renaissance-movie-lens_0
[2025-09-05T18:08:19.347Z] Running test renaissance-movie-lens_0 ...
[2025-09-05T18:08:19.347Z] ===============================================
[2025-09-05T18:08:19.347Z] renaissance-movie-lens_0 Start Time: Fri Sep 5 18:08:19 2025 Epoch Time (ms): 1757095699127
[2025-09-05T18:08:19.347Z] variation: NoOptions
[2025-09-05T18:08:19.347Z] JVM_OPTIONS:
[2025-09-05T18:08:19.347Z] { \
[2025-09-05T18:08:19.348Z] echo ""; echo "TEST SETUP:"; \
[2025-09-05T18:08:19.348Z] echo "Nothing to be done for setup."; \
[2025-09-05T18:08:19.348Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux_testList_1/aqa-tests/TKG/../TKG/output_17570939187985/renaissance-movie-lens_0"; \
[2025-09-05T18:08:19.348Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux_testList_1/aqa-tests/TKG/../TKG/output_17570939187985/renaissance-movie-lens_0"; \
[2025-09-05T18:08:19.348Z] echo ""; echo "TESTING:"; \
[2025-09-05T18:08:19.348Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux_testList_1/aqa-tests/TKG/../TKG/output_17570939187985/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-05T18:08:19.348Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux_testList_1/aqa-tests/TKG/../TKG/output_17570939187985/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-05T18:08:19.348Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-05T18:08:19.348Z] echo "Nothing to be done for teardown."; \
[2025-09-05T18:08:19.348Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux_testList_1/aqa-tests/TKG/../TKG/output_17570939187985/TestTargetResult";
[2025-09-05T18:08:19.348Z]
[2025-09-05T18:08:19.348Z] TEST SETUP:
[2025-09-05T18:08:19.348Z] Nothing to be done for setup.
[2025-09-05T18:08:19.348Z]
[2025-09-05T18:08:19.348Z] TESTING:
[2025-09-05T18:08:19.946Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-09-05T18:08:19.946Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_s390x_linux_testList_1/aqa-tests/TKG/output_17570939187985/renaissance-movie-lens_0/launcher-180819-1325738241055534095/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-09-05T18:08:19.946Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-09-05T18:08:19.946Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-09-05T18:08:26.274Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-09-05T18:08:35.741Z] 18:08:35.206 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-05T18:08:39.563Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-05T18:08:40.192Z] Training: 60056, validation: 20285, test: 19854
[2025-09-05T18:08:40.192Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-05T18:08:40.825Z] GC before operation: completed in 426.330 ms, heap usage 143.813 MB -> 75.734 MB.
[2025-09-05T18:08:49.762Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:08:57.307Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:09:04.841Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:09:10.772Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:09:15.705Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:09:19.106Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:09:23.097Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:09:26.028Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:09:26.729Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:09:27.395Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:09:27.395Z] Top recommended movies for user id 72:
[2025-09-05T18:09:27.395Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:09:27.395Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:09:27.396Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:09:27.396Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:09:27.396Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:09:27.396Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (46717.413 ms) ======
[2025-09-05T18:09:27.396Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-05T18:09:28.096Z] GC before operation: completed in 303.156 ms, heap usage 394.783 MB -> 92.622 MB.
[2025-09-05T18:09:34.302Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:09:40.516Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:09:46.544Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:09:50.322Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:09:54.226Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:09:58.109Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:10:01.027Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:10:05.244Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:10:05.244Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:10:05.244Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:10:05.244Z] Top recommended movies for user id 72:
[2025-09-05T18:10:05.244Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:10:05.244Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:10:05.244Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:10:05.244Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:10:05.244Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:10:05.244Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (37533.523 ms) ======
[2025-09-05T18:10:05.244Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-05T18:10:05.891Z] GC before operation: completed in 316.375 ms, heap usage 242.476 MB -> 87.687 MB.
