[2025-11-06T01:09:27.897Z] Running test renaissance-movie-lens_0 ... [2025-11-06T01:09:27.897Z] =============================================== [2025-11-06T01:09:27.897Z] renaissance-movie-lens_0 Start Time: Thu Nov 6 01:09:26 2025 Epoch Time (ms): 1762391366633 [2025-11-06T01:09:27.897Z] variation: NoOptions [2025-11-06T01:09:27.897Z] JVM_OPTIONS: [2025-11-06T01:09:27.897Z] { \ [2025-11-06T01:09:27.897Z] echo ""; echo "TEST SETUP:"; \ [2025-11-06T01:09:27.897Z] echo "Nothing to be done for setup."; \ [2025-11-06T01:09:27.897Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623897934879/renaissance-movie-lens_0"; \ [2025-11-06T01:09:27.897Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623897934879/renaissance-movie-lens_0"; \ [2025-11-06T01:09:27.897Z] echo ""; echo "TESTING:"; \ [2025-11-06T01:09:27.897Z] "/home/jenkins/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623897934879/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-06T01:09:27.898Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623897934879/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-06T01:09:27.898Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-06T01:09:27.898Z] echo "Nothing to be done for teardown."; \ [2025-11-06T01:09:27.898Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17623897934879/TestTargetResult"; [2025-11-06T01:09:27.898Z] [2025-11-06T01:09:27.898Z] TEST SETUP: [2025-11-06T01:09:27.898Z] Nothing to be done for setup. [2025-11-06T01:09:27.898Z] [2025-11-06T01:09:27.898Z] TESTING: [2025-11-06T01:09:33.332Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-06T01:09:41.543Z] 01:09:41.073 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-11-06T01:09:43.529Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-06T01:09:44.491Z] Training: 60056, validation: 20285, test: 19854 [2025-11-06T01:09:44.491Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-06T01:09:44.491Z] GC before operation: completed in 179.113 ms, heap usage 164.014 MB -> 74.400 MB. [2025-11-06T01:09:49.926Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:09:54.119Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:09:58.308Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:10:01.368Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:10:03.360Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:10:05.437Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:10:07.408Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:10:10.463Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:10:10.463Z] 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. [2025-11-06T01:10:10.463Z] The best model improves the baseline by 14.52%. [2025-11-06T01:10:10.463Z] Top recommended movies for user id 72: [2025-11-06T01:10:10.463Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:10:10.463Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:10:10.463Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:10:10.463Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:10:10.463Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:10:10.463Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (25916.682 ms) ====== [2025-11-06T01:10:10.463Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-06T01:10:10.463Z] GC before operation: completed in 187.844 ms, heap usage 191.002 MB -> 85.390 MB. [2025-11-06T01:10:13.508Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:10:16.551Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:10:19.608Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:10:22.292Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:10:24.266Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:10:26.241Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:10:28.216Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:10:30.198Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:10:30.198Z] 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. [2025-11-06T01:10:30.198Z] The best model improves the baseline by 14.52%. [2025-11-06T01:10:30.198Z] Top recommended movies for user id 72: [2025-11-06T01:10:30.198Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:10:30.198Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:10:30.198Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:10:30.198Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:10:30.198Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:10:30.198Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (19789.223 ms) ====== [2025-11-06T01:10:30.198Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-06T01:10:31.161Z] GC before operation: completed in 168.436 ms, heap usage 289.712 MB -> 87.640 MB. [2025-11-06T01:10:34.207Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:10:37.254Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:10:40.300Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:10:43.347Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:10:45.322Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:10:47.307Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:10:49.282Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:10:51.259Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:10:51.259Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T01:10:52.225Z] The best model improves the baseline by 14.52%. [2025-11-06T01:10:52.225Z] Top recommended movies for user id 72: [2025-11-06T01:10:52.225Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:10:52.225Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:10:52.225Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:10:52.225Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:10:52.225Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:10:52.225Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21234.321 ms) ====== [2025-11-06T01:10:52.225Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-06T01:10:52.225Z] GC before operation: completed in 180.003 ms, heap usage 240.923 MB -> 88.132 MB. [2025-11-06T01:10:55.278Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:10:58.329Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:11:01.378Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:11:04.424Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:11:06.451Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:11:08.428Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:11:10.404Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:11:12.380Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:11:12.380Z] 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. [2025-11-06T01:11:12.380Z] The best model improves the baseline by 14.52%. [2025-11-06T01:11:12.381Z] Top recommended movies for user id 72: [2025-11-06T01:11:12.381Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:11:12.381Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:11:12.381Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:11:12.381Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:11:12.381Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:11:12.381Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20609.908 ms) ====== [2025-11-06T01:11:12.381Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-06T01:11:13.345Z] GC