Test Results Summary Service

renaissance-movie-lens_0

[2026-02-11T23:05:42.602Z] Running test renaissance-movie-lens_0 ... [2026-02-11T23:05:42.602Z] =============================================== [2026-02-11T23:05:42.602Z] renaissance-movie-lens_0 Start Time: Wed Feb 11 18:05:41 2026 Epoch Time (ms): 1770851141897 [2026-02-11T23:05:42.602Z] variation: NoOptions [2026-02-11T23:05:42.602Z] JVM_OPTIONS: [2026-02-11T23:05:42.602Z] { \ [2026-02-11T23:05:42.602Z] echo ""; echo "TEST SETUP:"; \ [2026-02-11T23:05:42.602Z] echo "Nothing to be done for setup."; \ [2026-02-11T23:05:42.602Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17708507582995/renaissance-movie-lens_0"; \ [2026-02-11T23:05:42.602Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17708507582995/renaissance-movie-lens_0"; \ [2026-02-11T23:05:42.602Z] echo ""; echo "TESTING:"; \ [2026-02-11T23:05:42.602Z] "/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_17708507582995/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2026-02-11T23:05:42.602Z] 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_17708507582995/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2026-02-11T23:05:42.602Z] echo ""; echo "TEST TEARDOWN:"; \ [2026-02-11T23:05:42.602Z] echo "Nothing to be done for teardown."; \ [2026-02-11T23:05:42.602Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17708507582995/TestTargetResult"; [2026-02-11T23:05:42.602Z] [2026-02-11T23:05:42.602Z] TEST SETUP: [2026-02-11T23:05:42.602Z] Nothing to be done for setup. [2026-02-11T23:05:42.602Z] [2026-02-11T23:05:42.602Z] TESTING: [2026-02-11T23:05:45.655Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2026-02-11T23:05:48.009Z] 18:05:47.548 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. [2026-02-11T23:05:48.862Z] Got 100004 ratings from 671 users on 9066 movies. [2026-02-11T23:05:49.227Z] Training: 60056, validation: 20285, test: 19854 [2026-02-11T23:05:49.227Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2026-02-11T23:05:49.227Z] GC before operation: completed in 61.027 ms, heap usage 208.393 MB -> 75.734 MB. [2026-02-11T23:05:52.299Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:05:54.155Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:05:56.521Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:05:57.742Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:05:58.511Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:05:59.289Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:06:00.069Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:06:01.302Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:06:01.302Z] 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. [2026-02-11T23:06:01.302Z] The best model improves the baseline by 14.52%. [2026-02-11T23:06:01.302Z] Top recommended movies for user id 72: [2026-02-11T23:06:01.302Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:06:01.302Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:06:01.302Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:06:01.302Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:06:01.302Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:06:01.302Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (12076.731 ms) ====== [2026-02-11T23:06:01.302Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2026-02-11T23:06:01.302Z] GC before operation: completed in 46.316 ms, heap usage 395.283 MB -> 90.328 MB. [2026-02-11T23:06:02.516Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:06:04.328Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:06:05.529Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:06:06.741Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:06:07.508Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:06:08.260Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:06:09.016Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:06:09.782Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:06:09.782Z] 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. [2026-02-11T23:06:09.782Z] The best model improves the baseline by 14.52%. [2026-02-11T23:06:09.782Z] Top recommended movies for user id 72: [2026-02-11T23:06:09.782Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:06:09.782Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:06:09.782Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:06:09.782Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:06:09.782Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:06:09.782Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8519.309 ms) ====== [2026-02-11T23:06:09.782Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2026-02-11T23:06:09.782Z] GC before operation: completed in 43.837 ms, heap usage 244.564 MB -> 93.208 MB. [2026-02-11T23:06:11.533Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:06:12.748Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:06:13.952Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:06:15.692Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:06:16.468Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:06:17.229Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:06:17.977Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:06:18.724Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:06:18.724Z] 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. [2026-02-11T23:06:19.071Z] The best model improves the baseline by 14.52%. [2026-02-11T23:06:19.071Z] Top recommended movies for user id 72: [2026-02-11T23:06:19.071Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:06:19.071Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:06:19.071Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:06:19.071Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:06:19.071Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:06:19.071Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (9112.048 ms) ====== [2026-02-11T23:06:19.071Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2026-02-11T23:06:19.071Z] GC before operation: completed in 45.231 ms, heap usage 439.370 MB -> 93.210 MB. [2026-02-11T23:06:20.814Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:06:22.013Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:06:23.223Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:06:24.458Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:06:25.199Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:06:25.948Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:06:26.711Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:06:27.463Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:06:27.463Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2026-02-11T23:06:27.463Z] The best model improves the baseline by 14.52%. [2026-02-11T23:06:27.463Z] Top recommended movies for user id 72: [2026-02-11T23:06:27.463Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:06:27.463Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:06:27.463Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:06:27.463Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:06:27.463Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:06:27.463Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (8421.136 