[2025-07-02T13:40:10.336Z] Running test renaissance-movie-lens_0 ... [2025-07-02T13:40:10.336Z] =============================================== [2025-07-02T13:40:10.336Z] renaissance-movie-lens_0 Start Time: Wed Jul 2 09:40:10 2025 Epoch Time (ms): 1751463610092 [2025-07-02T13:40:10.336Z] variation: NoOptions [2025-07-02T13:40:10.336Z] JVM_OPTIONS: [2025-07-02T13:40:10.336Z] { \ [2025-07-02T13:40:10.336Z] echo ""; echo "TEST SETUP:"; \ [2025-07-02T13:40:10.336Z] echo "Nothing to be done for setup."; \ [2025-07-02T13:40:10.336Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17514630069594/renaissance-movie-lens_0"; \ [2025-07-02T13:40:10.336Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17514630069594/renaissance-movie-lens_0"; \ [2025-07-02T13:40:10.336Z] echo ""; echo "TESTING:"; \ [2025-07-02T13:40:10.336Z] "/Users/admin/workspace/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17514630069594/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-07-02T13:40:10.336Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17514630069594/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-07-02T13:40:10.336Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-07-02T13:40:10.336Z] echo "Nothing to be done for teardown."; \ [2025-07-02T13:40:10.336Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17514630069594/TestTargetResult"; [2025-07-02T13:40:10.336Z] [2025-07-02T13:40:10.336Z] TEST SETUP: [2025-07-02T13:40:10.336Z] Nothing to be done for setup. [2025-07-02T13:40:10.336Z] [2025-07-02T13:40:10.336Z] TESTING: [2025-07-02T13:40:13.506Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-07-02T13:40:16.612Z] 09:40:16.280 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB. [2025-07-02T13:40:17.896Z] Got 100004 ratings from 671 users on 9066 movies. [2025-07-02T13:40:17.896Z] Training: 60056, validation: 20285, test: 19854 [2025-07-02T13:40:17.896Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-07-02T13:40:17.896Z] GC before operation: completed in 60.915 ms, heap usage 375.435 MB -> 75.743 MB. [2025-07-02T13:40:21.928Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:40:23.692Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:40:25.479Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:40:26.699Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:40:27.916Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:40:28.688Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:40:29.514Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:40:30.779Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:40:30.779Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:40:30.779Z] The best model improves the baseline by 14.52%. [2025-07-02T13:40:30.779Z] Top recommended movies for user id 72: [2025-07-02T13:40:30.779Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:40:30.779Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:40:30.779Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:40:30.779Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:40:30.779Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:40:30.779Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (12747.384 ms) ====== [2025-07-02T13:40:30.779Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-07-02T13:40:30.779Z] GC before operation: completed in 53.097 ms, heap usage 406.987 MB -> 91.491 MB. [2025-07-02T13:40:32.541Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:40:33.763Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:40:34.994Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:40:36.236Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:40:37.002Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:40:37.769Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:40:38.534Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:40:39.308Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:40:39.659Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:40:39.659Z] The best model improves the baseline by 14.52%. [2025-07-02T13:40:39.659Z] Top recommended movies for user id 72: [2025-07-02T13:40:39.659Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:40:39.659Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:40:39.659Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:40:39.659Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:40:39.659Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:40:39.659Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8724.827 ms) ====== [2025-07-02T13:40:39.659Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-07-02T13:40:39.660Z] GC before operation: completed in 51.313 ms, heap usage 120.250 MB -> 91.371 MB. [2025-07-02T13:40:40.882Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:40:42.117Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:40:43.351Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:40:44.602Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:40:45.364Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:40:46.125Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:40:46.906Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:40:47.661Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:40:47.661Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:40:47.661Z] The best model improves the baseline by 14.52%. [2025-07-02T13:40:47.661Z] Top recommended movies for user id 72: [2025-07-02T13:40:47.661Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:40:47.661Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:40:47.661Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:40:47.661Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:40:47.661Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:40:47.661Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (8114.251 ms) ====== [2025-07-02T13:40:47.661Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-07-02T13:40:47.661Z] GC before operation: completed in 55.047 ms, heap usage 405.972 MB -> 89.078 MB. [2025-07-02T13:40:48.897Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:40:50.202Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:40:51.459Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:40:52.684Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:40:53.443Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:40:54.204Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:40:54.975Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:40:55.741Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:40:55.741Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:40:55.741Z] The best model improves the baseline by 14.52%. [2025-07-02T13:40:55.741Z] Top recommended movies for user id 72: [2025-07-02T13:40:55.741Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:40:55.741Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:40:55.741Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:40:55.741Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:40:55.741Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:40:55.741Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (7948.085 