renaissance-movie-lens_0
[2025-11-13T10:34:00.137Z] Running test renaissance-movie-lens_0 ...
[2025-11-13T10:34:00.137Z] ===============================================
[2025-11-13T10:34:00.137Z] renaissance-movie-lens_0 Start Time: Thu Nov 13 10:33:59 2025 Epoch Time (ms): 1763030039914
[2025-11-13T10:34:00.137Z] variation: NoOptions
[2025-11-13T10:34:00.137Z] JVM_OPTIONS:
[2025-11-13T10:34:00.137Z] { \
[2025-11-13T10:34:00.137Z] echo ""; echo "TEST SETUP:"; \
[2025-11-13T10:34:00.137Z] echo "Nothing to be done for setup."; \
[2025-11-13T10:34:00.137Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17630247206909/renaissance-movie-lens_0"; \
[2025-11-13T10:34:00.137Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17630247206909/renaissance-movie-lens_0"; \
[2025-11-13T10:34:00.137Z] echo ""; echo "TESTING:"; \
[2025-11-13T10:34:00.137Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17630247206909/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-13T10:34:00.137Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17630247206909/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-13T10:34:00.137Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-13T10:34:00.137Z] echo "Nothing to be done for teardown."; \
[2025-11-13T10:34:00.137Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17630247206909/TestTargetResult";
[2025-11-13T10:34:00.137Z]
[2025-11-13T10:34:00.137Z] TEST SETUP:
[2025-11-13T10:34:00.137Z] Nothing to be done for setup.
[2025-11-13T10:34:00.137Z]
[2025-11-13T10:34:00.137Z] TESTING:
[2025-11-13T10:34:23.203Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-13T10:34:56.625Z] 10:34:55.021 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-11-13T10:35:07.672Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-13T10:35:08.811Z] Training: 60056, validation: 20285, test: 19854
[2025-11-13T10:35:08.811Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-13T10:35:09.509Z] GC before operation: completed in 562.678 ms, heap usage 473.051 MB -> 77.747 MB.
[2025-11-13T10:35:43.057Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:35:56.230Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:36:09.329Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:36:22.424Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:36:28.320Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:36:35.554Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:36:42.815Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:36:48.682Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:36:49.385Z] 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.
[2025-11-13T10:36:49.385Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:36:50.527Z] Top recommended movies for user id 72:
[2025-11-13T10:36:50.527Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:36:50.529Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:36:50.529Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:36:50.529Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:36:50.529Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:36:50.529Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (101291.084 ms) ======
[2025-11-13T10:36:50.529Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-13T10:36:51.722Z] GC before operation: completed in 897.455 ms, heap usage 937.557 MB -> 94.605 MB.
[2025-11-13T10:37:02.547Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:37:15.633Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:37:24.621Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:37:35.468Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:37:40.193Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:37:46.075Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:37:51.973Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:37:58.170Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:37:59.315Z] 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.
[2025-11-13T10:37:59.315Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:38:00.024Z] Top recommended movies for user id 72:
[2025-11-13T10:38:00.024Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:38:00.024Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:38:00.024Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:38:00.024Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:38:00.024Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:38:00.024Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (68514.884 ms) ======
[2025-11-13T10:38:00.024Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-13T10:38:01.207Z] GC before operation: completed in 938.072 ms, heap usage 372.207 MB -> 90.184 MB.
[2025-11-13T10:38:12.235Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:38:21.111Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:38:29.972Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:38:38.993Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:38:44.862Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:38:50.724Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:38:56.617Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:39:02.484Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:39:03.185Z] 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.
[2025-11-13T10:39:03.185Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:39:03.884Z] Top recommended movies for user id 72:
[2025-11-13T10:39:03.884Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:39:03.884Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:39:03.884Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:39:03.884Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:39:03.884Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:39:03.884Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (62745.368 ms) ======
[2025-11-13T10:39:03.884Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-13T10:39:04.610Z] GC before operation: completed in 945.283 ms, heap usage 478.999 MB -> 90.918 MB.
