Test Results Summary Service

renaissance-movie-lens_0

[2026-01-21T07:08:05.009Z] Running test renaissance-movie-lens_0 ... [2026-01-21T07:08:05.009Z] =============================================== [2026-01-21T07:08:05.009Z] renaissance-movie-lens_0 Start Time: Wed Jan 21 02:08:04 2026 Epoch Time (ms): 1768979284735 [2026-01-21T07:08:05.009Z] variation: NoOptions [2026-01-21T07:08:05.009Z] JVM_OPTIONS: [2026-01-21T07:08:05.009Z] { \ [2026-01-21T07:08:05.009Z] echo ""; echo "TEST SETUP:"; \ [2026-01-21T07:08:05.009Z] echo "Nothing to be done for setup."; \ [2026-01-21T07:08:05.009Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17689787394584/renaissance-movie-lens_0"; \ [2026-01-21T07:08:05.009Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17689787394584/renaissance-movie-lens_0"; \ [2026-01-21T07:08:05.009Z] echo ""; echo "TESTING:"; \ [2026-01-21T07:08:05.009Z] "/Users/admin/workspace/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17689787394584/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2026-01-21T07:08:05.009Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17689787394584/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2026-01-21T07:08:05.009Z] echo ""; echo "TEST TEARDOWN:"; \ [2026-01-21T07:08:05.009Z] echo "Nothing to be done for teardown."; \ [2026-01-21T07:08:05.009Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17689787394584/TestTargetResult"; [2026-01-21T07:08:05.009Z] [2026-01-21T07:08:05.009Z] TEST SETUP: [2026-01-21T07:08:05.009Z] Nothing to be done for setup. [2026-01-21T07:08:05.009Z] [2026-01-21T07:08:05.009Z] TESTING: [2026-01-21T07:08:10.074Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2026-01-21T07:08:15.064Z] 02:08:14.794 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2026-01-21T07:08:16.418Z] Got 100004 ratings from 671 users on 9066 movies. [2026-01-21T07:08:16.796Z] Training: 60056, validation: 20285, test: 19854 [2026-01-21T07:08:16.796Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2026-01-21T07:08:16.796Z] GC before operation: completed in 89.967 ms, heap usage 260.985 MB -> 74.663 MB. [2026-01-21T07:08:20.926Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:08:24.116Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:08:26.567Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:08:29.020Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:08:30.280Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:08:31.523Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:08:32.804Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:08:34.076Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:08:34.460Z] 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. [2026-01-21T07:08:34.460Z] The best model improves the baseline by 14.52%. [2026-01-21T07:08:34.827Z] Top recommended movies for user id 72: [2026-01-21T07:08:34.827Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:08:34.827Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:08:34.827Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:08:34.827Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:08:34.827Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:08:34.827Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (17823.292 ms) ====== [2026-01-21T07:08:34.827Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2026-01-21T07:08:34.827Z] GC before operation: completed in 95.399 ms, heap usage 143.080 MB -> 85.500 MB. [2026-01-21T07:08:37.298Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:08:39.140Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:08:41.554Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:08:44.031Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:08:45.295Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:08:46.540Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:08:47.831Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:08:49.102Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:08:49.465Z] 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. [2026-01-21T07:08:49.465Z] The best model improves the baseline by 14.52%. [2026-01-21T07:08:49.465Z] Top recommended movies for user id 72: [2026-01-21T07:08:49.465Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:08:49.465Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:08:49.465Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:08:49.465Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:08:49.465Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:08:49.465Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (14727.429 ms) ====== [2026-01-21T07:08:49.465Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2026-01-21T07:08:49.465Z] GC before operation: completed in 95.104 ms, heap usage 107.602 MB -> 87.626 MB. [2026-01-21T07:08:51.897Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:08:54.341Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:08:56.238Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:08:58.659Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:08:59.433Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:09:00.764Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:09:02.044Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:09:03.336Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:09:03.699Z] 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. [2026-01-21T07:09:03.699Z] The best model improves the baseline by 14.52%. [2026-01-21T07:09:03.699Z] Top recommended movies for user id 72: [2026-01-21T07:09:03.699Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:09:03.699Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:09:03.699Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:09:03.699Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:09:03.699Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:09:03.699Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (14176.655 ms) ====== [2026-01-21T07:09:03.699Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2026-01-21T07:09:03.699Z] GC before operation: completed in 94.211 ms, heap usage 123.994 MB -> 88.233 MB. [2026-01-21T07:09:06.134Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:09:07.939Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:09:10.383Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:09:12.190Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:09:13.462Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:09:14.744Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:09:16.019Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:09:17.266Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:09:17.655Z] 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. [2026-01-21T07:09:17.655Z] The best model improves the baseline by 14.52%. [2026-01-21T07:09:17.655Z] Top recommended movies for user id 72: [2026-01-21T07:09:17.655Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:09:17.655Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:09:17.655Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:09:17.655Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:09:17.655Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:09:17.655Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (13718.562 ms) ====== [2026-01-21T07:09:17.655Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2026-01-21T07:09:17.655Z] GC before operation: completed in 73.985 ms, heap usage 112.186 MB -> 88.542 MB. [2026-01-21T07:09:20.097Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:09:21.895Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:09:24.