ms) ====== [2025-07-02T13:40:55.741Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-07-02T13:40:55.741Z] GC before operation: completed in 51.570 ms, heap usage 97.568 MB -> 91.211 MB. [2025-07-02T13:40:56.974Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:40:58.217Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:40:59.445Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:41:00.697Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:41:01.070Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:41:01.845Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:41:02.621Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:41:03.005Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:41:03.005Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:41:03.005Z] The best model improves the baseline by 14.52%. [2025-07-02T13:41:03.386Z] Top recommended movies for user id 72: [2025-07-02T13:41:03.386Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:41:03.386Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:41:03.386Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:41:03.386Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:41:03.386Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:41:03.386Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (7381.449 ms) ====== [2025-07-02T13:41:03.386Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-07-02T13:41:03.386Z] GC before operation: completed in 46.740 ms, heap usage 346.824 MB -> 89.351 MB. [2025-07-02T13:41:04.155Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:41:05.396Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:41:06.644Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:41:07.404Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:41:08.175Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:41:08.538Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:41:09.295Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:41:09.669Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:41:10.053Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:41:10.053Z] The best model improves the baseline by 14.52%. [2025-07-02T13:41:10.053Z] Top recommended movies for user id 72: [2025-07-02T13:41:10.053Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:41:10.053Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:41:10.053Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:41:10.053Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:41:10.053Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:41:10.053Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (6726.138 ms) ====== [2025-07-02T13:41:10.053Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-07-02T13:41:10.053Z] GC before operation: completed in 44.681 ms, heap usage 102.109 MB -> 89.683 MB. [2025-07-02T13:41:11.090Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:41:12.348Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:41:13.605Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:41:14.365Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:41:15.123Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:41:15.887Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:41:16.249Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:41:17.026Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:41:17.026Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:41:17.026Z] The best model improves the baseline by 14.52%. [2025-07-02T13:41:17.026Z] Top recommended movies for user id 72: [2025-07-02T13:41:17.026Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:41:17.026Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:41:17.026Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:41:17.026Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:41:17.026Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:41:17.026Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (7155.546 ms) ====== [2025-07-02T13:41:17.026Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-07-02T13:41:17.389Z] GC before operation: completed in 48.152 ms, heap usage 225.370 MB -> 91.307 MB. [2025-07-02T13:41:18.629Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:41:19.394Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:41:20.629Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:41:21.865Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:41:22.635Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:41:23.521Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:41:24.277Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:41:25.516Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:41:25.516Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:41:25.516Z] The best model improves the baseline by 14.52%. [2025-07-02T13:41:25.516Z] Top recommended movies for user id 72: [2025-07-02T13:41:25.516Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:41:25.516Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:41:25.516Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:41:25.516Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:41:25.516Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:41:25.516Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (8262.603 ms) ====== [2025-07-02T13:41:25.516Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-07-02T13:41:25.516Z] GC before operation: completed in 61.917 ms, heap usage 472.010 MB -> 90.182 MB. [2025-07-02T13:41:26.760Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:41:28.074Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:41:29.871Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:41:31.118Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:41:31.498Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:41:32.254Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:41:33.101Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:41:33.895Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:41:33.895Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:41:34.247Z] The best model improves the baseline by 14.52%. [2025-07-02T13:41:34.247Z] Top recommended movies for user id 72: [2025-07-02T13:41:34.247Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:41:34.247Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:41:34.247Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:41:34.247Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:41:34.247Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:41:34.247Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8614.120 ms) ====== [2025-07-02T13:41:34.247Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-07-02T13:41:34.247Z] GC before operation: completed in 54.336 ms, heap usage 271.240 MB -> 89.710 MB. [2025-07-02T13:41:35.460Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:41:36.691Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:41:37.951Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:41:38.712Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:41:39.461Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:41:39.826Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:41:40.589Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:41:41.348Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:41:41.348Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:41:41.348Z] The