[2025-09-26T13:17:40.092Z] Running test renaissance-movie-lens_0 ... [2025-09-26T13:17:40.092Z] =============================================== [2025-09-26T13:17:40.092Z] renaissance-movie-lens_0 Start Time: Fri Sep 26 13:17:39 2025 Epoch Time (ms): 1758892659993 [2025-09-26T13:17:40.092Z] variation: NoOptions [2025-09-26T13:17:40.092Z] JVM_OPTIONS: [2025-09-26T13:17:40.092Z] { \ [2025-09-26T13:17:40.092Z] echo ""; echo "TEST SETUP:"; \ [2025-09-26T13:17:40.092Z] echo "Nothing to be done for setup."; \ [2025-09-26T13:17:40.092Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17588910811969/renaissance-movie-lens_0"; \ [2025-09-26T13:17:40.092Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17588910811969/renaissance-movie-lens_0"; \ [2025-09-26T13:17:40.092Z] echo ""; echo "TESTING:"; \ [2025-09-26T13:17:40.092Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17588910811969/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-26T13:17:40.092Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17588910811969/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-26T13:17:40.092Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-26T13:17:40.092Z] echo "Nothing to be done for teardown."; \ [2025-09-26T13:17:40.092Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17588910811969/TestTargetResult"; [2025-09-26T13:17:40.092Z] [2025-09-26T13:17:40.092Z] TEST SETUP: [2025-09-26T13:17:40.092Z] Nothing to be done for setup. [2025-09-26T13:17:40.092Z] [2025-09-26T13:17:40.092Z] TESTING: [2025-09-26T13:17:50.587Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-09-26T13:17:57.591Z] 13:17:56.766 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-09-26T13:17:59.711Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-26T13:18:00.790Z] Training: 60056, validation: 20285, test: 19854 [2025-09-26T13:18:00.790Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-26T13:18:00.790Z] GC before operation: completed in 152.886 ms, heap usage 251.174 MB -> 75.454 MB. [2025-09-26T13:18:09.371Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:18:12.964Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:18:16.605Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:18:20.211Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:18:23.004Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:18:24.565Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:18:27.357Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:18:28.905Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:18:28.905Z] 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. [2025-09-26T13:18:28.905Z] The best model improves the baseline by 14.34%. [2025-09-26T13:18:29.204Z] Top recommended movies for user id 72: [2025-09-26T13:18:29.204Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:18:29.204Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:18:29.204Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:18:29.204Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:18:29.204Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:18:29.204Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28422.482 ms) ====== [2025-09-26T13:18:29.204Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-26T13:18:29.508Z] GC before operation: completed in 136.354 ms, heap usage 117.750 MB -> 90.060 MB. [2025-09-26T13:18:32.303Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:18:35.099Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:18:37.888Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:18:40.004Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:18:41.604Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:18:43.144Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:18:44.204Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:18:45.753Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:18:45.753Z] 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. [2025-09-26T13:18:46.054Z] The best model improves the baseline by 14.34%. [2025-09-26T13:18:46.054Z] Top recommended movies for user id 72: [2025-09-26T13:18:46.054Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:18:46.054Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:18:46.054Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:18:46.054Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:18:46.054Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:18:46.054Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16708.177 ms) ====== [2025-09-26T13:18:46.054Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-26T13:18:46.356Z] GC before operation: completed in 149.365 ms, heap usage 385.754 MB -> 87.960 MB. [2025-09-26T13:18:48.478Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:18:51.271Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:18:53.390Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:18:55.507Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:18:57.053Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:18:58.117Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:18:59.665Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:19:01.218Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:19:01.517Z] 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. [2025-09-26T13:19:01.517Z] The best model improves the baseline by 14.34%. [2025-09-26T13:19:01.517Z] Top recommended movies for user id 72: [2025-09-26T13:19:01.517Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:19:01.517Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:19:01.517Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:19:01.517Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:19:01.517Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:19:01.518Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15372.680 ms) ====== [2025-09-26T13:19:01.518Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-26T13:19:01.826Z] GC before operation: completed in 138.528 ms, heap usage 246.257 MB -> 88.538 MB. [2025-09-26T13:19:04.000Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:19:06.119Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:19:08.905Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:19:10.451Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:19:11.994Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:19:13.058Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:19:14.602Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:19:15.662Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:19:15.961Z] 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. [2025-09-26T13:19:15.961Z] The best model improves the baseline by 14.34%. [2025-09-26T13:19:15.961Z] Top recommended movies for user id 72: [2025-09-26T13:19:15.961Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:19:15.961Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:19:15.961Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:19:15.961Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:19:15.961Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:19:15.961Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (14260.692 ms) ====== [2025-09-26T13:19:15.961Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-26T13:19:16.260Z] GC