[2025-11-06T06:45:12.021Z] Running test renaissance-movie-lens_0 ... [2025-11-06T06:45:12.021Z] =============================================== [2025-11-06T06:45:12.021Z] renaissance-movie-lens_0 Start Time: Thu Nov 6 06:45:11 2025 Epoch Time (ms): 1762411511892 [2025-11-06T06:45:12.021Z] variation: NoOptions [2025-11-06T06:45:12.021Z] JVM_OPTIONS: [2025-11-06T06:45:12.021Z] { \ [2025-11-06T06:45:12.021Z] echo ""; echo "TEST SETUP:"; \ [2025-11-06T06:45:12.021Z] echo "Nothing to be done for setup."; \ [2025-11-06T06:45:12.021Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../TKG/output_17624115105587/renaissance-movie-lens_0"; \ [2025-11-06T06:45:12.021Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../TKG/output_17624115105587/renaissance-movie-lens_0"; \ [2025-11-06T06:45:12.021Z] echo ""; echo "TESTING:"; \ [2025-11-06T06:45:12.021Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_rerun/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_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../TKG/output_17624115105587/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-06T06:45:12.021Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../TKG/output_17624115105587/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-06T06:45:12.021Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-06T06:45:12.021Z] echo "Nothing to be done for teardown."; \ [2025-11-06T06:45:12.021Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_rerun/aqa-tests/TKG/../TKG/output_17624115105587/TestTargetResult"; [2025-11-06T06:45:12.021Z] [2025-11-06T06:45:12.021Z] TEST SETUP: [2025-11-06T06:45:12.021Z] Nothing to be done for setup. [2025-11-06T06:45:12.021Z] [2025-11-06T06:45:12.021Z] TESTING: [2025-11-06T06:45:35.030Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-06T06:46:09.750Z] 06:46:07.120 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-11-06T06:46:18.614Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-06T06:46:21.577Z] Training: 60056, validation: 20285, test: 19854 [2025-11-06T06:46:21.577Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-06T06:46:21.907Z] GC before operation: completed in 580.177 ms, heap usage 448.215 MB -> 76.360 MB. [2025-11-06T06:46:49.640Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:47:05.494Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:47:18.680Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:47:31.770Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:47:39.010Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:47:46.265Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:47:52.154Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:47:59.399Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:48:00.536Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:48:00.536Z] The best model improves the baseline by 14.52%. [2025-11-06T06:48:01.680Z] Top recommended movies for user id 72: [2025-11-06T06:48:01.680Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:48:01.680Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:48:01.680Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:48:01.680Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:48:01.680Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:48:01.680Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (99889.819 ms) ====== [2025-11-06T06:48:01.680Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-06T06:48:02.859Z] GC before operation: completed in 1188.862 ms, heap usage 1.074 GB -> 97.959 MB. [2025-11-06T06:48:15.098Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:48:25.899Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:48:36.672Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:48:45.528Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:48:52.805Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:48:58.677Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:49:04.558Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:49:10.442Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:49:11.142Z] 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. [2025-11-06T06:49:11.142Z] The best model improves the baseline by 14.52%. [2025-11-06T06:49:11.842Z] Top recommended movies for user id 72: [2025-11-06T06:49:11.842Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:49:11.842Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:49:11.842Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:49:11.842Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:49:11.842Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:49:11.842Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (68850.300 ms) ====== [2025-11-06T06:49:11.842Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-06T06:49:13.000Z] GC before operation: completed in 919.338 ms, heap usage 568.050 MB -> 92.633 MB. [2025-11-06T06:49:23.785Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:49:32.640Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:49:43.428Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:49:52.283Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:49:57.764Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:50:03.633Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:50:10.888Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:50:15.640Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:50:16.786Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:50:16.786Z] The best model improves the baseline by 14.52%. [2025-11-06T06:50:17.937Z] Top recommended movies for user id 72: [2025-11-06T06:50:17.937Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:50:17.937Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:50:17.937Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:50:17.937Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:50:17.937Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:50:17.937Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (64996.916 ms) ====== [2025-11-06T06:50:17.937Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-06T06:50:18.657Z] GC before operation: completed in 882.937 ms, heap usage 172.993 MB -> 89.681 MB. [2025-11-06T06:50:29.432Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:50:38.293Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:50:47.140Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:50:55.992Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:51:00.723Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:51:06.597Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:51:11.322Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:51:17.203Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:51:17.905Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:51:17.905Z] The best model improves the baseline by 14.52%. [2025-11-06T06:51:18.602Z] Top recommended movies for user id 72: [2025-11-06T06:51:18.602Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:51:18.602Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:51:18.602Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:51:18.602Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:51:18.602Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:51:18.602Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (60060.773 