ms) ====== [2026-02-11T23:06:27.463Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2026-02-11T23:06:27.463Z] GC before operation: completed in 50.482 ms, heap usage 477.527 MB -> 91.359 MB. [2026-02-11T23:06:28.674Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:06:29.881Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:06:31.107Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:06:32.335Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:06:33.101Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:06:33.864Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:06:34.619Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:06:35.437Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:06:35.437Z] 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. [2026-02-11T23:06:35.437Z] The best model improves the baseline by 14.52%. [2026-02-11T23:06:35.789Z] Top recommended movies for user id 72: [2026-02-11T23:06:35.789Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:06:35.789Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:06:35.789Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:06:35.789Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:06:35.789Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:06:35.789Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8166.065 ms) ====== [2026-02-11T23:06:35.789Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2026-02-11T23:06:35.789Z] GC before operation: completed in 49.163 ms, heap usage 116.201 MB -> 89.586 MB. [2026-02-11T23:06:37.041Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:06:39.443Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:06:40.651Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:06:42.414Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:06:43.646Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:06:44.394Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:06:45.617Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:06:46.901Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:06:46.901Z] 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. [2026-02-11T23:06:46.901Z] The best model improves the baseline by 14.52%. [2026-02-11T23:06:46.901Z] Top recommended movies for user id 72: [2026-02-11T23:06:46.901Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:06:46.901Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:06:46.901Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:06:46.901Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:06:46.901Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:06:46.901Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (11209.246 ms) ====== [2026-02-11T23:06:46.901Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2026-02-11T23:06:46.901Z] GC before operation: completed in 58.015 ms, heap usage 275.341 MB -> 93.809 MB. [2026-02-11T23:06:49.339Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:06:51.133Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:06:53.538Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:06:55.323Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:06:56.112Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:06:57.368Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:06:58.157Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:06:58.920Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:06:59.275Z] 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. [2026-02-11T23:06:59.275Z] The best model improves the baseline by 14.52%. [2026-02-11T23:06:59.275Z] Top recommended movies for user id 72: [2026-02-11T23:06:59.275Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:06:59.275Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:06:59.275Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:06:59.275Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:06:59.275Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:06:59.275Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (12257.173 ms) ====== [2026-02-11T23:06:59.275Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2026-02-11T23:06:59.275Z] GC before operation: completed in 56.198 ms, heap usage 560.605 MB -> 93.622 MB. [2026-02-11T23:07:01.094Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:07:02.353Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:07:04.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:07:05.394Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:07:06.712Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:07:07.486Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:07:08.238Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:07:09.006Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:07:09.006Z] 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. [2026-02-11T23:07:09.006Z] The best model improves the baseline by 14.52%. [2026-02-11T23:07:09.006Z] Top recommended movies for user id 72: [2026-02-11T23:07:09.006Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:07:09.006Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:07:09.006Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:07:09.006Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:07:09.006Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:07:09.006Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (9781.809 ms) ====== [2026-02-11T23:07:09.006Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2026-02-11T23:07:09.006Z] GC before operation: completed in 45.261 ms, heap usage 608.330 MB -> 93.902 MB. [2026-02-11T23:07:10.234Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:07:11.465Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:07:12.700Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:07:13.443Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:07:14.207Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:07:14.984Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:07:15.746Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:07:16.107Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:07:16.455Z] 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. [2026-02-11T23:07:16.455Z] The best model improves the baseline by 14.52%. [2026-02-11T23:07:16.455Z] Top recommended movies for user id 72: [2026-02-11T23:07:16.455Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:07:16.455Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:07:16.455Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:07:16.455Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:07:16.455Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:07:16.455Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (7334.600 ms) ====== [2026-02-11T23:07:16.455Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2026-02-11T23:07:16.455Z] GC before operation: completed in 43.004 ms, heap usage 278.452 MB -> 93.746 MB. [2026-02-11T23:07:17.668Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:07:18.899Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:07:19.669Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:07:20.890Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:07:21.657Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:07:22.423Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:07:24.183Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:07:25.427Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:07:25.427Z] 