renaissance-movie-lens_0
[2025-12-13T18:35:15.729Z] Running test renaissance-movie-lens_0 ...
[2025-12-13T18:35:15.729Z] ===============================================
[2025-12-13T18:35:15.729Z] renaissance-movie-lens_0 Start Time: Sat Dec 13 18:35:15 2025 Epoch Time (ms): 1765650915374
[2025-12-13T18:35:15.729Z] variation: NoOptions
[2025-12-13T18:35:15.729Z] JVM_OPTIONS:
[2025-12-13T18:35:15.729Z] { \
[2025-12-13T18:35:15.729Z] echo ""; echo "TEST SETUP:"; \
[2025-12-13T18:35:15.729Z] echo "Nothing to be done for setup."; \
[2025-12-13T18:35:15.729Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17656474872646/renaissance-movie-lens_0"; \
[2025-12-13T18:35:15.729Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17656474872646/renaissance-movie-lens_0"; \
[2025-12-13T18:35:15.729Z] echo ""; echo "TESTING:"; \
[2025-12-13T18:35:15.729Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17656474872646/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-13T18:35:15.729Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17656474872646/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-13T18:35:15.729Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-13T18:35:15.729Z] echo "Nothing to be done for teardown."; \
[2025-12-13T18:35:15.729Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17656474872646/TestTargetResult";
[2025-12-13T18:35:15.729Z]
[2025-12-13T18:35:15.729Z] TEST SETUP:
[2025-12-13T18:35:15.729Z] Nothing to be done for setup.
[2025-12-13T18:35:15.729Z]
[2025-12-13T18:35:15.729Z] TESTING:
[2025-12-13T18:35:17.952Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-13T18:35:17.952Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/output_17656474872646/renaissance-movie-lens_0/launcher-183516-12649077405941675816/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-13T18:35:17.952Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-13T18:35:17.952Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-13T18:35:40.927Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-13T18:36:14.340Z] 18:36:09.272 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-13T18:36:19.058Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-13T18:36:21.990Z] Training: 60056, validation: 20285, test: 19854
[2025-12-13T18:36:21.990Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-13T18:36:21.990Z] GC before operation: completed in 551.820 ms, heap usage 401.095 MB -> 76.155 MB.
[2025-12-13T18:36:49.661Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:37:02.845Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:37:13.639Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:37:24.419Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:37:31.675Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:37:38.907Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:37:44.878Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:37:50.744Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:37:51.875Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:37:52.199Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:37:52.900Z] Top recommended movies for user id 72:
[2025-12-13T18:37:52.900Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:37:52.900Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:37:52.900Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:37:52.900Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:37:52.900Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:37:52.900Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (90856.831 ms) ======
[2025-12-13T18:37:52.900Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-13T18:37:54.065Z] GC before operation: completed in 1057.943 ms, heap usage 647.374 MB -> 95.027 MB.
[2025-12-13T18:38:07.140Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:38:14.358Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:38:25.150Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:38:34.032Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:38:38.765Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:38:44.616Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:38:51.878Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:38:57.739Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:38:57.739Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:38:57.739Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:38:58.477Z] Top recommended movies for user id 72:
[2025-12-13T18:38:58.477Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:38:58.477Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:38:58.477Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:38:58.477Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:38:58.477Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:38:58.477Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (64483.562 ms) ======
[2025-12-13T18:38:58.477Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-13T18:38:59.641Z] GC before operation: completed in 967.977 ms, heap usage 759.354 MB -> 92.762 MB.
[2025-12-13T18:39:10.562Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:39:17.832Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:39:26.666Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:39:35.545Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:39:40.252Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:39:45.151Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:39:49.860Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:39:54.570Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:39:55.701Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:39:55.701Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:39:56.399Z] Top recommended movies for user id 72:
[2025-12-13T18:39:56.399Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:39:56.399Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:39:56.399Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:39:56.399Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:39:56.399Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:39:56.399Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (56975.964 ms) ======
[2025-12-13T18:39:56.399Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-13T18:39:57.563Z] GC before operation: completed in 919.491 ms, heap usage 291.234 MB -> 89.724 MB.
[2025-12-13T18:40:06.395Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:40:15.272Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:40:22.580Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:40:31.416Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:40:36.148Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:40:40.859Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:40:45.588Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:40:51.444Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:40:51.444Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:40:51.444Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:40:52.175Z] Top recommended movies for user id 72:
[2025-12-13T18:40:52.175Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:40:52.175Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:40:52.175Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:40:52.175Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:40:52.175Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:40:52.176Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (54889.843 ms) ======
[2025-12-13T18:40:52.176Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-13T18:40:53.341Z] GC before operation: completed in 844.801 ms, heap usage 170.700 MB -> 89.975 MB.
[2025-12-13T18:41:02.287Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:41:11.143Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:41:18.349Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:41:27.194Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:41:31.904Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:41:36.647Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:41:41.348Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:41:47.206Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:41:47.206Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:41:47.526Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:41:47.848Z] Top recommended movies for user id 72:
[2025-12-13T18:41:47.848Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:41:47.848Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:41:47.848Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:41:47.848Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:41:47.848Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:41:47.848Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (54846.939 ms) ======
[2025-12-13T18:41:47.848Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-13T18:41:48.999Z] GC before operation: completed in 793.933 ms, heap usage 304.503 MB -> 89.985 MB.