ms) ====== [2025-11-06T06:51:18.602Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-06T06:51:19.339Z] GC before operation: completed in 763.008 ms, heap usage 644.322 MB -> 93.685 MB. [2025-11-06T06:51:30.173Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:51:39.019Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:51:49.811Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:51:57.056Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:52:02.929Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:52:07.670Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:52:13.562Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:52:19.457Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:52:20.864Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:52:20.864Z] The best model improves the baseline by 14.52%. [2025-11-06T06:52:20.864Z] Top recommended movies for user id 72: [2025-11-06T06:52:20.864Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:52:20.864Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:52:20.864Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:52:20.864Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:52:20.864Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:52:20.864Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (61452.251 ms) ====== [2025-11-06T06:52:20.864Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-06T06:52:21.588Z] GC before operation: completed in 746.397 ms, heap usage 547.667 MB -> 90.312 MB. [2025-11-06T06:52:32.378Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:52:41.238Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:52:50.093Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:52:58.950Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:53:03.676Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:53:09.620Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:53:15.499Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:53:21.366Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:53:22.065Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:53:22.065Z] The best model improves the baseline by 14.52%. [2025-11-06T06:53:23.207Z] Top recommended movies for user id 72: [2025-11-06T06:53:23.207Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:53:23.207Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:53:23.207Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:53:23.207Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:53:23.207Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:53:23.207Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (61475.388 ms) ====== [2025-11-06T06:53:23.207Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-06T06:53:23.920Z] GC before operation: completed in 622.494 ms, heap usage 141.610 MB -> 90.150 MB. [2025-11-06T06:53:34.229Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:53:43.106Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:53:51.975Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:54:00.837Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:54:06.716Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:54:12.600Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:54:18.478Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:54:24.365Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:54:25.066Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:54:25.066Z] The best model improves the baseline by 14.52%. [2025-11-06T06:54:25.775Z] Top recommended movies for user id 72: [2025-11-06T06:54:25.775Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:54:25.775Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:54:25.775Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:54:25.775Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:54:25.775Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:54:25.775Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (61922.685 ms) ====== [2025-11-06T06:54:25.775Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-06T06:54:26.492Z] GC before operation: completed in 629.336 ms, heap usage 393.249 MB -> 90.418 MB. [2025-11-06T06:54:36.190Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:54:45.055Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:54:53.926Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:55:01.170Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:55:07.059Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:55:11.924Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:55:17.832Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:55:23.713Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:55:24.851Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:55:24.851Z] The best model improves the baseline by 14.52%. [2025-11-06T06:55:25.557Z] Top recommended movies for user id 72: [2025-11-06T06:55:25.557Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:55:25.557Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:55:25.557Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:55:25.557Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:55:25.557Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:55:25.557Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (59284.854 ms) ====== [2025-11-06T06:55:25.557Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-06T06:55:26.275Z] GC before operation: completed in 610.271 ms, heap usage 155.176 MB -> 90.279 MB. [2025-11-06T06:55:36.102Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:55:43.354Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:55:52.221Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:55:59.460Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:56:04.186Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:56:08.923Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:56:14.801Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:56:19.530Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:56:19.857Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:56:19.857Z] The best model improves the baseline by 14.52%. [2025-11-06T06:56:21.012Z] Top recommended movies for user id 72: [2025-11-06T06:56:21.012Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:56:21.012Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:56:21.012Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:56:21.012Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:56:21.012Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:56:21.012Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (54662.327 ms) ====== [2025-11-06T06:56:21.012Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-06T06:56:21.342Z] GC before operation: completed in 627.094 ms, heap usage 244.341 MB -> 90.312 MB. [2025-11-06T06:56:31.099Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:56:38.341Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:56:47.204Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:56:54.441Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:56:59.162Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:57:05.034Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:57:09.756Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:57:14.492Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:57:15.193Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:57:15.193Z] The