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:09:26.123Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:09:27.354Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:09:29.191Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:09:30.447Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:09:31.715Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:09:31.715Z] 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. [2026-01-21T07:09:31.715Z] The best model improves the baseline by 14.52%. [2026-01-21T07:09:31.715Z] Top recommended movies for user id 72: [2026-01-21T07:09:31.715Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:09:31.715Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:09:31.715Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:09:31.715Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:09:31.715Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:09:31.715Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14114.040 ms) ====== [2026-01-21T07:09:31.715Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2026-01-21T07:09:31.715Z] GC before operation: completed in 94.408 ms, heap usage 139.906 MB -> 88.510 MB. [2026-01-21T07:09:34.135Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:09:35.953Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:09:37.789Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:09:40.193Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:09:42.032Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:09:42.822Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:09:44.649Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:09:45.896Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:09:45.896Z] 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. [2026-01-21T07:09:45.896Z] The best model improves the baseline by 14.52%. [2026-01-21T07:09:45.896Z] Top recommended movies for user id 72: [2026-01-21T07:09:45.896Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:09:45.896Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:09:45.896Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:09:45.896Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:09:45.897Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:09:45.897Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14077.471 ms) ====== [2026-01-21T07:09:45.897Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2026-01-21T07:09:45.897Z] GC before operation: completed in 89.101 ms, heap usage 517.740 MB -> 89.309 MB. [2026-01-21T07:09:48.322Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:09:50.804Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:09:52.597Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:09:55.039Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:09:56.290Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:09:57.643Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:09:58.894Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:10:00.158Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:10:00.532Z] 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. [2026-01-21T07:10:00.532Z] The best model improves the baseline by 14.52%. [2026-01-21T07:10:00.532Z] Top recommended movies for user id 72: [2026-01-21T07:10:00.532Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:10:00.532Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:10:00.532Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:10:00.532Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:10:00.532Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:10:00.532Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14507.742 ms) ====== [2026-01-21T07:10:00.532Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2026-01-21T07:10:00.532Z] GC before operation: completed in 89.889 ms, heap usage 231.469 MB -> 88.886 MB. [2026-01-21T07:10:02.973Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:10:05.466Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:10:07.281Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:10:09.714Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:10:10.985Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:10:12.225Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:10:13.497Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:10:14.255Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:10:14.611Z] 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. [2026-01-21T07:10:14.611Z] The best model improves the baseline by 14.52%. [2026-01-21T07:10:14.611Z] Top recommended movies for user id 72: [2026-01-21T07:10:14.611Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:10:14.611Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:10:14.611Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:10:14.611Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:10:14.611Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:10:14.611Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13996.640 ms) ====== [2026-01-21T07:10:14.611Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2026-01-21T07:10:14.611Z] GC before operation: completed in 72.814 ms, heap usage 389.429 MB -> 89.292 MB. [2026-01-21T07:10:17.068Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:10:18.901Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:10:20.698Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:10:23.094Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:10:24.340Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:10:25.569Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:10:26.804Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:10:28.102Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:10:28.102Z] 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. [2026-01-21T07:10:28.102Z] The best model improves the baseline by 14.52%. [2026-01-21T07:10:28.102Z] Top recommended movies for user id 72: [2026-01-21T07:10:28.102Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:10:28.102Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:10:28.102Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:10:28.102Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:10:28.102Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:10:28.102Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13452.243 ms) ====== [2026-01-21T07:10:28.102Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2026-01-21T07:10:28.102Z] GC before operation: completed in 76.503 ms, heap usage 270.952 MB -> 89.045 MB. [2026-01-21T07:10:30.567Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:10:32.415Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:10:34.265Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:10:36.749Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:10:38.066Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:10:38.855Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:10:40.112Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:10:40.886Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:10:41.247Z] 