[2025-09-04T03:55:53.776Z] Running test renaissance-movie-lens_0 ... [2025-09-04T03:55:53.776Z] =============================================== [2025-09-04T03:55:53.776Z] renaissance-movie-lens_0 Start Time: Thu Sep 4 03:55:53 2025 Epoch Time (ms): 1756958153727 [2025-09-04T03:55:54.417Z] variation: NoOptions [2025-09-04T03:55:54.417Z] JVM_OPTIONS: [2025-09-04T03:55:54.417Z] { \ [2025-09-04T03:55:54.417Z] echo ""; echo "TEST SETUP:"; \ [2025-09-04T03:55:54.417Z] echo "Nothing to be done for setup."; \ [2025-09-04T03:55:54.417Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17569548563617/renaissance-movie-lens_0"; \ [2025-09-04T03:55:54.418Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17569548563617/renaissance-movie-lens_0"; \ [2025-09-04T03:55:54.418Z] echo ""; echo "TESTING:"; \ [2025-09-04T03:55:54.418Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_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_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17569548563617/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-04T03:55:54.418Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17569548563617/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-04T03:55:54.418Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-04T03:55:54.418Z] echo "Nothing to be done for teardown."; \ [2025-09-04T03:55:54.418Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17569548563617/TestTargetResult"; [2025-09-04T03:55:54.418Z] [2025-09-04T03:55:54.418Z] TEST SETUP: [2025-09-04T03:55:54.418Z] Nothing to be done for setup. [2025-09-04T03:55:54.418Z] [2025-09-04T03:55:54.418Z] TESTING: [2025-09-04T03:56:01.737Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-09-04T03:56:10.554Z] 03:56:10.263 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. [2025-09-04T03:56:13.897Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-04T03:56:15.277Z] Training: 60056, validation: 20285, test: 19854 [2025-09-04T03:56:15.277Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-04T03:56:15.931Z] GC before operation: completed in 369.762 ms, heap usage 203.991 MB -> 75.525 MB. [2025-09-04T03:56:26.462Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:56:32.450Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:56:40.274Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T03:56:46.406Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T03:56:51.596Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T03:56:54.591Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T03:56:59.399Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T03:57:02.418Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T03:57:02.418Z] 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. [2025-09-04T03:57:03.030Z] The best model improves the baseline by 14.34%. [2025-09-04T03:57:03.030Z] Top recommended movies for user id 72: [2025-09-04T03:57:03.030Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T03:57:03.030Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T03:57:03.030Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T03:57:03.030Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T03:57:03.030Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T03:57:03.030Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (47439.016 ms) ====== [2025-09-04T03:57:03.030Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-04T03:57:03.030Z] GC before operation: completed in 260.049 ms, heap usage 191.358 MB -> 99.205 MB. [2025-09-04T03:57:09.512Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:57:14.380Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:57:19.257Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T03:57:25.242Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T03:57:28.284Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T03:57:32.097Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T03:57:35.081Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T03:57:38.927Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T03:57:39.549Z] 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. [2025-09-04T03:57:39.549Z] The best model improves the baseline by 14.34%. [2025-09-04T03:57:40.169Z] Top recommended movies for user id 72: [2025-09-04T03:57:40.169Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T03:57:40.169Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T03:57:40.169Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T03:57:40.169Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T03:57:40.169Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T03:57:40.169Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (36831.243 ms) ====== [2025-09-04T03:57:40.169Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-04T03:57:40.169Z] GC before operation: completed in 234.794 ms, heap usage 182.460 MB -> 87.686 MB. [2025-09-04T03:57:46.388Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:57:53.949Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:57:59.467Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T03:58:05.492Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T03:58:09.604Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T03:58:12.585Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T03:58:16.457Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T03:58:20.369Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T03:58:20.369Z] 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. [2025-09-04T03:58:20.369Z] The best model improves the baseline by 14.34%. [2025-09-04T03:58:21.032Z] Top recommended movies for user id 72: [2025-09-04T03:58:21.032Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T03:58:21.032Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T03:58:21.032Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T03:58:21.032Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T03:58:21.032Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T03:58:21.032Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (40386.181 ms) ====== [2025-09-04T03:58:21.032Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-04T03:58:21.032Z] GC before operation: completed in 297.117 ms, heap usage 409.316 MB -> 88.781 MB. [2025-09-04T03:58:27.145Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:58:34.741Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:58:40.745Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T03:58:46.808Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T03:58:51.045Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T03:58:53.118Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T03:58:57.161Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T03:58:59.288Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T03:58:59.964Z] 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. [2025-09-04T03:58:59.964Z] The best model improves the baseline by 14.34%. [2025-09-04T03:59:00.622Z] Top recommended movies for user id 72: [2025-09-04T03:59:00.622Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T03:59:00.622Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T03:59:00.622Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T03:59:00.622Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T03:59:00.622Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T03:59:00.622Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (39498.875 