renaissance-movie-lens_0
[2025-12-27T18:42:41.538Z] Running test renaissance-movie-lens_0 ...
[2025-12-27T18:42:41.538Z] ===============================================
[2025-12-27T18:42:41.538Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 18:42:39 2025 Epoch Time (ms): 1766860959329
[2025-12-27T18:42:41.538Z] variation: NoOptions
[2025-12-27T18:42:41.538Z] JVM_OPTIONS:
[2025-12-27T18:42:41.538Z] { \
[2025-12-27T18:42:41.538Z] echo ""; echo "TEST SETUP:"; \
[2025-12-27T18:42:41.538Z] echo "Nothing to be done for setup."; \
[2025-12-27T18:42:41.538Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17668594028800/renaissance-movie-lens_0"; \
[2025-12-27T18:42:41.538Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17668594028800/renaissance-movie-lens_0"; \
[2025-12-27T18:42:41.538Z] echo ""; echo "TESTING:"; \
[2025-12-27T18:42:41.538Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/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_2/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17668594028800/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-27T18:42:41.538Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17668594028800/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-27T18:42:41.538Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-27T18:42:41.538Z] echo "Nothing to be done for teardown."; \
[2025-12-27T18:42:41.538Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17668594028800/TestTargetResult";
[2025-12-27T18:42:41.538Z]
[2025-12-27T18:42:41.538Z] TEST SETUP:
[2025-12-27T18:42:41.538Z] Nothing to be done for setup.
[2025-12-27T18:42:41.538Z]
[2025-12-27T18:42:41.538Z] TESTING:
[2025-12-27T18:42:41.875Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-27T18:42:41.875Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/output_17668594028800/renaissance-movie-lens_0/launcher-184240-2006572560805575814/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-27T18:42:41.875Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-27T18:42:41.875Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-27T18:43:05.027Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-27T18:43:38.465Z] 18:43:34.439 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-27T18:43:44.430Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-27T18:43:46.725Z] Training: 60056, validation: 20285, test: 19854
[2025-12-27T18:43:46.725Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-27T18:43:47.453Z] GC before operation: completed in 578.909 ms, heap usage 394.953 MB -> 76.022 MB.
[2025-12-27T18:44:15.344Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:44:28.560Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:44:39.462Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:44:50.454Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:44:57.797Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:45:05.134Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:45:11.093Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:45:17.063Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:45:17.785Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T18:45:18.122Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:45:19.293Z] Top recommended movies for user id 72:
[2025-12-27T18:45:19.293Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:45:19.293Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:45:19.293Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:45:19.293Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:45:19.293Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:45:19.293Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (92018.036 ms) ======
[2025-12-27T18:45:19.293Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-27T18:45:20.483Z] GC before operation: completed in 990.317 ms, heap usage 210.278 MB -> 88.372 MB.
[2025-12-27T18:45:31.430Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:45:42.328Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:45:51.314Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:46:02.225Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:46:07.045Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:46:13.027Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:46:19.001Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:46:24.967Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:46:25.304Z] 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.
[2025-12-27T18:46:25.304Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:46:26.024Z] Top recommended movies for user id 72:
[2025-12-27T18:46:26.024Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:46:26.024Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:46:26.024Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:46:26.024Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:46:26.024Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:46:26.024Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (65646.800 ms) ======
[2025-12-27T18:46:26.024Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-27T18:46:27.207Z] GC before operation: completed in 968.949 ms, heap usage 811.897 MB -> 92.733 MB.
[2025-12-27T18:46:38.104Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:46:45.447Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:46:54.441Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:47:03.666Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:47:08.511Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:47:13.309Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:47:19.263Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:47:24.064Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:47:24.785Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T18:47:24.785Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:47:25.516Z] Top recommended movies for user id 72:
[2025-12-27T18:47:25.516Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:47:25.516Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:47:25.516Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:47:25.516Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:47:25.516Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:47:25.516Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (58375.691 ms) ======
[2025-12-27T18:47:25.516Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-27T18:47:26.248Z] GC before operation: completed in 942.364 ms, heap usage 555.694 MB -> 89.802 MB.