[2025-09-05T18:10:11.993Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:10:18.194Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:10:24.133Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:10:29.067Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:10:31.989Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:10:36.036Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:10:38.937Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:10:41.908Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:10:42.557Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:10:42.557Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:10:43.247Z] Top recommended movies for user id 72:
[2025-09-05T18:10:43.247Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:10:43.247Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:10:43.247Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:10:43.247Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:10:43.247Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:10:43.247Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (37257.941 ms) ======
[2025-09-05T18:10:43.247Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-05T18:10:43.247Z] GC before operation: completed in 254.104 ms, heap usage 161.169 MB -> 88.163 MB.
[2025-09-05T18:10:48.304Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:10:53.978Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:11:00.147Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:11:06.253Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:11:10.125Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:11:13.073Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:11:18.016Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:11:20.067Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:11:20.782Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:11:21.455Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:11:21.455Z] Top recommended movies for user id 72:
[2025-09-05T18:11:21.455Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:11:21.455Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:11:21.455Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:11:21.455Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:11:21.455Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:11:21.456Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (38184.103 ms) ======
[2025-09-05T18:11:21.456Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-05T18:11:22.117Z] GC before operation: completed in 489.852 ms, heap usage 229.268 MB -> 88.515 MB.
[2025-09-05T18:11:28.245Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:11:35.036Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:11:41.349Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:11:46.264Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:11:50.249Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:11:54.280Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:11:59.537Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:12:04.825Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:12:04.825Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:12:04.825Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:12:05.561Z] Top recommended movies for user id 72:
[2025-09-05T18:12:05.561Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:12:05.561Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:12:05.561Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:12:05.561Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:12:05.561Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:12:05.561Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (43348.985 ms) ======
[2025-09-05T18:12:05.562Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-05T18:12:05.562Z] GC before operation: completed in 346.410 ms, heap usage 112.895 MB -> 88.340 MB.
[2025-09-05T18:12:13.126Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:12:18.496Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:12:26.237Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:12:31.240Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:12:36.165Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:12:39.007Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:12:41.979Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:12:45.841Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:12:45.841Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:12:45.841Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:12:46.482Z] Top recommended movies for user id 72:
[2025-09-05T18:12:46.482Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:12:46.482Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:12:46.482Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:12:46.482Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:12:46.482Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:12:46.482Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (40775.552 ms) ======
[2025-09-05T18:12:46.482Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-05T18:12:46.482Z] GC before operation: completed in 336.928 ms, heap usage 150.413 MB -> 88.726 MB.
[2025-09-05T18:12:52.546Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:13:00.276Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:13:05.572Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:13:12.059Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:13:15.142Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:13:19.248Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:13:22.227Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:13:26.237Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:13:26.237Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:13:26.948Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:13:26.948Z] Top recommended movies for user id 72:
[2025-09-05T18:13:26.948Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:13:26.948Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:13:26.948Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:13:26.948Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:13:26.948Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:13:26.948Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (40118.034 ms) ======
[2025-09-05T18:13:26.948Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-05T18:13:26.948Z] GC before operation: completed in 321.809 ms, heap usage 167.641 MB -> 88.677 MB.
[2025-09-05T18:13:34.630Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:13:39.687Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:13:47.290Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:13:53.106Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:13:55.971Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:13:58.877Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:14:02.664Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:14:05.585Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:14:06.276Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:14:06.276Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:14:06.276Z] Top recommended movies for user id 72:
[2025-09-05T18:14:06.276Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:14:06.276Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:14:06.276Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:14:06.276Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:14:06.276Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:14:06.276Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (39218.480 ms) ======
[2025-09-05T18:14:06.276Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-05T18:14:06.988Z] GC before operation: completed in 264.844 ms, heap usage 352.280 MB -> 89.339 MB.
