[2025-12-03T22:12:23.383Z] Running test renaissance-movie-lens_0 ... [2025-12-03T22:12:23.383Z] =============================================== [2025-12-03T22:12:23.383Z] renaissance-movie-lens_0 Start Time: Wed Dec 3 17:12:23 2025 Epoch Time (ms): 1764799943239 [2025-12-03T22:12:23.383Z] variation: NoOptions [2025-12-03T22:12:23.383Z] JVM_OPTIONS: [2025-12-03T22:12:23.383Z] { \ [2025-12-03T22:12:23.383Z] echo ""; echo "TEST SETUP:"; \ [2025-12-03T22:12:23.383Z] echo "Nothing to be done for setup."; \ [2025-12-03T22:12:23.383Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17647992112327/renaissance-movie-lens_0"; \ [2025-12-03T22:12:23.383Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17647992112327/renaissance-movie-lens_0"; \ [2025-12-03T22:12:23.383Z] echo ""; echo "TESTING:"; \ [2025-12-03T22:12:23.383Z] "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//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 "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17647992112327/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-03T22:12:23.383Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17647992112327/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-03T22:12:23.383Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-03T22:12:23.383Z] echo "Nothing to be done for teardown."; \ [2025-12-03T22:12:23.383Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17647992112327/TestTargetResult"; [2025-12-03T22:12:23.383Z] [2025-12-03T22:12:23.383Z] TEST SETUP: [2025-12-03T22:12:23.383Z] Nothing to be done for setup. [2025-12-03T22:12:23.383Z] [2025-12-03T22:12:23.383Z] TESTING: [2025-12-03T22:12:27.618Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-03T22:12:31.637Z] 17:12:31.187 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. [2025-12-03T22:12:32.902Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-03T22:12:32.902Z] Training: 60056, validation: 20285, test: 19854 [2025-12-03T22:12:32.902Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-03T22:12:32.902Z] GC before operation: completed in 55.110 ms, heap usage 262.479 MB -> 75.885 MB. [2025-12-03T22:12:36.006Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:12:37.912Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:12:39.691Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:12:40.910Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:12:41.669Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:12:42.924Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:12:44.184Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:12:44.957Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:12:44.957Z] 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. [2025-12-03T22:12:44.957Z] The best model improves the baseline by 14.52%. [2025-12-03T22:12:45.340Z] Top recommended movies for user id 72: [2025-12-03T22:12:45.341Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:12:45.341Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:12:45.341Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:12:45.341Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:12:45.341Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:12:45.341Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (12347.689 ms) ====== [2025-12-03T22:12:45.341Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-03T22:12:45.341Z] GC before operation: completed in 78.864 ms, heap usage 238.209 MB -> 93.456 MB. [2025-12-03T22:12:47.748Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:12:49.007Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:12:51.484Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:12:53.251Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:12:54.018Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:12:55.240Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:12:56.496Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:12:57.811Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:12:57.811Z] 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. [2025-12-03T22:12:57.811Z] The best model improves the baseline by 14.52%. [2025-12-03T22:12:57.811Z] Top recommended movies for user id 72: [2025-12-03T22:12:57.811Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:12:57.811Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:12:57.811Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:12:57.811Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:12:57.811Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:12:57.811Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (12446.728 ms) ====== [2025-12-03T22:12:57.811Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-03T22:12:57.811Z] GC before operation: completed in 66.493 ms, heap usage 216.937 MB -> 92.432 MB. [2025-12-03T22:12:59.622Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:13:01.429Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:13:03.275Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:13:05.091Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:13:05.880Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:13:07.142Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:13:07.920Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:13:08.725Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:13:08.725Z] 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. [2025-12-03T22:13:08.725Z] The best model improves the baseline by 14.52%. [2025-12-03T22:13:08.725Z] Top recommended movies for user id 72: [2025-12-03T22:13:08.725Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:13:08.725Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:13:08.725Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:13:08.725Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:13:08.725Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:13:08.725Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (11007.926 ms) ====== [2025-12-03T22:13:08.725Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-03T22:13:08.725Z] GC before operation: completed in 57.611 ms, heap usage 166.111 MB -> 89.373 MB. [2025-12-03T22:13:10.521Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:13:11.794Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:13:13.590Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:13:14.809Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:13:16.037Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:13:16.795Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:13:18.054Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:13:18.841Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:13:18.841Z] 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. [2025-12-03T22:13:18.841Z] The best model improves the baseline by 14.52%. [2025-12-03T22:13:18.841Z] Top recommended movies for user id 72: [2025-12-03T22:13:18.841Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:13:18.841Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:13:18.841Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:13:18.841Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:13:18.841Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:13:18.841Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (10029.744 