[2025-12-27T18:47:35.212Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:47:44.160Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:47:51.483Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:48:00.435Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:48:05.229Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:48:11.178Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:48:16.007Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:48:20.798Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:48:21.519Z] 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.
[2025-12-27T18:48:21.852Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:48:22.187Z] Top recommended movies for user id 72:
[2025-12-27T18:48:22.187Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:48:22.187Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:48:22.187Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:48:22.187Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:48:22.187Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:48:22.187Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (56070.783 ms) ======
[2025-12-27T18:48:22.187Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-27T18:48:23.384Z] GC before operation: completed in 948.549 ms, heap usage 641.576 MB -> 93.429 MB.
[2025-12-27T18:48:32.336Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:48:41.307Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:48:50.266Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:48:57.611Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:49:03.575Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:49:08.385Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:49:13.460Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:49:18.271Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:49:19.435Z] 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.
[2025-12-27T18:49:19.435Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:49:19.773Z] Top recommended movies for user id 72:
[2025-12-27T18:49:19.773Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:49:19.773Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:49:19.773Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:49:19.773Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:49:19.773Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:49:19.773Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (56578.896 ms) ======
[2025-12-27T18:49:19.773Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-27T18:49:20.949Z] GC before operation: completed in 962.462 ms, heap usage 541.625 MB -> 90.050 MB.
[2025-12-27T18:49:31.864Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:49:37.842Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:49:46.799Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:49:54.145Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:49:58.946Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:50:03.765Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:50:08.637Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:50:13.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:50:13.437Z] 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.
[2025-12-27T18:50:13.775Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:50:14.502Z] Top recommended movies for user id 72:
[2025-12-27T18:50:14.502Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:50:14.502Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:50:14.502Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:50:14.502Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:50:14.502Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:50:14.502Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (53494.887 ms) ======
[2025-12-27T18:50:14.502Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-27T18:50:15.241Z] GC before operation: completed in 793.342 ms, heap usage 519.265 MB -> 90.341 MB.
[2025-12-27T18:50:24.200Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:50:31.548Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:50:38.892Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:50:46.229Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:50:51.044Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:50:55.852Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:51:00.653Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:51:05.448Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:51:06.168Z] 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.
[2025-12-27T18:51:06.504Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:51:07.229Z] Top recommended movies for user id 72:
[2025-12-27T18:51:07.229Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:51:07.229Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:51:07.229Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:51:07.229Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:51:07.229Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:51:07.229Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (51968.935 ms) ======
[2025-12-27T18:51:07.229Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-27T18:51:07.962Z] GC before operation: completed in 764.495 ms, heap usage 247.488 MB -> 89.889 MB.
[2025-12-27T18:51:17.109Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:51:24.454Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:51:31.773Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:51:39.098Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:51:43.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:51:48.708Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:51:53.501Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:51:57.319Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:51:58.488Z] 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.
[2025-12-27T18:51:58.488Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:51:59.204Z] Top recommended movies for user id 72:
[2025-12-27T18:51:59.204Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:51:59.204Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:51:59.204Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:51:59.204Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:51:59.204Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:51:59.204Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (51276.815 ms) ======
[2025-12-27T18:51:59.204Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-27T18:51:59.927Z] GC before operation: completed in 722.448 ms, heap usage 220.130 MB -> 90.067 MB.
[2025-12-27T18:52:08.864Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:52:16.185Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:52:23.510Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:52:30.833Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:52:34.647Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:52:39.456Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:52:44.263Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:52:49.073Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:52:49.792Z] 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.
[2025-12-27T18:52:50.128Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:52:50.857Z] Top recommended movies for user id 72:
[2025-12-27T18:52:50.857Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:52:50.857Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:52:50.857Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:52:50.857Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:52:50.857Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:52:50.857Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (50861.396 ms) ======
[2025-12-27T18:52:50.857Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-27T18:52:51.582Z] GC before operation: completed in 680.517 ms, heap usage 525.663 MB -> 90.420 MB.
