renaissance-movie-lens_0
[2025-08-28T09:28:29.339Z] Running test renaissance-movie-lens_0 ...
[2025-08-28T09:28:29.339Z] ===============================================
[2025-08-28T09:28:29.339Z] renaissance-movie-lens_0 Start Time: Thu Aug 28 09:28:29 2025 Epoch Time (ms): 1756373309144
[2025-08-28T09:28:29.339Z] variation: NoOptions
[2025-08-28T09:28:29.339Z] JVM_OPTIONS:
[2025-08-28T09:28:29.339Z] { \
[2025-08-28T09:28:29.339Z] echo ""; echo "TEST SETUP:"; \
[2025-08-28T09:28:29.339Z] echo "Nothing to be done for setup."; \
[2025-08-28T09:28:29.339Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17563686166155/renaissance-movie-lens_0"; \
[2025-08-28T09:28:29.339Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17563686166155/renaissance-movie-lens_0"; \
[2025-08-28T09:28:29.339Z] echo ""; echo "TESTING:"; \
[2025-08-28T09:28:29.339Z] "/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_17563686166155/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-08-28T09:28:29.339Z] 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_17563686166155/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-08-28T09:28:29.339Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-08-28T09:28:29.339Z] echo "Nothing to be done for teardown."; \
[2025-08-28T09:28:29.339Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17563686166155/TestTargetResult";
[2025-08-28T09:28:29.339Z]
[2025-08-28T09:28:29.339Z] TEST SETUP:
[2025-08-28T09:28:29.339Z] Nothing to be done for setup.
[2025-08-28T09:28:29.339Z]
[2025-08-28T09:28:29.339Z] TESTING:
[2025-08-28T09:28:57.026Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-08-28T09:29:30.330Z] 09:29:24.923 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.
[2025-08-28T09:29:36.215Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-08-28T09:29:39.263Z] Training: 60056, validation: 20285, test: 19854
[2025-08-28T09:29:39.263Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-08-28T09:29:39.594Z] GC before operation: completed in 603.138 ms, heap usage 347.317 MB -> 76.065 MB.
[2025-08-28T09:30:07.318Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:30:26.451Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:30:39.584Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:30:52.817Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:31:00.059Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:31:07.307Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:31:14.588Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:31:20.458Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:31:21.629Z] 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.
[2025-08-28T09:31:21.955Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:31:23.100Z] Top recommended movies for user id 72:
[2025-08-28T09:31:23.100Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:31:23.100Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:31:23.100Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:31:23.100Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:31:23.100Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:31:23.100Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (103295.483 ms) ======
[2025-08-28T09:31:23.100Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-08-28T09:31:24.251Z] GC before operation: completed in 1075.079 ms, heap usage 800.941 MB -> 100.792 MB.
[2025-08-28T09:31:37.362Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:31:48.258Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:31:59.085Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:32:09.899Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:32:15.779Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:32:23.018Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:32:28.915Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:32:34.972Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:32:36.116Z] 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.
[2025-08-28T09:32:36.116Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:32:36.826Z] Top recommended movies for user id 72:
[2025-08-28T09:32:36.826Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:32:36.826Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:32:36.826Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:32:36.826Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:32:36.826Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:32:36.826Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (72925.959 ms) ======
[2025-08-28T09:32:36.826Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-08-28T09:32:38.006Z] GC before operation: completed in 974.497 ms, heap usage 376.071 MB -> 89.022 MB.
[2025-08-28T09:32:48.842Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:32:57.703Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:33:08.518Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:33:17.419Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:33:23.401Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:33:30.663Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:33:36.562Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:33:42.472Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:33:43.174Z] 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.
[2025-08-28T09:33:43.174Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:33:43.875Z] Top recommended movies for user id 72:
[2025-08-28T09:33:43.875Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:33:43.875Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:33:43.875Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:33:43.875Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:33:43.875Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:33:43.875Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (66110.888 ms) ======
[2025-08-28T09:33:43.875Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-08-28T09:33:45.052Z] GC before operation: completed in 791.811 ms, heap usage 365.748 MB -> 89.599 MB.
