[2025-08-30T10:29:14.077Z] Running test renaissance-movie-lens_0 ... [2025-08-30T10:29:14.077Z] =============================================== [2025-08-30T10:29:14.077Z] renaissance-movie-lens_0 Start Time: Sat Aug 30 10:29:13 2025 Epoch Time (ms): 1756549753969 [2025-08-30T10:29:14.077Z] variation: NoOptions [2025-08-30T10:29:14.077Z] JVM_OPTIONS: [2025-08-30T10:29:14.077Z] { \ [2025-08-30T10:29:14.077Z] echo ""; echo "TEST SETUP:"; \ [2025-08-30T10:29:14.077Z] echo "Nothing to be done for setup."; \ [2025-08-30T10:29:14.077Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux_testList_1/aqa-tests/TKG/../TKG/output_17565486695062/renaissance-movie-lens_0"; \ [2025-08-30T10:29:14.078Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux_testList_1/aqa-tests/TKG/../TKG/output_17565486695062/renaissance-movie-lens_0"; \ [2025-08-30T10:29:14.078Z] echo ""; echo "TESTING:"; \ [2025-08-30T10:29:14.078Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux_testList_1/aqa-tests/TKG/../TKG/output_17565486695062/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-08-30T10:29:14.078Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux_testList_1/aqa-tests/TKG/../TKG/output_17565486695062/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-08-30T10:29:14.078Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-08-30T10:29:14.078Z] echo "Nothing to be done for teardown."; \ [2025-08-30T10:29:14.078Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux_testList_1/aqa-tests/TKG/../TKG/output_17565486695062/TestTargetResult"; [2025-08-30T10:29:14.078Z] [2025-08-30T10:29:14.078Z] TEST SETUP: [2025-08-30T10:29:14.078Z] Nothing to be done for setup. [2025-08-30T10:29:14.078Z] [2025-08-30T10:29:14.078Z] TESTING: [2025-08-30T10:29:22.339Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-08-30T10:29:33.989Z] 10:29:33.227 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-08-30T10:29:37.409Z] Got 100004 ratings from 671 users on 9066 movies. [2025-08-30T10:29:37.409Z] Training: 60056, validation: 20285, test: 19854 [2025-08-30T10:29:37.409Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-08-30T10:29:38.176Z] GC before operation: completed in 272.825 ms, heap usage 314.439 MB -> 76.165 MB. [2025-08-30T10:29:48.066Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:29:54.928Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:30:00.546Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:30:05.016Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:30:08.448Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:30:10.922Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:30:14.336Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:30:16.813Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:30:16.813Z] 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. [2025-08-30T10:30:17.586Z] The best model improves the baseline by 14.52%. [2025-08-30T10:30:17.586Z] Top recommended movies for user id 72: [2025-08-30T10:30:17.586Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:30:17.586Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:30:17.586Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:30:17.586Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:30:17.586Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:30:17.586Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (39566.086 ms) ====== [2025-08-30T10:30:17.586Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-08-30T10:30:17.586Z] GC before operation: completed in 249.764 ms, heap usage 546.812 MB -> 96.160 MB. [2025-08-30T10:30:22.032Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:30:27.614Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:30:32.085Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:30:36.562Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:30:38.155Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:30:41.586Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:30:43.707Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:30:45.288Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:30:46.065Z] 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. [2025-08-30T10:30:46.065Z] The best model improves the baseline by 14.52%. [2025-08-30T10:30:46.065Z] Top recommended movies for user id 72: [2025-08-30T10:30:46.065Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:30:46.065Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:30:46.065Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:30:46.065Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:30:46.065Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:30:46.065Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (28396.216 ms) ====== [2025-08-30T10:30:46.065Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-08-30T10:30:46.828Z] GC before operation: completed in 267.565 ms, heap usage 373.733 MB -> 89.709 MB. [2025-08-30T10:30:50.250Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:30:53.655Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:30:57.130Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:30:59.614Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:31:02.079Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:31:04.541Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:31:07.025Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:31:08.608Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:31:09.371Z] 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. [2025-08-30T10:31:09.371Z] The best model improves the baseline by 14.52%. [2025-08-30T10:31:09.371Z] Top recommended movies for user id 72: [2025-08-30T10:31:09.371Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:31:09.371Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:31:09.371Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:31:09.371Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:31:09.371Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:31:09.371Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (22833.703 ms) ====== [2025-08-30T10:31:09.371Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-08-30T10:31:09.371Z] GC before operation: completed in 193.129 ms, heap usage 256.291 MB -> 89.683 MB. [2025-08-30T10:31:12.920Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:31:16.330Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:31:18.786Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:31:22.203Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:31:24.666Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:31:26.256Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:31:28.720Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:31:30.308Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:31:31.079Z] 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. [2025-08-30T10:31:31.079Z] The best model improves the baseline by 14.52%. [2025-08-30T10:31:31.079Z] Top recommended movies for user id 72: [2025-08-30T10:31:31.079Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:31:31.079Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:31:31.079Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:31:31.079Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:31:31.079Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:31:31.079Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21623.391 