[2025-05-28T23:02:22.921Z] Running test renaissance-movie-lens_0 ... [2025-05-28T23:02:22.921Z] =============================================== [2025-05-28T23:02:22.921Z] renaissance-movie-lens_0 Start Time: Wed May 28 23:02:21 2025 Epoch Time (ms): 1748473341511 [2025-05-28T23:02:22.921Z] variation: NoOptions [2025-05-28T23:02:22.921Z] JVM_OPTIONS: [2025-05-28T23:02:22.921Z] { \ [2025-05-28T23:02:22.921Z] echo ""; echo "TEST SETUP:"; \ [2025-05-28T23:02:22.921Z] echo "Nothing to be done for setup."; \ [2025-05-28T23:02:22.921Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17484688397500/renaissance-movie-lens_0"; \ [2025-05-28T23:02:22.921Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17484688397500/renaissance-movie-lens_0"; \ [2025-05-28T23:02:22.921Z] echo ""; echo "TESTING:"; \ [2025-05-28T23:02:22.921Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_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_riscv64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17484688397500/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-05-28T23:02:22.921Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17484688397500/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-05-28T23:02:22.921Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-05-28T23:02:22.921Z] echo "Nothing to be done for teardown."; \ [2025-05-28T23:02:22.921Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17484688397500/TestTargetResult"; [2025-05-28T23:02:22.921Z] [2025-05-28T23:02:22.921Z] TEST SETUP: [2025-05-28T23:02:22.921Z] Nothing to be done for setup. [2025-05-28T23:02:22.921Z] [2025-05-28T23:02:22.921Z] TESTING: [2025-05-28T23:02:46.788Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-05-28T23:03:20.081Z] 23:03:17.759 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-05-28T23:03:28.969Z] Got 100004 ratings from 671 users on 9066 movies. [2025-05-28T23:03:31.918Z] Training: 60056, validation: 20285, test: 19854 [2025-05-28T23:03:31.918Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-05-28T23:03:32.244Z] GC before operation: completed in 588.904 ms, heap usage 389.469 MB -> 76.257 MB. [2025-05-28T23:04:00.791Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:04:16.612Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:04:29.675Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:04:42.752Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:04:50.450Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:04:57.671Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:05:04.890Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:05:10.765Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:05:12.421Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:05:12.421Z] The best model improves the baseline by 14.52%. [2025-05-28T23:05:13.580Z] Top recommended movies for user id 72: [2025-05-28T23:05:13.580Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:05:13.580Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:05:13.580Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:05:13.580Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:05:13.580Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:05:13.580Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (101016.127 ms) ====== [2025-05-28T23:05:13.580Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-05-28T23:05:14.300Z] GC before operation: completed in 1091.022 ms, heap usage 509.421 MB -> 88.664 MB. [2025-05-28T23:05:27.938Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:05:38.862Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:05:47.734Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:05:58.526Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:06:04.392Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:06:10.256Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:06:16.828Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:06:22.689Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:06:23.828Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:06:24.154Z] The best model improves the baseline by 14.52%. [2025-05-28T23:06:24.853Z] Top recommended movies for user id 72: [2025-05-28T23:06:24.853Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:06:24.853Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:06:24.853Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:06:24.853Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:06:24.853Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:06:24.853Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (70296.846 ms) ====== [2025-05-28T23:06:24.853Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-05-28T23:06:25.578Z] GC before operation: completed in 978.530 ms, heap usage 377.392 MB -> 89.275 MB. [2025-05-28T23:06:36.347Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:06:47.104Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:06:56.388Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:07:05.269Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:07:09.987Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:07:17.222Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:07:23.091Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:07:27.832Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:07:28.532Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:07:28.532Z] The best model improves the baseline by 14.52%. [2025-05-28T23:07:29.680Z] Top recommended movies for user id 72: [2025-05-28T23:07:29.680Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:07:29.680Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:07:29.680Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:07:29.680Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:07:29.680Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:07:29.680Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (63835.392 ms) ====== [2025-05-28T23:07:29.680Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-05-28T23:07:30.404Z] GC before operation: completed in 884.617 ms, heap usage 136.860 MB -> 89.619 MB. [2025-05-28T23:07:40.147Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:07:50.912Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:07:59.766Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:08:08.601Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:08:13.309Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:08:19.786Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:08:25.650Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:08:31.559Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:08:31.559Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:08:31.559Z] The best model improves the baseline by 14.52%. [2025-05-28T23:08:32.257Z] Top recommended movies for user id 72: [2025-05-28T23:08:32.257Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:08:32.592Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:08:32.593Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:08:32.593Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:08:32.593Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:08:32.593Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (61965.050 