before operation: completed in 140.466 ms, heap usage 501.652 MB -> 92.441 MB. [2025-09-26T13:19:18.375Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:19:21.171Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:19:22.718Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:19:24.841Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:19:26.438Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:19:27.513Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:19:29.060Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:19:30.123Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:19:30.423Z] 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. [2025-09-26T13:19:30.423Z] The best model improves the baseline by 14.34%. [2025-09-26T13:19:30.423Z] Top recommended movies for user id 72: [2025-09-26T13:19:30.423Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:19:30.423Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:19:30.423Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:19:30.423Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:19:30.423Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:19:30.423Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14370.818 ms) ====== [2025-09-26T13:19:30.423Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-26T13:19:30.725Z] GC before operation: completed in 134.318 ms, heap usage 251.317 MB -> 88.788 MB. [2025-09-26T13:19:32.837Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:19:34.952Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:19:37.063Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:19:39.184Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:19:40.728Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:19:41.793Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:19:43.337Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:19:44.398Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:19:44.699Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-26T13:19:44.699Z] The best model improves the baseline by 14.34%. [2025-09-26T13:19:44.699Z] Top recommended movies for user id 72: [2025-09-26T13:19:44.699Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:19:44.699Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:19:44.699Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:19:44.699Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:19:44.699Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:19:44.699Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14147.832 ms) ====== [2025-09-26T13:19:44.699Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-26T13:19:45.003Z] GC before operation: completed in 141.374 ms, heap usage 142.690 MB -> 88.949 MB. [2025-09-26T13:19:47.143Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:19:49.261Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:19:51.374Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:19:52.918Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:19:54.467Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:19:55.534Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:19:57.079Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:19:58.149Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:19:58.450Z] 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. [2025-09-26T13:19:58.450Z] The best model improves the baseline by 14.34%. [2025-09-26T13:19:58.450Z] Top recommended movies for user id 72: [2025-09-26T13:19:58.450Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:19:58.450Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:19:58.450Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:19:58.450Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:19:58.450Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:19:58.450Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13505.269 ms) ====== [2025-09-26T13:19:58.450Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-26T13:19:58.752Z] GC before operation: completed in 130.534 ms, heap usage 435.944 MB -> 89.393 MB. [2025-09-26T13:20:00.864Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:20:02.985Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:20:05.102Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:20:06.647Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:20:07.788Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:20:09.330Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:20:10.393Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:20:11.941Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:20:11.941Z] 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. [2025-09-26T13:20:11.941Z] The best model improves the baseline by 14.34%. [2025-09-26T13:20:11.941Z] Top recommended movies for user id 72: [2025-09-26T13:20:11.941Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:20:11.941Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:20:11.941Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:20:11.941Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:20:11.941Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:20:11.941Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13404.061 ms) ====== [2025-09-26T13:20:11.941Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-26T13:20:12.244Z] GC before operation: completed in 131.871 ms, heap usage 248.429 MB -> 89.430 MB. [2025-09-26T13:20:14.353Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:20:16.463Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:20:18.575Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:20:20.690Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:20:22.235Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:20:23.300Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:20:24.363Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:20:25.916Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:20:25.916Z] 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. [2025-09-26T13:20:25.916Z] The best model improves the baseline by 14.34%. [2025-09-26T13:20:26.218Z] Top recommended movies for user id 72: [2025-09-26T13:20:26.218Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:20:26.218Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:20:26.218Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:20:26.218Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:20:26.218Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:20:26.218Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13956.038 ms) ====== [2025-09-26T13:20:26.218Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-26T13:20:26.218Z] GC before operation: completed in 136.109 ms, heap usage 193.446 MB -> 89.043 MB. [2025-09-26T13:20:28.343Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:20:30.482Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:20:32.597Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:20:34.711Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:20:35.778Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:20:36.841Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:20:38.387Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:20:39.453Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:20:39.752Z] 