[2025-11-29T13:37:09.442Z] Running test renaissance-movie-lens_0 ... [2025-11-29T13:37:09.442Z] =============================================== [2025-11-29T13:37:09.442Z] renaissance-movie-lens_0 Start Time: Sat Nov 29 13:37:09 2025 Epoch Time (ms): 1764423429195 [2025-11-29T13:37:09.442Z] variation: NoOptions [2025-11-29T13:37:09.442Z] JVM_OPTIONS: [2025-11-29T13:37:09.442Z] { \ [2025-11-29T13:37:09.442Z] echo ""; echo "TEST SETUP:"; \ [2025-11-29T13:37:09.442Z] echo "Nothing to be done for setup."; \ [2025-11-29T13:37:09.442Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17644217386136/renaissance-movie-lens_0"; \ [2025-11-29T13:37:09.442Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17644217386136/renaissance-movie-lens_0"; \ [2025-11-29T13:37:09.442Z] echo ""; echo "TESTING:"; \ [2025-11-29T13:37:09.442Z] "/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_17644217386136/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-29T13:37:09.442Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17644217386136/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-29T13:37:09.442Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-29T13:37:09.442Z] echo "Nothing to be done for teardown."; \ [2025-11-29T13:37:09.442Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17644217386136/TestTargetResult"; [2025-11-29T13:37:09.442Z] [2025-11-29T13:37:09.442Z] TEST SETUP: [2025-11-29T13:37:09.442Z] Nothing to be done for setup. [2025-11-29T13:37:09.442Z] [2025-11-29T13:37:09.442Z] TESTING: [2025-11-29T13:37:09.800Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called [2025-11-29T13:37:09.800Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_linux/aqa-tests/TKG/output_17644217386136/renaissance-movie-lens_0/launcher-133709-11241954346312928694/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar) [2025-11-29T13:37:09.800Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$ [2025-11-29T13:37:09.800Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release [2025-11-29T13:37:14.575Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-11-29T13:37:21.932Z] 13:37:20.672 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-11-29T13:37:23.601Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-29T13:37:24.753Z] Training: 60056, validation: 20285, test: 19854 [2025-11-29T13:37:24.753Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-29T13:37:24.753Z] GC before operation: completed in 115.570 ms, heap usage 143.057 MB -> 75.363 MB. [2025-11-29T13:37:32.018Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:37:36.826Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:37:41.603Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:37:44.567Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:37:46.827Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:37:49.089Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:37:50.767Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:37:52.507Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:37:52.840Z] 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. [2025-11-29T13:37:53.196Z] The best model improves the baseline by 14.34%. [2025-11-29T13:37:53.196Z] Top recommended movies for user id 72: [2025-11-29T13:37:53.196Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:37:53.196Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:37:53.196Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:37:53.196Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:37:53.196Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:37:53.196Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28539.416 ms) ====== [2025-11-29T13:37:53.196Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-29T13:37:53.196Z] GC before operation: completed in 152.057 ms, heap usage 451.048 MB -> 89.688 MB. [2025-11-29T13:37:56.234Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:37:58.522Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:38:01.491Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:38:03.759Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:38:04.902Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:38:06.056Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:38:07.731Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:38:08.875Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:38:09.219Z] 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. [2025-11-29T13:38:09.219Z] The best model improves the baseline by 14.34%. [2025-11-29T13:38:09.219Z] Top recommended movies for user id 72: [2025-11-29T13:38:09.219Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:38:09.219Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:38:09.219Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:38:09.219Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:38:09.219Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:38:09.219Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (15999.843 ms) ====== [2025-11-29T13:38:09.219Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-29T13:38:09.546Z] GC before operation: completed in 142.845 ms, heap usage 216.561 MB -> 87.518 MB. [2025-11-29T13:38:11.811Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:38:14.067Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:38:17.019Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:38:18.669Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:38:19.812Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:38:21.467Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:38:23.123Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:38:24.361Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:38:24.753Z] 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. [2025-11-29T13:38:24.753Z] The best model improves the baseline by 14.34%. [2025-11-29T13:38:24.753Z] Top recommended movies for user id 72: [2025-11-29T13:38:24.753Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:38:24.753Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:38:24.753Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:38:24.753Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:38:24.753Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:38:24.753Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15277.948 ms) ====== [2025-11-29T13:38:24.753Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-29T13:38:25.083Z] GC before operation: completed in 142.132 ms, heap usage 439.144 MB -> 91.686 MB. [2025-11-29T13:38:27.336Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:38:29.585Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:38:31.832Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:38:33.491Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:38:35.177Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:38:36.318Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:38:37.468Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:38:38.640Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:38:38.967Z] 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. [2025-11-29T13:38:38.967Z] The best model improves the baseline by 14.34%. [2025-11-29T13:38:38.967Z] Top recommended movies for user id 72: [2025-11-29T13:38:38.967Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:38:38.967Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:38:38.967Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:38:38.967Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:38:38.967Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:38:38.967Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14182.759 ms) ====== [2025-11-29T13:38:38.967Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-29T13:38:39.295Z] GC before operation: completed in 144.121 ms, heap usage 119.991 MB -> 88.793 MB. [2025-11-29T13:38:41.552Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:38:43.827Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:38:46.073Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:38:48.337Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:38:49.062Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:38:50.744Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:38:51.899Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:38:53.048Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:38:53.048Z] 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. [2025-11-29T13:38:53.048Z] The best model improves the baseline by 14.34%. [2025-11-29T13:38:53.378Z] Top recommended movies for user id 72: [2025-11-29T13:38:53.378Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:38:53.378Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:38:53.378Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:38:53.378Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:38:53.378Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:38:53.378Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14023.026 ms) ====== [2025-11-29T13:38:53.378Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-29T13:38:53.378Z] GC before operation: completed in 162.083 ms, heap usage 496.840 MB -> 92.241 MB. [2025-11-29T13:38:55.659Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:38:57.915Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:39:00.184Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:39:01.835Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:39:03.000Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:39:04.257Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:39:05.404Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:39:06.567Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:39:06.898Z] 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. [2025-11-29T13:39:06.898Z] The best model improves the baseline by 14.34%. [2025-11-29T13:39:06.898Z] Top recommended movies for user id 72: [2025-11-29T13:39:06.898Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:39:06.898Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:39:06.898Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:39:06.898Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:39:06.898Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:39:06.898Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13580.940 ms) ====== [2025-11-29T13:39:06.898Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-29T13:39:07.234Z] GC before operation: completed in 144.324 ms, heap usage 203.931 MB -> 88.645 MB. [2025-11-29T13:39:09.524Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:39:11.183Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:39:13.441Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:39:15.691Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:39:17.340Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:39:18.518Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:39:19.670Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:39:20.827Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:39:21.165Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:39:21.165Z] The best model improves the baseline by 14.34%. [2025-11-29T13:39:21.165Z] Top recommended movies for user id 72: [2025-11-29T13:39:21.165Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:39:21.165Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:39:21.165Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:39:21.165Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:39:21.165Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:39:21.165Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14117.572 ms) ====== [2025-11-29T13:39:21.165Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-29T13:39:21.504Z] GC before operation: completed in 132.612 ms, heap usage 251.110 MB -> 88.785 MB. [2025-11-29T13:39:23.805Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:39:25.540Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:39:27.826Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:39:29.507Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:39:30.667Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:39:32.037Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:39:33.696Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:39:34.409Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:39:34.739Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-29T13:39:34.739Z] The best model improves the baseline by 14.34%. [2025-11-29T13:39:34.739Z] Top recommended movies for user id 72: [2025-11-29T13:39:34.739Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:39:34.739Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:39:34.739Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:39:34.739Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:39:34.739Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:39:34.739Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13466.031 ms) ====== [2025-11-29T13:39:34.739Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-29T13:39:35.072Z] GC before operation: completed in 151.888 ms, heap usage 347.822 MB -> 89.164 MB. [2025-11-29T13:39:37.333Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:39:39.021Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:39:41.302Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:39:43.604Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:39:44.318Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:39:45.480Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:39:47.165Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:39:48.482Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:39:48.809Z] 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. [2025-11-29T13:39:48.809Z] The best model improves the baseline by 14.34%. [2025-11-29T13:39:48.809Z] Top recommended movies for user id 72: [2025-11-29T13:39:48.809Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:39:48.809Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:39:48.809Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:39:48.809Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:39:48.809Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:39:48.809Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13849.296 ms) ====== [2025-11-29T13:39:48.809Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-29T13:39:49.151Z] GC before operation: completed in 139.094 ms, heap usage 165.925 MB -> 88.744 