[2025-11-13T10:39:15.520Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:39:24.368Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:39:33.223Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:39:40.464Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:39:46.392Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:39:52.369Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:39:58.254Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:40:04.157Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:40:04.157Z] 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.
[2025-11-13T10:40:04.483Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:40:05.207Z] Top recommended movies for user id 72:
[2025-11-13T10:40:05.207Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:40:05.207Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:40:05.207Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:40:05.207Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:40:05.207Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:40:05.207Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (60331.192 ms) ======
[2025-11-13T10:40:05.207Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-13T10:40:05.992Z] GC before operation: completed in 948.819 ms, heap usage 687.398 MB -> 94.682 MB.
[2025-11-13T10:40:15.590Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:40:25.045Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:40:34.017Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:40:42.866Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:40:47.630Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:40:53.691Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:40:59.607Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:41:05.667Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:41:05.667Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-13T10:41:05.667Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:41:06.364Z] Top recommended movies for user id 72:
[2025-11-13T10:41:06.364Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:41:06.364Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:41:06.364Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:41:06.364Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:41:06.364Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:41:06.364Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (60425.886 ms) ======
[2025-11-13T10:41:06.364Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-13T10:41:07.536Z] GC before operation: completed in 953.369 ms, heap usage 698.729 MB -> 94.687 MB.
[2025-11-13T10:41:16.533Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:41:25.403Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:41:34.292Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:41:41.748Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:41:47.695Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:41:52.452Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:41:58.400Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:42:03.120Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:42:03.823Z] 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.
[2025-11-13T10:42:03.823Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:42:04.524Z] Top recommended movies for user id 72:
[2025-11-13T10:42:04.524Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:42:04.524Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:42:04.524Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:42:04.524Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:42:04.524Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:42:04.524Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (57204.029 ms) ======
[2025-11-13T10:42:04.524Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-13T10:42:05.698Z] GC before operation: completed in 933.242 ms, heap usage 438.651 MB -> 91.508 MB.
[2025-11-13T10:42:14.912Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:42:23.896Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:42:32.752Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:42:40.088Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:42:44.872Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:42:49.601Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:42:55.612Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:43:00.331Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:43:00.331Z] 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.
[2025-11-13T10:43:00.664Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:43:01.359Z] Top recommended movies for user id 72:
[2025-11-13T10:43:01.359Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:43:01.359Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:43:01.359Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:43:01.359Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:43:01.359Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:43:01.359Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55799.894 ms) ======
[2025-11-13T10:43:01.359Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-13T10:43:02.524Z] GC before operation: completed in 950.691 ms, heap usage 179.168 MB -> 91.162 MB.
[2025-11-13T10:43:13.462Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:43:20.800Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:43:28.024Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:43:36.994Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:43:40.743Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:43:45.640Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:43:51.507Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:43:56.226Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:43:56.926Z] 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.
[2025-11-13T10:43:56.926Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:43:57.633Z] Top recommended movies for user id 72:
[2025-11-13T10:43:57.633Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:43:57.633Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:43:57.633Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:43:57.633Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:43:57.633Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:43:57.633Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (55372.152 ms) ======
[2025-11-13T10:43:57.633Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-13T10:43:58.782Z] GC before operation: completed in 972.044 ms, heap usage 168.019 MB -> 91.306 MB.
[2025-11-13T10:44:07.872Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:44:16.851Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:44:24.089Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:44:31.735Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:44:36.569Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:44:42.606Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:44:48.485Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:44:54.371Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:44:54.709Z] 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.
[2025-11-13T10:44:54.709Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:44:55.406Z] Top recommended movies for user id 72:
[2025-11-13T10:44:55.406Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:44:55.406Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:44:55.406Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:44:55.406Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:44:55.406Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:44:55.406Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (56872.286 ms) ======
[2025-11-13T10:44:55.406Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-13T10:44:56.582Z] GC before operation: completed in 957.789 ms, heap usage 553.616 MB -> 94.905 MB.