before operation: completed in 189.502 ms, heap usage 438.441 MB -> 88.651 MB. [2025-11-06T01:11:16.397Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:11:19.469Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:11:23.230Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:11:25.206Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:11:27.187Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:11:29.165Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:11:31.140Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:11:33.114Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:11:33.114Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-06T01:11:33.114Z] The best model improves the baseline by 14.52%. [2025-11-06T01:11:34.077Z] Top recommended movies for user id 72: [2025-11-06T01:11:34.077Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:11:34.077Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:11:34.077Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:11:34.077Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:11:34.077Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:11:34.077Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20744.360 ms) ====== [2025-11-06T01:11:34.077Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-06T01:11:34.077Z] GC before operation: completed in 181.361 ms, heap usage 222.301 MB -> 88.343 MB. [2025-11-06T01:11:37.125Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:11:40.174Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:11:43.225Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:11:46.279Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:11:48.252Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:11:50.226Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:11:51.188Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:11:53.164Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:11:54.127Z] 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. [2025-11-06T01:11:54.127Z] The best model improves the baseline by 14.52%. [2025-11-06T01:11:54.127Z] Top recommended movies for user id 72: [2025-11-06T01:11:54.127Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:11:54.127Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:11:54.127Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:11:54.127Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:11:54.127Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:11:54.127Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20124.621 ms) ====== [2025-11-06T01:11:54.127Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-06T01:11:54.127Z] GC before operation: completed in 195.209 ms, heap usage 138.114 MB -> 88.573 MB. [2025-11-06T01:11:57.175Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:12:00.224Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:12:03.287Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:12:06.380Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:12:07.354Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:12:09.333Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:12:11.308Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:12:13.285Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:12:13.285Z] 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. [2025-11-06T01:12:13.285Z] The best model improves the baseline by 14.52%. [2025-11-06T01:12:14.249Z] Top recommended movies for user id 72: [2025-11-06T01:12:14.249Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:12:14.249Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:12:14.249Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:12:14.249Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:12:14.249Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:12:14.249Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19622.226 ms) ====== [2025-11-06T01:12:14.249Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-06T01:12:14.249Z] GC before operation: completed in 188.541 ms, heap usage 95.467 MB -> 88.614 MB. [2025-11-06T01:12:17.310Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:12:20.357Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:12:23.764Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:12:26.097Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:12:28.071Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:12:29.034Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:12:31.009Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:12:32.985Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:12:32.985Z] 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. [2025-11-06T01:12:32.985Z] The best model improves the baseline by 14.52%. [2025-11-06T01:12:33.956Z] Top recommended movies for user id 72: [2025-11-06T01:12:33.956Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:12:33.956Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:12:33.956Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:12:33.956Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:12:33.956Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:12:33.956Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (19534.478 ms) ====== [2025-11-06T01:12:33.956Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-06T01:12:33.956Z] GC before operation: completed in 194.377 ms, heap usage 388.104 MB -> 89.057 MB. [2025-11-06T01:12:37.009Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:12:38.984Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:12:42.032Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:12:45.079Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:12:47.059Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:12:49.037Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:12:50.000Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:12:51.973Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:12:51.973Z] 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. [2025-11-06T01:12:51.973Z] The best model improves the baseline by 14.52%. [2025-11-06T01:12:52.935Z] Top recommended movies for user id 72: [2025-11-06T01:12:52.935Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:12:52.935Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:12:52.935Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:12:52.935Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:12:52.935Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:12:52.935Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18834.145 ms) ====== [2025-11-06T01:12:52.935Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-06T01:12:52.935Z] GC before operation: completed in 200.617 ms, heap usage 354.858 MB -> 88.823 MB. [2025-11-06T01:12:55.980Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:12:59.062Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:13:02.135Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:13:05.249Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:13:06.212Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:13:08.196Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:13:10.171Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:13:12.184Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:13:12.184Z] 