[2025-09-25T02:10:24.229Z] Running test renaissance-movie-lens_0 ... [2025-09-25T02:10:24.229Z] =============================================== [2025-09-25T02:10:24.229Z] renaissance-movie-lens_0 Start Time: Thu Sep 25 02:10:24 2025 Epoch Time (ms): 1758766224151 [2025-09-25T02:10:24.537Z] variation: NoOptions [2025-09-25T02:10:24.538Z] JVM_OPTIONS: [2025-09-25T02:10:24.538Z] { \ [2025-09-25T02:10:24.538Z] echo ""; echo "TEST SETUP:"; \ [2025-09-25T02:10:24.538Z] echo "Nothing to be done for setup."; \ [2025-09-25T02:10:24.538Z] mkdir -p "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17587634461462\\renaissance-movie-lens_0"; \ [2025-09-25T02:10:24.538Z] cd "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17587634461462\\renaissance-movie-lens_0"; \ [2025-09-25T02:10:24.538Z] echo ""; echo "TESTING:"; \ [2025-09-25T02:10:24.538Z] "c:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\bin\\java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17587634461462\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-09-25T02:10:24.538Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17587634461462\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-25T02:10:24.538Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-25T02:10:24.538Z] echo "Nothing to be done for teardown."; \ [2025-09-25T02:10:24.538Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17587634461462\\TestTargetResult"; [2025-09-25T02:10:24.866Z] [2025-09-25T02:10:24.866Z] TEST SETUP: [2025-09-25T02:10:24.866Z] Nothing to be done for setup. [2025-09-25T02:10:24.866Z] [2025-09-25T02:10:24.866Z] TESTING: [2025-09-25T02:10:43.821Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-09-25T02:10:55.523Z] 02:10:54.615 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-09-25T02:10:59.809Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-25T02:11:00.739Z] Training: 60056, validation: 20285, test: 19854 [2025-09-25T02:11:00.739Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-25T02:11:01.581Z] GC before operation: completed in 239.139 ms, heap usage 278.053 MB -> 76.178 MB. [2025-09-25T02:11:15.786Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:11:27.016Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:11:35.965Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:11:44.945Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:11:48.818Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:11:53.555Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:11:58.326Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:12:03.275Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:12:03.977Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:12:03.977Z] The best model improves the baseline by 14.34%. [2025-09-25T02:12:04.427Z] Top recommended movies for user id 72: [2025-09-25T02:12:04.427Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:12:04.427Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:12:04.427Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:12:04.427Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:12:04.427Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:12:04.427Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (63363.259 ms) ====== [2025-09-25T02:12:04.427Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-25T02:12:05.145Z] GC before operation: completed in 317.254 ms, heap usage 182.632 MB -> 93.084 MB. [2025-09-25T02:12:13.876Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:12:21.152Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:12:28.303Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:12:35.548Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:12:39.377Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:12:44.361Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:12:49.098Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:12:52.839Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:12:53.528Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:12:53.528Z] The best model improves the baseline by 14.34%. [2025-09-25T02:12:53.944Z] Top recommended movies for user id 72: [2025-09-25T02:12:53.944Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:12:53.944Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:12:53.944Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:12:53.944Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:12:53.944Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:12:53.944Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (49323.274 ms) ====== [2025-09-25T02:12:53.944Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-25T02:12:54.338Z] GC before operation: completed in 266.122 ms, heap usage 412.990 MB -> 88.553 MB. [2025-09-25T02:13:03.425Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:13:10.549Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:13:17.667Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:13:24.788Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:13:28.509Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:13:33.190Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:13:36.887Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:13:41.706Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:13:41.706Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:13:41.706Z] The best model improves the baseline by 14.34%. [2025-09-25T02:13:42.113Z] Top recommended movies for user id 72: [2025-09-25T02:13:42.113Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:13:42.113Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:13:42.113Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:13:42.113Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:13:42.113Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:13:42.113Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (47894.322 ms) ====== [2025-09-25T02:13:42.113Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-25T02:13:42.470Z] GC before operation: completed in 232.731 ms, heap usage 189.526 MB -> 88.679 MB. [2025-09-25T02:13:51.346Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:13:58.542Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:14:05.797Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:14:12.966Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:14:16.683Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:14:21.361Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:14:25.143Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:14:29.803Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:14:29.803Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:14:29.803Z] The best model improves the baseline by 14.34%. [2025-09-25T02:14:30.342Z] Top recommended movies for user id 72: [2025-09-25T02:14:30.342Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:14:30.342Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:14:30.342Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:14:30.342Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:14:30.342Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:14:30.342Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (47706.952 