renaissance-movie-lens_0
[2025-12-27T16:14:03.072Z] Running test renaissance-movie-lens_0 ...
[2025-12-27T16:14:03.072Z] ===============================================
[2025-12-27T16:14:03.072Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 16:14:02 2025 Epoch Time (ms): 1766852042733
[2025-12-27T16:14:03.072Z] variation: NoOptions
[2025-12-27T16:14:03.072Z] JVM_OPTIONS:
[2025-12-27T16:14:03.072Z] { \
[2025-12-27T16:14:03.072Z] echo ""; echo "TEST SETUP:"; \
[2025-12-27T16:14:03.072Z] echo "Nothing to be done for setup."; \
[2025-12-27T16:14:03.072Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17668497587518/renaissance-movie-lens_0"; \
[2025-12-27T16:14:03.072Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17668497587518/renaissance-movie-lens_0"; \
[2025-12-27T16:14:03.072Z] echo ""; echo "TESTING:"; \
[2025-12-27T16:14:03.072Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17668497587518/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-27T16:14:03.072Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17668497587518/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-27T16:14:03.072Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-27T16:14:03.072Z] echo "Nothing to be done for teardown."; \
[2025-12-27T16:14:03.072Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17668497587518/TestTargetResult";
[2025-12-27T16:14:03.072Z]
[2025-12-27T16:14:03.073Z] TEST SETUP:
[2025-12-27T16:14:03.073Z] Nothing to be done for setup.
[2025-12-27T16:14:03.073Z]
[2025-12-27T16:14:03.073Z] TESTING:
[2025-12-27T16:14:04.040Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-27T16:14:04.040Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/output_17668497587518/renaissance-movie-lens_0/launcher-161403-4651976795501754584/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-27T16:14:04.040Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-27T16:14:04.040Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-27T16:14:14.721Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-27T16:14:30.759Z] 16:14:29.355 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-12-27T16:14:35.047Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-27T16:14:36.020Z] Training: 60056, validation: 20285, test: 19854
[2025-12-27T16:14:36.020Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-27T16:14:36.020Z] GC before operation: completed in 200.727 ms, heap usage 271.135 MB -> 75.742 MB.
[2025-12-27T16:14:52.115Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:14:58.967Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:15:05.834Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:15:12.695Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:15:15.791Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:15:18.883Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:15:23.142Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:15:26.241Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:15:27.224Z] 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.
[2025-12-27T16:15:27.224Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:15:27.224Z] Top recommended movies for user id 72:
[2025-12-27T16:15:27.224Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:15:27.224Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:15:27.224Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:15:27.224Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:15:27.224Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:15:27.224Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (50908.697 ms) ======
[2025-12-27T16:15:27.224Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-27T16:15:27.224Z] GC before operation: completed in 226.616 ms, heap usage 362.956 MB -> 92.821 MB.
[2025-12-27T16:15:32.731Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:15:38.246Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:15:44.478Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:15:49.978Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:15:53.063Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:15:56.167Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:16:00.426Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:16:03.687Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:16:03.687Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T16:16:03.687Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:16:04.671Z] Top recommended movies for user id 72:
[2025-12-27T16:16:04.671Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:16:04.671Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:16:04.671Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:16:04.671Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:16:04.671Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:16:04.672Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (37027.591 ms) ======
[2025-12-27T16:16:04.672Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-27T16:16:04.672Z] GC before operation: completed in 233.199 ms, heap usage 230.022 MB -> 88.355 MB.
[2025-12-27T16:16:11.541Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:16:17.053Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:16:22.569Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:16:26.820Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:16:29.921Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:16:34.182Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:16:37.287Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:16:40.383Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:16:41.361Z] 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.