[2025-09-05T18:14:13.057Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:14:19.214Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:14:26.931Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:14:33.135Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:14:36.699Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:14:39.711Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:14:43.757Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:14:47.805Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:14:48.459Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:14:48.459Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:14:49.145Z] Top recommended movies for user id 72:
[2025-09-05T18:14:49.146Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:14:49.146Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:14:49.146Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:14:49.146Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:14:49.146Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:14:49.146Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (42414.418 ms) ======
[2025-09-05T18:14:49.146Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-05T18:14:49.826Z] GC before operation: completed in 466.114 ms, heap usage 243.268 MB -> 88.943 MB.
[2025-09-05T18:14:54.737Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:15:01.184Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:15:07.267Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:15:12.206Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:15:17.239Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:15:19.396Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:15:23.326Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:15:28.221Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:15:28.221Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:15:28.221Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:15:28.221Z] Top recommended movies for user id 72:
[2025-09-05T18:15:28.221Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:15:28.221Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:15:28.221Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:15:28.221Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:15:28.221Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:15:28.221Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (38907.936 ms) ======
[2025-09-05T18:15:28.221Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-05T18:15:28.892Z] GC before operation: completed in 570.726 ms, heap usage 383.185 MB -> 89.466 MB.
[2025-09-05T18:15:34.973Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:15:41.211Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:15:48.533Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:15:54.777Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:15:58.722Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:16:02.737Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:16:07.250Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:16:11.337Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:16:12.003Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:16:12.003Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:16:12.003Z] Top recommended movies for user id 72:
[2025-09-05T18:16:12.003Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:16:12.003Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:16:12.003Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:16:12.003Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:16:12.003Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:16:12.003Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (43255.971 ms) ======
[2025-09-05T18:16:12.003Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-05T18:16:12.845Z] GC before operation: completed in 330.076 ms, heap usage 395.467 MB -> 89.187 MB.
[2025-09-05T18:16:20.257Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:16:26.643Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:16:32.786Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:16:39.114Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:16:43.145Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:16:47.248Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:16:51.795Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:16:55.720Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:16:55.720Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:16:55.720Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:16:56.341Z] Top recommended movies for user id 72:
[2025-09-05T18:16:56.341Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:16:56.341Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:16:56.341Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:16:56.341Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:16:56.341Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:16:56.341Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (43625.214 ms) ======
[2025-09-05T18:16:56.341Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-05T18:16:56.341Z] GC before operation: completed in 339.597 ms, heap usage 235.466 MB -> 89.110 MB.
[2025-09-05T18:17:04.080Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:17:10.362Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:17:18.095Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:17:25.805Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:17:30.000Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:17:33.238Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:17:36.719Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:17:40.665Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:17:42.026Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:17:42.026Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:17:42.026Z] Top recommended movies for user id 72:
[2025-09-05T18:17:42.026Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:17:42.026Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:17:42.026Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:17:42.026Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:17:42.026Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:17:42.026Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (45444.164 ms) ======
[2025-09-05T18:17:42.026Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-05T18:17:42.765Z] GC before operation: completed in 855.825 ms, heap usage 383.414 MB -> 89.617 MB.
[2025-09-05T18:17:50.387Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:17:56.868Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:18:03.257Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:18:09.544Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:18:14.574Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:18:16.665Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:18:20.987Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:18:24.020Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:18:24.020Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:18:24.020Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:18:24.696Z] Top recommended movies for user id 72:
[2025-09-05T18:18:24.696Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:18:24.696Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:18:24.696Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:18:24.696Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:18:24.696Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:18:24.696Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (41683.899 ms) ======
[2025-09-05T18:18:24.696Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-05T18:18:25.359Z] GC before operation: completed in 456.204 ms, heap usage 302.568 MB -> 89.204 MB.
[2025-09-05T18:18:30.212Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:18:37.730Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:18:45.157Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:18:54.201Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:18:57.210Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:19:00.275Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:19:04.176Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:19:08.251Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:19:08.922Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:19:08.922Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:19:08.922Z] Top recommended movies for user id 72:
[2025-09-05T18:19:08.922Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:19:08.922Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:19:08.922Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:19:08.922Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:19:08.922Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:19:08.922Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (44092.028 ms) ======
[2025-09-05T18:19:08.922Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-05T18:19:09.588Z] GC before operation: completed in 283.870 ms, heap usage 229.638 MB -> 89.352 MB.