ms) ====== [2025-05-28T23:08:32.593Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-05-28T23:08:33.315Z] GC before operation: completed in 935.182 ms, heap usage 902.007 MB -> 94.246 MB. [2025-05-28T23:08:44.074Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:08:52.937Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:09:02.374Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:09:09.602Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:09:15.465Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:09:21.331Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:09:27.178Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:09:33.041Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:09:33.364Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:09:33.364Z] The best model improves the baseline by 14.52%. [2025-05-28T23:09:34.508Z] Top recommended movies for user id 72: [2025-05-28T23:09:34.508Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:09:34.508Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:09:34.508Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:09:34.508Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:09:34.508Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:09:34.508Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (60887.301 ms) ====== [2025-05-28T23:09:34.508Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-05-28T23:09:35.208Z] GC before operation: completed in 774.432 ms, heap usage 207.243 MB -> 89.952 MB. [2025-05-28T23:09:44.860Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:09:53.705Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:10:02.556Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:10:11.468Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:10:15.269Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:10:20.727Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:10:26.579Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:10:31.307Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:10:32.005Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:10:32.005Z] The best model improves the baseline by 14.52%. [2025-05-28T23:10:32.779Z] Top recommended movies for user id 72: [2025-05-28T23:10:32.779Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:10:32.779Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:10:32.779Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:10:32.779Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:10:32.779Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:10:32.779Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (57763.946 ms) ====== [2025-05-28T23:10:32.779Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-05-28T23:10:33.476Z] GC before operation: completed in 809.632 ms, heap usage 1.091 GB -> 95.739 MB. [2025-05-28T23:10:44.254Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:10:51.479Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:11:00.818Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:11:08.214Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:11:14.072Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:11:18.781Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:11:23.488Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:11:28.208Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:11:29.336Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:11:29.336Z] The best model improves the baseline by 14.52%. [2025-05-28T23:11:30.034Z] Top recommended movies for user id 72: [2025-05-28T23:11:30.034Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:11:30.034Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:11:30.034Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:11:30.034Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:11:30.034Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:11:30.034Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (56429.370 ms) ====== [2025-05-28T23:11:30.034Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-05-28T23:11:30.740Z] GC before operation: completed in 761.388 ms, heap usage 736.354 MB -> 94.168 MB. [2025-05-28T23:11:40.483Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:11:47.698Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:11:56.574Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:12:03.809Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:12:08.532Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:12:14.390Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:12:19.020Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:12:24.896Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:12:25.227Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:12:25.555Z] The best model improves the baseline by 14.52%. [2025-05-28T23:12:26.252Z] Top recommended movies for user id 72: [2025-05-28T23:12:26.252Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:12:26.252Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:12:26.252Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:12:26.252Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:12:26.252Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:12:26.252Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (55497.750 ms) ====== [2025-05-28T23:12:26.252Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-05-28T23:12:26.969Z] GC before operation: completed in 676.207 ms, heap usage 307.965 MB -> 90.720 MB. [2025-05-28T23:12:35.830Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:12:44.697Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:12:53.551Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:13:02.969Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:13:07.694Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:13:13.559Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:13:19.425Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:13:24.136Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:13:25.270Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:13:25.270Z] The best model improves the baseline by 14.52%. [2025-05-28T23:13:26.418Z] Top recommended movies for user id 72: [2025-05-28T23:13:26.418Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:13:26.418Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:13:26.418Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:13:26.418Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:13:26.418Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:13:26.418Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (59252.857 ms) ====== [2025-05-28T23:13:26.418Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-05-28T23:13:26.754Z] GC before operation: completed in 681.177 ms, heap usage 154.390 MB -> 90.299 MB. [2025-05-28T23:13:35.618Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:13:43.540Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:13:52.382Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:13:59.638Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:14:04.365Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:14:10.235Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:14:15.407Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:14:19.536Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:14:20.667Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:14:20.667Z] The