[2025-12-27T16:16:41.361Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:16:41.361Z] Top recommended movies for user id 72:
[2025-12-27T16:16:41.361Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:16:41.361Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:16:41.361Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:16:41.361Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:16:41.361Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:16:41.361Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (36932.796 ms) ======
[2025-12-27T16:16:41.361Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-27T16:16:42.350Z] GC before operation: completed in 370.902 ms, heap usage 751.214 MB -> 93.038 MB.
[2025-12-27T16:16:47.867Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:16:49.858Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:16:54.100Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:16:57.171Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:16:59.161Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:17:01.146Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:17:03.151Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:17:05.148Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:17:05.148Z] 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.
[2025-12-27T16:17:05.148Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:17:05.148Z] Top recommended movies for user id 72:
[2025-12-27T16:17:05.148Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:17:05.148Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:17:05.148Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:17:05.148Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:17:05.148Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:17:05.148Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (23409.169 ms) ======
[2025-12-27T16:17:05.149Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-27T16:17:06.118Z] GC before operation: completed in 188.091 ms, heap usage 416.166 MB -> 89.561 MB.
[2025-12-27T16:17:09.276Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:17:12.348Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:17:16.163Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:17:19.243Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:17:22.328Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:17:24.331Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:17:26.327Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:17:28.324Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:17:28.324Z] 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.
[2025-12-27T16:17:28.324Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:17:28.324Z] Top recommended movies for user id 72:
[2025-12-27T16:17:28.324Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:17:28.324Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:17:28.324Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:17:28.324Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:17:28.324Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:17:28.324Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (22770.287 ms) ======
[2025-12-27T16:17:28.324Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-27T16:17:28.324Z] GC before operation: completed in 181.788 ms, heap usage 292.788 MB -> 89.457 MB.
[2025-12-27T16:17:32.552Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:17:35.631Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:17:38.700Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:17:40.693Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:17:42.697Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:17:44.696Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:17:46.687Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:17:47.657Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:17:48.634Z] 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.
[2025-12-27T16:17:48.634Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:17:48.634Z] Top recommended movies for user id 72:
[2025-12-27T16:17:48.634Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:17:48.634Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:17:48.634Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:17:48.634Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:17:48.634Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:17:48.634Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19918.026 ms) ======
[2025-12-27T16:17:48.634Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-27T16:17:48.634Z] GC before operation: completed in 161.362 ms, heap usage 165.638 MB -> 90.506 MB.
[2025-12-27T16:17:51.720Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:17:54.796Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:17:57.871Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:18:00.949Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:18:01.919Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:18:03.907Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:18:05.905Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:18:07.901Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:18:07.901Z] 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.
[2025-12-27T16:18:07.901Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:18:07.901Z] Top recommended movies for user id 72:
[2025-12-27T16:18:07.901Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:18:07.901Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:18:07.901Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:18:07.901Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:18:07.901Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:18:07.901Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19377.903 ms) ======
[2025-12-27T16:18:07.901Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-27T16:18:07.902Z] GC before operation: completed in 255.707 ms, heap usage 549.919 MB -> 93.368 MB.
[2025-12-27T16:18:10.973Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:18:14.047Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:18:17.128Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:18:20.204Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:18:22.198Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:18:23.173Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:18:25.255Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:18:27.250Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:18:27.250Z] 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.
[2025-12-27T16:18:27.250Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:18:27.250Z] Top recommended movies for user id 72:
[2025-12-27T16:18:27.250Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:18:27.250Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:18:27.250Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:18:27.250Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:18:27.250Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:18:27.250Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19191.801 ms) ======
[2025-12-27T16:18:27.250Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-27T16:18:28.219Z] GC before operation: completed in 249.058 ms, heap usage 246.458 MB -> 89.901 MB.
[2025-12-27T16:18:31.294Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:18:33.290Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:18:36.364Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:18:39.887Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:18:40.865Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:18:42.856Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:18:44.854Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:18:45.833Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:18:46.801Z] 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.
[2025-12-27T16:18:46.801Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:18:46.801Z] Top recommended movies for user id 72:
[2025-12-27T16:18:46.801Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:18:46.801Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:18:46.801Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:18:46.801Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:18:46.801Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:18:46.801Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18888.644 ms) ======
[2025-12-27T16:18:46.801Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-27T16:18:46.801Z] GC before operation: completed in 194.590 ms, heap usage 185.965 MB -> 89.668 MB.