ms) ====== [2025-09-25T02:14:30.342Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-25T02:14:30.342Z] GC before operation: completed in 216.045 ms, heap usage 220.858 MB -> 96.796 MB. [2025-09-25T02:14:39.280Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:14:46.408Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:14:53.823Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:15:03.005Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:15:06.710Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:15:11.464Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:15:16.439Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:15:21.280Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:15:21.280Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:15:21.823Z] The best model improves the baseline by 14.34%. [2025-09-25T02:15:21.823Z] Top recommended movies for user id 72: [2025-09-25T02:15:21.823Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:15:21.823Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:15:21.823Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:15:21.823Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:15:21.823Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:15:21.823Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (51303.843 ms) ====== [2025-09-25T02:15:21.823Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-25T02:15:21.823Z] GC before operation: completed in 196.604 ms, heap usage 277.159 MB -> 89.020 MB. [2025-09-25T02:15:30.807Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:15:38.256Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:15:47.463Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:15:54.808Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:15:58.797Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:16:03.823Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:16:08.724Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:16:13.563Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:16:13.563Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:16:13.563Z] The best model improves the baseline by 14.34%. [2025-09-25T02:16:14.280Z] Top recommended movies for user id 72: [2025-09-25T02:16:14.280Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:16:14.280Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:16:14.280Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:16:14.280Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:16:14.280Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:16:14.280Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (52144.062 ms) ====== [2025-09-25T02:16:14.280Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-25T02:16:14.606Z] GC before operation: completed in 226.883 ms, heap usage 279.545 MB -> 89.332 MB. [2025-09-25T02:16:23.629Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:16:31.154Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:16:38.729Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:16:47.642Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:16:51.514Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:16:56.313Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:17:01.831Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:17:05.612Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:17:06.358Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:17:06.358Z] The best model improves the baseline by 14.34%. [2025-09-25T02:17:06.980Z] Top recommended movies for user id 72: [2025-09-25T02:17:06.980Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:17:06.980Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:17:06.980Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:17:06.980Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:17:06.980Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:17:06.980Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (52425.859 ms) ====== [2025-09-25T02:17:06.980Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-25T02:17:06.980Z] GC before operation: completed in 190.079 ms, heap usage 630.148 MB -> 93.103 MB. [2025-09-25T02:17:14.204Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:17:21.446Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:17:30.233Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:17:36.017Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:17:40.625Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:17:44.315Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:17:49.082Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:17:52.780Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:17:53.111Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:17:53.451Z] The best model improves the baseline by 14.34%. [2025-09-25T02:17:53.928Z] Top recommended movies for user id 72: [2025-09-25T02:17:53.928Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:17:53.928Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:17:53.928Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:17:53.928Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:17:53.928Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:17:53.928Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (46860.468 ms) ====== [2025-09-25T02:17:53.928Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-25T02:17:54.254Z] GC before operation: completed in 212.563 ms, heap usage 207.228 MB -> 89.370 MB. [2025-09-25T02:18:01.350Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:18:10.400Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:18:17.760Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:18:24.910Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:18:30.643Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:18:35.435Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:18:40.176Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:18:44.952Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:18:44.952Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:18:44.952Z] The best model improves the baseline by 14.34%. [2025-09-25T02:18:45.476Z] Top recommended movies for user id 72: [2025-09-25T02:18:45.476Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:18:45.476Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:18:45.476Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:18:45.476Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:18:45.476Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:18:45.476Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (51358.588 ms) ====== [2025-09-25T02:18:45.476Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-25T02:18:45.789Z] GC before operation: completed in 193.153 ms, heap usage 276.840 MB -> 89.433 MB. [2025-09-25T02:18:55.105Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:19:02.369Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:19:09.703Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:19:18.520Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:19:22.312Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:19:26.224Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:19:30.935Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:19:36.288Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:19:36.288Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:19:36.288Z] The