MB. [2025-11-29T13:39:51.413Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:39:53.084Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:39:55.355Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:39:57.045Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:39:58.211Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:39:59.374Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:40:00.599Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:40:01.835Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:40:02.175Z] 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. [2025-11-29T13:40:02.175Z] The best model improves the baseline by 14.34%. [2025-11-29T13:40:02.175Z] Top recommended movies for user id 72: [2025-11-29T13:40:02.175Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:40:02.175Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:40:02.175Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:40:02.175Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:40:02.175Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:40:02.175Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13258.403 ms) ====== [2025-11-29T13:40:02.175Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-29T13:40:02.513Z] GC before operation: completed in 146.444 ms, heap usage 399.283 MB -> 89.411 MB. [2025-11-29T13:40:04.313Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:40:06.996Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:40:08.750Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:40:10.460Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:40:11.685Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:40:12.852Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:40:14.532Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:40:15.704Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:40:15.704Z] 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. [2025-11-29T13:40:15.704Z] The best model improves the baseline by 14.34%. [2025-11-29T13:40:16.037Z] Top recommended movies for user id 72: [2025-11-29T13:40:16.037Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:40:16.037Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:40:16.037Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:40:16.037Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:40:16.037Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:40:16.037Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13488.968 ms) ====== [2025-11-29T13:40:16.037Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-29T13:40:16.037Z] GC before operation: completed in 134.742 ms, heap usage 201.983 MB -> 88.699 MB. [2025-11-29T13:40:18.315Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:40:19.983Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:40:22.241Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:40:23.921Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:40:24.635Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:40:25.791Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:40:27.477Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:40:28.212Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:40:28.553Z] 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. [2025-11-29T13:40:28.553Z] The best model improves the baseline by 14.34%. [2025-11-29T13:40:28.553Z] Top recommended movies for user id 72: [2025-11-29T13:40:28.553Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:40:28.553Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:40:28.553Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:40:28.553Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:40:28.553Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:40:28.553Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12601.011 ms) ====== [2025-11-29T13:40:28.553Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-29T13:40:28.888Z] GC before operation: completed in 139.683 ms, heap usage 611.053 MB -> 92.922 MB. [2025-11-29T13:40:30.638Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:40:32.915Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:40:34.584Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:40:36.856Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:40:37.571Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:40:38.722Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:40:39.963Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:40:41.329Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:40:41.662Z] 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. [2025-11-29T13:40:41.662Z] The best model improves the baseline by 14.34%. [2025-11-29T13:40:41.662Z] Top recommended movies for user id 72: [2025-11-29T13:40:41.662Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:40:41.662Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:40:41.662Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:40:41.662Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:40:41.662Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:40:41.662Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (12923.156 ms) ====== [2025-11-29T13:40:41.662Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-29T13:40:41.990Z] GC before operation: completed in 135.055 ms, heap usage 150.675 MB -> 89.010 MB. [2025-11-29T13:40:43.910Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:40:46.284Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:40:48.529Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:40:49.763Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:40:51.413Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:40:52.117Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:40:53.767Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:40:54.471Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:40:54.799Z] 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. [2025-11-29T13:40:54.799Z] The best model improves the baseline by 14.34%. [2025-11-29T13:40:54.799Z] Top recommended movies for user id 72: [2025-11-29T13:40:54.799Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:40:54.799Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:40:54.799Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:40:54.799Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:40:54.799Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:40:54.799Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13025.501 ms) ====== [2025-11-29T13:40:54.799Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-29T13:40:55.125Z] GC before operation: completed in 129.750 ms, heap usage 116.247 MB -> 91.800 MB. [2025-11-29T13:40:57.372Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:40:59.029Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:41:01.276Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:41:02.929Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:41:04.088Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:41:05.238Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:41:06.396Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:41:07.598Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:41:07.598Z] 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. [2025-11-29T13:41:07.598Z] The best model improves the baseline by 14.34%. [2025-11-29T13:41:07.943Z] Top recommended movies for user id 72: [2025-11-29T13:41:07.943Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:41:07.943Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:41:07.943Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:41:07.943Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:41:07.943Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:41:07.943Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12788.147 