[2025-09-05T18:19:15.722Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:19:21.912Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:19:28.212Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:19:34.435Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:19:37.397Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:19:40.379Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:19:43.447Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:19:47.380Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:19:47.380Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:19:47.380Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:19:48.087Z] Top recommended movies for user id 72:
[2025-09-05T18:19:48.087Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:19:48.087Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:19:48.087Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:19:48.087Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:19:48.087Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:19:48.087Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (38470.412 ms) ======
[2025-09-05T18:19:48.087Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-05T18:19:48.087Z] GC before operation: completed in 215.649 ms, heap usage 175.330 MB -> 88.951 MB.
[2025-09-05T18:19:53.336Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:19:58.567Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:20:09.804Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:20:15.102Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:20:20.286Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:20:23.291Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:20:28.845Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:20:31.772Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:20:31.772Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:20:31.772Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:20:31.772Z] Top recommended movies for user id 72:
[2025-09-05T18:20:31.772Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:20:31.772Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:20:31.772Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:20:31.772Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:20:31.772Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:20:31.772Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (43781.546 ms) ======
[2025-09-05T18:20:31.772Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-05T18:20:32.648Z] GC before operation: completed in 221.134 ms, heap usage 205.305 MB -> 89.178 MB.
[2025-09-05T18:20:37.701Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:20:43.888Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:20:51.643Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:20:57.823Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:21:01.775Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:21:04.883Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:21:08.001Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:21:12.033Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:21:12.745Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:21:12.745Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:21:12.745Z] Top recommended movies for user id 72:
[2025-09-05T18:21:12.745Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:21:12.745Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:21:12.745Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:21:12.745Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:21:12.745Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:21:12.745Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (40922.393 ms) ======
[2025-09-05T18:21:12.745Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-05T18:21:13.366Z] GC before operation: completed in 273.798 ms, heap usage 165.173 MB -> 88.962 MB.
[2025-09-05T18:21:20.295Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:21:26.439Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:21:32.595Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:21:37.437Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:21:41.246Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:21:45.588Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:21:50.748Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:21:53.849Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:21:54.526Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:21:54.526Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:21:55.231Z] Top recommended movies for user id 72:
[2025-09-05T18:21:55.231Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:21:55.231Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:21:55.231Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:21:55.231Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:21:55.231Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:21:55.231Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (41598.294 ms) ======
[2025-09-05T18:21:55.231Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-05T18:21:55.231Z] GC before operation: completed in 345.146 ms, heap usage 140.574 MB -> 89.057 MB.
[2025-09-05T18:22:02.950Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T18:22:09.472Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T18:22:16.015Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T18:22:21.204Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T18:22:25.437Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T18:22:29.639Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T18:22:33.754Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T18:22:37.728Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T18:22:37.728Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-09-05T18:22:37.728Z] The best model improves the baseline by 14.34%.
[2025-09-05T18:22:38.447Z] Top recommended movies for user id 72:
[2025-09-05T18:22:38.447Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-09-05T18:22:38.447Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-09-05T18:22:38.447Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-09-05T18:22:38.447Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-09-05T18:22:38.447Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-09-05T18:22:38.447Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (43090.214 ms) ======
[2025-09-05T18:22:39.117Z] -----------------------------------
[2025-09-05T18:22:39.117Z] renaissance-movie-lens_0_PASSED
[2025-09-05T18:22:39.117Z] -----------------------------------
[2025-09-05T18:22:39.117Z]
[2025-09-05T18:22:39.117Z] TEST TEARDOWN:
[2025-09-05T18:22:39.117Z] Nothing to be done for teardown.
[2025-09-05T18:22:39.117Z] renaissance-movie-lens_0 Finish Time: Fri Sep 5 18:22:38 2025 Epoch Time (ms): 1757096558945