[2025-08-28T09:33:55.868Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:34:04.927Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:34:13.785Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:34:24.579Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:34:29.309Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:34:35.187Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:34:41.084Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:34:46.972Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:34:48.113Z] 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.
[2025-08-28T09:34:48.113Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:34:48.811Z] Top recommended movies for user id 72:
[2025-08-28T09:34:48.811Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:34:48.811Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:34:48.811Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:34:48.811Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:34:48.811Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:34:48.811Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (64133.887 ms) ======
[2025-08-28T09:34:48.811Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-08-28T09:34:50.101Z] GC before operation: completed in 920.100 ms, heap usage 510.565 MB -> 90.108 MB.
[2025-08-28T09:35:00.922Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:35:09.817Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:35:20.627Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:35:29.485Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:35:36.779Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:35:42.663Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:35:48.550Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:35:53.298Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:35:54.456Z] 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.
[2025-08-28T09:35:54.456Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:35:55.657Z] Top recommended movies for user id 72:
[2025-08-28T09:35:55.657Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:35:55.657Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:35:55.657Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:35:55.657Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:35:55.657Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:35:55.657Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (65459.068 ms) ======
[2025-08-28T09:35:55.657Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-08-28T09:35:55.997Z] GC before operation: completed in 790.968 ms, heap usage 373.617 MB -> 89.965 MB.
[2025-08-28T09:36:06.820Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:36:14.077Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:36:22.966Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:36:31.845Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:36:36.586Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:36:41.322Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:36:47.240Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:36:51.979Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:36:53.114Z] 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.
[2025-08-28T09:36:53.114Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:36:53.820Z] Top recommended movies for user id 72:
[2025-08-28T09:36:53.820Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:36:53.820Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:36:53.820Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:36:53.820Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:36:53.820Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:36:53.820Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (57697.768 ms) ======
[2025-08-28T09:36:53.820Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-08-28T09:36:54.986Z] GC before operation: completed in 905.930 ms, heap usage 682.451 MB -> 93.870 MB.
[2025-08-28T09:37:03.866Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:37:12.729Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:37:21.668Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:37:28.925Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:37:33.664Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:37:39.553Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:37:44.515Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:37:49.265Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:37:50.402Z] 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.
[2025-08-28T09:37:50.402Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:37:51.103Z] Top recommended movies for user id 72:
[2025-08-28T09:37:51.103Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:37:51.103Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:37:51.103Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:37:51.103Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:37:51.103Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:37:51.103Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (56379.278 ms) ======
[2025-08-28T09:37:51.103Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-08-28T09:37:51.829Z] GC before operation: completed in 818.365 ms, heap usage 301.407 MB -> 90.108 MB.
[2025-08-28T09:38:00.714Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:38:09.586Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:38:18.444Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:38:25.690Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:38:30.427Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:38:36.339Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:38:41.086Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:38:45.819Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:38:46.953Z] 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.
[2025-08-28T09:38:46.953Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:38:47.655Z] Top recommended movies for user id 72:
[2025-08-28T09:38:47.655Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:38:47.655Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:38:47.656Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:38:47.656Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:38:47.656Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:38:47.656Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (55679.814 ms) ======
[2025-08-28T09:38:47.656Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-08-28T09:38:48.374Z] GC before operation: completed in 823.733 ms, heap usage 269.330 MB -> 90.262 MB.
[2025-08-28T09:38:57.250Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:39:06.123Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:39:13.384Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:39:22.253Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:39:26.990Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:39:31.745Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:39:37.882Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:39:42.648Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:39:42.998Z] 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.
[2025-08-28T09:39:42.998Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:39:44.138Z] Top recommended movies for user id 72:
[2025-08-28T09:39:44.138Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:39:44.138Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:39:44.138Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:39:44.138Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:39:44.138Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:39:44.138Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (55426.314 ms) ======
[2025-08-28T09:39:44.138Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-08-28T09:39:44.850Z] GC before operation: completed in 817.233 ms, heap usage 121.433 MB -> 91.423 MB.
