[2025-12-06T13:03:19.733Z] Running test renaissance-movie-lens_0 ... [2025-12-06T13:03:19.733Z] =============================================== [2025-12-06T13:03:19.733Z] renaissance-movie-lens_0 Start Time: Sat Dec 6 13:03:19 2025 Epoch Time (ms): 1765026199542 [2025-12-06T13:03:19.733Z] variation: NoOptions [2025-12-06T13:03:19.733Z] JVM_OPTIONS: [2025-12-06T13:03:19.733Z] { \ [2025-12-06T13:03:19.733Z] echo ""; echo "TEST SETUP:"; \ [2025-12-06T13:03:19.733Z] echo "Nothing to be done for setup."; \ [2025-12-06T13:03:19.733Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17650241815482/renaissance-movie-lens_0"; \ [2025-12-06T13:03:19.733Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17650241815482/renaissance-movie-lens_0"; \ [2025-12-06T13:03:19.733Z] echo ""; echo "TESTING:"; \ [2025-12-06T13:03:19.733Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/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_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17650241815482/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-06T13:03:19.733Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17650241815482/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-06T13:03:19.733Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-06T13:03:19.733Z] echo "Nothing to be done for teardown."; \ [2025-12-06T13:03:19.733Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17650241815482/TestTargetResult"; [2025-12-06T13:03:19.733Z] [2025-12-06T13:03:19.733Z] TEST SETUP: [2025-12-06T13:03:19.733Z] Nothing to be done for setup. [2025-12-06T13:03:19.733Z] [2025-12-06T13:03:19.733Z] TESTING: [2025-12-06T13:03:20.048Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-12-06T13:03:20.048Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/output_17650241815482/renaissance-movie-lens_0/launcher-130319-3725890338780564915/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-12-06T13:03:20.048Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-12-06T13:03:20.048Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-12-06T13:03:24.684Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-12-06T13:03:31.790Z] 13:03:31.498 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-12-06T13:03:34.744Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-06T13:03:35.059Z] Training: 60056, validation: 20285, test: 19854 [2025-12-06T13:03:35.059Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-06T13:03:35.382Z] GC before operation: completed in 132.783 ms, heap usage 214.488 MB -> 75.386 MB. [2025-12-06T13:03:42.509Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:03:46.206Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:03:49.907Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:03:52.809Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:03:55.027Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:03:56.624Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:03:58.806Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:04:00.409Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:04:00.409Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:04:00.725Z] The best model improves the baseline by 14.34%. [2025-12-06T13:04:00.725Z] Top recommended movies for user id 72: [2025-12-06T13:04:00.725Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:04:00.725Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:04:00.725Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:04:00.725Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:04:00.725Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:04:00.725Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25606.408 ms) ====== [2025-12-06T13:04:00.725Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-06T13:04:01.046Z] GC before operation: completed in 153.296 ms, heap usage 217.977 MB -> 89.674 MB. [2025-12-06T13:04:04.038Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:04:06.230Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:04:09.098Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:04:11.274Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:04:12.373Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:04:13.969Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:04:15.067Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:04:17.245Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:04:17.245Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:04:17.245Z] The best model improves the baseline by 14.34%. [2025-12-06T13:04:17.569Z] Top recommended movies for user id 72: [2025-12-06T13:04:17.569Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:04:17.569Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:04:17.569Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:04:17.569Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:04:17.569Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:04:17.569Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16513.629 ms) ====== [2025-12-06T13:04:17.569Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-06T13:04:17.569Z] GC before operation: completed in 128.807 ms, heap usage 118.884 MB -> 87.383 MB. [2025-12-06T13:04:20.430Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:04:22.609Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:04:25.472Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:04:28.425Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:04:29.531Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:04:31.155Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:04:32.770Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:04:34.390Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:04:34.390Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:04:34.390Z] The best model improves the baseline by 14.34%. [2025-12-06T13:04:34.717Z] Top recommended movies for user id 72: [2025-12-06T13:04:34.717Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:04:34.717Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:04:34.717Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:04:34.717Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:04:34.717Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:04:34.717Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17002.083 ms) ====== [2025-12-06T13:04:34.717Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-06T13:04:34.717Z] GC before operation: completed in 131.318 ms, heap usage 231.674 MB -> 88.332 MB. [2025-12-06T13:04:37.621Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:04:39.877Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:04:42.814Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:04:45.030Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:04:46.204Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:04:47.959Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:04:49.588Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:04:50.722Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:04:51.043Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:04:51.043Z] The best model improves the baseline by 14.34%. [2025-12-06T13:04:51.361Z] Top recommended movies for user id 72: [2025-12-06T13:04:51.361Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:04:51.361Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:04:51.361Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:04:51.361Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:04:51.361Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:04:51.361Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16631.880 ms) ====== [2025-12-06T13:04:51.361Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-06T13:04:51.711Z] GC before operation: completed in 141.676 ms, heap usage 222.806 MB -> 88.624 MB. [2025-12-06T13:04:54.187Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:04:57.042Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:04:59.215Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:05:00.815Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:05:02.411Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:05:03.512Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:05:05.103Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:05:06.202Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:05:06.520Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:05:06.520Z] The best model improves the baseline by 14.34%. [2025-12-06T13:05:06.520Z] Top recommended movies for user id 72: [2025-12-06T13:05:06.520Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:05:06.520Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:05:06.520Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:05:06.520Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:05:06.520Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:05:06.520Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14976.011 ms) ====== [2025-12-06T13:05:06.520Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-06T13:05:06.520Z] GC before operation: completed in 153.715 ms, heap usage 537.076 MB -> 92.276 MB. [2025-12-06T13:05:09.384Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:05:11.072Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:05:13.928Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:05:15.533Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:05:17.157Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:05:18.271Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:05:19.381Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:05:20.988Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:05:20.988Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:05:20.988Z] The best model improves the baseline by 14.34%. [2025-12-06T13:05:21.313Z] Top recommended movies for user id 72: [2025-12-06T13:05:21.313Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:05:21.313Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:05:21.313Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:05:21.313Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:05:21.313Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:05:21.313Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14473.318 ms) ====== [2025-12-06T13:05:21.313Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-06T13:05:21.313Z] GC before operation: completed in 138.499 ms, heap usage 145.873 MB -> 88.712 MB. [2025-12-06T13:05:23.523Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:05:25.725Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:05:27.924Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:05:30.116Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:05:31.721Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:05:32.883Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:05:34.476Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:05:36.073Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:05:36.073Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:05:36.073Z] The best model improves the baseline by 14.34%. [2025-12-06T13:05:36.073Z] Top recommended movies for user id 72: [2025-12-06T13:05:36.073Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:05:36.073Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:05:36.073Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:05:36.073Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:05:36.073Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:05:36.073Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14873.932 ms) ====== [2025-12-06T13:05:36.073Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-06T13:05:36.387Z] GC before operation: completed in 139.271 ms, heap usage 223.652 MB -> 88.802 MB. [2025-12-06T13:05:38.559Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:05:40.729Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:05:42.906Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:05:45.081Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:05:45.759Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:05:47.349Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:05:48.451Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:05:50.048Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:05:50.048Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:05:50.048Z] The best model improves the baseline by 14.34%. [2025-12-06T13:05:50.048Z] Top recommended movies for user id 72: [2025-12-06T13:05:50.048Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:05:50.048Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:05:50.048Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:05:50.048Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:05:50.048Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:05:50.048Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13805.902 ms) ====== [2025-12-06T13:05:50.048Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-06T13:05:50.361Z] GC before operation: completed in 153.396 ms, heap usage 300.654 MB -> 89.166 MB. [2025-12-06T13:05:52.596Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:05:54.786Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:05:56.515Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:05:58.775Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:05:59.893Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:06:01.513Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:06:02.630Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:06:03.742Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:06:04.063Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:06:04.063Z] The best model improves the baseline by 14.34%. [2025-12-06T13:06:04.063Z] Top recommended movies for user id 72: [2025-12-06T13:06:04.063Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:06:04.063Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:06:04.063Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:06:04.063Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:06:04.063Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:06:04.063Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13920.369 ms) ====== [2025-12-06T13:06:04.063Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-06T13:06:04.383Z] GC before operation: completed in 144.071 ms, heap usage 492.788 MB -> 92.491 