[2025-05-07T19:43:25.427Z] Running test renaissance-movie-lens_0 ... [2025-05-07T19:43:25.427Z] =============================================== [2025-05-07T19:43:25.427Z] renaissance-movie-lens_0 Start Time: Wed May 7 19:43:24 2025 Epoch Time (ms): 1746647004730 [2025-05-07T19:43:25.427Z] variation: NoOptions [2025-05-07T19:43:25.427Z] JVM_OPTIONS: [2025-05-07T19:43:25.427Z] { \ [2025-05-07T19:43:25.427Z] echo ""; echo "TEST SETUP:"; \ [2025-05-07T19:43:25.427Z] echo "Nothing to be done for setup."; \ [2025-05-07T19:43:25.427Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17466416504249/renaissance-movie-lens_0"; \ [2025-05-07T19:43:25.427Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17466416504249/renaissance-movie-lens_0"; \ [2025-05-07T19:43:25.427Z] echo ""; echo "TESTING:"; \ [2025-05-07T19:43:25.428Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/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_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17466416504249/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-05-07T19:43:25.428Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17466416504249/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-05-07T19:43:25.428Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-05-07T19:43:25.428Z] echo "Nothing to be done for teardown."; \ [2025-05-07T19:43:25.428Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17466416504249/TestTargetResult"; [2025-05-07T19:43:25.428Z] [2025-05-07T19:43:25.428Z] TEST SETUP: [2025-05-07T19:43:25.428Z] Nothing to be done for setup. [2025-05-07T19:43:25.428Z] [2025-05-07T19:43:25.428Z] TESTING: [2025-05-07T19:43:39.049Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-05-07T19:44:04.783Z] 19:44:02.937 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. [2025-05-07T19:44:11.599Z] Got 100004 ratings from 671 users on 9066 movies. [2025-05-07T19:44:13.171Z] Training: 60056, validation: 20285, test: 19854 [2025-05-07T19:44:13.171Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-05-07T19:44:13.947Z] GC before operation: completed in 573.300 ms, heap usage 282.141 MB -> 74.450 MB. [2025-05-07T19:44:40.154Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:44:53.787Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:45:05.388Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:45:19.128Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:45:25.957Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:45:32.049Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:45:38.849Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:45:45.767Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:45:46.532Z] 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. [2025-05-07T19:45:47.296Z] The best model improves the baseline by 14.52%. [2025-05-07T19:45:48.120Z] Top recommended movies for user id 72: [2025-05-07T19:45:48.120Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:45:48.120Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:45:48.120Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:45:48.120Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:45:48.120Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:45:48.120Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (94235.466 ms) ====== [2025-05-07T19:45:48.120Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-05-07T19:45:48.878Z] GC before operation: completed in 523.706 ms, heap usage 130.548 MB -> 85.219 MB. [2025-05-07T19:45:58.663Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:46:08.472Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:46:20.285Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:46:30.595Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:46:36.093Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:46:41.633Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:46:47.133Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:46:52.639Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:46:53.403Z] 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. [2025-05-07T19:46:53.403Z] The best model improves the baseline by 14.52%. [2025-05-07T19:46:54.168Z] Top recommended movies for user id 72: [2025-05-07T19:46:54.168Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:46:54.168Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:46:54.168Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:46:54.168Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:46:54.168Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:46:54.168Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (65701.461 ms) ====== [2025-05-07T19:46:54.168Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-05-07T19:46:54.934Z] GC before operation: completed in 542.316 ms, heap usage 121.974 MB -> 87.314 MB. [2025-05-07T19:47:04.767Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:47:14.594Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:47:24.383Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:47:34.758Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:47:40.353Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:47:44.767Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:47:51.541Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:47:55.919Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:47:57.483Z] 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. [2025-05-07T19:47:57.483Z] The best model improves the baseline by 14.52%. [2025-05-07T19:47:57.483Z] Top recommended movies for user id 72: [2025-05-07T19:47:57.483Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:47:57.483Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:47:57.483Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:47:57.483Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:47:57.483Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:47:57.483Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (62756.593 ms) ====== [2025-05-07T19:47:57.483Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-05-07T19:47:58.241Z] GC before operation: completed in 582.383 ms, heap usage 294.482 MB -> 88.182 MB. [2025-05-07T19:48:09.905Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:48:21.795Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:48:30.438Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:48:38.957Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:48:47.537Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:48:53.297Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:48:59.032Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:49:07.479Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:49:07.479Z] 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. [2025-05-07T19:49:07.479Z] The best model improves the baseline by 14.52%. [2025-05-07T19:49:07.479Z] Top recommended movies for user id 72: [2025-05-07T19:49:07.