best model improves the baseline by 14.52%. [2025-11-06T06:57:15.892Z] Top recommended movies for user id 72: [2025-11-06T06:57:15.892Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:57:15.892Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:57:15.892Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:57:15.892Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:57:15.892Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:57:15.892Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (54398.160 ms) ====== [2025-11-06T06:57:15.892Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-06T06:57:16.613Z] GC before operation: completed in 675.586 ms, heap usage 808.665 MB -> 94.590 MB. [2025-11-06T06:57:25.471Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:57:33.993Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:57:41.241Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:57:50.094Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:57:53.860Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:57:59.755Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:58:04.482Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:58:09.221Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:58:09.922Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:58:10.247Z] The best model improves the baseline by 14.52%. [2025-11-06T06:58:10.963Z] Top recommended movies for user id 72: [2025-11-06T06:58:10.963Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:58:10.963Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:58:10.963Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:58:10.963Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:58:10.963Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:58:10.963Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (54250.526 ms) ====== [2025-11-06T06:58:10.963Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-06T06:58:11.666Z] GC before operation: completed in 635.704 ms, heap usage 336.175 MB -> 90.505 MB. [2025-11-06T06:58:20.520Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:58:28.661Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:58:35.906Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:58:44.765Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:58:48.526Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:58:53.255Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:58:59.136Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:59:03.861Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T06:59:04.188Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T06:59:04.515Z] The best model improves the baseline by 14.52%. [2025-11-06T06:59:05.239Z] Top recommended movies for user id 72: [2025-11-06T06:59:05.239Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T06:59:05.239Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T06:59:05.239Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T06:59:05.239Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T06:59:05.239Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T06:59:05.239Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (53616.231 ms) ====== [2025-11-06T06:59:05.239Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-06T06:59:05.948Z] GC before operation: completed in 657.948 ms, heap usage 462.225 MB -> 90.850 MB. [2025-11-06T06:59:14.806Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T06:59:22.043Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T06:59:31.820Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T06:59:39.055Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T06:59:43.795Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T06:59:49.705Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T06:59:54.434Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T06:59:59.172Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T07:00:00.316Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T07:00:00.641Z] The best model improves the baseline by 14.52%. [2025-11-06T07:00:00.966Z] Top recommended movies for user id 72: [2025-11-06T07:00:00.966Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T07:00:00.966Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T07:00:00.966Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T07:00:00.966Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T07:00:00.966Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T07:00:00.966Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (55367.816 ms) ====== [2025-11-06T07:00:00.966Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-06T07:00:01.724Z] GC before operation: completed in 664.636 ms, heap usage 503.888 MB -> 91.074 MB. [2025-11-06T07:00:10.667Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T07:00:19.538Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T07:00:27.239Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T07:00:34.482Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T07:00:40.366Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T07:00:45.092Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T07:00:49.818Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T07:00:54.546Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T07:00:55.690Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T07:00:56.016Z] The best model improves the baseline by 14.52%. [2025-11-06T07:00:56.341Z] Top recommended movies for user id 72: [2025-11-06T07:00:56.341Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T07:00:56.341Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T07:00:56.341Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T07:00:56.341Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T07:00:56.341Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T07:00:56.341Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (54701.343 ms) ====== [2025-11-06T07:00:56.341Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-06T07:00:57.084Z] GC before operation: completed in 668.902 ms, heap usage 508.036 MB -> 90.916 MB. [2025-11-06T07:01:05.947Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T07:01:14.803Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T07:01:22.041Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T07:01:30.649Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T07:01:35.376Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T07:01:41.256Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T07:01:45.984Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T07:01:51.867Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T07:01:52.202Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T07:01:52.543Z] The best model improves the baseline by 14.52%. [2025-11-06T07:01:53.246Z] Top recommended movies for user id 72: [2025-11-06T07:01:53.246Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T07:01:53.246Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T07:01:53.246Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T07:01:53.246Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T07:01:53.246Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T07:01:53.246Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (56098.592 