renaissance-movie-lens_0
[2025-10-04T05:34:46.168Z] Running test renaissance-movie-lens_0 ...
[2025-10-04T05:34:46.168Z] ===============================================
[2025-10-04T05:34:46.168Z] renaissance-movie-lens_0 Start Time: Sat Oct 4 05:34:46 2025 Epoch Time (ms): 1759556086020
[2025-10-04T05:34:46.168Z] variation: NoOptions
[2025-10-04T05:34:46.168Z] JVM_OPTIONS:
[2025-10-04T05:34:46.168Z] { \
[2025-10-04T05:34:46.168Z] echo ""; echo "TEST SETUP:"; \
[2025-10-04T05:34:46.168Z] echo "Nothing to be done for setup."; \
[2025-10-04T05:34:46.168Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_1759551527469/renaissance-movie-lens_0"; \
[2025-10-04T05:34:46.168Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_1759551527469/renaissance-movie-lens_0"; \
[2025-10-04T05:34:46.168Z] echo ""; echo "TESTING:"; \
[2025-10-04T05:34:46.168Z] "/home/jenkins/workspace/Test_openjdk21_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_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_1759551527469/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-10-04T05:34:46.168Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_1759551527469/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-10-04T05:34:46.168Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-10-04T05:34:46.168Z] echo "Nothing to be done for teardown."; \
[2025-10-04T05:34:46.168Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_1759551527469/TestTargetResult";
[2025-10-04T05:34:46.168Z]
[2025-10-04T05:34:46.168Z] TEST SETUP:
[2025-10-04T05:34:46.168Z] Nothing to be done for setup.
[2025-10-04T05:34:46.168Z]
[2025-10-04T05:34:46.168Z] TESTING:
[2025-10-04T05:35:13.886Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-10-04T05:35:41.738Z] 05:35:41.328 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-10-04T05:35:54.877Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-10-04T05:35:55.585Z] Training: 60056, validation: 20285, test: 19854
[2025-10-04T05:35:55.585Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-10-04T05:35:56.311Z] GC before operation: completed in 626.336 ms, heap usage 599.330 MB -> 76.309 MB.
[2025-10-04T05:36:24.082Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:36:43.245Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:36:56.352Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:37:09.460Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:37:16.715Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:37:23.972Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:37:31.348Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:37:37.248Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:37:38.386Z] 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.
[2025-10-04T05:37:38.386Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:37:39.537Z] Top recommended movies for user id 72:
[2025-10-04T05:37:39.537Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:37:39.537Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:37:39.537Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:37:39.537Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:37:39.537Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:37:39.537Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (103258.029 ms) ======
[2025-10-04T05:37:39.537Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-10-04T05:37:40.723Z] GC before operation: completed in 1058.815 ms, heap usage 773.862 MB -> 96.497 MB.
[2025-10-04T05:37:53.835Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:38:04.638Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:38:15.569Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:38:24.440Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:38:30.335Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:38:36.227Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:38:43.483Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:38:48.214Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:38:49.425Z] 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.
[2025-10-04T05:38:49.425Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:38:50.138Z] Top recommended movies for user id 72:
[2025-10-04T05:38:50.138Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:38:50.138Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:38:50.138Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:38:50.138Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:38:50.138Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:38:50.138Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (69566.264 ms) ======
[2025-10-04T05:38:50.138Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-10-04T05:38:51.303Z] GC before operation: completed in 1147.714 ms, heap usage 1.007 GB -> 93.784 MB.
[2025-10-04T05:39:02.137Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:39:12.958Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:39:21.838Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:39:30.711Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:39:35.555Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:39:42.819Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:39:47.568Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:39:53.466Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:39:54.612Z] 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.
[2025-10-04T05:39:54.612Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:39:55.319Z] Top recommended movies for user id 72:
[2025-10-04T05:39:55.319Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:39:55.319Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:39:55.319Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:39:55.319Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:39:55.319Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:39:55.319Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (63943.422 ms) ======
[2025-10-04T05:39:55.319Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-10-04T05:39:56.487Z] GC before operation: completed in 950.074 ms, heap usage 729.584 MB -> 93.469 MB.