[2025-08-28T09:39:53.722Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:40:02.590Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:40:11.458Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:40:18.713Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:40:23.452Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:40:29.325Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:40:34.080Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:40:39.952Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:40:40.659Z] 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.
[2025-08-28T09:40:40.660Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:40:41.379Z] Top recommended movies for user id 72:
[2025-08-28T09:40:41.379Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:40:41.379Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:40:41.379Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:40:41.379Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:40:41.379Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:40:41.379Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (56578.102 ms) ======
[2025-08-28T09:40:41.379Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-08-28T09:40:42.103Z] GC before operation: completed in 807.583 ms, heap usage 200.434 MB -> 90.269 MB.
[2025-08-28T09:40:50.966Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:40:59.825Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:41:08.673Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:41:15.912Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:41:20.653Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:41:26.529Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:41:31.755Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:41:37.636Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:41:37.971Z] 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.
[2025-08-28T09:41:37.971Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:41:38.670Z] Top recommended movies for user id 72:
[2025-08-28T09:41:38.670Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:41:38.670Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:41:38.670Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:41:38.670Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:41:38.670Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:41:38.670Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (56587.207 ms) ======
[2025-08-28T09:41:38.670Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-08-28T09:41:39.388Z] GC before operation: completed in 798.910 ms, heap usage 181.046 MB -> 89.978 MB.
[2025-08-28T09:41:48.260Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:41:57.386Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:42:06.247Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:42:15.111Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:42:19.836Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:42:25.712Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:42:31.618Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:42:36.352Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:42:37.487Z] 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.
[2025-08-28T09:42:37.487Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:42:38.188Z] Top recommended movies for user id 72:
[2025-08-28T09:42:38.188Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:42:38.188Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:42:38.188Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:42:38.188Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:42:38.188Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:42:38.188Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (58649.522 ms) ======
[2025-08-28T09:42:38.188Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-08-28T09:42:38.910Z] GC before operation: completed in 812.494 ms, heap usage 352.986 MB -> 90.399 MB.
[2025-08-28T09:42:47.767Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:42:56.649Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:43:05.502Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:43:14.363Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:43:20.253Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:43:24.980Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:43:30.856Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:43:36.730Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:43:37.056Z] 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.
[2025-08-28T09:43:37.383Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:43:38.085Z] Top recommended movies for user id 72:
[2025-08-28T09:43:38.085Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:43:38.085Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:43:38.085Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:43:38.085Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:43:38.085Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:43:38.085Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (59113.633 ms) ======
[2025-08-28T09:43:38.085Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-08-28T09:43:38.809Z] GC before operation: completed in 804.652 ms, heap usage 433.278 MB -> 90.633 MB.
[2025-08-28T09:43:49.622Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:43:56.861Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:44:06.018Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:44:14.921Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:44:18.692Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:44:23.436Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:44:29.316Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:44:34.051Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:44:34.376Z] 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.
[2025-08-28T09:44:34.377Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:44:35.077Z] Top recommended movies for user id 72:
[2025-08-28T09:44:35.077Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:44:35.077Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:44:35.077Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:44:35.077Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:44:35.077Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:44:35.077Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (56248.427 ms) ======
[2025-08-28T09:44:35.077Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-08-28T09:44:36.234Z] GC before operation: completed in 876.292 ms, heap usage 435.310 MB -> 90.543 MB.
[2025-08-28T09:44:45.096Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:44:53.976Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:45:01.214Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:45:10.069Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:45:13.818Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:45:19.691Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:45:24.431Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:45:29.163Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:45:29.493Z] 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.
[2025-08-28T09:45:29.822Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:45:30.535Z] Top recommended movies for user id 72:
[2025-08-28T09:45:30.535Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:45:30.535Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:45:30.535Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:45:30.535Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:45:30.535Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:45:30.535Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (54395.746 ms) ======
[2025-08-28T09:45:30.535Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-08-28T09:45:31.252Z] GC before operation: completed in 841.019 ms, heap usage 297.623 MB -> 90.593 MB.