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. [2025-11-06T01:13:13.148Z] The best model improves the baseline by 14.52%. [2025-11-06T01:13:13.148Z] Top recommended movies for user id 72: [2025-11-06T01:13:13.148Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:13:13.148Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:13:13.148Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:13:13.148Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:13:13.148Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:13:13.148Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20131.817 ms) ====== [2025-11-06T01:13:13.148Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-06T01:13:13.148Z] GC before operation: completed in 168.179 ms, heap usage 121.317 MB -> 88.769 MB. [2025-11-06T01:13:16.197Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:13:18.349Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:13:21.395Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:13:24.471Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:13:26.864Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:13:27.827Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:13:29.865Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:13:30.828Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:13:30.828Z] 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. [2025-11-06T01:13:30.828Z] The best model improves the baseline by 14.52%. [2025-11-06T01:13:31.789Z] Top recommended movies for user id 72: [2025-11-06T01:13:31.789Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:13:31.789Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:13:31.789Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:13:31.789Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:13:31.789Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:13:31.789Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18395.770 ms) ====== [2025-11-06T01:13:31.789Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-06T01:13:31.789Z] GC before operation: completed in 166.989 ms, heap usage 416.384 MB -> 88.837 MB. [2025-11-06T01:13:34.836Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:13:37.883Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:13:40.929Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:13:42.911Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:13:44.891Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:13:46.863Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:13:48.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:13:49.800Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:13:50.765Z] 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. [2025-11-06T01:13:50.765Z] The best model improves the baseline by 14.52%. [2025-11-06T01:13:50.765Z] Top recommended movies for user id 72: [2025-11-06T01:13:50.765Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:13:50.765Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:13:50.765Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:13:50.765Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:13:50.765Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:13:50.765Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19087.445 ms) ====== [2025-11-06T01:13:50.765Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-06T01:13:50.765Z] GC before operation: completed in 189.125 ms, heap usage 392.312 MB -> 89.046 MB. [2025-11-06T01:13:53.827Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:13:56.874Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:13:59.924Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:14:03.008Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:14:03.997Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:14:06.104Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:14:08.094Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:14:10.068Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:14:10.068Z] 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. [2025-11-06T01:14:10.068Z] The best model improves the baseline by 14.52%. [2025-11-06T01:14:10.068Z] Top recommended movies for user id 72: [2025-11-06T01:14:10.068Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:14:10.068Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:14:10.068Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:14:10.068Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:14:10.068Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:14:10.068Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (19552.349 ms) ====== [2025-11-06T01:14:10.068Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-06T01:14:11.043Z] GC before operation: completed in 209.466 ms, heap usage 447.572 MB -> 89.232 MB. [2025-11-06T01:14:13.023Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:14:16.076Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:14:19.137Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:14:22.191Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:14:24.167Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:14:26.139Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:14:27.811Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:14:28.784Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:14:29.750Z] 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. [2025-11-06T01:14:29.750Z] The best model improves the baseline by 14.52%. [2025-11-06T01:14:29.750Z] Top recommended movies for user id 72: [2025-11-06T01:14:29.750Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:14:29.750Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:14:29.750Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:14:29.750Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:14:29.750Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:14:29.750Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19108.097 ms) ====== [2025-11-06T01:14:29.750Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-06T01:14:29.750Z] GC before operation: completed in 182.605 ms, heap usage 355.932 MB -> 88.861 MB. [2025-11-06T01:14:32.806Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:14:35.870Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:14:38.919Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:14:41.963Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:14:43.940Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:14:44.910Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:14:46.885Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:14:48.867Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:14:48.867Z] 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. [2025-11-06T01:14:48.867Z] The best model improves the baseline by 14.52%. [2025-11-06T01:14:48.867Z] Top recommended movies for user id 72: [2025-11-06T01:14:48.867Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:14:48.867Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:14:48.867Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:14:48.867Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:14:48.867Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:14:48.867Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19168.155 