[2025-05-28T22:41:40.999Z] Running test renaissance-movie-lens_0 ... [2025-05-28T22:41:40.999Z] =============================================== [2025-05-28T22:41:40.999Z] renaissance-movie-lens_0 Start Time: Wed May 28 22:41:40 2025 Epoch Time (ms): 1748472100305 [2025-05-28T22:41:40.999Z] variation: NoOptions [2025-05-28T22:41:40.999Z] JVM_OPTIONS: [2025-05-28T22:41:40.999Z] { \ [2025-05-28T22:41:40.999Z] echo ""; echo "TEST SETUP:"; \ [2025-05-28T22:41:40.999Z] echo "Nothing to be done for setup."; \ [2025-05-28T22:41:40.999Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17484696472907/renaissance-movie-lens_0"; \ [2025-05-28T22:41:40.999Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17484696472907/renaissance-movie-lens_0"; \ [2025-05-28T22:41:40.999Z] echo ""; echo "TESTING:"; \ [2025-05-28T22:41:40.999Z] "/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_17484696472907/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-05-28T22:41:40.999Z] 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_17484696472907/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-05-28T22:41:40.999Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-05-28T22:41:40.999Z] echo "Nothing to be done for teardown."; \ [2025-05-28T22:41:40.999Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17484696472907/TestTargetResult"; [2025-05-28T22:41:40.999Z] [2025-05-28T22:41:40.999Z] TEST SETUP: [2025-05-28T22:41:40.999Z] Nothing to be done for setup. [2025-05-28T22:41:40.999Z] [2025-05-28T22:41:40.999Z] TESTING: [2025-05-28T22:41:46.872Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-05-28T22:41:55.727Z] 22:41:54.863 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. [2025-05-28T22:41:59.468Z] Got 100004 ratings from 671 users on 9066 movies. [2025-05-28T22:41:59.792Z] Training: 60056, validation: 20285, test: 19854 [2025-05-28T22:41:59.792Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-05-28T22:41:59.792Z] GC before operation: completed in 158.224 ms, heap usage 201.060 MB -> 75.694 MB. [2025-05-28T22:42:08.656Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:42:14.534Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:42:19.245Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:42:23.944Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:42:26.169Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:42:29.080Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:42:31.328Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:42:33.542Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:42:33.865Z] 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. [2025-05-28T22:42:34.198Z] The best model improves the baseline by 14.34%. [2025-05-28T22:42:34.198Z] Top recommended movies for user id 72: [2025-05-28T22:42:34.198Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:42:34.198Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:42:34.198Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:42:34.198Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:42:34.198Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:42:34.198Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (34485.609 ms) ====== [2025-05-28T22:42:34.198Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-05-28T22:42:34.520Z] GC before operation: completed in 210.338 ms, heap usage 151.176 MB -> 96.822 MB. [2025-05-28T22:42:38.291Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:42:42.034Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:42:45.813Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:42:48.731Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:42:50.365Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:42:51.998Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:42:54.224Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:42:55.852Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:42:56.175Z] 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. [2025-05-28T22:42:56.497Z] The best model improves the baseline by 14.34%. [2025-05-28T22:42:56.497Z] Top recommended movies for user id 72: [2025-05-28T22:42:56.497Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:42:56.497Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:42:56.497Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:42:56.497Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:42:56.497Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:42:56.497Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (22034.623 ms) ====== [2025-05-28T22:42:56.497Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-05-28T22:42:56.821Z] GC before operation: completed in 203.412 ms, heap usage 445.368 MB -> 88.263 MB. [2025-05-28T22:42:59.786Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:43:03.518Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:43:06.506Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:43:10.249Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:43:11.382Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:43:13.622Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:43:15.849Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:43:18.070Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:43:18.070Z] 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. [2025-05-28T22:43:18.070Z] The best model improves the baseline by 14.34%. [2025-05-28T22:43:18.393Z] Top recommended movies for user id 72: [2025-05-28T22:43:18.393Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:43:18.393Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:43:18.393Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:43:18.393Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:43:18.393Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:43:18.393Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21542.789 ms) ====== [2025-05-28T22:43:18.393Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-05-28T22:43:18.393Z] GC before operation: completed in 184.890 ms, heap usage 188.943 MB -> 88.383 MB. [2025-05-28T22:43:21.317Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:43:24.225Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:43:27.981Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:43:30.896Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:43:32.526Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:43:34.166Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:43:36.388Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:43:38.020Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:43:38.020Z] 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. [2025-05-28T22:43:38.343Z] The best model improves the baseline by 14.34%. [2025-05-28T22:43:38.343Z] Top recommended movies for user id 72: [2025-05-28T22:43:38.343Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:43:38.343Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:43:38.343Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:43:38.343Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:43:38.343Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:43:38.343Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19937.103 ms) ====== [2025-05-28T22:43:38.343Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-05-28T22:43:38.666Z] GC