Test Results Summary Service

renaissance-movie-lens_0

[2025-12-27T12:57:24.385Z] Running test renaissance-movie-lens_0 ... [2025-12-27T12:57:24.385Z] =============================================== [2025-12-27T12:57:24.385Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 07:57:24 2025 Epoch Time (ms): 1766840244226 [2025-12-27T12:57:24.385Z] variation: NoOptions [2025-12-27T12:57:24.385Z] JVM_OPTIONS: [2025-12-27T12:57:24.385Z] { \ [2025-12-27T12:57:24.385Z] echo ""; echo "TEST SETUP:"; \ [2025-12-27T12:57:24.385Z] echo "Nothing to be done for setup."; \ [2025-12-27T12:57:24.385Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17668396191782/renaissance-movie-lens_0"; \ [2025-12-27T12:57:24.385Z] cd "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17668396191782/renaissance-movie-lens_0"; \ [2025-12-27T12:57:24.385Z] echo ""; echo "TESTING:"; \ [2025-12-27T12:57:24.385Z] "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_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_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17668396191782/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-27T12:57:24.385Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17668396191782/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-27T12:57:24.385Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-27T12:57:24.385Z] echo "Nothing to be done for teardown."; \ [2025-12-27T12:57:24.385Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17668396191782/TestTargetResult"; [2025-12-27T12:57:24.385Z] [2025-12-27T12:57:24.385Z] TEST SETUP: [2025-12-27T12:57:24.385Z] Nothing to be done for setup. [2025-12-27T12:57:24.385Z] [2025-12-27T12:57:24.385Z] TESTING: [2025-12-27T12:57:24.737Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-27T12:57:24.737Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_aarch64_mac/aqa-tests/TKG/output_17668396191782/renaissance-movie-lens_0/launcher-075724-9737612199064859624/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-27T12:57:24.737Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-27T12:57:24.737Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-27T12:57:28.732Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-27T12:57:32.718Z] 07:57:32.666 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-27T12:57:33.957Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-27T12:57:34.323Z] Training: 60056, validation: 20285, test: 19854 [2025-12-27T12:57:34.323Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-27T12:57:34.323Z] GC before operation: completed in 81.598 ms, heap usage 299.500 MB -> 76.013 MB. [2025-12-27T12:57:37.600Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:57:39.410Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:57:41.195Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:57:42.430Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:57:43.242Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:57:43.999Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:57:44.774Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:57:45.545Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:57:45.545Z] 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. [2025-12-27T12:57:45.900Z] The best model improves the baseline by 14.52%. [2025-12-27T12:57:45.900Z] Top recommended movies for user id 72: [2025-12-27T12:57:45.900Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:57:45.900Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:57:45.900Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:57:45.900Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:57:45.900Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:57:45.900Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (11561.667 ms) ====== [2025-12-27T12:57:45.900Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-27T12:57:45.900Z] GC before operation: completed in 52.993 ms, heap usage 431.453 MB -> 93.646 MB. [2025-12-27T12:57:47.142Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:57:48.414Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:57:49.662Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:57:50.933Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:57:51.710Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:57:52.483Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:57:53.257Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:57:54.068Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:57:54.068Z] 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. [2025-12-27T12:57:54.068Z] The best model improves the baseline by 14.52%. [2025-12-27T12:57:54.068Z] Top recommended movies for user id 72: [2025-12-27T12:57:54.068Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:57:54.068Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:57:54.068Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:57:54.068Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:57:54.068Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:57:54.068Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8353.895 ms) ====== [2025-12-27T12:57:54.068Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-27T12:57:54.482Z] GC before operation: completed in 52.230 ms, heap usage 306.478 MB -> 88.964 MB. [2025-12-27T12:57:55.707Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:57:56.974Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:57:58.202Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:57:59.434Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:58:00.219Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:58:01.005Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:58:01.385Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:58:02.171Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:58:02.171Z] 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. [2025-12-27T12:58:02.527Z] The best model improves the baseline by 14.52%. [2025-12-27T12:58:02.527Z] Top recommended movies for user id 72: [2025-12-27T12:58:02.527Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:58:02.527Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:58:02.527Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:58:02.527Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:58:02.527Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:58:02.527Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (8134.119 ms) ====== [2025-12-27T12:58:02.527Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-27T12:58:02.527Z] GC before operation: completed in 58.798 ms, heap usage 336.999 MB -> 89.777 MB. [2025-12-27T12:58:03.791Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:58:05.075Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:58:06.907Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:58:08.185Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:58:08.563Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:58:09.860Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:58:10.686Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:58:11.546Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:58:11.546Z] 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. [2025-12-27T12:58:11.546Z] The best model improves the baseline by 14.52%. [2025-12-27T12:58:11.546Z] Top recommended movies for user id 72: [2025-12-27T12:58:11.546Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:58:11.546Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:58:11.546Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:58:11.546Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:58:11.546Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:58:11.546Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9165.073 ms) ====== [2025-12-27T12:58:11.546Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-27T12:58:11.546Z] GC before operation: completed in 49.652 ms, heap usage 338.894 MB -> 90.030 MB. [2025-12-27T12:58:12.818Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:58:14.607Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:58:15.843Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:58:17.094Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:58:17.871Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:58:19.113Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:58:19.884Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:58:20.645Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:58:20.646Z] 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. [2025-12-27T12:58:20.646Z] The best model improves the baseline by 14.52%. [2025-12-27T12:58:20.646Z] Top recommended movies for user id 72: [2025-12-27T12:58:20.646Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:58:20.646Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:58:20.646Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:58:20.646Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:58:20.646Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:58:20.646Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (9074.335 ms) ====== [2025-12-27T12:58:20.646Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-27T12:58:20.646Z] GC before operation: completed in 48.220 ms, heap usage 296.750 MB -> 89.976 MB. [2025-12-27T12:58:22.411Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:58:23.651Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:58:25.413Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:58:26.206Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:58:27.456Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:58:28.234Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:58:28.610Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:58:29.395Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:58:29.395Z] 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. [2025-12-27T12:58:29.395Z] The best model improves the baseline by 14.52%. [2025-12-27T12:58:29.758Z] Top recommended movies for user id 72: [2025-12-27T12:58:29.758Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:58:29.758Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:58:29.758Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:58:29.758Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:58:29.758Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:58:29.758Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8811.495 ms) ====== [2025-12-27T12:58:29.758Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-27T12:58:29.758Z] GC before operation: completed in 46.188 ms, heap usage 418.778 MB -> 90.496 MB. [2025-12-27T12:58:31.257Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:58:32.528Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:58:34.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:58:36.089Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:58:36.890Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:58:38.130Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:58:38.907Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:58:40.165Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:58:40.165Z] 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. [2025-12-27T12:58:40.165Z] The best model improves the baseline by 14.52%. [2025-12-27T12:58:40.521Z] Top recommended movies for user id 72: [2025-12-27T12:58:40.521Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:58:40.521Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:58:40.521Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:58:40.521Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:58:40.521Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:58:40.521Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (10750.807 ms) ====== [2025-12-27T12:58:40.521Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-27T12:58:40.521Z] GC before operation: completed in 71.497 ms, heap usage 366.646 MB -> 90.360 MB. [2025-12-27T12:58:42.481Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:58:43.897Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:58:45.712Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:58:46.978Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:58:47.798Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:58:49.080Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:58:49.842Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:58:51.088Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:58:51.088Z] 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. [2025-12-27T12:58:51.088Z] The best model improves the baseline by 14.52%. [2025-12-27T12:58:51.088Z] Top recommended movies for user id 72: [2025-12-27T12:58:51.088Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:58:51.088Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:58:51.088Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:58:51.088Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:58:51.088Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:58:51.088Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (10727.927 ms) ====== [2025-12-27T12:58:51.088Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-27T12:58:51.453Z] GC before operation: completed in 61.670 ms, heap usage 386.377 MB -> 90.591 MB. [2025-12-27T12:58:52.720Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:58:54.523Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:58:56.355Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:58:57.586Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:58:58.368Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:58:59.645Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:59:00.442Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:59:01.253Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:59:01.653Z] 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. [2025-12-27T12:59:01.653Z] The best model improves the baseline by 14.52%. [2025-12-27T12:59:01.653Z] Top recommended movies for user id 72: [2025-12-27T12:59:01.653Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:59:01.653Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:59:01.653Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:59:01.653Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:59:01.653Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:59:01.653Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (10329.181 ms) ====== [2025-12-27T12:59:01.653Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-27T12:59:01.653Z] GC before operation: completed in 67.412 ms, heap usage 358.305 MB -> 90.492 