[2025-06-30T20:39:07.003Z] Running test renaissance-movie-lens_0 ... [2025-06-30T20:39:07.003Z] =============================================== [2025-06-30T20:39:07.003Z] renaissance-movie-lens_0 Start Time: Mon Jun 30 20:39:05 2025 Epoch Time (ms): 1751315945996 [2025-06-30T20:39:07.003Z] variation: NoOptions [2025-06-30T20:39:07.003Z] JVM_OPTIONS: [2025-06-30T20:39:07.003Z] { \ [2025-06-30T20:39:07.003Z] echo ""; echo "TEST SETUP:"; \ [2025-06-30T20:39:07.003Z] echo "Nothing to be done for setup."; \ [2025-06-30T20:39:07.003Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17513145714329/renaissance-movie-lens_0"; \ [2025-06-30T20:39:07.003Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17513145714329/renaissance-movie-lens_0"; \ [2025-06-30T20:39:07.003Z] echo ""; echo "TESTING:"; \ [2025-06-30T20:39:07.003Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17513145714329/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-30T20:39:07.003Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17513145714329/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-30T20:39:07.003Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-30T20:39:07.003Z] echo "Nothing to be done for teardown."; \ [2025-06-30T20:39:07.003Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17513145714329/TestTargetResult"; [2025-06-30T20:39:07.003Z] [2025-06-30T20:39:07.003Z] TEST SETUP: [2025-06-30T20:39:07.003Z] Nothing to be done for setup. [2025-06-30T20:39:07.003Z] [2025-06-30T20:39:07.003Z] TESTING: [2025-06-30T20:39:12.386Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-30T20:39:19.098Z] 20:39:18.317 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-06-30T20:39:21.064Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-30T20:39:21.064Z] Training: 60056, validation: 20285, test: 19854 [2025-06-30T20:39:21.064Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-30T20:39:22.033Z] GC before operation: completed in 147.846 ms, heap usage 311.116 MB -> 75.968 MB. [2025-06-30T20:39:27.401Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:39:30.400Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:39:34.295Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:39:37.266Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:39:39.219Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:39:40.159Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:39:42.130Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:39:44.054Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:39:44.054Z] 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. [2025-06-30T20:39:44.054Z] The best model improves the baseline by 14.52%. [2025-06-30T20:39:44.992Z] Top recommended movies for user id 72: [2025-06-30T20:39:44.992Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:39:44.992Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:39:44.992Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:39:44.992Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:39:44.992Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:39:44.992Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23177.386 ms) ====== [2025-06-30T20:39:44.992Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-30T20:39:44.992Z] GC before operation: completed in 144.420 ms, heap usage 302.744 MB -> 86.739 MB. [2025-06-30T20:39:47.998Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:39:49.935Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:39:52.942Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:39:55.999Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:39:56.964Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:39:58.912Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:40:00.864Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:40:01.822Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:40:01.822Z] 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. [2025-06-30T20:40:02.766Z] The best model improves the baseline by 14.52%. [2025-06-30T20:40:02.766Z] Top recommended movies for user id 72: [2025-06-30T20:40:02.766Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:40:02.766Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:40:02.766Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:40:02.766Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:40:02.766Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:40:02.766Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17598.493 ms) ====== [2025-06-30T20:40:02.766Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-30T20:40:02.766Z] GC before operation: completed in 156.207 ms, heap usage 340.624 MB -> 88.887 MB. [2025-06-30T20:40:04.783Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:40:07.898Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:40:10.934Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:40:12.883Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:40:14.871Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:40:16.865Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:40:17.820Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:40:19.810Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:40:19.810Z] 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. [2025-06-30T20:40:19.810Z] The best model improves the baseline by 14.52%. [2025-06-30T20:40:19.810Z] Top recommended movies for user id 72: [2025-06-30T20:40:19.810Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:40:19.810Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:40:19.810Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:40:19.810Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:40:19.810Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:40:19.810Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17528.947 ms) ====== [2025-06-30T20:40:19.810Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-30T20:40:20.782Z] GC before operation: completed in 158.253 ms, heap usage 290.067 MB -> 89.608 MB. [2025-06-30T20:40:22.738Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:40:24.751Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:40:27.707Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:40:29.683Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:40:31.636Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:40:32.599Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:40:34.709Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:40:35.661Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:40:36.625Z] 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. [2025-06-30T20:40:36.625Z] The best model improves the baseline by 14.52%. [2025-06-30T20:40:36.625Z] Top recommended movies for user id 72: [2025-06-30T20:40:36.625Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:40:36.625Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:40:36.625Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:40:36.625Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:40:36.625Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:40:36.625Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16067.215 ms) ====== [2025-06-30T20:40:36.625Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-30T20:40:36.625Z] GC