ms) ====== [2025-12-03T22:13:18.841Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-03T22:13:18.841Z] GC before operation: completed in 84.384 ms, heap usage 228.980 MB -> 89.692 MB. [2025-12-03T22:13:20.648Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:13:22.430Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:13:24.241Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:13:26.072Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:13:26.845Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:13:27.610Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:13:28.848Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:13:29.612Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:13:29.612Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:13:29.612Z] The best model improves the baseline by 14.52%. [2025-12-03T22:13:29.976Z] Top recommended movies for user id 72: [2025-12-03T22:13:29.976Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:13:29.976Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:13:29.976Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:13:29.976Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:13:29.976Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:13:29.976Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (10853.990 ms) ====== [2025-12-03T22:13:29.976Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-03T22:13:29.976Z] GC before operation: completed in 53.378 ms, heap usage 133.109 MB -> 91.154 MB. [2025-12-03T22:13:31.743Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:13:33.511Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:13:35.312Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:13:37.112Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:13:37.892Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:13:39.124Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:13:40.344Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:13:41.103Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:13:41.479Z] 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. [2025-12-03T22:13:41.479Z] The best model improves the baseline by 14.52%. [2025-12-03T22:13:41.479Z] Top recommended movies for user id 72: [2025-12-03T22:13:41.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:13:41.479Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:13:41.479Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:13:41.479Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:13:41.479Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:13:41.479Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (11579.657 ms) ====== [2025-12-03T22:13:41.479Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-03T22:13:41.479Z] GC before operation: completed in 79.010 ms, heap usage 264.671 MB -> 90.097 MB. [2025-12-03T22:13:43.361Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:13:45.147Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:13:46.956Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:13:48.206Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:13:49.418Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:13:50.646Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:13:51.409Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:13:52.621Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:13:52.621Z] 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. [2025-12-03T22:13:52.621Z] The best model improves the baseline by 14.52%. [2025-12-03T22:13:52.972Z] Top recommended movies for user id 72: [2025-12-03T22:13:52.972Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:13:52.972Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:13:52.972Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:13:52.972Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:13:52.972Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:13:52.972Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (11231.494 ms) ====== [2025-12-03T22:13:52.972Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-03T22:13:52.972Z] GC before operation: completed in 74.365 ms, heap usage 177.510 MB -> 89.932 MB. [2025-12-03T22:13:54.762Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:13:56.008Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:13:57.837Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:13:59.653Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:14:00.977Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:14:01.761Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:14:03.060Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:14:04.334Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:14:04.334Z] 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. [2025-12-03T22:14:04.334Z] The best model improves the baseline by 14.52%. [2025-12-03T22:14:04.334Z] Top recommended movies for user id 72: [2025-12-03T22:14:04.334Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:14:04.334Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:14:04.334Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:14:04.334Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:14:04.334Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:14:04.334Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (11568.907 ms) ====== [2025-12-03T22:14:04.334Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-03T22:14:04.700Z] GC before operation: completed in 69.249 ms, heap usage 158.661 MB -> 90.131 MB. [2025-12-03T22:14:06.533Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:14:07.780Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:14:09.581Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:14:11.375Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:14:12.162Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:14:13.478Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:14:14.271Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:14:15.573Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:14:15.573Z] 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. [2025-12-03T22:14:15.573Z] The best model improves the baseline by 14.52%. [2025-12-03T22:14:15.573Z] Top recommended movies for user id 72: [2025-12-03T22:14:15.573Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:14:15.573Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:14:15.573Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:14:15.573Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:14:15.573Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:14:15.573Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (11172.122 ms) ====== [2025-12-03T22:14:15.573Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-03T22:14:15.925Z] GC before operation: completed in 63.900 ms, heap usage 538.077 MB -> 93.695 MB. [2025-12-03T22:14:17.703Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:14:19.698Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:14:21.505Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:14:23.301Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:14:24.058Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:14:25.353Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:14:26.145Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:14:26.911Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:14:27.265Z] 