[2025-12-27T16:18:50.018Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:18:53.104Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:18:56.201Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:18:59.355Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:19:00.330Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:19:02.328Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:19:04.328Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:19:05.302Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:19:06.274Z] 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.
[2025-12-27T16:19:06.274Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:19:06.274Z] Top recommended movies for user id 72:
[2025-12-27T16:19:06.274Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:19:06.274Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:19:06.274Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:19:06.274Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:19:06.274Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:19:06.274Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19179.456 ms) ======
[2025-12-27T16:19:06.274Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-27T16:19:06.274Z] GC before operation: completed in 235.993 ms, heap usage 370.122 MB -> 90.208 MB.
[2025-12-27T16:19:09.495Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:19:12.580Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:19:14.582Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:19:17.667Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:19:19.668Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:19:22.397Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:19:23.375Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:19:25.373Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:19:25.373Z] 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.
[2025-12-27T16:19:25.373Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:19:25.373Z] Top recommended movies for user id 72:
[2025-12-27T16:19:25.373Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:19:25.373Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:19:25.373Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:19:25.373Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:19:25.373Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:19:25.373Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19137.478 ms) ======
[2025-12-27T16:19:25.373Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-27T16:19:25.373Z] GC before operation: completed in 227.147 ms, heap usage 182.436 MB -> 89.662 MB.
[2025-12-27T16:19:28.573Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:19:31.644Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:19:34.825Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:19:36.816Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:19:38.806Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:19:40.804Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:19:42.802Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:19:43.775Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:19:43.775Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T16:19:43.775Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:19:44.751Z] Top recommended movies for user id 72:
[2025-12-27T16:19:44.751Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:19:44.751Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:19:44.751Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:19:44.751Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:19:44.751Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:19:44.751Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18706.570 ms) ======
[2025-12-27T16:19:44.751Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-27T16:19:44.751Z] GC before operation: completed in 184.993 ms, heap usage 694.421 MB -> 93.836 MB.
[2025-12-27T16:19:47.826Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:19:50.929Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:19:54.004Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:19:57.083Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:19:58.058Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:20:01.139Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:20:02.161Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:20:04.154Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:20:05.122Z] 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.
[2025-12-27T16:20:05.122Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:20:05.122Z] Top recommended movies for user id 72:
[2025-12-27T16:20:05.122Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:20:05.122Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:20:05.122Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:20:05.122Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:20:05.122Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:20:05.122Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20305.226 ms) ======
[2025-12-27T16:20:05.122Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-27T16:20:05.122Z] GC before operation: completed in 196.211 ms, heap usage 97.253 MB -> 89.979 MB.
[2025-12-27T16:20:08.281Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:20:11.364Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:20:14.448Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:20:17.615Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:20:19.302Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:20:21.309Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:20:23.437Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:20:25.435Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:20:25.435Z] 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.
[2025-12-27T16:20:25.435Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:20:25.435Z] Top recommended movies for user id 72:
[2025-12-27T16:20:25.435Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:20:25.435Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:20:25.435Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:20:25.435Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:20:25.435Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:20:25.435Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20491.798 ms) ======
[2025-12-27T16:20:25.435Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-27T16:20:25.435Z] GC before operation: completed in 165.424 ms, heap usage 367.297 MB -> 90.063 MB.
[2025-12-27T16:20:28.631Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:20:31.700Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:20:34.762Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:20:37.865Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:20:39.854Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:20:40.823Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:20:43.948Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:20:44.915Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:20:44.915Z] 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.
[2025-12-27T16:20:45.884Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:20:45.884Z] Top recommended movies for user id 72:
[2025-12-27T16:20:45.884Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:20:45.884Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:20:45.884Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:20:45.884Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:20:45.884Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:20:45.884Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19883.511 ms) ======
[2025-12-27T16:20:45.884Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-27T16:20:45.884Z] GC before operation: completed in 158.818 ms, heap usage 113.688 MB -> 89.990 MB.