before operation: completed in 164.674 ms, heap usage 228.899 MB -> 89.748 MB. [2025-06-30T20:40:38.583Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:40:41.559Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:40:43.529Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:40:46.550Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:40:47.531Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:40:49.573Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:40:50.518Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:40:52.499Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:40:52.499Z] 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. [2025-06-30T20:40:52.499Z] The best model improves the baseline by 14.52%. [2025-06-30T20:40:52.499Z] Top recommended movies for user id 72: [2025-06-30T20:40:52.499Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:40:52.499Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:40:52.499Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:40:52.499Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:40:52.499Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:40:52.499Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15958.477 ms) ====== [2025-06-30T20:40:52.499Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-30T20:40:52.499Z] GC before operation: completed in 190.456 ms, heap usage 364.007 MB -> 89.951 MB. [2025-06-30T20:40:55.597Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:40:57.565Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:41:00.569Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:41:02.554Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:41:03.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:41:05.500Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:41:07.446Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:41:08.395Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:41:08.395Z] 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. [2025-06-30T20:41:08.395Z] The best model improves the baseline by 14.52%. [2025-06-30T20:41:09.341Z] Top recommended movies for user id 72: [2025-06-30T20:41:09.341Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:41:09.341Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:41:09.341Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:41:09.341Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:41:09.341Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:41:09.341Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16257.162 ms) ====== [2025-06-30T20:41:09.341Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-30T20:41:09.341Z] GC before operation: completed in 170.738 ms, heap usage 99.511 MB -> 89.888 MB. [2025-06-30T20:41:11.403Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:41:13.345Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:41:16.330Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:41:18.465Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:41:19.420Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:41:21.275Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:41:22.215Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:41:23.155Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:41:24.092Z] 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. [2025-06-30T20:41:24.092Z] The best model improves the baseline by 14.52%. [2025-06-30T20:41:24.092Z] Top recommended movies for user id 72: [2025-06-30T20:41:24.092Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:41:24.092Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:41:24.092Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:41:24.092Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:41:24.092Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:41:24.092Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14807.531 ms) ====== [2025-06-30T20:41:24.092Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-30T20:41:24.092Z] GC before operation: completed in 170.219 ms, heap usage 283.731 MB -> 90.147 MB. [2025-06-30T20:41:26.022Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:41:29.012Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:41:30.941Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:41:32.871Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:41:33.825Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:41:35.759Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:41:36.705Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:41:38.636Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:41:38.636Z] 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. [2025-06-30T20:41:38.636Z] The best model improves the baseline by 14.52%. [2025-06-30T20:41:38.636Z] Top recommended movies for user id 72: [2025-06-30T20:41:38.636Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:41:38.636Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:41:38.636Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:41:38.636Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:41:38.636Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:41:38.636Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14793.821 ms) ====== [2025-06-30T20:41:38.636Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-30T20:41:39.572Z] GC before operation: completed in 215.431 ms, heap usage 288.297 MB -> 90.316 MB. [2025-06-30T20:41:41.524Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:41:43.464Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:41:46.452Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:41:48.401Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:41:49.339Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:41:51.265Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:41:52.208Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:41:54.142Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:41:54.142Z] 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. [2025-06-30T20:41:54.142Z] The best model improves the baseline by 14.52%. [2025-06-30T20:41:54.142Z] Top recommended movies for user id 72: [2025-06-30T20:41:54.142Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:41:54.142Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:41:54.142Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:41:54.142Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:41:54.142Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:41:54.142Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15231.178 ms) ====== [2025-06-30T20:41:54.142Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-30T20:41:54.142Z] GC before operation: completed in 181.842 ms, heap usage 495.916 MB -> 90.367 MB. [2025-06-30T20:41:57.146Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:41:59.072Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:42:01.013Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:42:02.975Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:42:03.911Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:42:05.860Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:42:06.814Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:42:10.061Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:42:10.061Z] 