best model improves the baseline by 14.52%. [2025-07-02T13:41:41.348Z] Top recommended movies for user id 72: [2025-07-02T13:41:41.348Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:41:41.348Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:41:41.348Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:41:41.348Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:41:41.348Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:41:41.348Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (7156.987 ms) ====== [2025-07-02T13:41:41.348Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-07-02T13:41:41.348Z] GC before operation: completed in 50.271 ms, heap usage 157.029 MB -> 90.905 MB. [2025-07-02T13:41:42.578Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:41:43.798Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:41:44.555Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:41:45.773Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:41:46.130Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:41:46.889Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:41:47.663Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:41:48.026Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:41:48.389Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:41:48.389Z] The best model improves the baseline by 14.52%. [2025-07-02T13:41:48.389Z] Top recommended movies for user id 72: [2025-07-02T13:41:48.389Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:41:48.389Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:41:48.389Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:41:48.389Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:41:48.389Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:41:48.389Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (6978.234 ms) ====== [2025-07-02T13:41:48.389Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-07-02T13:41:48.389Z] GC before operation: completed in 53.078 ms, heap usage 507.405 MB -> 93.370 MB. [2025-07-02T13:41:49.618Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:41:50.830Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:41:52.066Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:41:52.828Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:41:53.597Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:41:53.955Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:41:54.724Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:41:55.506Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:41:55.506Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:41:55.506Z] The best model improves the baseline by 14.52%. [2025-07-02T13:41:55.506Z] Top recommended movies for user id 72: [2025-07-02T13:41:55.506Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:41:55.506Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:41:55.506Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:41:55.506Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:41:55.506Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:41:55.506Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (6995.346 ms) ====== [2025-07-02T13:41:55.506Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-07-02T13:41:55.506Z] GC before operation: completed in 46.380 ms, heap usage 308.618 MB -> 89.920 MB. [2025-07-02T13:41:56.743Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:41:58.045Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:41:58.811Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:42:00.026Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:42:00.794Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:42:01.153Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:42:01.920Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:42:02.739Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:42:02.739Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:42:02.739Z] The best model improves the baseline by 14.52%. [2025-07-02T13:42:02.739Z] Top recommended movies for user id 72: [2025-07-02T13:42:02.739Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:42:02.739Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:42:02.739Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:42:02.739Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:42:02.739Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:42:02.739Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (7163.513 ms) ====== [2025-07-02T13:42:02.739Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-07-02T13:42:02.739Z] GC before operation: completed in 45.884 ms, heap usage 116.959 MB -> 89.702 MB. [2025-07-02T13:42:04.010Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:42:04.803Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:42:06.035Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:42:06.791Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:42:07.556Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:42:08.328Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:42:09.085Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:42:09.855Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:42:09.855Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:42:09.855Z] The best model improves the baseline by 14.52%. [2025-07-02T13:42:09.855Z] Top recommended movies for user id 72: [2025-07-02T13:42:09.855Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:42:09.855Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:42:09.855Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:42:09.855Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:42:09.855Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:42:09.855Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (7101.247 ms) ====== [2025-07-02T13:42:09.855Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-07-02T13:42:09.855Z] GC before operation: completed in 48.974 ms, heap usage 239.584 MB -> 91.485 MB. [2025-07-02T13:42:11.164Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:42:11.944Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:42:12.748Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:42:14.016Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:42:14.378Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:42:15.208Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:42:16.003Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:42:16.393Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:42:16.393Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:42:16.393Z] The best model improves the baseline by 14.52%. [2025-07-02T13:42:16.393Z] Top recommended movies for user id 72: [2025-07-02T13:42:16.393Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:42:16.393Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:42:16.393Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:42:16.393Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:42:16.393Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:42:16.393Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (6660.542 