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. [2025-09-26T13:20:39.752Z] The best model improves the baseline by 14.34%. [2025-09-26T13:20:39.752Z] Top recommended movies for user id 72: [2025-09-26T13:20:39.752Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:20:39.752Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:20:39.752Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:20:39.752Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:20:39.752Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:20:39.752Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13609.745 ms) ====== [2025-09-26T13:20:39.752Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-26T13:20:40.054Z] GC before operation: completed in 139.284 ms, heap usage 203.076 MB -> 89.224 MB. [2025-09-26T13:20:42.170Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:20:44.285Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:20:46.400Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:20:47.944Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:20:49.012Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:20:50.612Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:20:51.671Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:20:52.731Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:20:53.031Z] 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. [2025-09-26T13:20:53.031Z] The best model improves the baseline by 14.34%. [2025-09-26T13:20:53.031Z] Top recommended movies for user id 72: [2025-09-26T13:20:53.031Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:20:53.031Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:20:53.031Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:20:53.031Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:20:53.031Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:20:53.031Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13100.055 ms) ====== [2025-09-26T13:20:53.031Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-26T13:20:53.334Z] GC before operation: completed in 133.482 ms, heap usage 398.355 MB -> 89.423 MB. [2025-09-26T13:20:55.454Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:20:56.999Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:20:59.108Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:21:01.221Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:21:02.282Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:21:03.346Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:21:04.407Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:21:05.955Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:21:05.956Z] 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. [2025-09-26T13:21:05.956Z] The best model improves the baseline by 14.34%. [2025-09-26T13:21:05.956Z] Top recommended movies for user id 72: [2025-09-26T13:21:05.956Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:21:05.956Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:21:05.956Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:21:05.956Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:21:05.956Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:21:05.956Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (12764.327 ms) ====== [2025-09-26T13:21:05.956Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-26T13:21:06.255Z] GC before operation: completed in 137.511 ms, heap usage 628.638 MB -> 93.160 MB. [2025-09-26T13:21:08.367Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:21:10.481Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:21:12.022Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:21:14.181Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:21:15.242Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:21:16.787Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:21:17.855Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:21:18.919Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:21:19.219Z] 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. [2025-09-26T13:21:19.219Z] The best model improves the baseline by 14.34%. [2025-09-26T13:21:19.219Z] Top recommended movies for user id 72: [2025-09-26T13:21:19.219Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:21:19.219Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:21:19.219Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:21:19.219Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:21:19.219Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:21:19.219Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13228.189 ms) ====== [2025-09-26T13:21:19.219Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-26T13:21:19.521Z] GC before operation: completed in 128.506 ms, heap usage 170.597 MB -> 89.381 MB. [2025-09-26T13:21:21.638Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:21:23.750Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:21:25.879Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:21:27.426Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:21:28.971Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:21:30.032Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:21:31.093Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:21:32.154Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:21:32.454Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-09-26T13:21:32.454Z] The best model improves the baseline by 14.34%. [2025-09-26T13:21:32.454Z] Top recommended movies for user id 72: [2025-09-26T13:21:32.454Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:21:32.454Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:21:32.454Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:21:32.454Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:21:32.454Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:21:32.454Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12987.496 ms) ====== [2025-09-26T13:21:32.454Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-26T13:21:32.758Z] GC before operation: completed in 134.416 ms, heap usage 754.497 MB -> 94.526 MB. [2025-09-26T13:21:34.926Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:21:36.468Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:21:38.585Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:21:40.137Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:21:41.680Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:21:42.739Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:21:43.803Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:21:44.868Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:21:45.169Z] 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. [2025-09-26T13:21:45.169Z] The best model improves the baseline by 14.34%. [2025-09-26T13:21:45.169Z] Top recommended movies for user id 72: [2025-09-26T13:21:45.169Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:21:45.169Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:21:45.169Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:21:45.169Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:21:45.169Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:21:45.169Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12655.778 