[2025-12-27T18:53:00.542Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:53:07.871Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:53:16.871Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:53:24.659Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:53:28.485Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:53:34.446Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:53:39.250Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:53:44.051Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:53:45.100Z] 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.
[2025-12-27T18:53:45.439Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:53:46.171Z] Top recommended movies for user id 72:
[2025-12-27T18:53:46.171Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:53:46.171Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:53:46.171Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:53:46.171Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:53:46.171Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:53:46.171Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (54690.520 ms) ======
[2025-12-27T18:53:46.171Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-27T18:53:46.894Z] GC before operation: completed in 638.885 ms, heap usage 136.975 MB -> 90.130 MB.
[2025-12-27T18:53:55.869Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:54:03.178Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:54:12.142Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:54:19.464Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:54:24.252Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:54:30.213Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:54:35.176Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:54:41.150Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:54:41.150Z] 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.
[2025-12-27T18:54:41.150Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:54:41.875Z] Top recommended movies for user id 72:
[2025-12-27T18:54:41.875Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:54:41.875Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:54:41.875Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:54:41.875Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:54:41.875Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:54:41.875Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (55070.506 ms) ======
[2025-12-27T18:54:41.875Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-27T18:54:42.601Z] GC before operation: completed in 635.065 ms, heap usage 508.735 MB -> 90.375 MB.
[2025-12-27T18:54:51.557Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:54:58.893Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:55:07.848Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:55:15.327Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:55:20.144Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:55:24.949Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:55:29.764Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:55:34.569Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:55:35.733Z] 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.
[2025-12-27T18:55:35.733Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:55:36.479Z] Top recommended movies for user id 72:
[2025-12-27T18:55:36.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:55:36.479Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:55:36.479Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:55:36.479Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:55:36.479Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:55:36.479Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (53919.955 ms) ======
[2025-12-27T18:55:36.479Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-27T18:55:37.205Z] GC before operation: completed in 658.009 ms, heap usage 113.458 MB -> 90.004 MB.
[2025-12-27T18:55:46.163Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:55:53.747Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:56:01.111Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:56:08.502Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:56:13.300Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:56:18.108Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:56:22.917Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:56:27.957Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:56:28.680Z] 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.
[2025-12-27T18:56:28.680Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:56:29.403Z] Top recommended movies for user id 72:
[2025-12-27T18:56:29.403Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:56:29.403Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:56:29.403Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:56:29.403Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:56:29.403Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:56:29.403Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (52387.213 ms) ======
[2025-12-27T18:56:29.403Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-27T18:56:30.137Z] GC before operation: completed in 693.891 ms, heap usage 540.238 MB -> 90.687 MB.
[2025-12-27T18:56:39.101Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:56:46.432Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:56:53.784Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:57:01.123Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:57:05.923Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:57:10.807Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:57:15.671Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:57:19.497Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:57:20.667Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T18:57:20.667Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:57:21.005Z] Top recommended movies for user id 72:
[2025-12-27T18:57:21.005Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:57:21.005Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:57:21.005Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:57:21.005Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:57:21.005Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:57:21.005Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (51058.643 ms) ======
[2025-12-27T18:57:21.005Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-27T18:57:21.733Z] GC before operation: completed in 667.152 ms, heap usage 121.410 MB -> 89.956 MB.
[2025-12-27T18:57:30.705Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:57:38.046Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:57:45.684Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:57:53.017Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:57:56.861Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:58:01.681Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:58:06.479Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:58:11.276Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:58:11.611Z] 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.
[2025-12-27T18:58:11.612Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:58:12.338Z] Top recommended movies for user id 72:
[2025-12-27T18:58:12.338Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:58:12.338Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:58:12.338Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:58:12.338Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:58:12.338Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:58:12.338Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (50432.815 ms) ======
[2025-12-27T18:58:12.338Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-27T18:58:13.070Z] GC before operation: completed in 661.067 ms, heap usage 281.518 MB -> 90.369 MB.
[2025-12-27T18:58:22.120Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:58:29.455Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:58:36.785Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:58:44.119Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:58:47.941Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:58:52.759Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:58:58.796Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:59:02.620Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:59:03.341Z] 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.