ms) ====== [2025-07-02T13:42:16.393Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-07-02T13:42:16.393Z] GC before operation: completed in 48.597 ms, heap usage 477.348 MB -> 90.268 MB. [2025-07-02T13:42:17.630Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:42:18.266Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:42:19.539Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:42:20.323Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:42:20.681Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:42:21.437Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:42:22.210Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:42:22.980Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:42:22.980Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:42:22.980Z] The best model improves the baseline by 14.52%. [2025-07-02T13:42:22.980Z] Top recommended movies for user id 72: [2025-07-02T13:42:22.981Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:42:22.981Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:42:22.981Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:42:22.981Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:42:22.981Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:42:22.981Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (6382.503 ms) ====== [2025-07-02T13:42:22.981Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-07-02T13:42:22.981Z] GC before operation: completed in 49.038 ms, heap usage 207.918 MB -> 89.719 MB. [2025-07-02T13:42:24.228Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:42:24.999Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:42:26.241Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:42:27.472Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:42:28.303Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:42:28.656Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:42:29.422Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:42:30.187Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:42:30.548Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:42:30.548Z] The best model improves the baseline by 14.52%. [2025-07-02T13:42:30.548Z] Top recommended movies for user id 72: [2025-07-02T13:42:30.548Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:42:30.548Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:42:30.548Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:42:30.548Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:42:30.548Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:42:30.548Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (7487.093 ms) ====== [2025-07-02T13:42:30.548Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-07-02T13:42:30.548Z] GC before operation: completed in 63.824 ms, heap usage 432.781 MB -> 90.133 MB. [2025-07-02T13:42:31.844Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:42:33.070Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:42:34.384Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:42:35.633Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:42:36.414Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:42:36.772Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:42:37.554Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:42:38.322Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:42:38.677Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:42:38.677Z] The best model improves the baseline by 14.52%. [2025-07-02T13:42:38.677Z] Top recommended movies for user id 72: [2025-07-02T13:42:38.677Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:42:38.677Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:42:38.677Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:42:38.677Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:42:38.677Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:42:38.677Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8060.135 ms) ====== [2025-07-02T13:42:38.677Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-07-02T13:42:38.677Z] GC before operation: completed in 64.945 ms, heap usage 110.621 MB -> 89.640 MB. [2025-07-02T13:42:39.932Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:42:41.691Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:42:42.984Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:42:43.756Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:42:44.534Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:42:45.298Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:42:46.067Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:42:46.831Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:42:46.832Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:42:46.832Z] The best model improves the baseline by 14.52%. [2025-07-02T13:42:47.198Z] Top recommended movies for user id 72: [2025-07-02T13:42:47.198Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:42:47.198Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:42:47.198Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:42:47.198Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:42:47.198Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:42:47.198Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8401.115 ms) ====== [2025-07-02T13:42:47.198Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-07-02T13:42:47.198Z] GC before operation: completed in 62.376 ms, heap usage 307.192 MB -> 89.947 MB. [2025-07-02T13:42:48.418Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:42:49.649Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:42:50.874Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:42:52.158Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:42:52.938Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:42:53.305Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:42:54.550Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:42:54.925Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:42:55.311Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-07-02T13:42:55.311Z] The best model improves the baseline by 14.52%. [2025-07-02T13:42:55.311Z] Top recommended movies for user id 72: [2025-07-02T13:42:55.311Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-07-02T13:42:55.311Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-07-02T13:42:55.311Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-07-02T13:42:55.311Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-07-02T13:42:55.311Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-07-02T13:42:55.311Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (8149.963 ms) ====== [2025-07-02T13:42:55.667Z] ----------------------------------- [2025-07-02T13:42:55.667Z] renaissance-movie-lens_0_PASSED [2025-07-02T13:42:55.667Z] ----------------------------------- [2025-07-02T13:42:55.667Z] [2025-07-02T13:42:55.667Z] TEST TEARDOWN: [2025-07-02T13:42:55.667Z] Nothing to be done for teardown. [2025-07-02T13:42:55.667Z] renaissance-movie-lens_0 Finish Time: Wed Jul 2 09:42:55 2025 Epoch Time (ms): 1751463775333