves the baseline by 14.52%. [2025-11-26T22:50:40.152Z] Top recommended movies for user id 72: [2025-11-26T22:50:40.152Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:50:40.152Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:50:40.152Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:50:40.152Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:50:40.152Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:50:40.152Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (61882.528 ms) ====== [2025-11-26T22:50:40.152Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-26T22:50:40.678Z] GC before operation: completed in 270.601 ms, heap usage 713.992 MB -> 92.900 MB. [2025-11-26T22:50:51.160Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:51:03.453Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:51:12.204Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:51:19.065Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:51:25.269Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:51:31.364Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:51:37.831Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:51:42.474Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:51:44.075Z] 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. [2025-11-26T22:51:44.075Z] The best model improves the baseline by 14.52%. [2025-11-26T22:51:44.075Z] Top recommended movies for user id 72: [2025-11-26T22:51:44.075Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:51:44.075Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:51:44.075Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:51:44.075Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:51:44.075Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:51:44.075Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (63620.863 ms) ====== [2025-11-26T22:51:44.075Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-26T22:51:44.596Z] GC before operation: completed in 494.147 ms, heap usage 732.184 MB -> 92.866 MB. [2025-11-26T22:51:54.742Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:52:05.886Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:52:24.078Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:52:34.258Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:52:41.588Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:52:50.214Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:52:54.797Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:53:00.675Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:53:01.896Z] 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. [2025-11-26T22:53:01.896Z] The best model improves the baseline by 14.52%. [2025-11-26T22:53:01.896Z] Top recommended movies for user id 72: [2025-11-26T22:53:01.896Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:53:01.896Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:53:01.896Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:53:01.896Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:53:01.896Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:53:01.896Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (77338.461 ms) ====== [2025-11-26T22:53:01.896Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-26T22:53:02.357Z] GC before operation: completed in 202.826 ms, heap usage 1.657 GB -> 96.320 MB. [2025-11-26T22:53:14.530Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:53:32.007Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:53:46.653Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:54:04.493Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:54:10.635Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:54:19.510Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:54:25.467Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:54:31.306Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:54:33.543Z] 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. [2025-11-26T22:54:33.543Z] The best model improves the baseline by 14.52%. [2025-11-26T22:54:34.052Z] Top recommended movies for user id 72: [2025-11-26T22:54:34.052Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:54:34.052Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:54:34.052Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:54:34.052Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:54:34.052Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:54:34.052Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (91695.518 ms) ====== [2025-11-26T22:54:34.052Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-26T22:54:34.052Z] GC before operation: completed in 336.301 ms, heap usage 529.383 MB -> 89.452 MB. [2025-11-26T22:54:52.467Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:55:06.963Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:55:21.898Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:55:32.887Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:55:39.902Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:55:45.587Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:55:52.897Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:56:00.448Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:56:01.705Z] 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. [2025-11-26T22:56:01.706Z] The best model improves the baseline by 14.52%. [2025-11-26T22:56:02.239Z] Top recommended movies for user id 72: [2025-11-26T22:56:02.239Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:56:02.239Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:56:02.239Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:56:02.239Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:56:02.239Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:56:02.239Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (87819.208 ms) ====== [2025-11-26T22:56:02.239Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-26T22:56:02.749Z] GC before operation: completed in 471.360 ms, heap usage 1.881 GB -> 95.597 MB. [2025-11-26T22:56:18.553Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:56:33.970Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:56:46.694Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:56:59.833Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:57:06.030Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:57:16.638Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:57:23.962Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:57:29.883Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:57:30.805Z] 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. [2025-11-26T22:57:30.805Z] The best model improves the baseline by 14.52%. [2025-11-26T22:57:31.289Z] Top recommended movies for user id 72: [2025-11-26T22:57:31.289Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:57:31.289Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:57:31.289Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:57:31.289Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:57:31.289Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:57:31.289Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (88893.445 ms) ====== [2025-11-26T22:57:31.289Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-26T22:57:32.367Z] GC before operation: completed in 763.104 ms, heap usage 443.594 MB -> 89.268 MB. [2025-11-26T22:57:44.688Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:57:58.113Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:58:08.727Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:58:21.301Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:58:26.120Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:58:30.721Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:58:37.686Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:58:42.168Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:58:43.756Z] 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. [2025-11-26T22:58:43.756Z] The best model improves the baseline by 14.52%. [2025-11-26T22:58:43.756Z] Top recommended movies for user id 72: [2025-11-26T22:58:43.756Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:58:43.756Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:58:43.756Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:58:43.756Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:58:43.756Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:58:43.756Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (71793.575 ms) ====== [2025-11-26T22:58:43.756Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-26T22:58:44.168Z] GC before operation: completed in 313.248 ms, heap usage 1.593 GB -> 95.454 MB. [2025-11-26T22:58:59.220Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T22:59:08.137Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T22:59:20.763Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T22:59:29.292Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T22:59:34.632Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T22:59:39.459Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T22:59:45.140Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T22:59:49.959Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T22:59:50.418Z] 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. [2025-11-26T22:59:50.418Z] The best model improves the baseline by 14.52%. [2025-11-26T22:59:50.874Z] Top recommended movies for user id 72: [2025-11-26T22:59:50.874Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T22:59:50.874Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T22:59:50.874Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T22:59:50.874Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T22:59:50.874Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T22:59:50.874Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (66484.491 