best model improves the baseline by 14.34%. [2025-09-25T02:19:36.937Z] Top recommended movies for user id 72: [2025-09-25T02:19:36.937Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:19:36.937Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:19:36.937Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:19:36.937Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:19:36.937Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:19:36.937Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (51250.092 ms) ====== [2025-09-25T02:19:36.937Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-25T02:19:37.272Z] GC before operation: completed in 167.696 ms, heap usage 275.766 MB -> 89.583 MB. [2025-09-25T02:19:44.580Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:19:53.967Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:20:01.690Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:20:09.056Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:20:13.832Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:20:18.414Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:20:23.389Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:20:28.675Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:20:28.675Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:20:28.675Z] The best model improves the baseline by 14.34%. [2025-09-25T02:20:28.675Z] Top recommended movies for user id 72: [2025-09-25T02:20:28.675Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:20:28.675Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:20:28.675Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:20:28.675Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:20:28.675Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:20:28.675Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (51610.162 ms) ====== [2025-09-25T02:20:28.675Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-25T02:20:28.981Z] GC before operation: completed in 169.945 ms, heap usage 276.997 MB -> 89.338 MB. [2025-09-25T02:20:36.260Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:20:43.534Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:20:50.709Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:20:58.135Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:21:01.037Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:21:05.749Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:21:10.502Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:21:14.271Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:21:15.017Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:21:15.017Z] The best model improves the baseline by 14.34%. [2025-09-25T02:21:15.017Z] Top recommended movies for user id 72: [2025-09-25T02:21:15.017Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:21:15.017Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:21:15.017Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:21:15.017Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:21:15.017Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:21:15.017Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (46154.058 ms) ====== [2025-09-25T02:21:15.017Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-25T02:21:15.357Z] GC before operation: completed in 172.503 ms, heap usage 112.541 MB -> 89.305 MB. [2025-09-25T02:21:22.485Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:21:29.665Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:21:37.089Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:21:42.932Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:21:47.778Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:21:51.919Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:21:55.666Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:22:00.392Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:22:00.392Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:22:00.392Z] The best model improves the baseline by 14.34%. [2025-09-25T02:22:00.984Z] Top recommended movies for user id 72: [2025-09-25T02:22:00.984Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:22:00.984Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:22:00.984Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:22:00.984Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:22:00.984Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:22:00.984Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (45675.648 ms) ====== [2025-09-25T02:22:00.984Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-25T02:22:00.984Z] GC before operation: completed in 176.530 ms, heap usage 574.857 MB -> 93.404 MB. [2025-09-25T02:22:10.492Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:22:16.325Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:22:23.529Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:22:30.713Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:22:34.467Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:22:38.226Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:22:42.958Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:22:46.762Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:22:47.160Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:22:47.160Z] The best model improves the baseline by 14.34%. [2025-09-25T02:22:47.806Z] Top recommended movies for user id 72: [2025-09-25T02:22:47.806Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:22:47.806Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:22:47.806Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:22:47.806Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:22:47.806Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:22:47.806Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (46711.352 ms) ====== [2025-09-25T02:22:47.806Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-25T02:22:47.806Z] GC before operation: completed in 168.896 ms, heap usage 204.051 MB -> 89.340 MB. [2025-09-25T02:22:55.036Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:23:02.247Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:23:09.509Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:23:16.645Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:23:20.393Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:23:24.119Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:23:28.839Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:23:32.538Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:23:33.287Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:23:33.287Z] The best model improves the baseline by 14.34%. [2025-09-25T02:23:34.031Z] Top recommended movies for user id 72: [2025-09-25T02:23:34.031Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:23:34.031Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:23:34.031Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:23:34.031Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:23:34.031Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:23:34.031Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (46037.208 