before operation: completed in 190.987 ms, heap usage 168.747 MB -> 88.710 MB. [2025-05-28T22:43:41.610Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:43:45.347Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:43:48.261Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:43:51.180Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:43:52.812Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:43:54.443Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:43:56.667Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:43:58.301Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:43:58.301Z] 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. [2025-05-28T22:43:58.301Z] The best model improves the baseline by 14.34%. [2025-05-28T22:43:58.623Z] Top recommended movies for user id 72: [2025-05-28T22:43:58.623Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:43:58.623Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:43:58.623Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:43:58.623Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:43:58.623Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:43:58.623Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19989.744 ms) ====== [2025-05-28T22:43:58.623Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-05-28T22:43:58.945Z] GC before operation: completed in 175.375 ms, heap usage 427.729 MB -> 89.128 MB. [2025-05-28T22:44:01.940Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:44:04.856Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:44:08.608Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:44:10.829Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:44:12.462Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:44:14.095Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:44:16.318Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:44:17.957Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:44:18.281Z] 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. [2025-05-28T22:44:18.281Z] The best model improves the baseline by 14.34%. [2025-05-28T22:44:18.281Z] Top recommended movies for user id 72: [2025-05-28T22:44:18.281Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:44:18.281Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:44:18.281Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:44:18.281Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:44:18.281Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:44:18.281Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19540.689 ms) ====== [2025-05-28T22:44:18.281Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-05-28T22:44:18.602Z] GC before operation: completed in 177.525 ms, heap usage 384.746 MB -> 89.391 MB. [2025-05-28T22:44:21.513Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:44:24.428Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:44:28.234Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:44:30.456Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:44:32.674Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:44:33.798Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:44:36.014Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:44:37.646Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:44:37.646Z] 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. [2025-05-28T22:44:37.646Z] The best model improves the baseline by 14.34%. [2025-05-28T22:44:37.973Z] Top recommended movies for user id 72: [2025-05-28T22:44:37.973Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:44:37.973Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:44:37.973Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:44:37.973Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:44:37.973Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:44:37.973Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19446.892 ms) ====== [2025-05-28T22:44:37.973Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-05-28T22:44:38.301Z] GC before operation: completed in 190.349 ms, heap usage 667.315 MB -> 93.187 MB. [2025-05-28T22:44:41.271Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:44:43.489Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:44:46.406Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:44:49.325Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:44:50.957Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:44:52.615Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:44:54.865Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:44:56.500Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:44:56.869Z] 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. [2025-05-28T22:44:56.869Z] The best model improves the baseline by 14.34%. [2025-05-28T22:44:57.192Z] Top recommended movies for user id 72: [2025-05-28T22:44:57.192Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:44:57.192Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:44:57.192Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:44:57.193Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:44:57.193Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:44:57.193Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18974.137 ms) ====== [2025-05-28T22:44:57.193Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-05-28T22:44:57.193Z] GC before operation: completed in 166.047 ms, heap usage 312.681 MB -> 89.475 MB. [2025-05-28T22:45:00.106Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:45:03.020Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:45:06.750Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:45:09.667Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:45:11.296Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:45:13.520Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:45:15.152Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:45:17.378Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:45:17.378Z] 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. [2025-05-28T22:45:17.378Z] The best model improves the baseline by 14.34%. [2025-05-28T22:45:17.701Z] Top recommended movies for user id 72: [2025-05-28T22:45:17.701Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:45:17.701Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:45:17.701Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:45:17.701Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:45:17.701Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:45:17.701Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20367.688 ms) ====== [2025-05-28T22:45:17.701Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-05-28T22:45:17.701Z] GC before operation: completed in 157.592 ms, heap usage 221.326 MB -> 89.130 MB. [2025-05-28T22:45:21.511Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:45:24.430Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:45:28.187Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:45:31.102Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:45:32.733Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:45:34.371Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:45:36.008Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:45:38.229Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:45:38.229Z] 