ms) ====== [2025-09-04T03:59:00.622Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-04T03:59:01.261Z] GC before operation: completed in 417.560 ms, heap usage 284.121 MB -> 88.749 MB. [2025-09-04T03:59:07.753Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:59:15.341Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:59:20.457Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T03:59:27.008Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T03:59:29.435Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T03:59:33.035Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T03:59:35.158Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T03:59:39.009Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T03:59:39.009Z] 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. [2025-09-04T03:59:39.009Z] The best model improves the baseline by 14.34%. [2025-09-04T03:59:40.046Z] Top recommended movies for user id 72: [2025-09-04T03:59:40.046Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T03:59:40.046Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T03:59:40.046Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T03:59:40.046Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T03:59:40.046Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T03:59:40.046Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (38542.213 ms) ====== [2025-09-04T03:59:40.046Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-04T03:59:40.046Z] GC before operation: completed in 232.862 ms, heap usage 284.070 MB -> 88.737 MB. [2025-09-04T03:59:44.969Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T03:59:51.080Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T03:59:57.410Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:00:04.930Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:00:08.161Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:00:11.995Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:00:15.978Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:00:18.888Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:00:18.888Z] 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. [2025-09-04T04:00:18.888Z] The best model improves the baseline by 14.34%. [2025-09-04T04:00:19.592Z] Top recommended movies for user id 72: [2025-09-04T04:00:19.592Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:00:19.592Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:00:19.592Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:00:19.592Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:00:19.593Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:00:19.593Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (39544.007 ms) ====== [2025-09-04T04:00:19.593Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-04T04:00:19.593Z] GC before operation: completed in 329.978 ms, heap usage 269.459 MB -> 89.039 MB. [2025-09-04T04:00:25.807Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:00:31.005Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:00:35.944Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:00:39.779Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:00:42.779Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:00:46.695Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:00:48.913Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:00:52.268Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:00:53.004Z] 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. [2025-09-04T04:00:53.004Z] The best model improves the baseline by 14.34%. [2025-09-04T04:00:53.004Z] Top recommended movies for user id 72: [2025-09-04T04:00:53.004Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:00:53.004Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:00:53.004Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:00:53.004Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:00:53.004Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:00:53.004Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (33383.775 ms) ====== [2025-09-04T04:00:53.004Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-04T04:00:53.004Z] GC before operation: completed in 309.133 ms, heap usage 141.896 MB -> 88.863 MB. [2025-09-04T04:00:57.148Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:01:02.140Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:01:06.608Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:01:10.457Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:01:14.278Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:01:17.520Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:01:19.678Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:01:21.938Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:01:22.638Z] 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. [2025-09-04T04:01:22.638Z] The best model improves the baseline by 14.34%. [2025-09-04T04:01:22.638Z] Top recommended movies for user id 72: [2025-09-04T04:01:22.638Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:01:22.638Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:01:22.638Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:01:22.638Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:01:22.638Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:01:22.638Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (29420.300 ms) ====== [2025-09-04T04:01:22.638Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-04T04:01:22.638Z] GC before operation: completed in 184.245 ms, heap usage 356.642 MB -> 89.483 MB. [2025-09-04T04:01:27.815Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:01:31.923Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:01:36.836Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:01:40.599Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:01:42.800Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:01:45.721Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:01:48.730Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:01:50.853Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:01:51.478Z] 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. [2025-09-04T04:01:51.479Z] The best model improves the baseline by 14.34%. [2025-09-04T04:01:51.479Z] Top recommended movies for user id 72: [2025-09-04T04:01:51.