[2025-06-11T22:32:33.285Z] Running test renaissance-movie-lens_0 ... [2025-06-11T22:32:33.285Z] =============================================== [2025-06-11T22:32:33.285Z] renaissance-movie-lens_0 Start Time: Wed Jun 11 22:32:29 2025 Epoch Time (ms): 1749681149991 [2025-06-11T22:32:33.285Z] variation: NoOptions [2025-06-11T22:32:33.285Z] JVM_OPTIONS: [2025-06-11T22:32:33.285Z] { \ [2025-06-11T22:32:33.285Z] echo ""; echo "TEST SETUP:"; \ [2025-06-11T22:32:33.285Z] echo "Nothing to be done for setup."; \ [2025-06-11T22:32:33.285Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17496769855803/renaissance-movie-lens_0"; \ [2025-06-11T22:32:33.285Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17496769855803/renaissance-movie-lens_0"; \ [2025-06-11T22:32:33.285Z] echo ""; echo "TESTING:"; \ [2025-06-11T22:32:33.285Z] "/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_17496769855803/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-11T22:32:33.285Z] 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_17496769855803/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-11T22:32:33.285Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-11T22:32:33.285Z] echo "Nothing to be done for teardown."; \ [2025-06-11T22:32:33.285Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux/aqa-tests/TKG/../TKG/output_17496769855803/TestTargetResult"; [2025-06-11T22:32:33.285Z] [2025-06-11T22:32:33.285Z] TEST SETUP: [2025-06-11T22:32:33.285Z] Nothing to be done for setup. [2025-06-11T22:32:33.285Z] [2025-06-11T22:32:33.285Z] TESTING: [2025-06-11T22:32:56.267Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-11T22:33:29.653Z] 22:33:25.551 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-06-11T22:33:37.043Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-11T22:33:39.288Z] Training: 60056, validation: 20285, test: 19854 [2025-06-11T22:33:39.288Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-11T22:33:39.612Z] GC before operation: completed in 563.015 ms, heap usage 487.483 MB -> 76.446 MB. [2025-06-11T22:34:07.321Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:34:26.431Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:34:39.581Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:34:52.785Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:35:00.021Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:35:08.903Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:35:16.151Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:35:23.393Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:35:24.199Z] 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. [2025-06-11T22:35:24.532Z] The best model improves the baseline by 14.52%. [2025-06-11T22:35:26.190Z] Top recommended movies for user id 72: [2025-06-11T22:35:26.190Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:35:26.190Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:35:26.190Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:35:26.190Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:35:26.190Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:35:26.190Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (106406.614 ms) ====== [2025-06-11T22:35:26.190Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-11T22:35:26.914Z] GC before operation: completed in 909.935 ms, heap usage 130.455 MB -> 86.941 MB. [2025-06-11T22:35:40.004Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:35:48.861Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:35:59.654Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:36:10.543Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:36:16.417Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:36:22.288Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:36:29.577Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:36:35.445Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:36:35.774Z] 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. [2025-06-11T22:36:36.099Z] The best model improves the baseline by 14.52%. [2025-06-11T22:36:36.799Z] Top recommended movies for user id 72: [2025-06-11T22:36:36.799Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:36:36.799Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:36:36.799Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:36:36.799Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:36:36.799Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:36:36.799Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (69878.732 ms) ====== [2025-06-11T22:36:36.799Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-11T22:36:37.957Z] GC before operation: completed in 1021.222 ms, heap usage 450.587 MB -> 89.470 MB. [2025-06-11T22:36:48.862Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:36:59.670Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:37:08.556Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:37:19.378Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:37:23.980Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:37:29.860Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:37:35.838Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:37:41.719Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:37:42.420Z] 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. [2025-06-11T22:37:42.744Z] The best model improves the baseline by 14.52%. [2025-06-11T22:37:43.444Z] Top recommended movies for user id 72: [2025-06-11T22:37:43.444Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:37:43.444Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:37:43.444Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:37:43.444Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:37:43.444Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:37:43.444Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (65622.917 ms) ====== [2025-06-11T22:37:43.444Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-11T22:37:44.599Z] GC before operation: completed in 1047.081 ms, heap usage 841.843 MB -> 94.060 MB. [2025-06-11T22:37:55.371Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:38:04.265Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:38:13.226Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:38:22.301Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:38:27.019Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:38:32.985Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:38:38.855Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:38:44.710Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:38:45.037Z] 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. [2025-06-11T22:38:45.363Z] The best model improves the baseline by 14.52%. [2025-06-11T22:38:46.062Z] Top recommended movies for user id 72: [2025-06-11T22:38:46.062Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:38:46.063Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:38:46.063Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:38:46.063Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:38:46.063Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:38:46.063Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (61615.395 