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. [2025-12-03T22:14:27.265Z] The best model improves the baseline by 14.52%. [2025-12-03T22:14:27.265Z] Top recommended movies for user id 72: [2025-12-03T22:14:27.265Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:14:27.265Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:14:27.265Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:14:27.265Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:14:27.265Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:14:27.265Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (11510.523 ms) ====== [2025-12-03T22:14:27.265Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-03T22:14:27.265Z] GC before operation: completed in 72.457 ms, heap usage 603.038 MB -> 94.046 MB. [2025-12-03T22:14:29.034Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:14:30.834Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:14:32.065Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:14:33.822Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:14:34.614Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:14:35.407Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:14:36.662Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:14:37.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:14:37.437Z] 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. [2025-12-03T22:14:37.437Z] The best model improves the baseline by 14.52%. [2025-12-03T22:14:37.811Z] Top recommended movies for user id 72: [2025-12-03T22:14:37.811Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:14:37.811Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:14:37.811Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:14:37.811Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:14:37.811Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:14:37.811Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (10326.660 ms) ====== [2025-12-03T22:14:37.811Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-03T22:14:37.811Z] GC before operation: completed in 81.353 ms, heap usage 475.998 MB -> 90.349 MB. [2025-12-03T22:14:39.616Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:14:40.908Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:14:42.753Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:14:44.036Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:14:45.318Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:14:46.101Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:14:46.907Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:14:47.694Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:14:48.079Z] 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. [2025-12-03T22:14:48.079Z] The best model improves the baseline by 14.52%. [2025-12-03T22:14:48.079Z] Top recommended movies for user id 72: [2025-12-03T22:14:48.079Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:14:48.079Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:14:48.079Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:14:48.079Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:14:48.079Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:14:48.079Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (10300.801 ms) ====== [2025-12-03T22:14:48.079Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-03T22:14:48.079Z] GC before operation: completed in 70.168 ms, heap usage 238.936 MB -> 90.139 MB. [2025-12-03T22:14:49.985Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:14:51.288Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:14:53.062Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:14:54.906Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:14:55.746Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:14:56.530Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:14:57.305Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:14:58.332Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:14:58.695Z] 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. [2025-12-03T22:14:58.695Z] The best model improves the baseline by 14.52%. [2025-12-03T22:14:58.695Z] Top recommended movies for user id 72: [2025-12-03T22:14:58.695Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:14:58.695Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:14:58.695Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:14:58.695Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:14:58.695Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:14:58.695Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (10486.085 ms) ====== [2025-12-03T22:14:58.695Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-03T22:14:58.695Z] GC before operation: completed in 75.481 ms, heap usage 293.665 MB -> 94.872 MB. [2025-12-03T22:15:00.486Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:15:01.769Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:15:03.595Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:15:05.062Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:15:05.812Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:15:06.612Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:15:07.869Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:15:08.642Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:15:08.642Z] 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. [2025-12-03T22:15:08.642Z] The best model improves the baseline by 14.52%. [2025-12-03T22:15:08.642Z] Top recommended movies for user id 72: [2025-12-03T22:15:08.642Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:15:08.642Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:15:08.642Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:15:08.642Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:15:08.642Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:15:08.642Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (10106.397 ms) ====== [2025-12-03T22:15:08.642Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-03T22:15:08.996Z] GC before operation: completed in 71.589 ms, heap usage 500.282 MB -> 92.884 MB. [2025-12-03T22:15:10.786Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:15:12.028Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:15:13.884Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:15:15.118Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:15:15.896Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:15:17.164Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:15:17.972Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:15:18.747Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:15:19.110Z] 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. [2025-12-03T22:15:19.110Z] The best model improves the baseline by 14.52%. [2025-12-03T22:15:19.110Z] Top recommended movies for user id 72: [2025-12-03T22:15:19.110Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:15:19.110Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:15:19.110Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:15:19.110Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:15:19.110Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:15:19.110Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (10202.598 