[2025-10-04T05:40:09.596Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:40:18.513Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:40:27.390Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:40:38.200Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:40:42.947Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:40:50.213Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:40:56.219Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:41:00.982Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:41:01.694Z] 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.
[2025-10-04T05:41:02.024Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:41:02.729Z] Top recommended movies for user id 72:
[2025-10-04T05:41:02.729Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:41:02.729Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:41:02.729Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:41:02.729Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:41:02.729Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:41:02.729Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (66464.611 ms) ======
[2025-10-04T05:41:02.729Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-10-04T05:41:03.459Z] GC before operation: completed in 841.180 ms, heap usage 308.907 MB -> 90.811 MB.
[2025-10-04T05:41:14.290Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:41:23.201Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:41:34.026Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:41:42.923Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:41:48.831Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:41:54.741Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:42:00.640Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:42:06.529Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:42:06.858Z] 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.
[2025-10-04T05:42:06.858Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:42:08.020Z] Top recommended movies for user id 72:
[2025-10-04T05:42:08.020Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:42:08.020Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:42:08.020Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:42:08.020Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:42:08.020Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:42:08.020Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (64249.633 ms) ======
[2025-10-04T05:42:08.020Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-10-04T05:42:08.752Z] GC before operation: completed in 879.373 ms, heap usage 125.506 MB -> 90.499 MB.
[2025-10-04T05:42:19.572Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:42:26.835Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:42:35.725Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:42:44.602Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:42:49.353Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:42:54.098Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:43:00.008Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:43:04.750Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:43:05.903Z] 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.
[2025-10-04T05:43:05.903Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:43:06.613Z] Top recommended movies for user id 72:
[2025-10-04T05:43:06.613Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:43:06.613Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:43:06.613Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:43:06.613Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:43:06.613Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:43:06.613Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (57806.468 ms) ======
[2025-10-04T05:43:06.613Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-10-04T05:43:07.352Z] GC before operation: completed in 892.798 ms, heap usage 507.256 MB -> 91.370 MB.
[2025-10-04T05:43:16.268Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:43:25.148Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:43:34.042Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:43:42.931Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:43:46.708Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:43:52.954Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:43:57.737Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:44:02.472Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:44:03.632Z] 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.
[2025-10-04T05:44:03.632Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:44:04.347Z] Top recommended movies for user id 72:
[2025-10-04T05:44:04.347Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:44:04.347Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:44:04.347Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:44:04.347Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:44:04.347Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:44:04.347Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (56805.230 ms) ======
[2025-10-04T05:44:04.347Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-10-04T05:44:05.078Z] GC before operation: completed in 880.709 ms, heap usage 564.199 MB -> 94.601 MB.
[2025-10-04T05:44:13.954Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:44:22.827Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:44:31.710Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:44:38.988Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:44:43.725Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:44:49.624Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:44:54.357Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:44:59.099Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:44:59.805Z] 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.
[2025-10-04T05:45:00.146Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:45:00.849Z] Top recommended movies for user id 72:
[2025-10-04T05:45:00.849Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:45:00.849Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:45:00.849Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:45:00.849Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:45:00.849Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:45:00.849Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (55650.268 ms) ======
[2025-10-04T05:45:00.849Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-10-04T05:45:01.574Z] GC before operation: completed in 873.473 ms, heap usage 205.621 MB -> 91.148 MB.
[2025-10-04T05:45:12.370Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:45:19.627Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:45:26.893Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:45:35.760Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:45:39.538Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:45:45.702Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:45:50.437Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:45:56.326Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:45:56.326Z] 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.
[2025-10-04T05:45:56.326Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:45:57.483Z] Top recommended movies for user id 72:
[2025-10-04T05:45:57.483Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:45:57.483Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:45:57.483Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:45:57.483Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:45:57.483Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:45:57.483Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (55622.903 ms) ======
[2025-10-04T05:45:57.483Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-10-04T05:45:58.212Z] GC before operation: completed in 907.376 ms, heap usage 1.318 GB -> 96.915 MB.