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. [2026-01-21T07:10:41.247Z] The best model improves the baseline by 14.52%. [2026-01-21T07:10:41.247Z] Top recommended movies for user id 72: [2026-01-21T07:10:41.247Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:10:41.247Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:10:41.247Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:10:41.247Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:10:41.247Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:10:41.247Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12935.646 ms) ====== [2026-01-21T07:10:41.247Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2026-01-21T07:10:41.247Z] GC before operation: completed in 73.077 ms, heap usage 454.358 MB -> 89.505 MB. [2026-01-21T07:10:43.030Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:10:44.817Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:10:46.612Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:10:48.415Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:10:49.702Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:10:50.482Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:10:51.759Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:10:53.057Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:10:53.057Z] 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. [2026-01-21T07:10:53.057Z] The best model improves the baseline by 14.52%. [2026-01-21T07:10:53.057Z] Top recommended movies for user id 72: [2026-01-21T07:10:53.057Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:10:53.057Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:10:53.057Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:10:53.057Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:10:53.057Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:10:53.057Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (11895.918 ms) ====== [2026-01-21T07:10:53.057Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2026-01-21T07:10:53.057Z] GC before operation: completed in 91.914 ms, heap usage 410.882 MB -> 89.059 MB. [2026-01-21T07:10:55.544Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:10:57.178Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:10:58.494Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:10:59.777Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:11:01.104Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:11:02.433Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:11:03.241Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:11:04.509Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:11:04.509Z] 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. [2026-01-21T07:11:04.509Z] The best model improves the baseline by 14.52%. [2026-01-21T07:11:04.509Z] Top recommended movies for user id 72: [2026-01-21T07:11:04.509Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:11:04.509Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:11:04.509Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:11:04.509Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:11:04.509Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:11:04.509Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (11259.120 ms) ====== [2026-01-21T07:11:04.509Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2026-01-21T07:11:04.509Z] GC before operation: completed in 62.767 ms, heap usage 342.678 MB -> 89.205 MB. [2026-01-21T07:11:06.302Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:11:07.567Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:11:09.354Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:11:11.136Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:11:11.926Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:11:12.699Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:11:13.481Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:11:14.266Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:11:14.266Z] 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. [2026-01-21T07:11:14.266Z] The best model improves the baseline by 14.52%. [2026-01-21T07:11:14.266Z] Top recommended movies for user id 72: [2026-01-21T07:11:14.266Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:11:14.266Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:11:14.266Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:11:14.266Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:11:14.266Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:11:14.266Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (9879.540 ms) ====== [2026-01-21T07:11:14.266Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2026-01-21T07:11:14.619Z] GC before operation: completed in 63.894 ms, heap usage 383.953 MB -> 89.388 MB. [2026-01-21T07:11:15.864Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:11:17.095Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:11:18.900Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:11:21.328Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:11:22.596Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:11:23.849Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:11:25.144Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:11:26.460Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:11:26.830Z] 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. [2026-01-21T07:11:26.830Z] The best model improves the baseline by 14.52%. [2026-01-21T07:11:26.830Z] Top recommended movies for user id 72: [2026-01-21T07:11:26.830Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:11:26.830Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:11:26.830Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:11:26.830Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:11:26.830Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:11:26.830Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12277.537 ms) ====== [2026-01-21T07:11:26.830Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2026-01-21T07:11:26.830Z] GC before operation: completed in 92.507 ms, heap usage 495.420 MB -> 89.315 MB. [2026-01-21T07:11:29.249Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:11:31.069Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:11:33.526Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:11:35.329Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:11:36.591Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:11:37.823Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:11:39.075Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:11:40.328Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:11:40.696Z] 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. [2026-01-21T07:11:40.696Z] The best model improves the baseline by 14.52%. [2026-01-21T07:11:40.696Z] Top recommended movies for user id 72: [2026-01-21T07:11:40.696Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:11:40.696Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:11:40.696Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:11:40.696Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:11:40.696Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:11:40.696Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13760.566 