ms) ====== [2025-12-03T22:15:19.110Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-03T22:15:19.110Z] GC before operation: completed in 80.389 ms, heap usage 294.156 MB -> 92.699 MB. [2025-12-03T22:15:20.876Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:15:22.105Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:15:23.868Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:15:25.100Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:15:26.337Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:15:27.098Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:15:28.338Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:15:29.098Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:15:29.098Z] 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. [2025-12-03T22:15:29.098Z] The best model improves the baseline by 14.52%. [2025-12-03T22:15:29.098Z] Top recommended movies for user id 72: [2025-12-03T22:15:29.098Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:15:29.098Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:15:29.098Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:15:29.098Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:15:29.098Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:15:29.098Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (10085.653 ms) ====== [2025-12-03T22:15:29.098Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-03T22:15:29.449Z] GC before operation: completed in 77.581 ms, heap usage 274.550 MB -> 90.209 MB. [2025-12-03T22:15:30.688Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:15:32.458Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:15:34.273Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:15:35.529Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:15:36.762Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:15:37.549Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:15:38.802Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:15:39.610Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:15:39.610Z] 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. [2025-12-03T22:15:39.610Z] The best model improves the baseline by 14.52%. [2025-12-03T22:15:39.610Z] Top recommended movies for user id 72: [2025-12-03T22:15:39.610Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:15:39.610Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:15:39.610Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:15:39.610Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:15:39.610Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:15:39.610Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (10444.751 ms) ====== [2025-12-03T22:15:39.610Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-03T22:15:39.966Z] GC before operation: completed in 59.493 ms, heap usage 158.881 MB -> 90.268 MB. [2025-12-03T22:15:41.794Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:15:43.058Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:15:44.851Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:15:46.106Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:15:47.367Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:15:48.139Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:15:48.947Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:15:50.232Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:15:50.232Z] 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. [2025-12-03T22:15:50.232Z] The best model improves the baseline by 14.52%. [2025-12-03T22:15:50.232Z] Top recommended movies for user id 72: [2025-12-03T22:15:50.232Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:15:50.232Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:15:50.232Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:15:50.232Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:15:50.232Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:15:50.232Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (10485.879 ms) ====== [2025-12-03T22:15:50.232Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-03T22:15:50.232Z] GC before operation: completed in 51.874 ms, heap usage 358.821 MB -> 90.316 MB. [2025-12-03T22:15:52.102Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:15:53.875Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:15:55.119Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:15:56.907Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:15:57.713Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:15:58.984Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:15:59.744Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:16:00.534Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:16:00.906Z] 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. [2025-12-03T22:16:00.906Z] The best model improves the baseline by 14.52%. [2025-12-03T22:16:00.906Z] Top recommended movies for user id 72: [2025-12-03T22:16:00.906Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:16:00.906Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:16:00.906Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:16:00.906Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:16:00.907Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:16:00.907Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (10462.704 ms) ====== [2025-12-03T22:16:00.907Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-03T22:16:00.907Z] GC before operation: completed in 72.677 ms, heap usage 280.244 MB -> 93.849 MB. [2025-12-03T22:16:02.735Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:16:04.000Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:16:05.796Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:16:07.598Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:16:08.365Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:16:09.129Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:16:10.350Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:16:11.144Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:16:11.563Z] 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. [2025-12-03T22:16:11.563Z] The best model improves the baseline by 14.52%. [2025-12-03T22:16:11.563Z] Top recommended movies for user id 72: [2025-12-03T22:16:11.563Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:16:11.563Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:16:11.563Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:16:11.563Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:16:11.563Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:16:11.563Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (10594.810 ms) ====== [2025-12-03T22:16:11.936Z] ----------------------------------- [2025-12-03T22:16:11.936Z] renaissance-movie-lens_0_PASSED [2025-12-03T22:16:11.936Z] ----------------------------------- [2025-12-03T22:16:11.936Z] [2025-12-03T22:16:11.936Z] TEST TEARDOWN: [2025-12-03T22:16:11.936Z] Nothing to be done for teardown. [2025-12-03T22:16:11.936Z] renaissance-movie-lens_0 Finish Time: Wed Dec 3 17:16:11 2025 Epoch Time (ms): 1764800171696