[2025-10-04T05:46:07.080Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:46:15.972Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:46:24.856Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:46:33.722Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:46:38.459Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:46:44.353Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:46:50.240Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:46:54.976Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:46:56.122Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-10-04T05:46:56.451Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:46:57.171Z] Top recommended movies for user id 72:
[2025-10-04T05:46:57.171Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:46:57.171Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:46:57.171Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:46:57.171Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:46:57.171Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:46:57.171Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (58898.887 ms) ======
[2025-10-04T05:46:57.171Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-10-04T05:46:57.898Z] GC before operation: completed in 823.494 ms, heap usage 378.577 MB -> 91.564 MB.
[2025-10-04T05:47:06.764Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:47:15.641Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:47:24.511Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:47:33.399Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:47:38.148Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:47:44.035Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:47:49.924Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:47:54.701Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:47:55.411Z] 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.
[2025-10-04T05:47:55.738Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:47:56.227Z] Top recommended movies for user id 72:
[2025-10-04T05:47:56.227Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:47:56.227Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:47:56.227Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:47:56.227Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:47:56.227Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:47:56.227Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (58357.918 ms) ======
[2025-10-04T05:47:56.227Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-10-04T05:47:57.432Z] GC before operation: completed in 927.750 ms, heap usage 406.481 MB -> 91.403 MB.
[2025-10-04T05:48:06.372Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:48:15.261Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:48:24.139Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:48:33.026Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:48:37.787Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:48:43.682Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:48:48.438Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:48:54.329Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:48:55.033Z] 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.
[2025-10-04T05:48:55.360Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:48:56.065Z] Top recommended movies for user id 72:
[2025-10-04T05:48:56.065Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:48:56.065Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:48:56.065Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:48:56.065Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:48:56.065Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:48:56.065Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (58812.413 ms) ======
[2025-10-04T05:48:56.065Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-10-04T05:48:56.803Z] GC before operation: completed in 846.350 ms, heap usage 173.493 MB -> 91.286 MB.
[2025-10-04T05:49:05.683Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:49:12.929Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:49:21.822Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:49:29.093Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:49:34.982Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:49:40.880Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:49:45.617Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:49:50.360Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:49:51.064Z] 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.
[2025-10-04T05:49:51.064Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:49:51.769Z] Top recommended movies for user id 72:
[2025-10-04T05:49:51.769Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:49:51.769Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:49:51.769Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:49:51.769Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:49:51.769Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:49:51.769Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (54929.924 ms) ======
[2025-10-04T05:49:51.769Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-10-04T05:49:52.940Z] GC before operation: completed in 907.745 ms, heap usage 990.460 MB -> 96.252 MB.
[2025-10-04T05:50:01.816Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:50:10.759Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:50:19.646Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:50:26.949Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:50:31.700Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:50:37.597Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:50:42.331Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:50:47.068Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:50:47.400Z] 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.
[2025-10-04T05:50:47.727Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:50:48.452Z] Top recommended movies for user id 72:
[2025-10-04T05:50:48.452Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:50:48.452Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:50:48.452Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:50:48.452Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:50:48.452Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:50:48.452Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (55603.741 ms) ======
[2025-10-04T05:50:48.452Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-10-04T05:50:49.182Z] GC before operation: completed in 906.737 ms, heap usage 1.120 GB -> 96.581 MB.
[2025-10-04T05:50:58.065Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:51:06.938Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:51:15.817Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:51:23.081Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:51:27.824Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:51:32.560Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:51:37.298Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:51:42.036Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:51:42.740Z] 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.
[2025-10-04T05:51:42.740Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:51:43.446Z] Top recommended movies for user id 72:
[2025-10-04T05:51:43.446Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:51:43.446Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:51:43.446Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:51:43.446Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:51:43.446Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:51:43.446Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (54401.985 ms) ======
[2025-10-04T05:51:43.446Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-10-04T05:51:44.618Z] GC before operation: completed in 871.858 ms, heap usage 242.738 MB -> 91.619 MB.