ms) ====== [2026-01-21T07:11:40.696Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2026-01-21T07:11:40.696Z] GC before operation: completed in 89.356 ms, heap usage 449.543 MB -> 89.485 MB. [2026-01-21T07:11:43.126Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:11:44.966Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:11:47.391Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:11:49.826Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:11:51.062Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:11:52.837Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:11:53.649Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:11:54.948Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:11:55.454Z] 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. [2026-01-21T07:11:55.454Z] The best model improves the baseline by 14.52%. [2026-01-21T07:11:55.454Z] Top recommended movies for user id 72: [2026-01-21T07:11:55.454Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:11:55.454Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:11:55.454Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:11:55.454Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:11:55.454Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:11:55.454Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14591.209 ms) ====== [2026-01-21T07:11:55.454Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2026-01-21T07:11:55.454Z] GC before operation: completed in 92.313 ms, heap usage 109.113 MB -> 88.939 MB. [2026-01-21T07:11:57.260Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:11:59.705Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:12:01.616Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:12:04.098Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:12:05.398Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:12:06.678Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:12:07.959Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:12:09.215Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:12:09.596Z] 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. [2026-01-21T07:12:09.596Z] The best model improves the baseline by 14.52%. [2026-01-21T07:12:09.596Z] Top recommended movies for user id 72: [2026-01-21T07:12:09.596Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:12:09.596Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:12:09.596Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:12:09.596Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:12:09.596Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:12:09.596Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14311.957 ms) ====== [2026-01-21T07:12:09.596Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2026-01-21T07:12:09.953Z] GC before operation: completed in 102.571 ms, heap usage 441.649 MB -> 89.409 MB. [2026-01-21T07:12:12.363Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:12:14.817Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:12:17.267Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:12:19.085Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:12:20.358Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:12:22.152Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:12:22.933Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:12:24.768Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:12:24.768Z] 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. [2026-01-21T07:12:24.768Z] The best model improves the baseline by 14.52%. [2026-01-21T07:12:24.768Z] Top recommended movies for user id 72: [2026-01-21T07:12:24.768Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:12:24.768Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:12:24.768Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:12:24.768Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:12:24.768Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:12:24.768Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14960.424 ms) ====== [2026-01-21T07:12:24.768Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2026-01-21T07:12:24.768Z] GC before operation: completed in 78.924 ms, heap usage 333.491 MB -> 89.109 MB. [2026-01-21T07:12:27.203Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:12:29.027Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:12:31.469Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:12:33.271Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:12:34.500Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:12:35.264Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:12:36.029Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:12:36.861Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:12:37.221Z] 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. [2026-01-21T07:12:37.221Z] The best model improves the baseline by 14.52%. [2026-01-21T07:12:37.221Z] Top recommended movies for user id 72: [2026-01-21T07:12:37.221Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:12:37.221Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:12:37.221Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:12:37.221Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:12:37.221Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:12:37.221Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12298.644 ms) ====== [2026-01-21T07:12:37.221Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2026-01-21T07:12:37.221Z] GC before operation: completed in 64.056 ms, heap usage 321.227 MB -> 89.254 MB. [2026-01-21T07:12:38.459Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-01-21T07:12:40.238Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-01-21T07:12:41.479Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-01-21T07:12:43.297Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-01-21T07:12:44.536Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-01-21T07:12:45.773Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-01-21T07:12:47.002Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-01-21T07:12:48.253Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-01-21T07:12:48.611Z] 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. [2026-01-21T07:12:48.611Z] The best model improves the baseline by 14.52%. [2026-01-21T07:12:48.611Z] Top recommended movies for user id 72: [2026-01-21T07:12:48.611Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-01-21T07:12:48.611Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-01-21T07:12:48.611Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-01-21T07:12:48.611Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-01-21T07:12:48.611Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-01-21T07:12:48.611Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (11335.190 ms) ====== [2026-01-21T07:12:48.968Z] ----------------------------------- [2026-01-21T07:12:48.968Z] renaissance-movie-lens_0_PASSED [2026-01-21T07:12:48.968Z] ----------------------------------- [2026-01-21T07:12:49.323Z] [2026-01-21T07:12:49.323Z] TEST TEARDOWN: [2026-01-21T07:12:49.323Z] Nothing to be done for teardown. [2026-01-21T07:12:49.323Z] renaissance-movie-lens_0 Finish Time: Wed Jan 21 02:12:48 2026 Epoch Time (ms): 1768979568936