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:49:07.479Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:49:07.479Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:49:07.479Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:49:07.479Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:49:07.479Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (68841.787 ms) ====== [2025-05-07T19:49:07.479Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-05-07T19:49:07.479Z] GC before operation: completed in 253.363 ms, heap usage 97.206 MB -> 88.559 MB. [2025-05-07T19:49:13.200Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:49:25.337Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:49:32.350Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:49:46.252Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:49:50.923Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:49:55.590Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:50:01.383Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:50:06.750Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:50:07.538Z] 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. [2025-05-07T19:50:07.538Z] The best model improves the baseline by 14.52%. [2025-05-07T19:50:08.334Z] Top recommended movies for user id 72: [2025-05-07T19:50:08.334Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:50:08.334Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:50:08.334Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:50:08.334Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:50:08.334Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:50:08.334Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (60695.956 ms) ====== [2025-05-07T19:50:08.334Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-05-07T19:50:08.334Z] GC before operation: completed in 526.742 ms, heap usage 110.843 MB -> 88.133 MB. [2025-05-07T19:50:16.991Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:50:27.191Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:50:35.900Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:50:44.092Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:50:48.190Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:50:52.283Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:50:56.357Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:50:59.658Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:50:59.658Z] 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. [2025-05-07T19:50:59.658Z] The best model improves the baseline by 14.52%. [2025-05-07T19:50:59.658Z] Top recommended movies for user id 72: [2025-05-07T19:50:59.658Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:50:59.658Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:50:59.658Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:50:59.658Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:50:59.658Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:50:59.658Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (51309.305 ms) ====== [2025-05-07T19:50:59.658Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-05-07T19:51:00.585Z] GC before operation: completed in 175.111 ms, heap usage 324.380 MB -> 88.727 MB. [2025-05-07T19:51:05.878Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:51:11.175Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:51:17.779Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:51:25.819Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:51:31.094Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:51:36.389Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:51:41.857Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:51:47.139Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:51:48.616Z] 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. [2025-05-07T19:51:48.616Z] The best model improves the baseline by 14.52%. [2025-05-07T19:51:49.559Z] Top recommended movies for user id 72: [2025-05-07T19:51:49.559Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:51:49.559Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:51:49.559Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:51:49.559Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:51:49.559Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:51:49.559Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (48946.866 ms) ====== [2025-05-07T19:51:49.559Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-05-07T19:51:49.559Z] GC before operation: completed in 576.933 ms, heap usage 149.522 MB -> 88.406 MB. [2025-05-07T19:52:01.685Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:52:15.384Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:52:25.449Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:52:41.011Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:52:49.300Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:52:55.976Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:53:01.304Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:53:06.659Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:53:07.597Z] 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. [2025-05-07T19:53:07.597Z] The best model improves the baseline by 14.52%. [2025-05-07T19:53:07.597Z] Top recommended movies for user id 72: [2025-05-07T19:53:07.597Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:53:07.597Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:53:07.597Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:53:07.597Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:53:07.597Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:53:07.597Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (78221.770 ms) ====== [2025-05-07T19:53:07.597Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-05-07T19:53:08.534Z] GC before operation: completed in 427.846 ms, heap usage 259.738 MB -> 88.775 MB. [2025-05-07T19:53:15.853Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:53:23.908Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:53:31.989Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:53:40.056Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:53:45.370Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:53:52.055Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:53:57.373Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:54:01.468Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:54:02.405Z] 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. [2025-05-07T19:54:02.405Z] The best model improves the baseline by 14.52%. [2025-05-07T19:54:02.405Z] Top recommended movies for user id 72: [2025-05-07T19:54:02.405Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:54:02.405Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:54:02.405Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:54:02.405Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:54:02.405Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:54:02.405Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (54341.606 ms) ====== [2025-05-07T19:54:02.405Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-05-07T19:54:03.368Z] GC before operation: completed in 389.926 ms, heap usage 506.021 MB -> 88.934 MB. [2025-05-07T19:54:10.003Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:54:18.765Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:54:27.065Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:54:36.756Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:54:40.871Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:54:46.215Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:54:51.538Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:54:55.654Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:54:56.593Z] 