ms) ====== [2025-11-06T07:01:53.246Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-06T07:01:53.966Z] GC before operation: completed in 639.667 ms, heap usage 300.144 MB -> 90.877 MB. [2025-11-06T07:02:02.821Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T07:02:11.695Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T07:02:20.554Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T07:02:29.260Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T07:02:33.989Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T07:02:38.725Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T07:02:45.990Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T07:02:50.718Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T07:02:51.049Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T07:02:51.377Z] The best model improves the baseline by 14.52%. [2025-11-06T07:02:52.094Z] Top recommended movies for user id 72: [2025-11-06T07:02:52.094Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T07:02:52.094Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T07:02:52.094Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T07:02:52.094Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T07:02:52.094Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T07:02:52.094Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (58054.671 ms) ====== [2025-11-06T07:02:52.094Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-06T07:02:52.427Z] GC before operation: completed in 648.903 ms, heap usage 430.447 MB -> 90.818 MB. [2025-11-06T07:03:01.300Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T07:03:10.195Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T07:03:19.074Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T07:03:27.265Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T07:03:33.150Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T07:03:37.928Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T07:03:43.802Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T07:03:48.526Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T07:03:49.669Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T07:03:49.669Z] The best model improves the baseline by 14.52%. [2025-11-06T07:03:49.994Z] Top recommended movies for user id 72: [2025-11-06T07:03:49.994Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T07:03:49.994Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T07:03:49.994Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T07:03:49.994Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T07:03:49.994Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T07:03:49.994Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (57537.033 ms) ====== [2025-11-06T07:03:49.994Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-06T07:03:50.717Z] GC before operation: completed in 640.830 ms, heap usage 422.882 MB -> 90.908 MB. [2025-11-06T07:03:59.573Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T07:04:08.427Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T07:04:15.663Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T07:04:22.887Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T07:04:28.974Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T07:04:33.692Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T07:04:38.415Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T07:04:43.143Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T07:04:43.845Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T07:04:44.172Z] The best model improves the baseline by 14.52%. [2025-11-06T07:04:44.873Z] Top recommended movies for user id 72: [2025-11-06T07:04:44.873Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T07:04:44.873Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T07:04:44.873Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T07:04:44.873Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T07:04:44.873Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T07:04:44.873Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (54052.612 ms) ====== [2025-11-06T07:04:44.873Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-06T07:04:45.598Z] GC before operation: completed in 667.202 ms, heap usage 207.247 MB -> 90.513 MB. [2025-11-06T07:04:54.450Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T07:05:01.684Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T07:05:10.579Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T07:05:17.833Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T07:05:22.507Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T07:05:27.405Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T07:05:32.139Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T07:05:38.037Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T07:05:38.037Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T07:05:38.366Z] The best model improves the baseline by 14.52%. [2025-11-06T07:05:39.081Z] Top recommended movies for user id 72: [2025-11-06T07:05:39.081Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T07:05:39.081Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T07:05:39.081Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T07:05:39.081Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T07:05:39.081Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T07:05:39.081Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (53409.516 ms) ====== [2025-11-06T07:05:39.081Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-06T07:05:39.412Z] GC before operation: completed in 671.149 ms, heap usage 274.414 MB -> 90.737 MB. [2025-11-06T07:05:48.286Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T07:05:55.520Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T07:06:04.378Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T07:06:11.631Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T07:06:16.375Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T07:06:21.983Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T07:06:26.718Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T07:06:31.464Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T07:06:31.464Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T07:06:31.791Z] The best model improves the baseline by 14.52%. [2025-11-06T07:06:32.495Z] Top recommended movies for user id 72: [2025-11-06T07:06:32.495Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T07:06:32.495Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T07:06:32.495Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T07:06:32.495Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T07:06:32.495Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T07:06:32.495Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (52868.525 ms) ====== [2025-11-06T07:06:36.270Z] ----------------------------------- [2025-11-06T07:06:36.270Z] renaissance-movie-lens_0_PASSED [2025-11-06T07:06:36.270Z] ----------------------------------- [2025-11-06T07:06:36.270Z] [2025-11-06T07:06:36.270Z] TEST TEARDOWN: [2025-11-06T07:06:36.270Z] Nothing to be done for teardown. [2025-11-06T07:06:36.624Z] renaissance-movie-lens_0 Finish Time: Thu Nov 6 07:06:36 2025 Epoch Time (ms): 1762412796270