[2025-09-04T06:26:06.436Z] Running test renaissance-movie-lens_0 ... [2025-09-04T06:26:06.436Z] =============================================== [2025-09-04T06:26:06.436Z] renaissance-movie-lens_0 Start Time: Thu Sep 4 06:26:05 2025 Epoch Time (ms): 1756967165802 [2025-09-04T06:26:06.436Z] variation: NoOptions [2025-09-04T06:26:06.436Z] JVM_OPTIONS: [2025-09-04T06:26:06.436Z] { \ [2025-09-04T06:26:06.436Z] echo ""; echo "TEST SETUP:"; \ [2025-09-04T06:26:06.436Z] echo "Nothing to be done for setup."; \ [2025-09-04T06:26:06.436Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17569661009691/renaissance-movie-lens_0"; \ [2025-09-04T06:26:06.436Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17569661009691/renaissance-movie-lens_0"; \ [2025-09-04T06:26:06.436Z] echo ""; echo "TESTING:"; \ [2025-09-04T06:26:06.436Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-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_alpine-linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17569661009691/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-04T06:26:06.436Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17569661009691/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-04T06:26:06.436Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-04T06:26:06.436Z] echo "Nothing to be done for teardown."; \ [2025-09-04T06:26:06.436Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17569661009691/TestTargetResult"; [2025-09-04T06:26:06.436Z] [2025-09-04T06:26:06.436Z] TEST SETUP: [2025-09-04T06:26:06.436Z] Nothing to be done for setup. [2025-09-04T06:26:06.436Z] [2025-09-04T06:26:06.436Z] TESTING: [2025-09-04T06:26:13.330Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-09-04T06:26:21.690Z] 06:26:20.839 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. [2025-09-04T06:26:24.496Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-04T06:26:25.279Z] Training: 60056, validation: 20285, test: 19854 [2025-09-04T06:26:25.279Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-04T06:26:25.279Z] GC before operation: completed in 195.257 ms, heap usage 447.133 MB -> 76.041 MB. [2025-09-04T06:26:35.293Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:26:40.951Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:26:45.442Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:26:49.947Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:26:52.451Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:26:54.951Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:26:57.445Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:26:59.929Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:26:59.929Z] 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. [2025-09-04T06:26:59.929Z] The best model improves the baseline by 14.52%. [2025-09-04T06:27:00.706Z] Top recommended movies for user id 72: [2025-09-04T06:27:00.706Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:27:00.706Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:27:00.706Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:27:00.706Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:27:00.706Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:27:00.706Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (35154.015 ms) ====== [2025-09-04T06:27:00.706Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-04T06:27:00.706Z] GC before operation: completed in 195.294 ms, heap usage 395.827 MB -> 97.991 MB. [2025-09-04T06:27:05.190Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:27:08.646Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:27:12.652Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:27:16.100Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:27:18.603Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:27:21.111Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:27:23.595Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:27:25.202Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:27:26.027Z] 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. [2025-09-04T06:27:26.027Z] The best model improves the baseline by 14.52%. [2025-09-04T06:27:26.027Z] Top recommended movies for user id 72: [2025-09-04T06:27:26.027Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:27:26.027Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:27:26.027Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:27:26.027Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:27:26.027Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:27:26.027Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (25685.096 ms) ====== [2025-09-04T06:27:26.027Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-04T06:27:26.806Z] GC before operation: completed in 171.395 ms, heap usage 161.426 MB -> 88.627 MB. [2025-09-04T06:27:30.265Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:27:34.782Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:27:38.240Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:27:41.690Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:27:44.184Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:27:46.673Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:27:49.159Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:27:50.766Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:27:51.541Z] 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. [2025-09-04T06:27:51.541Z] The best model improves the baseline by 14.52%. [2025-09-04T06:27:51.541Z] Top recommended movies for user id 72: [2025-09-04T06:27:51.541Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:27:51.541Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:27:51.541Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:27:51.541Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:27:51.541Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:27:51.541Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (25031.266 ms) ====== [2025-09-04T06:27:51.541Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-04T06:27:51.541Z] GC before operation: completed in 175.373 ms, heap usage 255.631 MB -> 89.376 MB. [2025-09-04T06:27:54.991Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:27:58.954Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:28:02.407Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:28:05.857Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:28:07.479Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:28:09.967Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:28:11.568Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:28:14.061Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:28:14.061Z] 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. [2025-09-04T06:28:14.061Z] The best model improves the baseline by 14.52%. [2025-09-04T06:28:14.061Z] Top recommended movies for user id 72: [2025-09-04T06:28:14.061Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:28:14.061Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:28:14.061Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:28:14.061Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:28:14.061Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:28:14.061Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22780.672 