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. [2025-06-30T20:42:10.061Z] The best model improves the baseline by 14.52%. [2025-06-30T20:42:10.061Z] Top recommended movies for user id 72: [2025-06-30T20:42:10.061Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:42:10.061Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:42:10.061Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:42:10.061Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:42:10.061Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:42:10.061Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14577.862 ms) ====== [2025-06-30T20:42:10.061Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-30T20:42:10.061Z] GC before operation: completed in 136.655 ms, heap usage 347.823 MB -> 90.375 MB. [2025-06-30T20:42:12.010Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:42:13.948Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:42:15.893Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:42:18.897Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:42:19.842Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:42:21.774Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:42:22.719Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:42:24.650Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:42:24.650Z] 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. [2025-06-30T20:42:24.650Z] The best model improves the baseline by 14.52%. [2025-06-30T20:42:24.650Z] Top recommended movies for user id 72: [2025-06-30T20:42:24.650Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:42:24.650Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:42:24.650Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:42:24.650Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:42:24.650Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:42:24.650Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15576.228 ms) ====== [2025-06-30T20:42:24.650Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-30T20:42:24.650Z] GC before operation: completed in 172.282 ms, heap usage 458.825 MB -> 90.317 MB. [2025-06-30T20:42:27.638Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:42:29.571Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:42:32.555Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:42:34.618Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:42:35.558Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:42:37.494Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:42:38.448Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:42:39.388Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:42:40.323Z] 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. [2025-06-30T20:42:40.324Z] The best model improves the baseline by 14.52%. [2025-06-30T20:42:40.324Z] Top recommended movies for user id 72: [2025-06-30T20:42:40.324Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:42:40.324Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:42:40.324Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:42:40.324Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:42:40.324Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:42:40.324Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15205.602 ms) ====== [2025-06-30T20:42:40.324Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-30T20:42:40.324Z] GC before operation: completed in 145.096 ms, heap usage 429.556 MB -> 90.594 MB. [2025-06-30T20:42:42.250Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:42:45.221Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:42:47.161Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:42:50.149Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:42:51.097Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:42:53.021Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:42:53.959Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:42:55.887Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:42:55.887Z] 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. [2025-06-30T20:42:55.887Z] The best model improves the baseline by 14.52%. [2025-06-30T20:42:55.887Z] Top recommended movies for user id 72: [2025-06-30T20:42:55.887Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:42:55.887Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:42:55.887Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:42:55.887Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:42:55.887Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:42:55.887Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15576.778 ms) ====== [2025-06-30T20:42:55.887Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-30T20:42:55.887Z] GC before operation: completed in 186.124 ms, heap usage 346.120 MB -> 90.446 MB. [2025-06-30T20:42:58.850Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:43:00.767Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:43:03.713Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:43:05.628Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:43:06.564Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:43:08.481Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:43:09.417Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:43:11.342Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:43:11.342Z] 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. [2025-06-30T20:43:11.342Z] The best model improves the baseline by 14.52%. [2025-06-30T20:43:11.342Z] Top recommended movies for user id 72: [2025-06-30T20:43:11.342Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:43:11.342Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:43:11.342Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:43:11.342Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:43:11.342Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:43:11.342Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15343.816 ms) ====== [2025-06-30T20:43:11.342Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-30T20:43:11.342Z] GC before operation: completed in 146.013 ms, heap usage 339.173 MB -> 90.327 MB. [2025-06-30T20:43:14.318Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:43:16.238Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:43:18.154Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:43:20.078Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:43:22.002Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:43:22.934Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:43:24.854Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:43:25.787Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:43:25.787Z] 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. [2025-06-30T20:43:25.787Z] The best model improves the baseline by 14.52%. [2025-06-30T20:43:26.720Z] Top recommended movies for user id 72: [2025-06-30T20:43:26.720Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:43:26.720Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:43:26.720Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:43:26.720Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:43:26.720Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:43:26.720Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14760.147 