MB. [2025-12-06T13:06:06.632Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:06:08.834Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:06:10.438Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:06:12.616Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:06:13.724Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:06:14.846Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:06:16.453Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:06:17.557Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:06:17.872Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:06:17.872Z] The best model improves the baseline by 14.34%. [2025-12-06T13:06:17.872Z] Top recommended movies for user id 72: [2025-12-06T13:06:17.872Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:06:17.872Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:06:17.872Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:06:17.872Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:06:17.872Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:06:17.872Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13568.048 ms) ====== [2025-12-06T13:06:17.872Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-06T13:06:18.189Z] GC before operation: completed in 139.928 ms, heap usage 390.657 MB -> 89.315 MB. [2025-12-06T13:06:20.378Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:06:21.988Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:06:24.167Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:06:26.358Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:06:27.484Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:06:28.594Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:06:30.195Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:06:31.340Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:06:31.340Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:06:31.340Z] The best model improves the baseline by 14.34%. [2025-12-06T13:06:31.669Z] Top recommended movies for user id 72: [2025-12-06T13:06:31.669Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:06:31.669Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:06:31.669Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:06:31.669Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:06:31.669Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:06:31.669Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13505.807 ms) ====== [2025-12-06T13:06:31.669Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-06T13:06:31.669Z] GC before operation: completed in 136.376 ms, heap usage 489.512 MB -> 92.495 MB. [2025-12-06T13:06:33.922Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:06:35.572Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:06:37.782Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:06:39.446Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:06:41.081Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:06:42.193Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:06:43.311Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:06:44.455Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:06:44.775Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:06:44.775Z] The best model improves the baseline by 14.34%. [2025-12-06T13:06:44.775Z] Top recommended movies for user id 72: [2025-12-06T13:06:44.775Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:06:44.775Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:06:44.775Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:06:44.775Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:06:44.775Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:06:44.775Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13129.101 ms) ====== [2025-12-06T13:06:44.775Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-06T13:06:45.113Z] GC before operation: completed in 136.362 ms, heap usage 394.143 MB -> 89.306 MB. [2025-12-06T13:06:46.826Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:06:49.065Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:06:51.308Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:06:52.931Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:06:54.070Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:06:55.750Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:06:56.876Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:06:58.019Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:06:58.019Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:06:58.019Z] The best model improves the baseline by 14.34%. [2025-12-06T13:06:58.340Z] Top recommended movies for user id 72: [2025-12-06T13:06:58.340Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:06:58.340Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:06:58.340Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:06:58.340Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:06:58.340Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:06:58.340Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13342.781 ms) ====== [2025-12-06T13:06:58.340Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-06T13:06:58.340Z] GC before operation: completed in 137.204 ms, heap usage 116.519 MB -> 92.407 MB. [2025-12-06T13:07:00.572Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:07:03.001Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:07:05.156Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:07:06.773Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:07:07.880Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:07:08.990Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:07:10.588Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:07:11.690Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:07:11.690Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:07:11.690Z] The best model improves the baseline by 14.34%. [2025-12-06T13:07:11.690Z] Top recommended movies for user id 72: [2025-12-06T13:07:11.690Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:07:11.690Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:07:11.690Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:07:11.690Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:07:11.690Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:07:11.690Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13381.926 ms) ====== [2025-12-06T13:07:11.690Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-06T13:07:12.010Z] GC before operation: completed in 139.153 ms, heap usage 409.702 MB -> 89.220 MB. [2025-12-06T13:07:14.183Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:07:16.358Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:07:17.952Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:07:20.125Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:07:21.222Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:07:22.368Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:07:23.475Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:07:24.574Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:07:24.893Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:07:24.893Z] The best model improves the baseline by 14.34%. [2025-12-06T13:07:24.893Z] Top recommended movies for user id 72: [2025-12-06T13:07:24.893Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:07:24.893Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:07:24.893Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:07:24.893Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:07:24.893Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:07:24.893Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13044.481 