ms) ====== [2025-09-26T13:21:45.169Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-26T13:21:45.473Z] GC before operation: completed in 131.760 ms, heap usage 409.390 MB -> 89.767 MB. [2025-09-26T13:21:47.588Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:21:49.151Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:21:51.272Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:21:52.818Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:21:54.418Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:21:55.479Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:21:56.544Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:21:57.613Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:21:57.916Z] 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. [2025-09-26T13:21:57.916Z] The best model improves the baseline by 14.34%. [2025-09-26T13:21:57.916Z] Top recommended movies for user id 72: [2025-09-26T13:21:57.916Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:21:57.916Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:21:57.916Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:21:57.916Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:21:57.916Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:21:57.916Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12589.066 ms) ====== [2025-09-26T13:21:57.916Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-26T13:21:58.218Z] GC before operation: completed in 137.261 ms, heap usage 546.412 MB -> 93.117 MB. [2025-09-26T13:22:00.334Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:22:01.879Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:22:03.988Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:22:05.537Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:22:07.083Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:22:08.145Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:22:09.207Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:22:10.752Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:22:10.752Z] 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. [2025-09-26T13:22:10.752Z] The best model improves the baseline by 14.34%. [2025-09-26T13:22:10.752Z] Top recommended movies for user id 72: [2025-09-26T13:22:10.752Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:22:10.752Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:22:10.752Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:22:10.752Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:22:10.752Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:22:10.752Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (12655.616 ms) ====== [2025-09-26T13:22:10.752Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-26T13:22:11.055Z] GC before operation: completed in 131.147 ms, heap usage 213.740 MB -> 89.418 MB. [2025-09-26T13:22:13.167Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:22:15.281Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:22:17.418Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:22:18.964Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:22:20.027Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:22:21.090Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:22:22.632Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:22:23.699Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:22:24.001Z] 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. [2025-09-26T13:22:24.001Z] The best model improves the baseline by 14.34%. [2025-09-26T13:22:24.001Z] Top recommended movies for user id 72: [2025-09-26T13:22:24.001Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:22:24.001Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:22:24.001Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:22:24.001Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:22:24.001Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:22:24.001Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13082.756 ms) ====== [2025-09-26T13:22:24.001Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-26T13:22:24.001Z] GC before operation: completed in 125.444 ms, heap usage 211.100 MB -> 89.240 MB. [2025-09-26T13:22:26.115Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:22:28.232Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:22:30.348Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:22:31.892Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:22:32.955Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:22:34.505Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:22:35.563Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:22:36.684Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:22:36.684Z] 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. [2025-09-26T13:22:36.684Z] The best model improves the baseline by 14.34%. [2025-09-26T13:22:36.984Z] Top recommended movies for user id 72: [2025-09-26T13:22:36.984Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:22:36.984Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:22:36.984Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:22:36.984Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:22:36.984Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:22:36.984Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12787.867 ms) ====== [2025-09-26T13:22:36.984Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-26T13:22:36.984Z] GC before operation: completed in 131.207 ms, heap usage 116.086 MB -> 92.960 MB. [2025-09-26T13:22:39.098Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-26T13:22:41.211Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-26T13:22:42.752Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-26T13:22:44.859Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-26T13:22:45.926Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-26T13:22:46.986Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-26T13:22:48.045Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-26T13:22:49.178Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-26T13:22:49.480Z] 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. [2025-09-26T13:22:49.480Z] The best model improves the baseline by 14.34%. [2025-09-26T13:22:49.480Z] Top recommended movies for user id 72: [2025-09-26T13:22:49.480Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-26T13:22:49.480Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-26T13:22:49.480Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-26T13:22:49.480Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-26T13:22:49.480Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-26T13:22:49.480Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12514.120 ms) ====== [2025-09-26T13:22:50.133Z] ----------------------------------- [2025-09-26T13:22:50.133Z] renaissance-movie-lens_0_PASSED [2025-09-26T13:22:50.133Z] ----------------------------------- [2025-09-26T13:22:50.133Z] [2025-09-26T13:22:50.133Z] TEST TEARDOWN: [2025-09-26T13:22:50.133Z] Nothing to be done for teardown. [2025-09-26T13:22:50.133Z] renaissance-movie-lens_0 Finish Time: Fri Sep 26 13:22:49 2025 Epoch Time (ms): 1758892969883