[2025-12-13T18:41:57.860Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:42:05.089Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:42:14.153Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:42:21.365Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:42:25.105Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:42:29.833Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:42:34.533Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:42:40.407Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:42:40.736Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:42:41.062Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:42:41.774Z] Top recommended movies for user id 72:
[2025-12-13T18:42:41.774Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:42:41.774Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:42:41.774Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:42:41.774Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:42:41.774Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:42:41.774Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (52875.128 ms) ======
[2025-12-13T18:42:41.774Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-13T18:42:42.480Z] GC before operation: completed in 658.560 ms, heap usage 455.445 MB -> 90.510 MB.
[2025-12-13T18:42:51.325Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:42:58.528Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:43:07.388Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:43:16.227Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:43:20.008Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:43:24.729Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:43:29.547Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:43:34.268Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:43:35.917Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:43:35.917Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:43:36.241Z] Top recommended movies for user id 72:
[2025-12-13T18:43:36.241Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:43:36.241Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:43:36.241Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:43:36.241Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:43:36.241Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:43:36.241Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (53951.745 ms) ======
[2025-12-13T18:43:36.241Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-13T18:43:36.956Z] GC before operation: completed in 654.893 ms, heap usage 334.016 MB -> 90.262 MB.
[2025-12-13T18:43:45.809Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:43:54.652Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:44:01.862Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:44:09.729Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:44:14.430Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:44:19.153Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:44:25.058Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:44:29.765Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:44:30.460Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:44:30.460Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:44:31.156Z] Top recommended movies for user id 72:
[2025-12-13T18:44:31.156Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:44:31.156Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:44:31.156Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:44:31.156Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:44:31.156Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:44:31.156Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (54287.290 ms) ======
[2025-12-13T18:44:31.156Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-13T18:44:31.869Z] GC before operation: completed in 648.653 ms, heap usage 182.437 MB -> 90.331 MB.
[2025-12-13T18:44:40.699Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:44:48.019Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:44:56.843Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:45:04.055Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:45:09.904Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:45:14.615Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:45:19.320Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:45:24.107Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:45:24.431Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:45:24.756Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:45:25.454Z] Top recommended movies for user id 72:
[2025-12-13T18:45:25.454Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:45:25.454Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:45:25.454Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:45:25.454Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:45:25.454Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:45:25.454Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (53636.596 ms) ======
[2025-12-13T18:45:25.454Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-13T18:45:26.159Z] GC before operation: completed in 660.497 ms, heap usage 302.706 MB -> 90.399 MB.
[2025-12-13T18:45:34.995Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:45:42.219Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:45:49.436Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:45:56.748Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:46:00.617Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:46:05.320Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:46:10.028Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:46:14.737Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:46:15.060Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:46:15.060Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:46:15.775Z] Top recommended movies for user id 72:
[2025-12-13T18:46:15.775Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:46:15.775Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:46:15.775Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:46:15.775Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:46:15.775Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:46:15.775Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (49491.328 ms) ======
[2025-12-13T18:46:15.775Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-13T18:46:16.480Z] GC before operation: completed in 684.420 ms, heap usage 448.706 MB -> 90.787 MB.
[2025-12-13T18:46:25.313Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:46:32.525Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:46:39.769Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:46:47.154Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:46:50.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:46:55.598Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:47:00.309Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:47:05.108Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:47:05.803Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:47:05.803Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:47:06.521Z] Top recommended movies for user id 72:
[2025-12-13T18:47:06.521Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:47:06.521Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:47:06.521Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:47:06.521Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:47:06.521Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:47:06.521Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (50101.037 ms) ======
[2025-12-13T18:47:06.521Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-13T18:47:07.239Z] GC before operation: completed in 693.297 ms, heap usage 541.102 MB -> 90.604 MB.
[2025-12-13T18:47:16.066Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:47:21.923Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:47:29.142Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:47:36.528Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:47:41.234Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:47:45.938Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:47:50.643Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:47:54.384Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:47:55.513Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:47:55.513Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:47:56.225Z] Top recommended movies for user id 72:
[2025-12-13T18:47:56.225Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:47:56.225Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:47:56.225Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:47:56.225Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:47:56.225Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:47:56.225Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (48948.440 ms) ======
[2025-12-13T18:47:56.225Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-13T18:47:56.928Z] GC before operation: completed in 687.683 ms, heap usage 450.546 MB -> 90.727 MB.
[2025-12-13T18:48:05.780Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:48:11.645Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:48:20.488Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:48:26.349Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:48:31.057Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:48:35.760Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:48:40.523Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:48:45.255Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:48:45.956Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:48:46.296Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:48:46.626Z] Top recommended movies for user id 72:
[2025-12-13T18:48:46.626Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:48:46.626Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:48:46.626Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:48:46.626Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:48:46.626Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:48:46.626Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (50004.026 ms) ======
[2025-12-13T18:48:46.626Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-13T18:48:47.339Z] GC before operation: completed in 674.520 ms, heap usage 262.305 MB -> 90.590 MB.