ms) ====== [2025-09-25T02:23:34.031Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-25T02:23:34.031Z] GC before operation: completed in 170.839 ms, heap usage 194.477 MB -> 95.822 MB. [2025-09-25T02:23:41.126Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:23:48.269Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:23:55.420Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:24:02.596Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:24:06.336Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:24:10.113Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:24:14.744Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:24:18.468Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:24:19.176Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:24:19.176Z] The best model improves the baseline by 14.34%. [2025-09-25T02:24:19.786Z] Top recommended movies for user id 72: [2025-09-25T02:24:19.786Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:24:19.786Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:24:19.786Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:24:19.786Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:24:19.786Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:24:19.786Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (45630.683 ms) ====== [2025-09-25T02:24:19.786Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-25T02:24:19.786Z] GC before operation: completed in 164.896 ms, heap usage 169.092 MB -> 89.444 MB. [2025-09-25T02:24:26.998Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:24:34.090Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:24:41.235Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:24:48.353Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:24:52.084Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:24:56.756Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:25:00.484Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:25:05.164Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:25:05.517Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:25:05.517Z] The best model improves the baseline by 14.34%. [2025-09-25T02:25:05.985Z] Top recommended movies for user id 72: [2025-09-25T02:25:05.985Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:25:05.985Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:25:05.985Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:25:05.985Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:25:05.985Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:25:05.985Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (46058.663 ms) ====== [2025-09-25T02:25:05.985Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-25T02:25:05.985Z] GC before operation: completed in 168.216 ms, heap usage 121.964 MB -> 97.207 MB. [2025-09-25T02:25:13.086Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:25:20.202Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:25:27.347Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:25:34.558Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:25:38.307Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:25:42.037Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:25:46.764Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:25:50.567Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:25:50.897Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:25:50.897Z] The best model improves the baseline by 14.34%. [2025-09-25T02:25:51.600Z] Top recommended movies for user id 72: [2025-09-25T02:25:51.601Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:25:51.601Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:25:51.601Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:25:51.601Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:25:51.601Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:25:51.601Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (45327.054 ms) ====== [2025-09-25T02:25:51.601Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-25T02:25:51.978Z] GC before operation: completed in 174.558 ms, heap usage 219.109 MB -> 89.476 MB. [2025-09-25T02:25:59.218Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:26:05.091Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:26:12.306Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:26:19.898Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:26:23.707Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:26:28.797Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:26:32.923Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:26:37.846Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:26:39.016Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:26:39.016Z] The best model improves the baseline by 14.34%. [2025-09-25T02:26:39.016Z] Top recommended movies for user id 72: [2025-09-25T02:26:39.016Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:26:39.016Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:26:39.016Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:26:39.016Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:26:39.016Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:26:39.016Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (47410.486 ms) ====== [2025-09-25T02:26:39.016Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-25T02:26:39.451Z] GC before operation: completed in 175.173 ms, heap usage 308.299 MB -> 89.684 MB. [2025-09-25T02:26:46.664Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-25T02:26:55.779Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-25T02:27:03.363Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-25T02:27:10.584Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-25T02:27:15.283Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-25T02:27:20.343Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-25T02:27:25.144Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-25T02:27:29.872Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-25T02:27:29.872Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-25T02:27:29.872Z] The best model improves the baseline by 14.34%. [2025-09-25T02:27:29.872Z] Top recommended movies for user id 72: [2025-09-25T02:27:29.872Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-25T02:27:29.872Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-25T02:27:29.872Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-25T02:27:29.872Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-25T02:27:29.872Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-25T02:27:29.872Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (50997.418 ms) ====== [2025-09-25T02:27:30.574Z] ----------------------------------- [2025-09-25T02:27:30.574Z] renaissance-movie-lens_0_PASSED [2025-09-25T02:27:30.574Z] ----------------------------------- [2025-09-25T02:27:31.239Z] [2025-09-25T02:27:31.239Z] TEST TEARDOWN: [2025-09-25T02:27:31.239Z] Nothing to be done for teardown. [2025-09-25T02:27:31.239Z] renaissance-movie-lens_0 Finish Time: Thu Sep 25 02:27:31 2025 Epoch Time (ms): 1758767251118