ms) ====== [2025-08-30T10:31:31.079Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-08-30T10:31:31.079Z] GC before operation: completed in 136.074 ms, heap usage 294.739 MB -> 89.977 MB. [2025-08-30T10:31:34.490Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:31:37.924Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:31:41.353Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:31:44.774Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:31:47.248Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:31:49.717Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:31:52.189Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:31:53.796Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:31:54.562Z] 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. [2025-08-30T10:31:54.562Z] The best model improves the baseline by 14.52%. [2025-08-30T10:31:54.562Z] Top recommended movies for user id 72: [2025-08-30T10:31:54.562Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:31:54.562Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:31:54.562Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:31:54.562Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:31:54.562Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:31:54.562Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (23541.046 ms) ====== [2025-08-30T10:31:54.562Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-08-30T10:31:55.337Z] GC before operation: completed in 132.724 ms, heap usage 196.894 MB -> 90.261 MB. [2025-08-30T10:31:58.770Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:32:02.841Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:32:06.260Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:32:09.749Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:32:12.207Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:32:14.672Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:32:17.149Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:32:19.616Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:32:19.616Z] 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. [2025-08-30T10:32:19.616Z] The best model improves the baseline by 14.52%. [2025-08-30T10:32:20.390Z] Top recommended movies for user id 72: [2025-08-30T10:32:20.390Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:32:20.390Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:32:20.390Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:32:20.390Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:32:20.390Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:32:20.390Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (25176.805 ms) ====== [2025-08-30T10:32:20.390Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-08-30T10:32:20.390Z] GC before operation: completed in 140.303 ms, heap usage 99.263 MB -> 90.256 MB. [2025-08-30T10:32:23.820Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:32:27.269Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:32:30.731Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:32:34.159Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:32:36.630Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:32:39.097Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:32:41.558Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:32:43.147Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:32:43.913Z] 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. [2025-08-30T10:32:43.913Z] The best model improves the baseline by 14.52%. [2025-08-30T10:32:43.913Z] Top recommended movies for user id 72: [2025-08-30T10:32:43.913Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:32:43.913Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:32:43.913Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:32:43.913Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:32:43.913Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:32:43.913Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (23841.937 ms) ====== [2025-08-30T10:32:43.913Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-08-30T10:32:44.677Z] GC before operation: completed in 194.313 ms, heap usage 282.953 MB -> 90.171 MB. [2025-08-30T10:32:48.125Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:32:51.548Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:32:54.968Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:32:58.395Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:33:00.857Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:33:03.339Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:33:05.801Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:33:07.398Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:33:08.163Z] 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. [2025-08-30T10:33:08.163Z] The best model improves the baseline by 14.52%. [2025-08-30T10:33:08.163Z] Top recommended movies for user id 72: [2025-08-30T10:33:08.163Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:33:08.163Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:33:08.163Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:33:08.163Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:33:08.163Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:33:08.163Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (23992.733 ms) ====== [2025-08-30T10:33:08.163Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-08-30T10:33:08.163Z] GC before operation: completed in 131.508 ms, heap usage 249.331 MB -> 90.471 MB. [2025-08-30T10:33:12.628Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:33:16.042Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:33:20.499Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:33:23.917Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:33:26.396Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:33:28.499Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:33:30.957Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:33:32.537Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:33:33.305Z] 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. [2025-08-30T10:33:33.305Z] The best model improves the baseline by 14.52%. [2025-08-30T10:33:33.305Z] Top recommended movies for user id 72: [2025-08-30T10:33:33.305Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:33:33.305Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:33:33.305Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:33:33.305Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:33:33.305Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:33:33.305Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (25150.287 ms) ====== [2025-08-30T10:33:33.305Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-08-30T10:33:34.075Z] GC before operation: completed in 171.451 ms, heap usage 286.991 MB -> 90.311 MB. [2025-08-30T10:33:37.496Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:33:41.957Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:33:45.374Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:33:48.883Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:33:58.084Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:34:00.547Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:34:03.010Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:34:05.482Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:34:05.482Z] 