ms) ====== [2025-09-04T06:28:14.061Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-04T06:28:14.835Z] GC before operation: completed in 158.862 ms, heap usage 243.768 MB -> 89.657 MB. [2025-09-04T06:28:18.277Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:28:21.743Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:28:25.339Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:28:29.852Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:28:31.464Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:28:33.947Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:28:36.426Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:28:38.028Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:28:38.803Z] 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. [2025-09-04T06:28:38.803Z] The best model improves the baseline by 14.52%. [2025-09-04T06:28:38.803Z] Top recommended movies for user id 72: [2025-09-04T06:28:38.803Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:28:38.803Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:28:38.803Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:28:38.803Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:28:38.803Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:28:38.803Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (24260.242 ms) ====== [2025-09-04T06:28:38.803Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-04T06:28:38.803Z] GC before operation: completed in 167.033 ms, heap usage 202.102 MB -> 89.460 MB. [2025-09-04T06:28:43.307Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:28:46.425Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:28:49.884Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:28:53.335Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:28:54.934Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:28:57.425Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:28:59.913Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:29:01.515Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:29:02.290Z] 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. [2025-09-04T06:29:02.290Z] The best model improves the baseline by 14.52%. [2025-09-04T06:29:02.290Z] Top recommended movies for user id 72: [2025-09-04T06:29:02.290Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:29:02.290Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:29:02.290Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:29:02.290Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:29:02.290Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:29:02.290Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (23282.261 ms) ====== [2025-09-04T06:29:02.290Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-04T06:29:02.290Z] GC before operation: completed in 158.627 ms, heap usage 414.380 MB -> 90.113 MB. [2025-09-04T06:29:05.730Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:29:09.207Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:29:12.657Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:29:18.335Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:29:21.782Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:29:24.287Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:29:27.901Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:29:30.408Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:29:31.183Z] 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. [2025-09-04T06:29:31.183Z] The best model improves the baseline by 14.52%. [2025-09-04T06:29:31.183Z] Top recommended movies for user id 72: [2025-09-04T06:29:31.183Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:29:31.183Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:29:31.183Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:29:31.183Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:29:31.183Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:29:31.183Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (28840.245 ms) ====== [2025-09-04T06:29:31.183Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-04T06:29:31.183Z] GC before operation: completed in 271.575 ms, heap usage 400.652 MB -> 90.071 MB. [2025-09-04T06:29:36.296Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:29:41.938Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:29:46.456Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:29:50.969Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:29:53.467Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:29:55.954Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:29:58.460Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:30:00.947Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:30:00.947Z] 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. [2025-09-04T06:30:00.947Z] The best model improves the baseline by 14.52%. [2025-09-04T06:30:01.733Z] Top recommended movies for user id 72: [2025-09-04T06:30:01.733Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:30:01.733Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:30:01.733Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:30:01.733Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:30:01.733Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:30:01.733Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (30034.948 ms) ====== [2025-09-04T06:30:01.733Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-04T06:30:01.733Z] GC before operation: completed in 224.521 ms, heap usage 773.090 MB -> 94.125 MB. [2025-09-04T06:30:06.278Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:30:09.755Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:30:15.413Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:30:19.938Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:30:22.428Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:30:26.430Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:30:28.931Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:30:32.401Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:30:32.402Z] 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. [2025-09-04T06:30:32.402Z] The best model improves the baseline by 14.52%. [2025-09-04T06:30:32.402Z] Top recommended movies for user id 72: [2025-09-04T06:30:32.402Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:30:32.402Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:30:32.402Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:30:32.402Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:30:32.402Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:30:32.402Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (30945.434 ms) ====== [2025-09-04T06:30:32.402Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-04T06:30:33.176Z] GC before operation: completed in 267.679 ms, heap usage 549.647 MB -> 93.534 MB. [2025-09-04T06:30:37.671Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:30:42.201Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:30:47.883Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:30:52.391Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:30:54.905Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:30:57.396Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:31:00.936Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:31:04.415Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:31:04.415Z] 