[2025-08-28T09:45:40.171Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:45:49.039Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:45:57.898Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:46:06.776Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:46:11.510Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:46:16.466Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:46:24.056Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:46:28.796Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:46:29.499Z] 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.
[2025-08-28T09:46:29.824Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:46:30.529Z] Top recommended movies for user id 72:
[2025-08-28T09:46:30.529Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:46:30.529Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:46:30.529Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:46:30.529Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:46:30.529Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:46:30.529Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (59144.195 ms) ======
[2025-08-28T09:46:30.529Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-08-28T09:46:31.232Z] GC before operation: completed in 829.593 ms, heap usage 150.936 MB -> 90.110 MB.
[2025-08-28T09:46:40.116Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:46:48.972Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:46:57.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:47:06.695Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:47:11.432Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:47:17.314Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:47:23.193Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:47:28.096Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:47:28.807Z] 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.
[2025-08-28T09:47:29.215Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:47:29.546Z] Top recommended movies for user id 72:
[2025-08-28T09:47:29.547Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:47:29.887Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:47:29.887Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:47:29.887Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:47:29.887Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:47:29.887Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (58512.603 ms) ======
[2025-08-28T09:47:29.887Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-08-28T09:47:30.615Z] GC before operation: completed in 835.232 ms, heap usage 188.100 MB -> 90.339 MB.
[2025-08-28T09:47:41.391Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:47:48.630Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:47:55.873Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:48:04.908Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:48:08.676Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:48:14.560Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:48:20.462Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:48:25.203Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:48:25.904Z] 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.
[2025-08-28T09:48:25.904Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:48:26.610Z] Top recommended movies for user id 72:
[2025-08-28T09:48:26.610Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:48:26.610Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:48:26.610Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:48:26.610Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:48:26.610Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:48:26.610Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (56186.604 ms) ======
[2025-08-28T09:48:26.610Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-08-28T09:48:27.774Z] GC before operation: completed in 817.696 ms, heap usage 185.037 MB -> 90.413 MB.
[2025-08-28T09:48:36.661Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:48:45.517Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:48:54.515Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:49:03.370Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:49:08.095Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:49:14.000Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:49:18.739Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:49:24.621Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:49:25.327Z] 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.
[2025-08-28T09:49:25.327Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:49:26.059Z] Top recommended movies for user id 72:
[2025-08-28T09:49:26.059Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:49:26.059Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:49:26.059Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:49:26.059Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:49:26.059Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:49:26.059Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (58509.295 ms) ======
[2025-08-28T09:49:26.059Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-08-28T09:49:26.796Z] GC before operation: completed in 822.710 ms, heap usage 374.986 MB -> 90.592 MB.
[2025-08-28T09:49:35.877Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-08-28T09:49:44.748Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-08-28T09:49:53.633Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-08-28T09:50:02.504Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-08-28T09:50:07.249Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-08-28T09:50:13.143Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-08-28T09:50:17.873Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-08-28T09:50:23.837Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-08-28T09:50:24.163Z] 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.
[2025-08-28T09:50:24.163Z] The best model improves the baseline by 14.52%.
[2025-08-28T09:50:24.867Z] Top recommended movies for user id 72:
[2025-08-28T09:50:24.868Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-08-28T09:50:24.868Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-08-28T09:50:24.868Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-08-28T09:50:24.868Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-08-28T09:50:24.868Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-08-28T09:50:24.868Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (58035.712 ms) ======
[2025-08-28T09:50:27.813Z] -----------------------------------
[2025-08-28T09:50:27.813Z] renaissance-movie-lens_0_PASSED
[2025-08-28T09:50:27.813Z] -----------------------------------
[2025-08-28T09:50:28.140Z]
[2025-08-28T09:50:28.140Z] TEST TEARDOWN:
[2025-08-28T09:50:28.140Z] Nothing to be done for teardown.
[2025-08-28T09:50:28.140Z] renaissance-movie-lens_0 Finish Time: Thu Aug 28 09:50:28 2025 Epoch Time (ms): 1756374628114