[2025-12-27T18:59:03.341Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:59:04.061Z] Top recommended movies for user id 72:
[2025-12-27T18:59:04.061Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:59:04.061Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:59:04.061Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:59:04.061Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:59:04.061Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:59:04.061Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (51083.959 ms) ======
[2025-12-27T18:59:04.061Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-27T18:59:04.804Z] GC before operation: completed in 701.274 ms, heap usage 633.315 MB -> 93.925 MB.
[2025-12-27T18:59:13.784Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T18:59:21.121Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T18:59:28.461Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T18:59:35.937Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T18:59:40.753Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T18:59:44.582Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T18:59:49.383Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T18:59:54.204Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T18:59:54.924Z] 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.
[2025-12-27T18:59:55.268Z] The best model improves the baseline by 14.52%.
[2025-12-27T18:59:56.002Z] Top recommended movies for user id 72:
[2025-12-27T18:59:56.002Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T18:59:56.002Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T18:59:56.002Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T18:59:56.002Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T18:59:56.003Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T18:59:56.003Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (51057.699 ms) ======
[2025-12-27T18:59:56.003Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-27T18:59:56.345Z] GC before operation: completed in 662.293 ms, heap usage 203.109 MB -> 90.246 MB.
[2025-12-27T19:00:05.317Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T19:00:12.736Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T19:00:20.090Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T19:00:27.421Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T19:00:32.230Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T19:00:37.030Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T19:00:41.828Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T19:00:45.660Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T19:00:46.379Z] 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.
[2025-12-27T19:00:46.716Z] The best model improves the baseline by 14.52%.
[2025-12-27T19:00:47.468Z] Top recommended movies for user id 72:
[2025-12-27T19:00:47.468Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T19:00:47.468Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T19:00:47.468Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T19:00:47.468Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T19:00:47.468Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T19:00:47.468Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (50788.917 ms) ======
[2025-12-27T19:00:47.468Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-27T19:00:48.200Z] GC before operation: completed in 792.596 ms, heap usage 519.183 MB -> 90.503 MB.
[2025-12-27T19:00:57.161Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T19:01:04.493Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T19:01:11.808Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T19:01:19.137Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T19:01:23.936Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T19:01:28.835Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T19:01:33.635Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T19:01:39.609Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T19:01:39.609Z] 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.
[2025-12-27T19:01:39.947Z] The best model improves the baseline by 14.52%.
[2025-12-27T19:01:40.678Z] Top recommended movies for user id 72:
[2025-12-27T19:01:40.678Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T19:01:40.678Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T19:01:40.678Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T19:01:40.678Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T19:01:40.678Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T19:01:40.678Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (52584.491 ms) ======
[2025-12-27T19:01:40.678Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-27T19:01:41.412Z] GC before operation: completed in 673.070 ms, heap usage 289.787 MB -> 90.301 MB.
[2025-12-27T19:01:50.405Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T19:01:59.365Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T19:02:06.688Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T19:02:14.132Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T19:02:20.111Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T19:02:24.913Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T19:02:29.721Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T19:02:34.539Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T19:02:35.704Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T19:02:35.704Z] The best model improves the baseline by 14.52%.
[2025-12-27T19:02:36.423Z] Top recommended movies for user id 72:
[2025-12-27T19:02:36.423Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T19:02:36.423Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T19:02:36.423Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T19:02:36.423Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T19:02:36.423Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T19:02:36.423Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (55076.831 ms) ======
[2025-12-27T19:02:40.263Z] -----------------------------------
[2025-12-27T19:02:40.263Z] renaissance-movie-lens_0_PASSED
[2025-12-27T19:02:40.263Z] -----------------------------------
[2025-12-27T19:02:40.263Z]
[2025-12-27T19:02:40.263Z] TEST TEARDOWN:
[2025-12-27T19:02:40.263Z] Nothing to be done for teardown.
[2025-12-27T19:02:40.607Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 19:02:40 2025 Epoch Time (ms): 1766862160269