MB. [2025-12-27T12:59:03.482Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:59:04.805Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:59:06.630Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:59:08.443Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:59:09.231Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:59:10.484Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:59:11.377Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:59:12.147Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:59:12.147Z] 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. [2025-12-27T12:59:12.147Z] The best model improves the baseline by 14.52%. [2025-12-27T12:59:12.525Z] Top recommended movies for user id 72: [2025-12-27T12:59:12.525Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:59:12.525Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:59:12.525Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:59:12.525Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:59:12.525Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:59:12.525Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (10719.027 ms) ====== [2025-12-27T12:59:12.525Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-27T12:59:12.525Z] GC before operation: completed in 72.084 ms, heap usage 297.873 MB -> 90.603 MB. [2025-12-27T12:59:14.305Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:59:15.568Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:59:17.394Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:59:19.200Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:59:19.991Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:59:20.766Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:59:22.018Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:59:22.803Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:59:23.162Z] 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. [2025-12-27T12:59:23.162Z] The best model improves the baseline by 14.52%. [2025-12-27T12:59:23.162Z] Top recommended movies for user id 72: [2025-12-27T12:59:23.162Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:59:23.162Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:59:23.162Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:59:23.162Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:59:23.162Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:59:23.162Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (10692.447 ms) ====== [2025-12-27T12:59:23.162Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-27T12:59:23.162Z] GC before operation: completed in 69.456 ms, heap usage 103.468 MB -> 89.964 MB. [2025-12-27T12:59:24.952Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:59:27.400Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:59:28.864Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:59:30.685Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:59:31.498Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:59:32.276Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:59:33.048Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:59:34.379Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:59:34.379Z] 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. [2025-12-27T12:59:34.379Z] The best model improves the baseline by 14.52%. [2025-12-27T12:59:34.379Z] Top recommended movies for user id 72: [2025-12-27T12:59:34.379Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:59:34.379Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:59:34.379Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:59:34.379Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:59:34.379Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:59:34.379Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (11199.285 ms) ====== [2025-12-27T12:59:34.379Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-27T12:59:34.379Z] GC before operation: completed in 61.802 ms, heap usage 497.842 MB -> 90.765 MB. [2025-12-27T12:59:36.199Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:59:37.996Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:59:39.804Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:59:41.063Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:59:42.356Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:59:43.159Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:59:43.959Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:59:44.752Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:59:45.135Z] 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. [2025-12-27T12:59:45.135Z] The best model improves the baseline by 14.52%. [2025-12-27T12:59:45.135Z] Top recommended movies for user id 72: [2025-12-27T12:59:45.135Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:59:45.135Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:59:45.135Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:59:45.135Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:59:45.135Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:59:45.135Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (10728.723 ms) ====== [2025-12-27T12:59:45.135Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-27T12:59:45.135Z] GC before operation: completed in 64.921 ms, heap usage 97.849 MB -> 90.294 MB. [2025-12-27T12:59:46.991Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:59:48.818Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T12:59:50.243Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T12:59:52.078Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T12:59:52.848Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T12:59:54.181Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T12:59:54.986Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T12:59:55.798Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T12:59:55.798Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-27T12:59:55.798Z] The best model improves the baseline by 14.52%. [2025-12-27T12:59:56.190Z] Top recommended movies for user id 72: [2025-12-27T12:59:56.190Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T12:59:56.190Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T12:59:56.190Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T12:59:56.190Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T12:59:56.190Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T12:59:56.190Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (10729.792 ms) ====== [2025-12-27T12:59:56.190Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-27T12:59:56.190Z] GC before operation: completed in 75.979 ms, heap usage 200.330 MB -> 90.257 MB. [2025-12-27T12:59:58.069Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T12:59:59.355Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:00:01.247Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:00:02.267Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:00:03.246Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:00:04.032Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:00:05.298Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:00:06.098Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:00:06.098Z] 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. [2025-12-27T13:00:06.098Z] The best model improves the baseline by 14.52%. [2025-12-27T13:00:06.461Z] Top recommended movies for user id 72: [2025-12-27T13:00:06.461Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:00:06.461Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:00:06.461Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:00:06.461Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:00:06.461Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:00:06.461Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (10212.904 ms) ====== [2025-12-27T13:00:06.461Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-27T13:00:06.461Z] GC before operation: completed in 61.519 ms, heap usage 235.823 MB -> 90.553 MB. [2025-12-27T13:00:07.732Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:00:09.612Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:00:10.887Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:00:12.711Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:00:13.491Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:00:14.732Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:00:15.531Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:00:16.813Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:00:16.813Z] 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. [2025-12-27T13:00:16.813Z] The best model improves the baseline by 14.52%. [2025-12-27T13:00:16.813Z] Top recommended movies for user id 72: [2025-12-27T13:00:16.813Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:00:16.813Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:00:16.813Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:00:16.813Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:00:16.813Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:00:16.813Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (10553.487 ms) ====== [2025-12-27T13:00:16.813Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-27T13:00:17.173Z] GC before operation: completed in 72.932 ms, heap usage 496.641 MB -> 90.841 MB. [2025-12-27T13:00:18.444Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:00:20.265Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:00:22.068Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:00:23.343Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:00:24.573Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:00:25.349Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:00:26.724Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:00:27.722Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:00:27.722Z] 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. [2025-12-27T13:00:27.722Z] The best model improves the baseline by 14.52%. [2025-12-27T13:00:27.722Z] Top recommended movies for user id 72: [2025-12-27T13:00:27.722Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:00:27.722Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:00:27.722Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:00:27.722Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:00:27.722Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:00:27.722Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (10725.090 ms) ====== [2025-12-27T13:00:27.722Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-27T13:00:27.722Z] GC before operation: completed in 68.454 ms, heap usage 97.455 MB -> 94.252 MB. [2025-12-27T13:00:29.541Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:00:30.829Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:00:32.633Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:00:33.914Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:00:35.171Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:00:35.950Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:00:36.716Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:00:38.022Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:00:38.022Z] 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. [2025-12-27T13:00:38.022Z] The best model improves the baseline by 14.52%. [2025-12-27T13:00:38.022Z] Top recommended movies for user id 72: [2025-12-27T13:00:38.022Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:00:38.022Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:00:38.022Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:00:38.022Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:00:38.022Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:00:38.022Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (10137.821 ms) ====== [2025-12-27T13:00:38.022Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-27T13:00:38.022Z] GC before operation: completed in 60.310 ms, heap usage 181.536 MB -> 90.318 MB. [2025-12-27T13:00:39.822Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:00:41.054Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:00:42.865Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:00:44.081Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:00:44.839Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:00:46.090Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:00:46.466Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:00:47.699Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:00:47.699Z] 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. [2025-12-27T13:00:47.699Z] The best model improves the baseline by 14.52%. [2025-12-27T13:00:47.699Z] Top recommended movies for user id 72: [2025-12-27T13:00:47.699Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:00:47.699Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:00:47.699Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:00:47.699Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:00:47.699Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:00:47.699Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (9801.068 ms) ====== [2025-12-27T13:00:47.699Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-27T13:00:47.699Z] GC before operation: completed in 60.432 ms, heap usage 351.263 MB -> 90.692 MB. [2025-12-27T13:00:49.457Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-27T13:00:50.716Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-27T13:00:52.506Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-27T13:00:53.754Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-27T13:00:55.025Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-27T13:00:55.803Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-27T13:00:56.585Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-27T13:00:57.397Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-27T13:00:57.752Z] 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. [2025-12-27T13:00:57.752Z] The best model improves the baseline by 14.52%. [2025-12-27T13:00:57.752Z] Top recommended movies for user id 72: [2025-12-27T13:00:57.752Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-27T13:00:57.752Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-27T13:00:57.752Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-27T13:00:57.752Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-27T13:00:57.752Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-27T13:00:57.752Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (9875.019 ms) ====== [2025-12-27T13:00:58.110Z] ----------------------------------- [2025-12-27T13:00:58.110Z] renaissance-movie-lens_0_PASSED [2025-12-27T13:00:58.110Z] ----------------------------------- [2025-12-27T13:00:58.110Z] [2025-12-27T13:00:58.110Z] TEST TEARDOWN: [2025-12-27T13:00:58.110Z] Nothing to be done for teardown. [2025-12-27T13:00:58.110Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 08:00:57 2025 Epoch Time (ms): 1766840457907