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. [2025-09-04T06:31:04.415Z] The best model improves the baseline by 14.52%. [2025-09-04T06:31:05.199Z] Top recommended movies for user id 72: [2025-09-04T06:31:05.199Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:31:05.199Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:31:05.199Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:31:05.199Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:31:05.199Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:31:05.199Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (31818.054 ms) ====== [2025-09-04T06:31:05.199Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-04T06:31:05.199Z] GC before operation: completed in 246.700 ms, heap usage 242.798 MB -> 90.103 MB. [2025-09-04T06:31:10.852Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:31:14.839Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:31:20.513Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:31:25.055Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:31:28.536Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:31:31.056Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:31:34.545Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:31:37.044Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:31:37.825Z] 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. [2025-09-04T06:31:37.825Z] The best model improves the baseline by 14.52%. [2025-09-04T06:31:37.825Z] Top recommended movies for user id 72: [2025-09-04T06:31:37.825Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:31:37.825Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:31:37.825Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:31:37.825Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:31:37.825Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:31:37.825Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (33008.789 ms) ====== [2025-09-04T06:31:37.825Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-04T06:31:38.611Z] GC before operation: completed in 289.799 ms, heap usage 120.802 MB -> 89.925 MB. [2025-09-04T06:31:43.095Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:31:47.624Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:31:52.132Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:31:56.644Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:31:59.156Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:32:02.625Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:32:04.757Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:32:08.222Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:32:08.222Z] 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. [2025-09-04T06:32:08.222Z] The best model improves the baseline by 14.52%. [2025-09-04T06:32:08.222Z] Top recommended movies for user id 72: [2025-09-04T06:32:08.222Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:32:08.222Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:32:08.222Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:32:08.222Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:32:08.222Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:32:08.222Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (29921.393 ms) ====== [2025-09-04T06:32:08.222Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-04T06:32:08.998Z] GC before operation: completed in 324.194 ms, heap usage 536.857 MB -> 93.717 MB. [2025-09-04T06:32:13.536Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:32:18.038Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:32:23.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:32:27.249Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:32:30.699Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:32:33.192Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:32:36.657Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:32:39.153Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:32:39.153Z] 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. [2025-09-04T06:32:39.153Z] The best model improves the baseline by 14.52%. [2025-09-04T06:32:39.153Z] Top recommended movies for user id 72: [2025-09-04T06:32:39.153Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:32:39.153Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:32:39.153Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:32:39.153Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:32:39.153Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:32:39.153Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (30877.116 ms) ====== [2025-09-04T06:32:39.153Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-04T06:32:39.933Z] GC before operation: completed in 287.045 ms, heap usage 226.986 MB -> 90.171 MB. [2025-09-04T06:32:44.481Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:32:50.142Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:32:54.116Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:32:58.615Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:33:01.114Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:33:03.689Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:33:06.177Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:33:08.671Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:33:09.453Z] 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. [2025-09-04T06:33:09.453Z] The best model improves the baseline by 14.52%. [2025-09-04T06:33:09.453Z] Top recommended movies for user id 72: [2025-09-04T06:33:09.453Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:33:09.453Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:33:09.453Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:33:09.453Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:33:09.453Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:33:09.453Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (29912.655 ms) ====== [2025-09-04T06:33:09.453Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-04T06:33:10.231Z] GC before operation: completed in 328.691 ms, heap usage 489.526 MB -> 90.376 MB. [2025-09-04T06:33:14.743Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:33:19.250Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:33:23.777Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:33:28.468Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:33:30.960Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:33:33.178Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:33:36.642Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:33:39.135Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:33:39.135Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-04T06:33:39.135Z] The best model improves the baseline by 14.52%. [2025-09-04T06:33:39.135Z] Top recommended movies for user id 72: [2025-09-04T06:33:39.135Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:33:39.135Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:33:39.135Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:33:39.135Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:33:39.135Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:33:39.135Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (29449.451 