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:01:51.479Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:01:51.479Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:01:51.479Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:01:51.479Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:01:51.479Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (28855.420 ms) ====== [2025-09-04T04:01:51.479Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-04T04:01:52.122Z] GC before operation: completed in 198.379 ms, heap usage 266.697 MB -> 89.270 MB. [2025-09-04T04:01:55.965Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:01:59.249Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:02:04.122Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:02:08.005Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:02:10.907Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:02:12.954Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:02:14.988Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:02:17.047Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:02:17.659Z] 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. [2025-09-04T04:02:17.659Z] The best model improves the baseline by 14.34%. [2025-09-04T04:02:18.307Z] Top recommended movies for user id 72: [2025-09-04T04:02:18.308Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:02:18.308Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:02:18.308Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:02:18.308Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:02:18.308Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:02:18.308Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (26147.133 ms) ====== [2025-09-04T04:02:18.308Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-04T04:02:18.308Z] GC before operation: completed in 260.214 ms, heap usage 248.270 MB -> 89.391 MB. [2025-09-04T04:02:22.068Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:02:25.843Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:02:30.607Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:02:35.329Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:02:37.370Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:02:40.718Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:02:42.779Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:02:44.955Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:02:45.591Z] 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. [2025-09-04T04:02:45.591Z] The best model improves the baseline by 14.34%. [2025-09-04T04:02:45.591Z] Top recommended movies for user id 72: [2025-09-04T04:02:45.591Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:02:45.591Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:02:45.591Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:02:45.591Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:02:45.591Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:02:45.591Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27150.388 ms) ====== [2025-09-04T04:02:45.591Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-04T04:02:45.591Z] GC before operation: completed in 255.526 ms, heap usage 283.901 MB -> 89.093 MB. [2025-09-04T04:02:49.392Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:02:54.100Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:02:58.938Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:03:02.705Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:03:05.605Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:03:08.437Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:03:11.359Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:03:14.171Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:03:14.171Z] 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. [2025-09-04T04:03:14.171Z] The best model improves the baseline by 14.34%. [2025-09-04T04:03:14.854Z] Top recommended movies for user id 72: [2025-09-04T04:03:14.854Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:03:14.854Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:03:14.854Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:03:14.854Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:03:14.854Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:03:14.854Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (28890.768 ms) ====== [2025-09-04T04:03:14.854Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-04T04:03:14.854Z] GC before operation: completed in 291.138 ms, heap usage 258.031 MB -> 89.283 MB. [2025-09-04T04:03:19.660Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:03:23.467Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:03:27.418Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:03:32.246Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:03:34.270Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:03:37.088Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:03:39.939Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:03:41.993Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:03:41.993Z] 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. [2025-09-04T04:03:42.627Z] The best model improves the baseline by 14.34%. [2025-09-04T04:03:42.627Z] Top recommended movies for user id 72: [2025-09-04T04:03:42.627Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:03:42.627Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:03:42.627Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:03:42.627Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:03:42.627Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:03:42.627Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (27647.016 ms) ====== [2025-09-04T04:03:42.627Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-04T04:03:42.627Z] GC before operation: completed in 285.132 ms, heap usage 133.799 MB -> 89.174 MB. [2025-09-04T04:03:47.430Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:03:52.173Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:03:57.109Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:04:00.964Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:04:03.852Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:04:05.895Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:04:09.692Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:04:11.801Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:04:11.801Z] 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. [2025-09-04T04:04:12.645Z] The best model improves the baseline by 14.34%. [2025-09-04T04:04:12.645Z] Top recommended movies for user id 72: [2025-09-04T04:04:12.645Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:04:12.645Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:04:12.645Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:04:12.645Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:04:12.645Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:04:12.645Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (29434.814 ms) ====== [2025-09-04T04:04:12.645Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-04T04:04:12.645Z] GC before operation: completed in 307.040 ms, heap usage 411.763 MB -> 89.526 MB. [2025-09-04T04:04:17.539Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:04:21.275Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:04:26.041Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:04:29.844Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:04:32.892Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:04:35.735Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:04:37.860Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:04:40.736Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:04:40.736Z] 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. [2025-09-04T04:04:41.382Z] The best model improves the baseline by 14.34%. [2025-09-04T04:04:41.382Z] Top recommended movies for user id 72: [2025-09-04T04:04:41.382Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:04:41.382Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:04:41.382Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:04:41.382Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:04:41.382Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:04:41.382Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (28592.274 