ms) ====== [2025-06-30T20:43:26.720Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-30T20:43:26.720Z] GC before operation: completed in 158.130 ms, heap usage 371.372 MB -> 90.615 MB. [2025-06-30T20:43:28.636Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:43:31.599Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:43:33.606Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:43:35.523Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:43:37.442Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:43:38.376Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:43:40.291Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:43:42.212Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:43:42.212Z] 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. [2025-06-30T20:43:42.212Z] The best model improves the baseline by 14.52%. [2025-06-30T20:43:42.212Z] Top recommended movies for user id 72: [2025-06-30T20:43:42.212Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:43:42.212Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:43:42.212Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:43:42.212Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:43:42.212Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:43:42.212Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15752.135 ms) ====== [2025-06-30T20:43:42.212Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-30T20:43:42.212Z] GC before operation: completed in 161.102 ms, heap usage 290.344 MB -> 90.336 MB. [2025-06-30T20:43:45.175Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:43:47.093Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:43:49.010Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:43:51.970Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:43:52.905Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:43:54.012Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:43:55.459Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:43:57.375Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:43:57.375Z] 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. [2025-06-30T20:43:57.376Z] The best model improves the baseline by 14.52%. [2025-06-30T20:43:58.309Z] Top recommended movies for user id 72: [2025-06-30T20:43:58.309Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:43:58.309Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:43:58.309Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:43:58.309Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:43:58.309Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:43:58.309Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15396.030 ms) ====== [2025-06-30T20:43:58.309Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-30T20:43:58.309Z] GC before operation: completed in 159.681 ms, heap usage 429.425 MB -> 90.696 MB. [2025-06-30T20:44:00.227Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:44:03.188Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:44:05.106Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:44:07.026Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:44:08.945Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:44:09.886Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:44:11.808Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:44:12.740Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:44:13.675Z] 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. [2025-06-30T20:44:13.675Z] The best model improves the baseline by 14.52%. [2025-06-30T20:44:13.675Z] Top recommended movies for user id 72: [2025-06-30T20:44:13.675Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:44:13.675Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:44:13.675Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:44:13.675Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:44:13.675Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:44:13.675Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15591.562 ms) ====== [2025-06-30T20:44:13.675Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-30T20:44:13.675Z] GC before operation: completed in 135.397 ms, heap usage 457.842 MB -> 90.508 MB. [2025-06-30T20:44:15.593Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:44:18.555Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:44:20.474Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:44:22.393Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:44:24.310Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:44:25.245Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:44:27.174Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:44:28.107Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:44:28.107Z] 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. [2025-06-30T20:44:28.107Z] The best model improves the baseline by 14.52%. [2025-06-30T20:44:29.040Z] Top recommended movies for user id 72: [2025-06-30T20:44:29.040Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:44:29.040Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:44:29.040Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:44:29.040Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:44:29.040Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:44:29.040Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14860.557 ms) ====== [2025-06-30T20:44:29.040Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-30T20:44:29.040Z] GC before operation: completed in 122.567 ms, heap usage 379.844 MB -> 90.489 MB. [2025-06-30T20:44:30.957Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-30T20:44:32.919Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-30T20:44:34.838Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-30T20:44:36.756Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-30T20:44:38.683Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-30T20:44:39.616Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-30T20:44:41.597Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-30T20:44:42.533Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-30T20:44:42.533Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-30T20:44:42.533Z] The best model improves the baseline by 14.52%. [2025-06-30T20:44:43.479Z] Top recommended movies for user id 72: [2025-06-30T20:44:43.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-30T20:44:43.479Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-30T20:44:43.479Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-30T20:44:43.479Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-30T20:44:43.479Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-30T20:44:43.479Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14312.990 ms) ====== [2025-06-30T20:44:43.479Z] ----------------------------------- [2025-06-30T20:44:43.479Z] renaissance-movie-lens_0_PASSED [2025-06-30T20:44:43.479Z] ----------------------------------- [2025-06-30T20:44:43.479Z] [2025-06-30T20:44:43.479Z] TEST TEARDOWN: [2025-06-30T20:44:43.479Z] Nothing to be done for teardown. [2025-06-30T20:44:43.479Z] renaissance-movie-lens_0 Finish Time: Mon Jun 30 20:44:43 2025 Epoch Time (ms): 1751316283025