ms) ====== [2025-06-11T22:38:46.063Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-11T22:38:47.273Z] GC before operation: completed in 995.836 ms, heap usage 830.628 MB -> 94.334 MB. [2025-06-11T22:38:56.306Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:39:07.067Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:39:15.926Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:39:24.752Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:39:29.476Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:39:35.366Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:39:41.340Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:39:46.066Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:39:47.256Z] 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. [2025-06-11T22:39:47.256Z] The best model improves the baseline by 14.52%. [2025-06-11T22:39:47.954Z] Top recommended movies for user id 72: [2025-06-11T22:39:47.954Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:39:47.954Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:39:47.954Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:39:47.954Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:39:47.954Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:39:47.954Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (60789.588 ms) ====== [2025-06-11T22:39:47.954Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-11T22:39:49.128Z] GC before operation: completed in 1055.853 ms, heap usage 1.099 GB -> 95.354 MB. [2025-06-11T22:39:59.928Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:40:07.165Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:40:16.300Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:40:23.639Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:40:29.516Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:40:34.233Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:40:40.131Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:40:46.012Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:40:46.341Z] 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. [2025-06-11T22:40:46.341Z] The best model improves the baseline by 14.52%. [2025-06-11T22:40:47.042Z] Top recommended movies for user id 72: [2025-06-11T22:40:47.042Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:40:47.042Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:40:47.042Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:40:47.042Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:40:47.042Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:40:47.042Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (58172.215 ms) ====== [2025-06-11T22:40:47.042Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-11T22:40:48.196Z] GC before operation: completed in 913.787 ms, heap usage 817.425 MB -> 94.505 MB. [2025-06-11T22:40:57.175Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:41:06.106Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:41:14.948Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:41:22.176Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:41:26.942Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:41:31.808Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:41:37.680Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:41:42.399Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:41:43.100Z] 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. [2025-06-11T22:41:43.100Z] The best model improves the baseline by 14.52%. [2025-06-11T22:41:43.800Z] Top recommended movies for user id 72: [2025-06-11T22:41:43.800Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:41:43.800Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:41:43.800Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:41:43.800Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:41:43.800Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:41:43.800Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55799.703 ms) ====== [2025-06-11T22:41:43.800Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-11T22:41:44.957Z] GC before operation: completed in 897.731 ms, heap usage 457.523 MB -> 90.829 MB. [2025-06-11T22:41:53.835Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:42:01.058Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:42:10.265Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:42:17.496Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:42:23.361Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:42:28.087Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:42:32.809Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:42:37.568Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:42:38.707Z] 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. [2025-06-11T22:42:38.707Z] The best model improves the baseline by 14.52%. [2025-06-11T22:42:39.430Z] Top recommended movies for user id 72: [2025-06-11T22:42:39.430Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:42:39.430Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:42:39.430Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:42:39.430Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:42:39.430Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:42:39.430Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (54721.829 ms) ====== [2025-06-11T22:42:39.430Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-11T22:42:40.262Z] GC before operation: completed in 932.406 ms, heap usage 375.957 MB -> 90.944 MB. [2025-06-11T22:42:49.140Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:42:58.051Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:43:05.353Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:43:14.199Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:43:17.961Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:43:23.973Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:43:28.710Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:43:33.439Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:43:34.571Z] 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. [2025-06-11T22:43:34.571Z] The best model improves the baseline by 14.52%. [2025-06-11T22:43:35.270Z] Top recommended movies for user id 72: [2025-06-11T22:43:35.270Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:43:35.270Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:43:35.270Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:43:35.270Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:43:35.270Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:43:35.271Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (55065.357 ms) ====== [2025-06-11T22:43:35.271Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-11T22:43:36.450Z] GC before operation: completed in 886.765 ms, heap usage 828.292 MB -> 94.625 MB. [2025-06-11T22:43:45.297Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:43:54.136Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:44:03.202Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:44:12.041Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:44:17.019Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:44:21.774Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:44:27.670Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:44:33.554Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:44:33.877Z] 