[2025-12-13T18:48:56.177Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:49:03.391Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:49:12.216Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:49:19.838Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:49:25.692Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:49:29.460Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:49:35.316Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:49:40.017Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:49:40.342Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:49:40.663Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:49:41.368Z] Top recommended movies for user id 72:
[2025-12-13T18:49:41.368Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:49:41.368Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:49:41.368Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:49:41.368Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:49:41.368Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:49:41.368Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (53736.142 ms) ======
[2025-12-13T18:49:41.368Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-13T18:49:42.077Z] GC before operation: completed in 682.482 ms, heap usage 297.819 MB -> 90.464 MB.
[2025-12-13T18:49:50.901Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:49:58.248Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:50:05.456Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:50:11.349Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:50:16.123Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:50:20.824Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:50:24.561Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:50:29.301Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:50:29.996Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:50:29.996Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:50:30.706Z] Top recommended movies for user id 72:
[2025-12-13T18:50:30.706Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:50:30.706Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:50:30.706Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:50:30.706Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:50:30.706Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:50:30.706Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (48687.667 ms) ======
[2025-12-13T18:50:30.706Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-13T18:50:31.411Z] GC before operation: completed in 722.416 ms, heap usage 900.041 MB -> 95.082 MB.
[2025-12-13T18:50:40.324Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:50:47.542Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:50:54.768Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:51:01.991Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:51:05.736Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:51:10.458Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:51:15.178Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:51:19.966Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:51:20.294Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:51:20.617Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:51:20.940Z] Top recommended movies for user id 72:
[2025-12-13T18:51:20.940Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:51:20.940Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:51:20.940Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:51:20.940Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:51:20.940Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:51:20.940Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (49786.231 ms) ======
[2025-12-13T18:51:20.940Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-13T18:51:21.660Z] GC before operation: completed in 726.950 ms, heap usage 828.494 MB -> 94.482 MB.
[2025-12-13T18:51:30.507Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:51:37.733Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:51:45.000Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:51:53.893Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:51:57.632Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:52:02.337Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:52:07.294Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:52:11.996Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:52:12.697Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:52:12.697Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:52:13.395Z] Top recommended movies for user id 72:
[2025-12-13T18:52:13.395Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:52:13.395Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:52:13.395Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:52:13.395Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:52:13.395Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:52:13.395Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (51424.123 ms) ======
[2025-12-13T18:52:13.395Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-13T18:52:14.098Z] GC before operation: completed in 683.265 ms, heap usage 420.657 MB -> 90.797 MB.
[2025-12-13T18:52:23.007Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:52:30.218Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:52:39.040Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:52:46.250Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:52:50.996Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:52:56.860Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:53:01.577Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:53:06.277Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:53:06.604Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:53:06.926Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:53:07.629Z] Top recommended movies for user id 72:
[2025-12-13T18:53:07.629Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:53:07.629Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:53:07.629Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:53:07.629Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:53:07.629Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:53:07.629Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (53531.414 ms) ======
[2025-12-13T18:53:07.629Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-13T18:53:08.326Z] GC before operation: completed in 680.547 ms, heap usage 229.978 MB -> 90.315 MB.
[2025-12-13T18:53:15.557Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:53:24.404Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:53:31.602Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:53:38.817Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:53:43.518Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:53:48.216Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:53:52.922Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:53:57.634Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:53:58.764Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:53:58.764Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:53:59.460Z] Top recommended movies for user id 72:
[2025-12-13T18:53:59.460Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:53:59.460Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:53:59.460Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:53:59.460Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:53:59.460Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:53:59.460Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (51374.917 ms) ======
[2025-12-13T18:53:59.460Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-13T18:54:00.154Z] GC before operation: completed in 685.739 ms, heap usage 136.758 MB -> 90.324 MB.
[2025-12-13T18:54:09.138Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-13T18:54:15.003Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-13T18:54:22.262Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-13T18:54:29.473Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-13T18:54:34.186Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-13T18:54:37.923Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-13T18:54:42.700Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-13T18:54:46.498Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-13T18:54:47.628Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-13T18:54:47.628Z] The best model improves the baseline by 14.52%.
[2025-12-13T18:54:48.326Z] Top recommended movies for user id 72:
[2025-12-13T18:54:48.326Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-13T18:54:48.326Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-13T18:54:48.326Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-13T18:54:48.326Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-13T18:54:48.326Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-13T18:54:48.326Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (48033.456 ms) ======
[2025-12-13T18:54:52.075Z] -----------------------------------
[2025-12-13T18:54:52.075Z] renaissance-movie-lens_0_PASSED
[2025-12-13T18:54:52.075Z] -----------------------------------
[2025-12-13T18:54:52.075Z]
[2025-12-13T18:54:52.075Z] TEST TEARDOWN:
[2025-12-13T18:54:52.075Z] Nothing to be done for teardown.
[2025-12-13T18:54:52.075Z] renaissance-movie-lens_0 Finish Time: Sat Dec 13 18:54:51 2025 Epoch Time (ms): 1765652091853