[2025-11-13T10:45:07.480Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:45:18.420Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:45:27.549Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:45:38.437Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:45:42.187Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:45:47.173Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:45:53.050Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:45:57.868Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:45:58.581Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-13T10:45:58.581Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:45:59.286Z] Top recommended movies for user id 72:
[2025-11-13T10:45:59.286Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:45:59.286Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:45:59.286Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:45:59.286Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:45:59.286Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:45:59.286Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (62924.211 ms) ======
[2025-11-13T10:45:59.286Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-13T10:46:00.446Z] GC before operation: completed in 932.486 ms, heap usage 275.925 MB -> 93.319 MB.
[2025-11-13T10:46:11.249Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:46:18.481Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:46:27.429Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:46:34.660Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:46:39.562Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:46:44.274Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:46:49.294Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:46:54.013Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:46:54.706Z] 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.
[2025-11-13T10:46:55.032Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:46:55.750Z] Top recommended movies for user id 72:
[2025-11-13T10:46:55.750Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:46:55.750Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:46:55.750Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:46:55.750Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:46:55.750Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:46:55.750Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (55202.124 ms) ======
[2025-11-13T10:46:55.750Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-13T10:46:56.476Z] GC before operation: completed in 944.191 ms, heap usage 1.030 GB -> 96.360 MB.
[2025-11-13T10:47:05.324Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:47:14.401Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:47:21.654Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:47:28.883Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:47:33.594Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:47:38.316Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:47:43.161Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:47:48.162Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:47:48.857Z] 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.
[2025-11-13T10:47:49.188Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:47:49.883Z] Top recommended movies for user id 72:
[2025-11-13T10:47:49.883Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:47:49.883Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:47:49.883Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:47:49.883Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:47:49.883Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:47:49.883Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (53334.052 ms) ======
[2025-11-13T10:47:49.883Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-13T10:47:50.619Z] GC before operation: completed in 955.245 ms, heap usage 870.053 MB -> 95.690 MB.
[2025-11-13T10:47:59.566Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:48:06.990Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:48:15.873Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:48:23.098Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:48:27.833Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:48:33.698Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:48:38.865Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:48:43.615Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:48:44.326Z] 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.
[2025-11-13T10:48:44.326Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:48:45.037Z] Top recommended movies for user id 72:
[2025-11-13T10:48:45.037Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:48:45.037Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:48:45.037Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:48:45.037Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:48:45.037Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:48:45.037Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (54237.920 ms) ======
[2025-11-13T10:48:45.037Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-13T10:48:46.197Z] GC before operation: completed in 944.690 ms, heap usage 211.926 MB -> 91.490 MB.
[2025-11-13T10:48:55.050Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:49:02.305Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:49:11.247Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:49:18.519Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:49:24.395Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:49:29.118Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:49:33.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:49:38.682Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:49:39.004Z] 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.
[2025-11-13T10:49:39.342Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:49:40.056Z] Top recommended movies for user id 72:
[2025-11-13T10:49:40.056Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:49:40.056Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:49:40.056Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:49:40.056Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:49:40.056Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:49:40.056Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (53955.365 ms) ======
[2025-11-13T10:49:40.056Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-13T10:49:40.785Z] GC before operation: completed in 935.718 ms, heap usage 246.033 MB -> 91.341 MB.
[2025-11-13T10:49:49.682Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:49:58.632Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:50:05.895Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:50:13.126Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:50:17.870Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:50:22.587Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:50:27.412Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:50:32.149Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:50:32.847Z] 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.
[2025-11-13T10:50:32.847Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:50:33.567Z] Top recommended movies for user id 72:
[2025-11-13T10:50:33.567Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:50:33.567Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:50:33.567Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:50:33.567Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:50:33.567Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:50:33.567Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (52529.851 ms) ======
[2025-11-13T10:50:33.567Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-13T10:50:34.288Z] GC before operation: completed in 943.062 ms, heap usage 505.781 MB -> 91.960 MB.