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. [2026-02-11T23:07:25.427Z] The best model improves the baseline by 14.52%. [2026-02-11T23:07:25.427Z] Top recommended movies for user id 72: [2026-02-11T23:07:25.427Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:07:25.427Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:07:25.427Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:07:25.427Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:07:25.427Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:07:25.427Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (8955.679 ms) ====== [2026-02-11T23:07:25.427Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2026-02-11T23:07:25.427Z] GC before operation: completed in 66.648 ms, heap usage 431.277 MB -> 92.889 MB. [2026-02-11T23:07:27.202Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:07:27.979Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:07:29.204Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:07:30.425Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:07:31.269Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:07:32.023Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:07:32.781Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:07:33.997Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:07:33.997Z] 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. [2026-02-11T23:07:33.997Z] The best model improves the baseline by 14.52%. [2026-02-11T23:07:34.347Z] Top recommended movies for user id 72: [2026-02-11T23:07:34.347Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:07:34.347Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:07:34.347Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:07:34.347Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:07:34.347Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:07:34.347Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (8667.829 ms) ====== [2026-02-11T23:07:34.347Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2026-02-11T23:07:34.347Z] GC before operation: completed in 50.576 ms, heap usage 195.252 MB -> 90.109 MB. [2026-02-11T23:07:35.584Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:07:37.323Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:07:39.054Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:07:40.803Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:07:41.155Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:07:41.917Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:07:42.695Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:07:43.939Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:07:43.939Z] 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. [2026-02-11T23:07:43.939Z] The best model improves the baseline by 14.52%. [2026-02-11T23:07:43.939Z] Top recommended movies for user id 72: [2026-02-11T23:07:43.939Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:07:43.939Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:07:43.939Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:07:43.939Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:07:43.939Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:07:43.939Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (9840.161 ms) ====== [2026-02-11T23:07:43.939Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2026-02-11T23:07:44.285Z] GC before operation: completed in 75.043 ms, heap usage 270.269 MB -> 90.252 MB. [2026-02-11T23:07:45.509Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:07:46.734Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:07:47.958Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:07:49.183Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:07:49.939Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:07:50.705Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:07:51.469Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:07:52.253Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:07:52.253Z] 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. [2026-02-11T23:07:52.253Z] The best model improves the baseline by 14.52%. [2026-02-11T23:07:52.253Z] Top recommended movies for user id 72: [2026-02-11T23:07:52.253Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:07:52.253Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:07:52.253Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:07:52.253Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:07:52.253Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:07:52.253Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (8058.722 ms) ====== [2026-02-11T23:07:52.253Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2026-02-11T23:07:52.253Z] GC before operation: completed in 55.519 ms, heap usage 263.382 MB -> 90.384 MB. [2026-02-11T23:07:54.013Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:07:55.236Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:07:56.446Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:07:58.237Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:07:58.999Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:07:59.789Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:08:01.045Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:08:01.399Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:08:01.744Z] 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. [2026-02-11T23:08:01.744Z] The best model improves the baseline by 14.52%. [2026-02-11T23:08:01.744Z] Top recommended movies for user id 72: [2026-02-11T23:08:01.744Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:08:01.744Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:08:01.744Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:08:01.744Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:08:01.744Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:08:01.744Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (9373.593 ms) ====== [2026-02-11T23:08:01.744Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2026-02-11T23:08:01.744Z] GC before operation: completed in 49.111 ms, heap usage 473.460 MB -> 90.576 MB. [2026-02-11T23:08:02.503Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:08:03.742Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:08:04.489Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:08:05.705Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:08:06.051Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:08:06.796Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:08:07.142Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:08:07.886Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:08:07.886Z] 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. [2026-02-11T23:08:07.886Z] The best model improves the baseline by 14.52%. [2026-02-11T23:08:07.886Z] Top recommended movies for user id 72: [2026-02-11T23:08:07.886Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:08:07.886Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:08:07.886Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:08:07.886Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:08:07.886Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:08:07.886Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (6319.516 