ms) ====== [2025-09-04T04:04:41.382Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-04T04:04:41.382Z] GC before operation: completed in 307.385 ms, heap usage 276.189 MB -> 89.585 MB. [2025-09-04T04:04:46.099Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:04:49.907Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:04:54.772Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:04:58.658Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:05:02.571Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:05:04.689Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:05:08.524Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:05:11.446Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:05:11.446Z] 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. [2025-09-04T04:05:11.446Z] The best model improves the baseline by 14.34%. [2025-09-04T04:05:11.446Z] Top recommended movies for user id 72: [2025-09-04T04:05:11.446Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:05:11.446Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:05:11.446Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:05:11.446Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:05:11.446Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:05:11.446Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (30056.247 ms) ====== [2025-09-04T04:05:11.446Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-04T04:05:12.054Z] GC before operation: completed in 245.471 ms, heap usage 211.267 MB -> 89.245 MB. [2025-09-04T04:05:15.804Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:05:19.605Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:05:24.608Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:05:29.452Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:05:31.571Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:05:34.422Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:05:37.381Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:05:40.290Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:05:40.290Z] 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. [2025-09-04T04:05:40.290Z] The best model improves the baseline by 14.34%. [2025-09-04T04:05:41.148Z] Top recommended movies for user id 72: [2025-09-04T04:05:41.148Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:05:41.148Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:05:41.148Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:05:41.148Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:05:41.148Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:05:41.148Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (28864.422 ms) ====== [2025-09-04T04:05:41.148Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-04T04:05:41.148Z] GC before operation: completed in 287.752 ms, heap usage 146.637 MB -> 89.317 MB. [2025-09-04T04:05:44.932Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:05:49.728Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:05:55.807Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:05:59.673Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:06:02.543Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:06:05.484Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:06:07.536Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:06:09.573Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:06:10.211Z] 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. [2025-09-04T04:06:10.211Z] The best model improves the baseline by 14.34%. [2025-09-04T04:06:10.843Z] Top recommended movies for user id 72: [2025-09-04T04:06:10.843Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:06:10.843Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:06:10.843Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:06:10.843Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:06:10.843Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:06:10.843Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (29561.448 ms) ====== [2025-09-04T04:06:10.843Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-04T04:06:10.843Z] GC before operation: completed in 248.592 ms, heap usage 357.455 MB -> 89.533 MB. [2025-09-04T04:06:14.580Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:06:18.352Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:06:24.282Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:06:27.681Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:06:30.569Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:06:32.637Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:06:35.555Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:06:38.431Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:06:39.045Z] 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. [2025-09-04T04:06:39.045Z] The best model improves the baseline by 14.34%. [2025-09-04T04:06:39.045Z] Top recommended movies for user id 72: [2025-09-04T04:06:39.045Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:06:39.045Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:06:39.045Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:06:39.045Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:06:39.045Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:06:39.045Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (28285.874 ms) ====== [2025-09-04T04:06:39.045Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-04T04:06:39.045Z] GC before operation: completed in 206.142 ms, heap usage 275.913 MB -> 89.442 MB. [2025-09-04T04:06:43.812Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-04T04:06:46.687Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-04T04:06:51.502Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-04T04:06:56.311Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-04T04:06:58.559Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-04T04:07:00.580Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-04T04:07:03.520Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-04T04:07:06.415Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-04T04:07:06.415Z] 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. [2025-09-04T04:07:06.415Z] The best model improves the baseline by 14.34%. [2025-09-04T04:07:07.067Z] Top recommended movies for user id 72: [2025-09-04T04:07:07.067Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-09-04T04:07:07.067Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-09-04T04:07:07.067Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-09-04T04:07:07.067Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-09-04T04:07:07.067Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-09-04T04:07:07.067Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (27548.973 ms) ====== [2025-09-04T04:07:07.689Z] ----------------------------------- [2025-09-04T04:07:07.690Z] renaissance-movie-lens_0_PASSED [2025-09-04T04:07:07.690Z] ----------------------------------- [2025-09-04T04:07:07.690Z] [2025-09-04T04:07:07.690Z] TEST TEARDOWN: [2025-09-04T04:07:07.690Z] Nothing to be done for teardown. [2025-09-04T04:07:07.690Z] renaissance-movie-lens_0 Finish Time: Thu Sep 4 04:07:07 2025 Epoch Time (ms): 1756958827428