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. [2025-05-07T19:54:57.538Z] The best model improves the baseline by 14.52%. [2025-05-07T19:54:57.538Z] Top recommended movies for user id 72: [2025-05-07T19:54:57.538Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:54:57.538Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:54:57.538Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:54:57.538Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:54:57.538Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:54:57.538Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (54417.936 ms) ====== [2025-05-07T19:54:57.538Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-05-07T19:54:58.485Z] GC before operation: completed in 576.475 ms, heap usage 407.876 MB -> 89.031 MB. [2025-05-07T19:55:08.190Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:55:17.890Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:55:26.677Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:55:36.331Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:55:41.736Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:55:47.069Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:55:53.744Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:55:59.062Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:56:00.014Z] 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. [2025-05-07T19:56:00.014Z] The best model improves the baseline by 14.52%. [2025-05-07T19:56:00.014Z] Top recommended movies for user id 72: [2025-05-07T19:56:00.014Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:56:00.014Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:56:00.014Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:56:00.014Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:56:00.014Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:56:00.014Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (62201.670 ms) ====== [2025-05-07T19:56:00.014Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-05-07T19:56:00.962Z] GC before operation: completed in 479.882 ms, heap usage 370.047 MB -> 88.662 MB. [2025-05-07T19:56:10.661Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:56:18.753Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:56:29.152Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:56:37.215Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:56:42.114Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:56:49.285Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:56:56.421Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:57:02.276Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:57:03.068Z] 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. [2025-05-07T19:57:03.068Z] The best model improves the baseline by 14.52%. [2025-05-07T19:57:03.866Z] Top recommended movies for user id 72: [2025-05-07T19:57:03.867Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:57:03.867Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:57:03.867Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:57:03.867Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:57:03.867Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:57:03.867Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (62938.120 ms) ====== [2025-05-07T19:57:03.867Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-05-07T19:57:04.677Z] GC before operation: completed in 745.111 ms, heap usage 444.223 MB -> 88.981 MB. [2025-05-07T19:57:14.846Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:57:25.055Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:57:37.635Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:57:46.303Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:57:52.188Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:57:59.296Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:58:06.386Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:58:12.224Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:58:13.039Z] 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. [2025-05-07T19:58:13.837Z] The best model improves the baseline by 14.52%. [2025-05-07T19:58:13.837Z] Top recommended movies for user id 72: [2025-05-07T19:58:13.837Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:58:13.837Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:58:13.837Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:58:13.837Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:58:13.837Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:58:13.837Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (69625.474 ms) ====== [2025-05-07T19:58:13.837Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-05-07T19:58:14.641Z] GC before operation: completed in 594.627 ms, heap usage 212.114 MB -> 88.837 MB. [2025-05-07T19:58:23.207Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:58:32.930Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:58:43.280Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:58:51.922Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T19:58:57.709Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T19:59:03.568Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T19:59:09.397Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T19:59:14.056Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T19:59:14.867Z] 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. [2025-05-07T19:59:14.867Z] The best model improves the baseline by 14.52%. [2025-05-07T19:59:15.676Z] Top recommended movies for user id 72: [2025-05-07T19:59:15.676Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T19:59:15.676Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T19:59:15.676Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T19:59:15.676Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T19:59:15.676Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T19:59:15.676Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (61252.317 ms) ====== [2025-05-07T19:59:15.676Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-05-07T19:59:16.475Z] GC before operation: completed in 523.813 ms, heap usage 164.392 MB -> 88.574 MB. [2025-05-07T19:59:27.381Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T19:59:35.954Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T19:59:46.259Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T19:59:58.285Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T20:00:04.089Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T20:00:09.950Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T20:00:15.802Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T20:00:21.656Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T20:00:23.317Z] 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. [2025-05-07T20:00:23.317Z] The best model improves the baseline by 14.52%. [2025-05-07T20:00:23.317Z] Top recommended movies for user id 72: [2025-05-07T20:00:23.317Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T20:00:23.317Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T20:00:23.317Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T20:00:23.317Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T20:00:23.317Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T20:00:23.317Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (67096.996 