ms) ====== [2025-09-04T06:33:39.135Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-04T06:33:39.920Z] GC before operation: completed in 270.988 ms, heap usage 754.693 MB -> 94.183 MB. [2025-09-04T06:33:44.418Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:33:48.946Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:33:53.365Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:33:57.784Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:34:00.220Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:34:03.579Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:34:06.034Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:34:08.475Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:34:09.241Z] 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. [2025-09-04T06:34:09.241Z] The best model improves the baseline by 14.52%. [2025-09-04T06:34:09.241Z] Top recommended movies for user id 72: [2025-09-04T06:34:09.241Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:34:09.241Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:34:09.241Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:34:09.241Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:34:09.241Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:34:09.241Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (29499.953 ms) ====== [2025-09-04T06:34:09.241Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-04T06:34:09.241Z] GC before operation: completed in 307.839 ms, heap usage 475.516 MB -> 90.427 MB. [2025-09-04T06:34:14.813Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:34:17.243Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:34:22.770Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:34:27.455Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:34:29.912Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:34:33.288Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:34:36.671Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:34:39.120Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:34:39.880Z] 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. [2025-09-04T06:34:39.880Z] The best model improves the baseline by 14.52%. [2025-09-04T06:34:39.880Z] Top recommended movies for user id 72: [2025-09-04T06:34:39.880Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:34:39.880Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:34:39.880Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:34:39.880Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:34:39.880Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:34:39.880Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (30523.756 ms) ====== [2025-09-04T06:34:39.880Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-04T06:34:40.638Z] GC before operation: completed in 212.845 ms, heap usage 412.354 MB -> 90.429 MB. [2025-09-04T06:34:45.141Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:34:50.659Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:34:55.051Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:34:59.463Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:35:01.895Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:35:04.330Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:35:07.254Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:35:09.694Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:35:09.694Z] 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. [2025-09-04T06:35:10.456Z] The best model improves the baseline by 14.52%. [2025-09-04T06:35:10.456Z] Top recommended movies for user id 72: [2025-09-04T06:35:10.456Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:35:10.456Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:35:10.456Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:35:10.456Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:35:10.456Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:35:10.456Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (30078.586 ms) ====== [2025-09-04T06:35:10.456Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-04T06:35:10.456Z] GC before operation: completed in 278.139 ms, heap usage 222.530 MB -> 90.046 MB. [2025-09-04T06:35:14.837Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:35:19.240Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:35:24.803Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:35:28.188Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:35:30.691Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:35:33.134Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:35:36.517Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:35:38.972Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:35:38.972Z] 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. [2025-09-04T06:35:39.742Z] The best model improves the baseline by 14.52%. [2025-09-04T06:35:39.742Z] Top recommended movies for user id 72: [2025-09-04T06:35:39.742Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:35:39.742Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:35:39.742Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:35:39.742Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:35:39.742Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:35:39.742Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (28897.626 ms) ====== [2025-09-04T06:35:39.742Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-04T06:35:39.742Z] GC before operation: completed in 292.003 ms, heap usage 767.565 MB -> 94.213 MB. [2025-09-04T06:35:45.273Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T06:35:49.161Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T06:35:53.589Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T06:35:57.994Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T06:36:01.357Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T06:36:03.779Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T06:36:06.214Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T06:36:08.653Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T06:36:08.653Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-09-04T06:36:09.408Z] The best model improves the baseline by 14.52%. [2025-09-04T06:36:09.408Z] Top recommended movies for user id 72: [2025-09-04T06:36:09.408Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-09-04T06:36:09.408Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-09-04T06:36:09.408Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-09-04T06:36:09.408Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-09-04T06:36:09.408Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-09-04T06:36:09.408Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (29426.070 ms) ====== [2025-09-04T06:36:10.168Z] ----------------------------------- [2025-09-04T06:36:10.168Z] renaissance-movie-lens_0_PASSED [2025-09-04T06:36:10.168Z] ----------------------------------- [2025-09-04T06:36:10.168Z] [2025-09-04T06:36:10.168Z] TEST TEARDOWN: [2025-09-04T06:36:10.168Z] Nothing to be done for teardown. [2025-09-04T06:36:10.168Z] renaissance-movie-lens_0 Finish Time: Thu Sep 4 06:36:09 2025 Epoch Time (ms): 1756967769562