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. [2025-05-28T22:45:38.229Z] The best model improves the baseline by 14.34%. [2025-05-28T22:45:38.229Z] Top recommended movies for user id 72: [2025-05-28T22:45:38.229Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:45:38.229Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:45:38.229Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:45:38.229Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:45:38.229Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:45:38.229Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20511.293 ms) ====== [2025-05-28T22:45:38.229Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-05-28T22:45:38.550Z] GC before operation: completed in 173.980 ms, heap usage 405.256 MB -> 89.623 MB. [2025-05-28T22:45:41.463Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:45:44.407Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:45:47.330Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:45:50.336Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:45:51.508Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:45:53.731Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:45:55.370Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:45:57.007Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:45:57.007Z] 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. [2025-05-28T22:45:57.328Z] The best model improves the baseline by 14.34%. [2025-05-28T22:45:57.328Z] Top recommended movies for user id 72: [2025-05-28T22:45:57.329Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:45:57.329Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:45:57.329Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:45:57.329Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:45:57.329Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:45:57.329Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18864.372 ms) ====== [2025-05-28T22:45:57.329Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-05-28T22:45:57.654Z] GC before operation: completed in 154.737 ms, heap usage 112.944 MB -> 88.929 MB. [2025-05-28T22:46:00.595Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:46:03.507Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:46:05.730Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:46:08.647Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:46:10.277Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:46:11.908Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:46:13.542Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:46:15.198Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:46:15.198Z] 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. [2025-05-28T22:46:15.198Z] The best model improves the baseline by 14.34%. [2025-05-28T22:46:15.521Z] Top recommended movies for user id 72: [2025-05-28T22:46:15.521Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:46:15.521Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:46:15.521Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:46:15.521Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:46:15.521Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:46:15.521Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17889.701 ms) ====== [2025-05-28T22:46:15.521Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-05-28T22:46:15.521Z] GC before operation: completed in 162.417 ms, heap usage 605.530 MB -> 93.155 MB. [2025-05-28T22:46:18.449Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:46:21.374Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:46:24.299Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:46:26.560Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:46:28.195Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:46:29.839Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:46:31.483Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:46:33.113Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:46:33.435Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-05-28T22:46:33.436Z] The best model improves the baseline by 14.34%. [2025-05-28T22:46:33.760Z] Top recommended movies for user id 72: [2025-05-28T22:46:33.760Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:46:33.760Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:46:33.760Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:46:33.760Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:46:33.760Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:46:33.760Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18104.040 ms) ====== [2025-05-28T22:46:33.760Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-05-28T22:46:33.760Z] GC before operation: completed in 152.334 ms, heap usage 239.501 MB -> 89.474 MB. [2025-05-28T22:46:36.687Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:46:39.596Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:46:42.574Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:46:44.803Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:46:46.458Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:46:48.085Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:46:49.713Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:46:51.337Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:46:51.660Z] 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. [2025-05-28T22:46:51.660Z] The best model improves the baseline by 14.34%. [2025-05-28T22:46:51.982Z] Top recommended movies for user id 72: [2025-05-28T22:46:51.982Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:46:51.982Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:46:51.982Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:46:51.982Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:46:51.982Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:46:51.982Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18051.946 ms) ====== [2025-05-28T22:46:51.982Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-05-28T22:46:51.982Z] GC before operation: completed in 152.565 ms, heap usage 171.859 MB -> 89.190 MB. [2025-05-28T22:46:54.888Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:46:57.808Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:47:00.026Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:47:03.058Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:47:04.691Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:47:06.319Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:47:07.947Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:47:09.584Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:47:09.584Z] 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. [2025-05-28T22:47:09.584Z] The best model improves the baseline by 14.34%. [2025-05-28T22:47:09.905Z] Top recommended movies for user id 72: [2025-05-28T22:47:09.905Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:47:09.905Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:47:09.905Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:47:09.905Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:47:09.905Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:47:09.905Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17800.139 