[2025-11-13T10:50:43.126Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:50:51.989Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:50:59.203Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:51:06.747Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:51:11.477Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:51:16.199Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:51:22.054Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:51:26.758Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:51:27.082Z] 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.
[2025-11-13T10:51:27.083Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:51:27.777Z] Top recommended movies for user id 72:
[2025-11-13T10:51:27.777Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:51:27.777Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:51:27.777Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:51:27.777Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:51:27.777Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:51:27.777Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (53417.558 ms) ======
[2025-11-13T10:51:27.777Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-13T10:51:28.940Z] GC before operation: completed in 978.850 ms, heap usage 1.057 GB -> 96.582 MB.
[2025-11-13T10:51:37.786Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:51:45.092Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:51:53.936Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:51:59.805Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:52:05.692Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:52:09.455Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:52:15.324Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:52:20.123Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:52:21.259Z] 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.
[2025-11-13T10:52:21.259Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:52:21.956Z] Top recommended movies for user id 72:
[2025-11-13T10:52:21.956Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:52:21.956Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:52:21.956Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:52:21.956Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:52:21.956Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:52:21.956Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (53213.316 ms) ======
[2025-11-13T10:52:21.956Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-13T10:52:23.129Z] GC before operation: completed in 971.507 ms, heap usage 148.253 MB -> 94.680 MB.
[2025-11-13T10:52:33.917Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:52:44.686Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:52:55.476Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:53:04.373Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:53:10.235Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:53:14.960Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:53:19.688Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:53:24.545Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:53:25.692Z] 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.
[2025-11-13T10:53:25.692Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:53:26.392Z] Top recommended movies for user id 72:
[2025-11-13T10:53:26.392Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:53:26.392Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:53:26.392Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:53:26.392Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:53:26.392Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:53:26.392Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (63465.458 ms) ======
[2025-11-13T10:53:26.392Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-13T10:53:27.559Z] GC before operation: completed in 984.072 ms, heap usage 218.271 MB -> 97.018 MB.
[2025-11-13T10:53:38.318Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:53:47.300Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:53:54.569Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:54:01.915Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:54:06.638Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:54:11.361Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:54:17.210Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:54:22.008Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:54:22.334Z] 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.
[2025-11-13T10:54:22.334Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:54:23.036Z] Top recommended movies for user id 72:
[2025-11-13T10:54:23.036Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:54:23.036Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:54:23.036Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:54:23.036Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:54:23.036Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:54:23.036Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (55632.906 ms) ======
[2025-11-13T10:54:23.036Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-13T10:54:24.213Z] GC before operation: completed in 1005.505 ms, heap usage 805.351 MB -> 99.086 MB.
[2025-11-13T10:54:34.986Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-13T10:54:42.348Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-13T10:54:49.624Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-13T10:54:58.566Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-13T10:55:04.440Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-13T10:55:09.168Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-13T10:55:15.024Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-13T10:55:19.769Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-13T10:55:19.769Z] 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.
[2025-11-13T10:55:20.096Z] The best model improves the baseline by 14.52%.
[2025-11-13T10:55:20.794Z] Top recommended movies for user id 72:
[2025-11-13T10:55:20.794Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-13T10:55:20.794Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-13T10:55:20.794Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-13T10:55:20.794Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-13T10:55:20.794Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-13T10:55:20.794Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (56678.308 ms) ======
[2025-11-13T10:55:24.550Z] -----------------------------------
[2025-11-13T10:55:24.550Z] renaissance-movie-lens_0_PASSED
[2025-11-13T10:55:24.550Z] -----------------------------------
[2025-11-13T10:55:24.550Z]
[2025-11-13T10:55:24.550Z] TEST TEARDOWN:
[2025-11-13T10:55:24.550Z] Nothing to be done for teardown.
[2025-11-13T10:55:24.550Z] renaissance-movie-lens_0 Finish Time: Thu Nov 13 10:55:24 2025 Epoch Time (ms): 1763031324230