ms) ====== [2025-11-29T13:41:07.943Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-29T13:41:07.943Z] GC before operation: completed in 138.781 ms, heap usage 545.676 MB -> 92.819 MB. [2025-11-29T13:41:09.862Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:41:12.177Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:41:13.736Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:41:15.650Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:41:16.833Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:41:18.013Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:41:19.181Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:41:20.346Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:41:20.697Z] 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. [2025-11-29T13:41:20.697Z] The best model improves the baseline by 14.34%. [2025-11-29T13:41:20.697Z] Top recommended movies for user id 72: [2025-11-29T13:41:20.697Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:41:20.697Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:41:20.697Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:41:20.697Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:41:20.697Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:41:20.697Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12810.339 ms) ====== [2025-11-29T13:41:20.697Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-29T13:41:21.043Z] GC before operation: completed in 138.047 ms, heap usage 585.605 MB -> 92.772 MB. [2025-11-29T13:41:22.708Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:41:24.963Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:41:26.611Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:41:28.856Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:41:29.561Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:41:30.711Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:41:31.935Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:41:33.087Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:41:33.463Z] 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. [2025-11-29T13:41:33.463Z] The best model improves the baseline by 14.34%. [2025-11-29T13:41:33.463Z] Top recommended movies for user id 72: [2025-11-29T13:41:33.463Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:41:33.463Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:41:33.463Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:41:33.463Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:41:33.463Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:41:33.463Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12519.150 ms) ====== [2025-11-29T13:41:33.463Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-29T13:41:33.463Z] GC before operation: completed in 141.581 ms, heap usage 352.882 MB -> 89.241 MB. [2025-11-29T13:41:35.732Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:41:37.397Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:41:39.731Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:41:41.405Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:41:42.581Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:41:43.723Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:41:45.077Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:41:46.227Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:41:46.227Z] 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. [2025-11-29T13:41:46.227Z] The best model improves the baseline by 14.34%. [2025-11-29T13:41:46.557Z] Top recommended movies for user id 72: [2025-11-29T13:41:46.557Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:41:46.557Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:41:46.557Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:41:46.557Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:41:46.557Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:41:46.557Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (12911.349 ms) ====== [2025-11-29T13:41:46.557Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-29T13:41:46.558Z] GC before operation: completed in 137.981 ms, heap usage 405.895 MB -> 89.185 MB. [2025-11-29T13:41:48.813Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:41:50.478Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:41:52.724Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:41:54.435Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:41:55.137Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:41:56.285Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:41:57.462Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:41:58.631Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:41:58.968Z] 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. [2025-11-29T13:41:58.968Z] The best model improves the baseline by 14.34%. [2025-11-29T13:41:58.968Z] Top recommended movies for user id 72: [2025-11-29T13:41:58.968Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:41:58.968Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:41:58.968Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:41:58.968Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:41:58.968Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:41:58.968Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12448.549 ms) ====== [2025-11-29T13:41:58.968Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-29T13:41:59.300Z] GC before operation: completed in 133.614 ms, heap usage 350.893 MB -> 89.234 MB. [2025-11-29T13:42:00.974Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-29T13:42:03.252Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-29T13:42:04.911Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-29T13:42:06.568Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-29T13:42:07.711Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-29T13:42:08.854Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-29T13:42:10.094Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-29T13:42:11.241Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-29T13:42:11.581Z] 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. [2025-11-29T13:42:11.581Z] The best model improves the baseline by 14.34%. [2025-11-29T13:42:11.581Z] Top recommended movies for user id 72: [2025-11-29T13:42:11.581Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-29T13:42:11.581Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-29T13:42:11.581Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-29T13:42:11.581Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-29T13:42:11.581Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-29T13:42:11.581Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12422.650 ms) ====== [2025-11-29T13:42:12.293Z] ----------------------------------- [2025-11-29T13:42:12.293Z] renaissance-movie-lens_0_PASSED [2025-11-29T13:42:12.293Z] ----------------------------------- [2025-11-29T13:42:12.293Z] [2025-11-29T13:42:12.293Z] TEST TEARDOWN: [2025-11-29T13:42:12.293Z] Nothing to be done for teardown. [2025-11-29T13:42:12.293Z] renaissance-movie-lens_0 Finish Time: Sat Nov 29 13:42:11 2025 Epoch Time (ms): 1764423731937