ms) ====== [2025-05-28T22:47:09.905Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-05-28T22:47:09.905Z] GC before operation: completed in 159.870 ms, heap usage 445.208 MB -> 93.004 MB. [2025-05-28T22:47:12.820Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:47:15.732Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:47:18.660Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:47:20.914Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:47:22.553Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:47:24.190Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:47:25.829Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:47:27.467Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:47:27.789Z] 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. [2025-05-28T22:47:27.789Z] The best model improves the baseline by 14.34%. [2025-05-28T22:47:27.789Z] Top recommended movies for user id 72: [2025-05-28T22:47:27.789Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:47:27.789Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:47:27.789Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:47:27.789Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:47:27.789Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:47:27.789Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17913.307 ms) ====== [2025-05-28T22:47:27.789Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-05-28T22:47:28.108Z] GC before operation: completed in 158.764 ms, heap usage 248.485 MB -> 89.325 MB. [2025-05-28T22:47:31.102Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:47:34.017Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:47:36.931Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:47:39.155Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:47:40.795Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:47:42.437Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:47:44.080Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:47:45.724Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:47:45.724Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-05-28T22:47:45.724Z] The best model improves the baseline by 14.34%. [2025-05-28T22:47:46.046Z] Top recommended movies for user id 72: [2025-05-28T22:47:46.046Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:47:46.046Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:47:46.046Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:47:46.046Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:47:46.046Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:47:46.046Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17935.878 ms) ====== [2025-05-28T22:47:46.046Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-05-28T22:47:46.046Z] GC before operation: completed in 157.983 ms, heap usage 388.671 MB -> 89.717 MB. [2025-05-28T22:47:48.969Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:47:51.964Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:47:54.876Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:47:57.166Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:47:58.793Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:48:01.026Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:48:02.666Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:48:03.795Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:48:04.119Z] 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. [2025-05-28T22:48:04.119Z] The best model improves the baseline by 14.34%. [2025-05-28T22:48:04.445Z] Top recommended movies for user id 72: [2025-05-28T22:48:04.445Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:48:04.445Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:48:04.445Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:48:04.445Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:48:04.445Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:48:04.445Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18259.219 ms) ====== [2025-05-28T22:48:04.445Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-05-28T22:48:04.445Z] GC before operation: completed in 156.487 ms, heap usage 411.771 MB -> 89.610 MB. [2025-05-28T22:48:07.361Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:48:10.301Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:48:13.217Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:48:15.440Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:48:17.072Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:48:18.706Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:48:20.342Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:48:22.049Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:48:22.049Z] 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. [2025-05-28T22:48:22.049Z] The best model improves the baseline by 14.34%. [2025-05-28T22:48:22.375Z] Top recommended movies for user id 72: [2025-05-28T22:48:22.375Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:48:22.375Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:48:22.375Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:48:22.375Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:48:22.375Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:48:22.375Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17756.577 ms) ====== [2025-05-28T22:48:22.375Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-05-28T22:48:22.375Z] GC before operation: completed in 152.026 ms, heap usage 181.158 MB -> 89.243 MB. [2025-05-28T22:48:25.289Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T22:48:28.209Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T22:48:31.158Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T22:48:33.379Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T22:48:35.013Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T22:48:36.140Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T22:48:38.391Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T22:48:39.552Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T22:48:39.876Z] 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. [2025-05-28T22:48:39.876Z] The best model improves the baseline by 14.34%. [2025-05-28T22:48:39.876Z] Top recommended movies for user id 72: [2025-05-28T22:48:39.876Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-05-28T22:48:39.876Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-05-28T22:48:39.876Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-05-28T22:48:39.876Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-05-28T22:48:39.876Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-05-28T22:48:39.876Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17515.891 ms) ====== [2025-05-28T22:48:40.572Z] ----------------------------------- [2025-05-28T22:48:40.572Z] renaissance-movie-lens_0_PASSED [2025-05-28T22:48:40.572Z] ----------------------------------- [2025-05-28T22:48:40.572Z] [2025-05-28T22:48:40.572Z] TEST TEARDOWN: [2025-05-28T22:48:40.572Z] Nothing to be done for teardown. [2025-05-28T22:48:40.572Z] renaissance-movie-lens_0 Finish Time: Wed May 28 22:48:40 2025 Epoch Time (ms): 1748472520427