ms) ====== [2025-11-06T01:14:48.867Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-06T01:14:48.867Z] GC before operation: completed in 167.964 ms, heap usage 469.657 MB -> 89.333 MB. [2025-11-06T01:14:51.916Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:14:54.963Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:14:58.007Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:14:59.982Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:15:01.957Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:15:03.948Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:15:06.090Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:15:07.051Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:15:07.051Z] 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. [2025-11-06T01:15:08.011Z] The best model improves the baseline by 14.52%. [2025-11-06T01:15:08.011Z] Top recommended movies for user id 72: [2025-11-06T01:15:08.011Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:15:08.011Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:15:08.011Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:15:08.011Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:15:08.011Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:15:08.011Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18435.808 ms) ====== [2025-11-06T01:15:08.011Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-06T01:15:08.011Z] GC before operation: completed in 172.349 ms, heap usage 472.635 MB -> 89.176 MB. [2025-11-06T01:15:11.053Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:15:14.097Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:15:17.179Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:15:19.153Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:15:21.129Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:15:23.127Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:15:25.102Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:15:26.063Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:15:27.024Z] 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. [2025-11-06T01:15:27.024Z] The best model improves the baseline by 14.52%. [2025-11-06T01:15:27.024Z] Top recommended movies for user id 72: [2025-11-06T01:15:27.024Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:15:27.024Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:15:27.024Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:15:27.024Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:15:27.024Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:15:27.024Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18966.619 ms) ====== [2025-11-06T01:15:27.024Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-06T01:15:27.024Z] GC before operation: completed in 160.823 ms, heap usage 396.065 MB -> 89.163 MB. [2025-11-06T01:15:30.425Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:15:32.399Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:15:35.446Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:15:38.495Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:15:40.478Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:15:42.449Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:15:44.428Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:15:45.391Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:15:46.357Z] 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. [2025-11-06T01:15:46.357Z] The best model improves the baseline by 14.52%. [2025-11-06T01:15:46.357Z] Top recommended movies for user id 72: [2025-11-06T01:15:46.357Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:15:46.357Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:15:46.357Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:15:46.357Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:15:46.357Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:15:46.357Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19246.630 ms) ====== [2025-11-06T01:15:46.357Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-06T01:15:46.357Z] GC before operation: completed in 173.196 ms, heap usage 254.838 MB -> 88.804 MB. [2025-11-06T01:15:49.400Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:15:52.470Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:15:55.516Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:15:57.489Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:15:59.464Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:16:01.442Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:16:02.403Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:16:04.382Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:16:05.446Z] 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. [2025-11-06T01:16:05.446Z] The best model improves the baseline by 14.52%. [2025-11-06T01:16:05.446Z] Top recommended movies for user id 72: [2025-11-06T01:16:05.446Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:16:05.446Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:16:05.446Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:16:05.446Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:16:05.446Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:16:05.446Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18622.956 ms) ====== [2025-11-06T01:16:05.446Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-06T01:16:05.446Z] GC before operation: completed in 164.128 ms, heap usage 394.254 MB -> 89.102 MB. [2025-11-06T01:16:08.498Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T01:16:11.545Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T01:16:13.530Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T01:16:16.585Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T01:16:18.560Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T01:16:20.536Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T01:16:22.509Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T01:16:23.472Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T01:16:24.433Z] 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. [2025-11-06T01:16:24.433Z] The best model improves the baseline by 14.52%. [2025-11-06T01:16:24.433Z] Top recommended movies for user id 72: [2025-11-06T01:16:24.433Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-06T01:16:24.433Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-06T01:16:24.433Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-06T01:16:24.433Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-06T01:16:24.433Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-06T01:16:24.433Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19257.011 ms) ====== [2025-11-06T01:16:25.395Z] ----------------------------------- [2025-11-06T01:16:25.395Z] renaissance-movie-lens_0_PASSED [2025-11-06T01:16:25.395Z] ----------------------------------- [2025-11-06T01:16:25.395Z] [2025-11-06T01:16:25.395Z] TEST TEARDOWN: [2025-11-06T01:16:25.395Z] Nothing to be done for teardown. [2025-11-06T01:16:25.395Z] renaissance-movie-lens_0 Finish Time: Thu Nov 6 01:16:24 2025 Epoch Time (ms): 1762391784546