ms) ====== [2025-11-26T22:59:50.875Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-26T22:59:50.875Z] GC before operation: completed in 232.875 ms, heap usage 133.657 MB -> 92.278 MB. [2025-11-26T23:00:03.127Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:00:12.533Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:00:27.411Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:00:37.397Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:00:42.794Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:00:51.395Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:01:00.876Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:01:07.729Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:01:07.729Z] 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. [2025-11-26T23:01:07.729Z] The best model improves the baseline by 14.52%. [2025-11-26T23:01:09.443Z] Top recommended movies for user id 72: [2025-11-26T23:01:09.443Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:01:09.443Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:01:09.443Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:01:09.443Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:01:09.443Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:01:09.443Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (76873.807 ms) ====== [2025-11-26T23:01:09.443Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-26T23:01:09.443Z] GC before operation: completed in 926.508 ms, heap usage 1.569 GB -> 95.355 MB. [2025-11-26T23:01:22.402Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:01:35.543Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:01:49.018Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:02:02.365Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:02:09.133Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:02:16.613Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:02:24.110Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:02:31.167Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:02:31.660Z] 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. [2025-11-26T23:02:31.660Z] The best model improves the baseline by 14.52%. [2025-11-26T23:02:31.660Z] Top recommended movies for user id 72: [2025-11-26T23:02:31.661Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:02:31.661Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:02:31.661Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:02:31.661Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:02:31.661Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:02:31.661Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (82997.278 ms) ====== [2025-11-26T23:02:31.661Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-26T23:02:44.737Z] GC before operation: completed in 886.431 ms, heap usage 665.500 MB -> 93.284 MB. [2025-11-26T23:02:47.253Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:03:00.215Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:03:13.259Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:03:23.928Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:03:32.882Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:03:44.075Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:03:51.282Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:03:58.866Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:03:59.403Z] 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. [2025-11-26T23:03:59.403Z] The best model improves the baseline by 14.52%. [2025-11-26T23:03:59.403Z] Top recommended movies for user id 72: [2025-11-26T23:03:59.403Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:03:59.403Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:03:59.403Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:03:59.403Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:03:59.403Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:03:59.403Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (86854.827 ms) ====== [2025-11-26T23:03:59.403Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-26T23:03:59.909Z] GC before operation: completed in 335.361 ms, heap usage 935.253 MB -> 93.993 MB. [2025-11-26T23:04:15.351Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:04:26.117Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:04:38.966Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:04:53.709Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:05:02.606Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:05:09.995Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:05:17.066Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:05:22.284Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:05:23.919Z] 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. [2025-11-26T23:05:24.377Z] The best model improves the baseline by 14.52%. [2025-11-26T23:05:24.377Z] Top recommended movies for user id 72: [2025-11-26T23:05:24.377Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:05:24.377Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:05:24.377Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:05:24.377Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:05:24.377Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:05:24.377Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (84654.919 ms) ====== [2025-11-26T23:05:24.377Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-26T23:05:24.846Z] GC before operation: completed in 233.222 ms, heap usage 1.141 GB -> 94.856 MB. [2025-11-26T23:05:37.877Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:05:54.170Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:06:07.120Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:06:22.663Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:06:31.487Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:06:37.647Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:06:43.746Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:06:48.643Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:06:48.643Z] 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. [2025-11-26T23:06:48.643Z] The best model improves the baseline by 14.52%. [2025-11-26T23:06:48.643Z] Top recommended movies for user id 72: [2025-11-26T23:06:48.643Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:06:48.643Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:06:48.643Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:06:48.643Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:06:48.643Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:06:48.643Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (84027.446 ms) ====== [2025-11-26T23:06:48.643Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-26T23:06:49.120Z] GC before operation: completed in 413.101 ms, heap usage 1.581 GB -> 95.365 MB. [2025-11-26T23:07:01.775Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:07:10.364Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:07:22.867Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:07:37.484Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:07:44.570Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:07:50.591Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:07:56.681Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:08:01.344Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:08:01.344Z] 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. [2025-11-26T23:08:01.344Z] The best model improves the baseline by 14.52%. [2025-11-26T23:08:01.901Z] Top recommended movies for user id 72: [2025-11-26T23:08:01.901Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:08:01.901Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:08:01.901Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:08:01.901Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:08:01.901Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:08:01.901Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (72597.828 ms) ====== [2025-11-26T23:08:01.901Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-26T23:08:02.355Z] GC before operation: completed in 439.565 ms, heap usage 1.611 GB -> 95.460 MB. [2025-11-26T23:08:14.953Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:08:22.141Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:08:37.437Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:08:47.749Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:08:51.390Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:08:56.064Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:09:00.714Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:09:05.358Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:09:05.781Z] 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. [2025-11-26T23:09:05.781Z] The best model improves the baseline by 14.52%. [2025-11-26T23:09:05.781Z] Top recommended movies for user id 72: [2025-11-26T23:09:05.781Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:09:05.781Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:09:05.781Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:09:05.781Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:09:05.781Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:09:05.781Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (63702.014 ms) ====== [2025-11-26T23:09:08.590Z] ----------------------------------- [2025-11-26T23:09:08.590Z] renaissance-movie-lens_0_PASSED [2025-11-26T23:09:08.590Z] ----------------------------------- [2025-11-26T23:09:08.590Z] [2025-11-26T23:09:08.590Z] TEST TEARDOWN: [2025-11-26T23:09:08.590Z] Nothing to be done for teardown. [2025-11-26T23:09:08.590Z] renaissance-movie-lens_0 Finish Time: Wed Nov 26 15:09:08 2025 Epoch Time (ms): 1764198548072