[2025-10-04T05:51:53.485Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:52:00.738Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:52:09.610Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:52:18.876Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:52:24.761Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:52:29.487Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:52:35.382Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:52:41.277Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:52:41.277Z] 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.
[2025-10-04T05:52:41.607Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:52:42.320Z] Top recommended movies for user id 72:
[2025-10-04T05:52:42.320Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:52:42.320Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:52:42.320Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:52:42.320Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:52:42.320Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:52:42.320Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (57906.525 ms) ======
[2025-10-04T05:52:42.320Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-10-04T05:52:43.497Z] GC before operation: completed in 893.171 ms, heap usage 302.117 MB -> 91.606 MB.
[2025-10-04T05:52:52.369Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:53:01.240Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:53:10.110Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:53:17.358Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:53:22.110Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:53:26.856Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:53:31.594Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:53:36.355Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:53:37.500Z] 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.
[2025-10-04T05:53:37.500Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:53:38.218Z] Top recommended movies for user id 72:
[2025-10-04T05:53:38.218Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:53:38.218Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:53:38.218Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:53:38.218Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:53:38.218Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:53:38.218Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (54856.559 ms) ======
[2025-10-04T05:53:38.218Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-10-04T05:53:38.945Z] GC before operation: completed in 841.163 ms, heap usage 239.019 MB -> 91.586 MB.
[2025-10-04T05:53:47.830Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:53:56.711Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:54:03.987Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:54:11.239Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:54:17.146Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:54:21.910Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:54:27.919Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:54:31.677Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:54:32.816Z] 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.
[2025-10-04T05:54:32.816Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:54:33.965Z] Top recommended movies for user id 72:
[2025-10-04T05:54:33.965Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:54:33.965Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:54:33.965Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:54:33.965Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:54:33.965Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:54:33.965Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (54819.685 ms) ======
[2025-10-04T05:54:33.965Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-10-04T05:54:34.684Z] GC before operation: completed in 948.665 ms, heap usage 767.860 MB -> 95.248 MB.
[2025-10-04T05:54:43.551Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:54:52.422Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:54:59.683Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:55:06.933Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:55:11.667Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:55:16.412Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:55:22.298Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:55:27.040Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:55:27.368Z] 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.
[2025-10-04T05:55:27.703Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:55:28.424Z] Top recommended movies for user id 72:
[2025-10-04T05:55:28.424Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:55:28.424Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:55:28.424Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:55:28.424Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:55:28.424Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:55:28.424Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (53510.450 ms) ======
[2025-10-04T05:55:28.424Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-10-04T05:55:29.150Z] GC before operation: completed in 864.768 ms, heap usage 238.949 MB -> 91.463 MB.
[2025-10-04T05:55:38.032Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-04T05:55:45.296Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-04T05:55:54.170Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-04T05:56:03.034Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-04T05:56:07.774Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-04T05:56:12.529Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-04T05:56:18.418Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-04T05:56:23.153Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-04T05:56:24.295Z] 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.
[2025-10-04T05:56:24.295Z] The best model improves the baseline by 14.52%.
[2025-10-04T05:56:24.997Z] Top recommended movies for user id 72:
[2025-10-04T05:56:24.997Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-10-04T05:56:24.997Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-10-04T05:56:24.997Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-10-04T05:56:24.997Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-10-04T05:56:24.997Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-10-04T05:56:24.997Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (55907.087 ms) ======
[2025-10-04T05:56:28.965Z] -----------------------------------
[2025-10-04T05:56:28.965Z] renaissance-movie-lens_0_PASSED
[2025-10-04T05:56:28.965Z] -----------------------------------
[2025-10-04T05:56:28.965Z]
[2025-10-04T05:56:28.965Z] TEST TEARDOWN:
[2025-10-04T05:56:28.965Z] Nothing to be done for teardown.
[2025-10-04T05:56:28.965Z] renaissance-movie-lens_0 Finish Time: Sat Oct 4 05:56:28 2025 Epoch Time (ms): 1759557388242