ms) ====== [2026-02-11T23:08:07.886Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2026-02-11T23:08:07.886Z] GC before operation: completed in 43.497 ms, heap usage 215.148 MB -> 92.705 MB. [2026-02-11T23:08:09.105Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:08:09.855Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:08:11.067Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:08:11.821Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:08:12.588Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:08:12.938Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:08:13.686Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:08:14.435Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:08:14.435Z] 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. [2026-02-11T23:08:14.435Z] The best model improves the baseline by 14.52%. [2026-02-11T23:08:14.435Z] Top recommended movies for user id 72: [2026-02-11T23:08:14.435Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:08:14.435Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:08:14.435Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:08:14.435Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:08:14.435Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:08:14.435Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (6363.076 ms) ====== [2026-02-11T23:08:14.435Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2026-02-11T23:08:14.435Z] GC before operation: completed in 48.083 ms, heap usage 373.418 MB -> 93.711 MB. [2026-02-11T23:08:15.639Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:08:16.381Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:08:17.580Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:08:18.837Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:08:19.184Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:08:19.936Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:08:20.281Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:08:21.028Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:08:21.029Z] 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. [2026-02-11T23:08:21.029Z] The best model improves the baseline by 14.52%. [2026-02-11T23:08:21.029Z] Top recommended movies for user id 72: [2026-02-11T23:08:21.029Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:08:21.029Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:08:21.029Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:08:21.029Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:08:21.029Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:08:21.029Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (6699.286 ms) ====== [2026-02-11T23:08:21.029Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2026-02-11T23:08:21.378Z] GC before operation: completed in 46.708 ms, heap usage 222.098 MB -> 93.844 MB. [2026-02-11T23:08:22.125Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:08:23.375Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:08:24.114Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:08:25.320Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:08:25.670Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:08:26.018Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:08:27.234Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:08:27.586Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:08:27.586Z] 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. [2026-02-11T23:08:27.930Z] The best model improves the baseline by 14.52%. [2026-02-11T23:08:27.930Z] Top recommended movies for user id 72: [2026-02-11T23:08:27.930Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:08:27.930Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:08:27.930Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:08:27.930Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:08:27.930Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:08:27.930Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (6618.677 ms) ====== [2026-02-11T23:08:27.930Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2026-02-11T23:08:27.930Z] GC before operation: completed in 45.765 ms, heap usage 231.061 MB -> 92.655 MB. [2026-02-11T23:08:28.685Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:08:29.887Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:08:31.094Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:08:32.334Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:08:33.083Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:08:33.836Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:08:34.590Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:08:34.954Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:08:35.308Z] 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. [2026-02-11T23:08:35.308Z] The best model improves the baseline by 14.52%. [2026-02-11T23:08:35.308Z] Top recommended movies for user id 72: [2026-02-11T23:08:35.308Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:08:35.308Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:08:35.308Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:08:35.308Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:08:35.308Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:08:35.308Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (7340.444 ms) ====== [2026-02-11T23:08:35.308Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2026-02-11T23:08:35.308Z] GC before operation: completed in 42.655 ms, heap usage 538.943 MB -> 95.795 MB. [2026-02-11T23:08:36.074Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2026-02-11T23:08:37.280Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2026-02-11T23:08:38.500Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2026-02-11T23:08:39.262Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2026-02-11T23:08:40.039Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2026-02-11T23:08:40.395Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2026-02-11T23:08:41.158Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2026-02-11T23:08:41.926Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2026-02-11T23:08:41.926Z] 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. [2026-02-11T23:08:41.926Z] The best model improves the baseline by 14.52%. [2026-02-11T23:08:41.926Z] Top recommended movies for user id 72: [2026-02-11T23:08:41.926Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2026-02-11T23:08:41.926Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2026-02-11T23:08:41.926Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2026-02-11T23:08:41.926Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2026-02-11T23:08:41.926Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2026-02-11T23:08:41.926Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (6659.508 ms) ====== [2026-02-11T23:08:42.272Z] ----------------------------------- [2026-02-11T23:08:42.272Z] renaissance-movie-lens_0_PASSED [2026-02-11T23:08:42.272Z] ----------------------------------- [2026-02-11T23:08:42.272Z] [2026-02-11T23:08:42.272Z] TEST TEARDOWN: [2026-02-11T23:08:42.272Z] Nothing to be done for teardown. [2026-02-11T23:08:42.272Z] renaissance-movie-lens_0 Finish Time: Wed Feb 11 18:08:42 2026 Epoch Time (ms): 1770851322200