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. [2025-06-11T22:44:33.877Z] The best model improves the baseline by 14.52%. [2025-06-11T22:44:34.573Z] Top recommended movies for user id 72: [2025-06-11T22:44:34.573Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:44:34.573Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:44:34.573Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:44:34.573Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:44:34.573Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:44:34.573Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (58428.182 ms) ====== [2025-06-11T22:44:34.573Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-11T22:44:35.706Z] GC before operation: completed in 841.234 ms, heap usage 306.745 MB -> 90.931 MB. [2025-06-11T22:44:44.562Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:44:53.433Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:45:02.289Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:45:11.167Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:45:15.897Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:45:21.903Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:45:27.768Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:45:32.497Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:45:33.656Z] 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. [2025-06-11T22:45:33.656Z] The best model improves the baseline by 14.52%. [2025-06-11T22:45:34.372Z] Top recommended movies for user id 72: [2025-06-11T22:45:34.372Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:45:34.372Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:45:34.372Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:45:34.372Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:45:34.372Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:45:34.372Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (58621.705 ms) ====== [2025-06-11T22:45:34.372Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-11T22:45:35.098Z] GC before operation: completed in 834.154 ms, heap usage 443.711 MB -> 90.664 MB. [2025-06-11T22:45:43.937Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:45:52.782Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:46:01.669Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:46:10.569Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:46:15.238Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:46:21.125Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:46:27.026Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:46:31.733Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:46:32.867Z] 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. [2025-06-11T22:46:33.212Z] The best model improves the baseline by 14.52%. [2025-06-11T22:46:33.930Z] Top recommended movies for user id 72: [2025-06-11T22:46:33.930Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:46:33.930Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:46:33.930Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:46:33.930Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:46:33.930Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:46:33.930Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (58730.154 ms) ====== [2025-06-11T22:46:33.930Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-11T22:46:34.656Z] GC before operation: completed in 829.239 ms, heap usage 411.053 MB -> 90.941 MB. [2025-06-11T22:46:43.713Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:46:52.604Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:47:01.455Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:47:08.703Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:47:14.585Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:47:19.305Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:47:25.299Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:47:30.015Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:47:30.713Z] 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. [2025-06-11T22:47:30.713Z] The best model improves the baseline by 14.52%. [2025-06-11T22:47:31.416Z] Top recommended movies for user id 72: [2025-06-11T22:47:31.416Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:47:31.416Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:47:31.416Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:47:31.416Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:47:31.416Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:47:31.416Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (56814.482 ms) ====== [2025-06-11T22:47:31.416Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-11T22:47:32.144Z] GC before operation: completed in 855.272 ms, heap usage 307.993 MB -> 90.980 MB. [2025-06-11T22:47:42.939Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:47:50.165Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:47:59.021Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:48:08.016Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:48:13.879Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:48:18.596Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:48:24.485Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:48:30.427Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:48:30.427Z] 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. [2025-06-11T22:48:30.751Z] The best model improves the baseline by 14.52%. [2025-06-11T22:48:31.073Z] Top recommended movies for user id 72: [2025-06-11T22:48:31.411Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:48:31.411Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:48:31.411Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:48:31.411Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:48:31.411Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:48:31.411Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (58978.808 ms) ====== [2025-06-11T22:48:31.411Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-11T22:48:32.133Z] GC before operation: completed in 830.847 ms, heap usage 390.999 MB -> 90.810 MB. [2025-06-11T22:48:41.192Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:48:50.038Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:48:58.880Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:49:07.775Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:49:12.