ms) ====== [2025-05-07T20:00:23.317Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-05-07T20:00:24.130Z] GC before operation: completed in 538.917 ms, heap usage 408.199 MB -> 89.182 MB. [2025-05-07T20:00:34.997Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T20:00:45.218Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T20:00:57.362Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T20:01:09.109Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T20:01:17.706Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T20:01:23.539Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T20:01:29.567Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T20:01:36.705Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T20:01:36.705Z] 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. [2025-05-07T20:01:36.705Z] The best model improves the baseline by 14.52%. [2025-05-07T20:01:37.504Z] Top recommended movies for user id 72: [2025-05-07T20:01:37.504Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T20:01:37.504Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T20:01:37.504Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T20:01:37.504Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T20:01:37.504Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T20:01:37.504Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (73465.274 ms) ====== [2025-05-07T20:01:37.504Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-05-07T20:01:37.504Z] GC before operation: completed in 398.021 ms, heap usage 406.188 MB -> 88.998 MB. [2025-05-07T20:01:52.776Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T20:02:02.980Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T20:02:15.113Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T20:02:25.365Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T20:02:30.165Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T20:02:34.823Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T20:02:42.004Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T20:02:47.910Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T20:02:49.597Z] 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. [2025-05-07T20:02:49.597Z] The best model improves the baseline by 14.52%. [2025-05-07T20:02:50.396Z] Top recommended movies for user id 72: [2025-05-07T20:02:50.396Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T20:02:50.396Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T20:02:50.396Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T20:02:50.396Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T20:02:50.396Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T20:02:50.396Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (72209.610 ms) ====== [2025-05-07T20:02:50.396Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-05-07T20:02:50.396Z] GC before operation: completed in 604.954 ms, heap usage 309.609 MB -> 88.972 MB. [2025-05-07T20:03:02.472Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T20:03:12.755Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T20:03:21.316Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T20:03:28.428Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T20:03:34.529Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T20:03:40.388Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T20:03:47.686Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T20:03:54.851Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T20:03:54.851Z] 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. [2025-05-07T20:03:55.648Z] The best model improves the baseline by 14.52%. [2025-05-07T20:03:55.648Z] Top recommended movies for user id 72: [2025-05-07T20:03:55.648Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T20:03:55.648Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T20:03:55.648Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T20:03:55.648Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T20:03:55.648Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T20:03:55.648Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (65170.038 ms) ====== [2025-05-07T20:03:55.648Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-05-07T20:03:56.459Z] GC before operation: completed in 626.297 ms, heap usage 420.469 MB -> 88.949 MB. [2025-05-07T20:04:08.480Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T20:04:17.025Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T20:04:27.341Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T20:04:38.138Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T20:04:45.359Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T20:04:51.262Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T20:04:58.426Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T20:05:04.301Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T20:05:05.104Z] 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. [2025-05-07T20:05:05.914Z] The best model improves the baseline by 14.52%. [2025-05-07T20:05:05.914Z] Top recommended movies for user id 72: [2025-05-07T20:05:05.914Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T20:05:05.914Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T20:05:05.914Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T20:05:05.914Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T20:05:05.914Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T20:05:05.914Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (69688.892 ms) ====== [2025-05-07T20:05:05.914Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-05-07T20:05:06.721Z] GC before operation: completed in 633.895 ms, heap usage 173.808 MB -> 88.986 MB. [2025-05-07T20:05:16.979Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-07T20:05:29.096Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-07T20:05:38.283Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-07T20:05:48.674Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-07T20:05:54.517Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-07T20:06:01.716Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-07T20:06:08.907Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-07T20:06:16.099Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-07T20:06:16.099Z] 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. [2025-05-07T20:06:16.099Z] The best model improves the baseline by 14.52%. [2025-05-07T20:06:16.900Z] Top recommended movies for user id 72: [2025-05-07T20:06:16.900Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-05-07T20:06:16.900Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-05-07T20:06:16.900Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-05-07T20:06:16.900Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-05-07T20:06:16.900Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-05-07T20:06:16.900Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (70123.616 ms) ====== [2025-05-07T20:06:17.700Z] ----------------------------------- [2025-05-07T20:06:17.700Z] renaissance-movie-lens_0_PASSED [2025-05-07T20:06:17.700Z] ----------------------------------- [2025-05-07T20:06:17.700Z] [2025-05-07T20:06:17.700Z] TEST TEARDOWN: [2025-05-07T20:06:17.700Z] Nothing to be done for teardown. [2025-05-07T20:06:18.498Z] renaissance-movie-lens_0 Finish Time: Wed May 7 20:06:17 2025 Epoch Time (ms): 1746648377631