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. [2025-08-30T10:34:05.482Z] The best model improves the baseline by 14.52%. [2025-08-30T10:34:06.252Z] Top recommended movies for user id 72: [2025-08-30T10:34:06.252Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:34:06.252Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:34:06.252Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:34:06.252Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:34:06.252Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:34:06.252Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (32268.018 ms) ====== [2025-08-30T10:34:06.252Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-08-30T10:34:06.252Z] GC before operation: completed in 137.921 ms, heap usage 375.340 MB -> 90.619 MB. [2025-08-30T10:34:09.685Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:34:13.123Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:34:16.530Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:34:18.992Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:34:20.576Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:34:23.039Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:34:24.617Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:34:26.202Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:34:26.973Z] 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. [2025-08-30T10:34:26.973Z] The best model improves the baseline by 14.52%. [2025-08-30T10:34:26.973Z] Top recommended movies for user id 72: [2025-08-30T10:34:26.973Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:34:26.973Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:34:26.973Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:34:26.973Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:34:26.973Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:34:26.973Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20856.442 ms) ====== [2025-08-30T10:34:26.973Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-08-30T10:34:26.973Z] GC before operation: completed in 146.566 ms, heap usage 161.992 MB -> 90.109 MB. [2025-08-30T10:34:30.390Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:34:32.856Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:34:35.321Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:34:37.772Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:34:39.365Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:34:40.956Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:34:43.416Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:34:45.005Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:34:45.005Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-08-30T10:34:45.768Z] The best model improves the baseline by 14.52%. [2025-08-30T10:34:45.768Z] Top recommended movies for user id 72: [2025-08-30T10:34:45.768Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:34:45.768Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:34:45.768Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:34:45.768Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:34:45.768Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:34:45.768Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18406.993 ms) ====== [2025-08-30T10:34:45.768Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-08-30T10:34:45.768Z] GC before operation: completed in 131.256 ms, heap usage 184.091 MB -> 90.337 MB. [2025-08-30T10:34:48.232Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:34:51.101Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:34:53.571Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:34:56.027Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:34:57.626Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:34:59.202Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:34:59.974Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:35:01.552Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:35:01.552Z] 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. [2025-08-30T10:35:01.552Z] The best model improves the baseline by 14.52%. [2025-08-30T10:35:02.322Z] Top recommended movies for user id 72: [2025-08-30T10:35:02.322Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:35:02.322Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:35:02.322Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:35:02.322Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:35:02.322Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:35:02.322Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16347.251 ms) ====== [2025-08-30T10:35:02.322Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-08-30T10:35:02.322Z] GC before operation: completed in 110.760 ms, heap usage 378.031 MB -> 90.649 MB. [2025-08-30T10:35:04.772Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:35:07.248Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:35:09.703Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:35:12.151Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:35:14.615Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:35:16.198Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:35:17.773Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:35:19.358Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:35:19.358Z] 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. [2025-08-30T10:35:19.358Z] The best model improves the baseline by 14.52%. [2025-08-30T10:35:20.127Z] Top recommended movies for user id 72: [2025-08-30T10:35:20.127Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:35:20.127Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:35:20.127Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:35:20.127Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:35:20.127Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:35:20.127Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17637.631 ms) ====== [2025-08-30T10:35:20.127Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-08-30T10:35:20.128Z] GC before operation: completed in 138.730 ms, heap usage 295.097 MB -> 90.398 MB. [2025-08-30T10:35:22.581Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:35:25.987Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:35:29.398Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:35:31.852Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:35:33.430Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:35:35.015Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:35:36.610Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:35:38.189Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:35:38.189Z] 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. [2025-08-30T10:35:38.955Z] The best model improves the baseline by 14.52%. [2025-08-30T10:35:38.955Z] Top recommended movies for user id 72: [2025-08-30T10:35:38.955Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:35:38.955Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:35:38.955Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:35:38.955Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:35:38.955Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:35:38.955Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18792.037 