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:49:18.404Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:49:24.324Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:49:29.047Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:49:29.751Z] 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. [2025-06-11T22:49:29.751Z] The best model improves the baseline by 14.52%. [2025-06-11T22:49:30.450Z] Top recommended movies for user id 72: [2025-06-11T22:49:30.450Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:49:30.450Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:49:30.450Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:49:30.450Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:49:30.450Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:49:30.450Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (58507.625 ms) ====== [2025-06-11T22:49:30.450Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-11T22:49:31.621Z] GC before operation: completed in 862.138 ms, heap usage 301.441 MB -> 90.991 MB. [2025-06-11T22:49:40.528Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:49:49.370Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:49:58.219Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:50:05.519Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:50:10.290Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:50:15.016Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:50:19.752Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:50:24.485Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:50:25.619Z] 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. [2025-06-11T22:50:25.619Z] The best model improves the baseline by 14.52%. [2025-06-11T22:50:26.335Z] Top recommended movies for user id 72: [2025-06-11T22:50:26.335Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:50:26.335Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:50:26.335Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:50:26.335Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:50:26.335Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:50:26.335Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (54685.125 ms) ====== [2025-06-11T22:50:26.335Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-11T22:50:27.060Z] GC before operation: completed in 921.849 ms, heap usage 1.226 GB -> 96.270 MB. [2025-06-11T22:50:36.015Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:50:44.915Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:50:52.155Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:50:59.412Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:51:05.333Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:51:09.123Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:51:15.167Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:51:19.916Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:51:20.261Z] 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. [2025-06-11T22:51:20.261Z] The best model improves the baseline by 14.52%. [2025-06-11T22:51:20.973Z] Top recommended movies for user id 72: [2025-06-11T22:51:20.973Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:51:20.973Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:51:20.973Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:51:20.973Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:51:20.973Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:51:20.973Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (53875.394 ms) ====== [2025-06-11T22:51:20.973Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-11T22:51:21.703Z] GC before operation: completed in 876.953 ms, heap usage 394.674 MB -> 90.983 MB. [2025-06-11T22:51:30.559Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:51:39.411Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:51:46.649Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:51:55.522Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:52:00.358Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:52:05.083Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:52:09.814Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:52:15.684Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:52:15.684Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T22:52:16.009Z] The best model improves the baseline by 14.52%. [2025-06-11T22:52:16.334Z] Top recommended movies for user id 72: [2025-06-11T22:52:16.334Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:52:16.334Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:52:16.334Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:52:16.334Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:52:16.334Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:52:16.334Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (54644.096 ms) ====== [2025-06-11T22:52:16.334Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-11T22:52:17.489Z] GC before operation: completed in 930.163 ms, heap usage 532.308 MB -> 90.974 MB. [2025-06-11T22:52:26.356Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:52:33.720Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:52:42.605Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:52:49.835Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:52:54.560Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:52:59.290Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:53:05.190Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:53:09.905Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:53:10.231Z] 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. [2025-06-11T22:53:10.747Z] The best model improves the baseline by 14.52%. [2025-06-11T22:53:11.120Z] Top recommended movies for user id 72: [2025-06-11T22:53:11.120Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:53:11.120Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:53:11.120Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:53:11.120Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:53:11.120Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:53:11.120Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (53755.841 ms) ====== [2025-06-11T22:53:11.120Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-11T22:53:12.265Z] GC before operation: completed in 898.290 ms, heap usage 255.637 MB -> 90.748 MB. [2025-06-11T22:53:21.144Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T22:53:28.392Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T22:53:37.252Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T22:53:44.493Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T22:53:49.228Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T22:53:54.048Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T22:53:58.789Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T22:54:05.180Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T22:54:05.180Z] 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. [2025-06-11T22:54:05.180Z] The best model improves the baseline by 14.52%. [2025-06-11T22:54:05.180Z] Top recommended movies for user id 72: [2025-06-11T22:54:05.180Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T22:54:05.180Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T22:54:05.180Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T22:54:05.180Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T22:54:05.180Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T22:54:05.180Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (53093.367 ms) ====== [2025-06-11T22:54:08.937Z] ----------------------------------- [2025-06-11T22:54:08.937Z] renaissance-movie-lens_0_PASSED [2025-06-11T22:54:08.937Z] ----------------------------------- [2025-06-11T22:54:08.937Z] [2025-06-11T22:54:08.937Z] TEST TEARDOWN: [2025-06-11T22:54:08.937Z] Nothing to be done for teardown. [2025-06-11T22:54:08.937Z] renaissance-movie-lens_0 Finish Time: Wed Jun 11 22:54:08 2025 Epoch Time (ms): 1749682448666