ms) ====== [2025-12-06T13:07:24.893Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-06T13:07:25.205Z] GC before operation: completed in 137.886 ms, heap usage 165.556 MB -> 89.065 MB. [2025-12-06T13:07:27.376Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:07:29.548Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:07:31.143Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:07:33.315Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:07:34.413Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:07:35.508Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:07:36.605Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:07:37.706Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:07:38.021Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:07:38.021Z] The best model improves the baseline by 14.34%. [2025-12-06T13:07:38.021Z] Top recommended movies for user id 72: [2025-12-06T13:07:38.021Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:07:38.021Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:07:38.021Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:07:38.021Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:07:38.021Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:07:38.021Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12945.529 ms) ====== [2025-12-06T13:07:38.021Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-06T13:07:38.334Z] GC before operation: completed in 143.628 ms, heap usage 540.933 MB -> 92.762 MB. [2025-12-06T13:07:40.512Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:07:42.682Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:07:44.962Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:07:46.553Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:07:47.665Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:07:48.770Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:07:49.867Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:07:50.970Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:07:51.284Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:07:51.284Z] The best model improves the baseline by 14.34%. [2025-12-06T13:07:51.604Z] Top recommended movies for user id 72: [2025-12-06T13:07:51.604Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:07:51.604Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:07:51.604Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:07:51.604Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:07:51.604Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:07:51.604Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13272.827 ms) ====== [2025-12-06T13:07:51.604Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-06T13:07:51.604Z] GC before operation: completed in 137.612 ms, heap usage 159.409 MB -> 88.978 MB. [2025-12-06T13:07:53.788Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:07:55.394Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:07:57.583Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:07:59.770Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:08:00.877Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:08:01.981Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:08:03.091Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:08:04.192Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:08:04.530Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:08:04.530Z] The best model improves the baseline by 14.34%. [2025-12-06T13:08:04.530Z] Top recommended movies for user id 72: [2025-12-06T13:08:04.530Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:08:04.530Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:08:04.530Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:08:04.530Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:08:04.530Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:08:04.530Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13025.008 ms) ====== [2025-12-06T13:08:04.530Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-06T13:08:04.852Z] GC before operation: completed in 139.195 ms, heap usage 306.050 MB -> 89.113 MB. [2025-12-06T13:08:07.133Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:08:08.757Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:08:10.953Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:08:13.201Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:08:13.879Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:08:14.986Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:08:16.577Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:08:17.687Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:08:17.687Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:08:17.687Z] The best model improves the baseline by 14.34%. [2025-12-06T13:08:18.003Z] Top recommended movies for user id 72: [2025-12-06T13:08:18.003Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:08:18.003Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:08:18.003Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:08:18.003Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:08:18.003Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:08:18.003Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13114.826 ms) ====== [2025-12-06T13:08:18.003Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-06T13:08:18.003Z] GC before operation: completed in 133.126 ms, heap usage 145.378 MB -> 88.883 MB. [2025-12-06T13:08:20.180Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-06T13:08:22.361Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-06T13:08:23.952Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-06T13:08:26.127Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-06T13:08:27.225Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-06T13:08:28.401Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-06T13:08:29.502Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-06T13:08:31.105Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-06T13:08:31.105Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-12-06T13:08:31.417Z] The best model improves the baseline by 14.34%. [2025-12-06T13:08:31.417Z] Top recommended movies for user id 72: [2025-12-06T13:08:31.417Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-12-06T13:08:31.417Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-12-06T13:08:31.417Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-12-06T13:08:31.417Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-12-06T13:08:31.417Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-12-06T13:08:31.417Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13334.817 ms) ====== [2025-12-06T13:08:31.730Z] ----------------------------------- [2025-12-06T13:08:31.730Z] renaissance-movie-lens_0_PASSED [2025-12-06T13:08:31.730Z] ----------------------------------- [2025-12-06T13:08:31.730Z] [2025-12-06T13:08:31.730Z] TEST TEARDOWN: [2025-12-06T13:08:31.730Z] Nothing to be done for teardown. [2025-12-06T13:08:31.730Z] renaissance-movie-lens_0 Finish Time: Sat Dec 6 13:08:31 2025 Epoch Time (ms): 1765026511712