ms) ====== [2025-08-30T10:35:38.955Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-08-30T10:35:38.955Z] GC before operation: completed in 102.755 ms, heap usage 105.784 MB -> 92.810 MB. [2025-08-30T10:35:41.409Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:35:44.808Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:35:47.278Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:35:50.694Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:35:52.274Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:35:53.861Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:35:55.441Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:35:57.022Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:35:57.785Z] 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. [2025-08-30T10:35:57.785Z] The best model improves the baseline by 14.52%. [2025-08-30T10:35:57.785Z] Top recommended movies for user id 72: [2025-08-30T10:35:57.785Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:35:57.785Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:35:57.785Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:35:57.785Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:35:57.785Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:35:57.785Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18874.997 ms) ====== [2025-08-30T10:35:57.785Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-08-30T10:35:57.785Z] GC before operation: completed in 116.394 ms, heap usage 403.393 MB -> 90.614 MB. [2025-08-30T10:36:00.236Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:36:02.684Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:36:06.088Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:36:08.606Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:36:10.193Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:36:11.348Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:36:13.075Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:36:14.667Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:36:14.667Z] 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. [2025-08-30T10:36:14.667Z] The best model improves the baseline by 14.52%. [2025-08-30T10:36:15.884Z] Top recommended movies for user id 72: [2025-08-30T10:36:15.884Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:36:15.884Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:36:15.884Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:36:15.884Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:36:15.884Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:36:15.884Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17321.605 ms) ====== [2025-08-30T10:36:15.884Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-08-30T10:36:15.884Z] GC before operation: completed in 145.008 ms, heap usage 513.642 MB -> 90.859 MB. [2025-08-30T10:36:19.289Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:36:22.708Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:36:26.131Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:36:28.586Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:36:30.172Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:36:31.752Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:36:34.213Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:36:35.802Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:36:35.802Z] 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. [2025-08-30T10:36:35.803Z] The best model improves the baseline by 14.52%. [2025-08-30T10:36:36.567Z] Top recommended movies for user id 72: [2025-08-30T10:36:36.567Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:36:36.567Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:36:36.567Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:36:36.567Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:36:36.567Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:36:36.567Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20899.771 ms) ====== [2025-08-30T10:36:36.567Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-08-30T10:36:36.567Z] GC before operation: completed in 119.645 ms, heap usage 366.482 MB -> 90.559 MB. [2025-08-30T10:36:39.026Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:36:42.433Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:36:46.977Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:36:49.445Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:36:51.032Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:36:53.498Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:36:55.093Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:36:58.492Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:36:58.492Z] 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. [2025-08-30T10:36:58.492Z] The best model improves the baseline by 14.52%. [2025-08-30T10:36:59.260Z] Top recommended movies for user id 72: [2025-08-30T10:36:59.260Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:36:59.260Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:36:59.260Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:36:59.260Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:36:59.260Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:36:59.260Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (22603.102 ms) ====== [2025-08-30T10:36:59.260Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-08-30T10:36:59.260Z] GC before operation: completed in 146.572 ms, heap usage 243.048 MB -> 90.497 MB. [2025-08-30T10:37:01.723Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-30T10:37:05.138Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-30T10:37:09.578Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-30T10:37:12.049Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-30T10:37:16.474Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-30T10:37:21.845Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-30T10:37:24.300Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-30T10:37:26.053Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-30T10:37:26.819Z] 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. [2025-08-30T10:37:26.819Z] The best model improves the baseline by 14.52%. [2025-08-30T10:37:26.819Z] Top recommended movies for user id 72: [2025-08-30T10:37:26.819Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-30T10:37:26.819Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-30T10:37:26.819Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-30T10:37:26.819Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-30T10:37:26.819Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-30T10:37:26.819Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (27694.564 ms) ====== [2025-08-30T10:37:27.583Z] ----------------------------------- [2025-08-30T10:37:27.583Z] renaissance-movie-lens_0_PASSED [2025-08-30T10:37:27.583Z] ----------------------------------- [2025-08-30T10:37:27.583Z] [2025-08-30T10:37:27.583Z] TEST TEARDOWN: [2025-08-30T10:37:27.583Z] Nothing to be done for teardown. [2025-08-30T10:37:27.583Z] renaissance-movie-lens_0 Finish Time: Sat Aug 30 10:37:27 2025 Epoch Time (ms): 1756550247128