best model improves the baseline by 14.52%. [2025-05-28T23:14:21.397Z] Top recommended movies for user id 72: [2025-05-28T23:14:21.397Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:14:21.397Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:14:21.397Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:14:21.397Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:14:21.397Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:14:21.397Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (54348.573 ms) ====== [2025-05-28T23:14:21.397Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-05-28T23:14:22.109Z] GC before operation: completed in 712.170 ms, heap usage 523.485 MB -> 90.978 MB. [2025-05-28T23:14:30.942Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:14:38.175Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:14:47.018Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:14:54.269Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:14:59.640Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:15:04.396Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:15:10.258Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:15:14.982Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:15:15.681Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:15:15.681Z] The best model improves the baseline by 14.52%. [2025-05-28T23:15:16.380Z] Top recommended movies for user id 72: [2025-05-28T23:15:16.380Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:15:16.380Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:15:16.380Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:15:16.380Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:15:16.380Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:15:16.380Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (54413.234 ms) ====== [2025-05-28T23:15:16.380Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-05-28T23:15:17.099Z] GC before operation: completed in 706.562 ms, heap usage 386.018 MB -> 90.683 MB. [2025-05-28T23:15:25.953Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:15:35.369Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:15:44.222Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:15:51.464Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:15:57.323Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:16:02.055Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:16:07.922Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:16:13.083Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:16:14.227Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:16:14.551Z] The best model improves the baseline by 14.52%. [2025-05-28T23:16:15.251Z] Top recommended movies for user id 72: [2025-05-28T23:16:15.251Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:16:15.251Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:16:15.251Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:16:15.251Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:16:15.251Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:16:15.251Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (58109.249 ms) ====== [2025-05-28T23:16:15.251Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-05-28T23:16:15.970Z] GC before operation: completed in 704.913 ms, heap usage 300.230 MB -> 90.627 MB. [2025-05-28T23:16:26.776Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:16:34.001Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:16:42.901Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:16:52.252Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:16:58.125Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:17:03.988Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:17:09.853Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:17:14.581Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:17:15.729Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:17:15.729Z] The best model improves the baseline by 14.52%. [2025-05-28T23:17:16.427Z] Top recommended movies for user id 72: [2025-05-28T23:17:16.427Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:17:16.427Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:17:16.427Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:17:16.427Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:17:16.427Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:17:16.427Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (60365.211 ms) ====== [2025-05-28T23:17:16.427Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-05-28T23:17:17.133Z] GC before operation: completed in 710.735 ms, heap usage 425.354 MB -> 90.880 MB. [2025-05-28T23:17:27.916Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:17:35.310Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:17:44.381Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:17:53.290Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:17:59.147Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:18:03.860Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:18:09.750Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:18:15.955Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:18:15.955Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:18:16.291Z] The best model improves the baseline by 14.52%. [2025-05-28T23:18:16.993Z] Top recommended movies for user id 72: [2025-05-28T23:18:16.993Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:18:16.993Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:18:16.993Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:18:16.993Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:18:16.993Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:18:16.993Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (60076.325 ms) ====== [2025-05-28T23:18:16.993Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-05-28T23:18:17.725Z] GC before operation: completed in 699.626 ms, heap usage 264.374 MB -> 90.557 MB. [2025-05-28T23:18:26.564Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:18:35.407Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:18:44.240Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:18:51.469Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:18:55.851Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:19:01.714Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:19:06.427Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:19:11.145Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:19:11.843Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:19:11.843Z] The best model improves the baseline by 14.52%. [2025-05-28T23:19:12.540Z] Top recommended movies for user id 72: [2025-05-28T23:19:12.540Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:19:12.540Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:19:12.540Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:19:12.540Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:19:12.540Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:19:12.540Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (54848.900 