[2025-12-27T16:20:48.953Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:20:52.024Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:20:55.098Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:20:58.169Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:21:00.247Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:21:02.242Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:21:04.503Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:21:06.498Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:21:06.498Z] 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.
[2025-12-27T16:21:06.498Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:21:06.498Z] Top recommended movies for user id 72:
[2025-12-27T16:21:06.499Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:21:06.499Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:21:06.499Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:21:06.499Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:21:06.499Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:21:06.499Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20647.876 ms) ======
[2025-12-27T16:21:06.499Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-27T16:21:06.499Z] GC before operation: completed in 170.365 ms, heap usage 111.267 MB -> 93.040 MB.
[2025-12-27T16:21:09.847Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:21:13.149Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:21:15.143Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:21:18.221Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:21:20.221Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:21:22.292Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:21:24.284Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:21:26.273Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:21:26.273Z] 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.
[2025-12-27T16:21:26.273Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:21:26.273Z] Top recommended movies for user id 72:
[2025-12-27T16:21:26.274Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:21:26.274Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:21:26.274Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:21:26.274Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:21:26.274Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:21:26.274Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19598.205 ms) ======
[2025-12-27T16:21:26.274Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-27T16:21:26.274Z] GC before operation: completed in 188.307 ms, heap usage 448.132 MB -> 90.323 MB.
[2025-12-27T16:21:29.395Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:21:32.763Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:21:35.839Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:21:38.921Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:21:40.911Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:21:42.904Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:21:43.872Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:21:45.867Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:21:45.867Z] 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.
[2025-12-27T16:21:45.867Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:21:45.867Z] Top recommended movies for user id 72:
[2025-12-27T16:21:45.867Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:21:45.867Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:21:45.867Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:21:45.867Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:21:45.867Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:21:45.867Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19810.188 ms) ======
[2025-12-27T16:21:45.867Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-27T16:21:45.867Z] GC before operation: completed in 177.918 ms, heap usage 213.972 MB -> 89.835 MB.
[2025-12-27T16:21:49.104Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:21:52.181Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:21:55.252Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:21:57.252Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:21:59.437Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:22:00.955Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:22:02.947Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:22:04.941Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:22:04.941Z] 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.
[2025-12-27T16:22:04.941Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:22:05.917Z] Top recommended movies for user id 72:
[2025-12-27T16:22:05.917Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:22:05.917Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:22:05.917Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:22:05.917Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:22:05.917Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:22:05.917Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19161.557 ms) ======
[2025-12-27T16:22:05.917Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-27T16:22:05.917Z] GC before operation: completed in 261.138 ms, heap usage 367.374 MB -> 90.122 MB.
[2025-12-27T16:22:09.019Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T16:22:13.250Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T16:22:16.322Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T16:22:19.495Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T16:22:21.477Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T16:22:23.477Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T16:22:25.466Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T16:22:27.533Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T16:22:27.533Z] 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.
[2025-12-27T16:22:27.533Z] The best model improves the baseline by 14.52%.
[2025-12-27T16:22:27.533Z] Top recommended movies for user id 72:
[2025-12-27T16:22:27.533Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T16:22:27.533Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T16:22:27.533Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T16:22:27.533Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T16:22:27.533Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T16:22:27.533Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (21660.373 ms) ======
[2025-12-27T16:22:28.500Z] -----------------------------------
[2025-12-27T16:22:28.500Z] renaissance-movie-lens_0_PASSED
[2025-12-27T16:22:28.500Z] -----------------------------------
[2025-12-27T16:22:28.500Z]
[2025-12-27T16:22:28.500Z] TEST TEARDOWN:
[2025-12-27T16:22:28.500Z] Nothing to be done for teardown.
[2025-12-27T16:22:28.500Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 16:22:28 2025 Epoch Time (ms): 1766852548273