ms) ====== [2025-05-28T23:19:12.540Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-05-28T23:19:13.270Z] GC before operation: completed in 730.764 ms, heap usage 647.985 MB -> 94.520 MB. [2025-05-28T23:19:22.122Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:19:30.962Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:19:38.529Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:19:47.391Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:19:52.109Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:19:56.850Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:20:02.706Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:20:07.412Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:20:07.735Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:20:08.083Z] The best model improves the baseline by 14.52%. [2025-05-28T23:20:08.882Z] Top recommended movies for user id 72: [2025-05-28T23:20:08.882Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:20:08.882Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:20:08.882Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:20:08.882Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:20:08.882Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:20:08.882Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (55293.015 ms) ====== [2025-05-28T23:20:08.882Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-05-28T23:20:09.582Z] GC before operation: completed in 815.090 ms, heap usage 1.098 GB -> 95.765 MB. [2025-05-28T23:20:18.425Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:20:27.262Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:20:34.492Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:20:43.359Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:20:47.098Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:20:51.832Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:20:57.264Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:21:01.979Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:21:03.116Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:21:03.443Z] The best model improves the baseline by 14.52%. [2025-05-28T23:21:03.776Z] Top recommended movies for user id 72: [2025-05-28T23:21:03.776Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:21:03.776Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:21:03.776Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:21:03.776Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:21:03.776Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:21:03.776Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (54463.316 ms) ====== [2025-05-28T23:21:03.776Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-05-28T23:21:04.525Z] GC before operation: completed in 715.482 ms, heap usage 274.233 MB -> 90.831 MB. [2025-05-28T23:21:13.360Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:21:22.251Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:21:30.694Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:21:38.290Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:21:42.996Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:21:48.853Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:21:53.570Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:21:58.333Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:21:59.476Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:21:59.476Z] The best model improves the baseline by 14.52%. [2025-05-28T23:22:00.184Z] Top recommended movies for user id 72: [2025-05-28T23:22:00.184Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:22:00.184Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:22:00.184Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:22:00.184Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:22:00.184Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:22:00.184Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (55400.961 ms) ====== [2025-05-28T23:22:00.184Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-05-28T23:22:00.906Z] GC before operation: completed in 733.202 ms, heap usage 452.744 MB -> 90.927 MB. [2025-05-28T23:22:10.340Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:22:17.575Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:22:26.425Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:22:33.701Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:22:38.418Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:22:43.139Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:22:49.234Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:22:53.948Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:22:54.644Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:22:54.644Z] The best model improves the baseline by 14.52%. [2025-05-28T23:22:55.341Z] Top recommended movies for user id 72: [2025-05-28T23:22:55.681Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:22:55.681Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:22:55.681Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:22:55.681Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:22:55.681Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:22:55.681Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (54727.065 ms) ====== [2025-05-28T23:22:55.681Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-05-28T23:22:56.390Z] GC before operation: completed in 729.320 ms, heap usage 223.481 MB -> 90.663 MB. [2025-05-28T23:23:05.239Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T23:23:12.473Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T23:23:21.329Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T23:23:29.030Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T23:23:33.754Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T23:23:38.469Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T23:23:44.327Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T23:23:49.052Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T23:23:49.376Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-05-28T23:23:49.376Z] The best model improves the baseline by 14.52%. [2025-05-28T23:23:50.075Z] Top recommended movies for user id 72: [2025-05-28T23:23:50.075Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-28T23:23:50.075Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-28T23:23:50.075Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-28T23:23:50.075Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-28T23:23:50.075Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-28T23:23:50.075Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (53947.361 ms) ====== [2025-05-28T23:23:54.804Z] ----------------------------------- [2025-05-28T23:23:54.804Z] renaissance-movie-lens_0_PASSED [2025-05-28T23:23:54.804Z] ----------------------------------- [2025-05-28T23:23:54.804Z] [2025-05-28T23:23:54.804Z] TEST TEARDOWN: [2025-05-28T23:23:54.804Z] Nothing to be done for teardown. [2025-05-28T23:23:54.804Z] renaissance-movie-lens_0 Finish Time: Wed May 28 23:23:54 2025 Epoch Time (ms): 1748474634031