[2025-12-04T01:55:52.661Z] Running test renaissance-movie-lens_0 ... [2025-12-04T01:55:52.662Z] =============================================== [2025-12-04T01:55:52.662Z] renaissance-movie-lens_0 Start Time: Thu Dec 4 01:55:51 2025 Epoch Time (ms): 1764813351456 [2025-12-04T01:55:52.662Z] variation: NoOptions [2025-12-04T01:55:52.662Z] JVM_OPTIONS: [2025-12-04T01:55:52.662Z] { \ [2025-12-04T01:55:52.662Z] echo ""; echo "TEST SETUP:"; \ [2025-12-04T01:55:52.662Z] echo "Nothing to be done for setup."; \ [2025-12-04T01:55:52.662Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17648116735560/renaissance-movie-lens_0"; \ [2025-12-04T01:55:52.662Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17648116735560/renaissance-movie-lens_0"; \ [2025-12-04T01:55:52.662Z] echo ""; echo "TESTING:"; \ [2025-12-04T01:55:52.662Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_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_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17648116735560/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-04T01:55:52.662Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17648116735560/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-04T01:55:52.662Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-04T01:55:52.662Z] echo "Nothing to be done for teardown."; \ [2025-12-04T01:55:52.662Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17648116735560/TestTargetResult"; [2025-12-04T01:55:52.662Z] [2025-12-04T01:55:52.662Z] TEST SETUP: [2025-12-04T01:55:52.662Z] Nothing to be done for setup. [2025-12-04T01:55:52.662Z] [2025-12-04T01:55:52.662Z] TESTING: [2025-12-04T01:55:58.587Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-04T01:56:06.931Z] 01:56:05.823 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-04T01:56:08.909Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-04T01:56:09.859Z] Training: 60056, validation: 20285, test: 19854 [2025-12-04T01:56:09.859Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-04T01:56:09.859Z] GC before operation: completed in 226.825 ms, heap usage 274.554 MB -> 74.452 MB. [2025-12-04T01:56:16.732Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:56:20.888Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:56:24.106Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:56:28.273Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T01:56:30.233Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T01:56:32.194Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T01:56:34.206Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T01:56:36.160Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T01:56:37.337Z] 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. [2025-12-04T01:56:37.337Z] The best model improves the baseline by 14.52%. [2025-12-04T01:56:37.337Z] Top recommended movies for user id 72: [2025-12-04T01:56:37.337Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T01:56:37.337Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T01:56:37.337Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T01:56:37.337Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T01:56:37.337Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T01:56:37.337Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (27719.116 ms) ====== [2025-12-04T01:56:37.337Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-04T01:56:37.337Z] GC before operation: completed in 212.342 ms, heap usage 338.894 MB -> 89.943 MB. [2025-12-04T01:56:41.623Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:56:44.447Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:56:48.616Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:56:51.661Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T01:56:53.616Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T01:56:55.584Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T01:56:57.602Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T01:56:59.557Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T01:56:59.557Z] 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. [2025-12-04T01:56:59.557Z] The best model improves the baseline by 14.52%. [2025-12-04T01:57:00.509Z] Top recommended movies for user id 72: [2025-12-04T01:57:00.509Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T01:57:00.509Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T01:57:00.509Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T01:57:00.509Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T01:57:00.509Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T01:57:00.509Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (22581.782 ms) ====== [2025-12-04T01:57:00.509Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-04T01:57:00.509Z] GC before operation: completed in 189.627 ms, heap usage 333.277 MB -> 87.612 MB. [2025-12-04T01:57:03.524Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:57:06.539Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:57:09.588Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:57:12.601Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T01:57:14.555Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T01:57:16.507Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T01:57:18.458Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T01:57:20.411Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T01:57:21.362Z] 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. [2025-12-04T01:57:21.362Z] The best model improves the baseline by 14.52%. [2025-12-04T01:57:21.362Z] Top recommended movies for user id 72: [2025-12-04T01:57:21.362Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T01:57:21.362Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T01:57:21.362Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T01:57:21.362Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T01:57:21.362Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T01:57:21.362Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20926.145 ms) ====== [2025-12-04T01:57:21.362Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-04T01:57:21.362Z] GC before operation: completed in 181.631 ms, heap usage 331.727 MB -> 88.244 MB. [2025-12-04T01:57:25.116Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:57:28.261Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:57:31.304Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:57:34.319Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T01:57:36.281Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T01:57:38.235Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T01:57:40.188Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T01:57:42.143Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T01:57:43.096Z] 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. [2025-12-04T01:57:43.096Z] The best model improves the baseline by 14.52%. [2025-12-04T01:57:43.096Z] Top recommended movies for user id 72: [2025-12-04T01:57:43.096Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T01:57:43.096Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T01:57:43.096Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T01:57:43.096Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T01:57:43.096Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T01:57:43.096Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21632.692 ms) ====== [2025-12-04T01:57:43.096Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-04T01:57:43.096Z] GC before operation: completed in 196.855 ms, heap usage 126.641 MB -> 88.285 MB. [2025-12-04T01:57:46.112Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:57:49.126Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:57:52.306Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:57:55.389Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T01:57:57.648Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T01:57:59.602Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T01:58:01.555Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T01:58:03.510Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T01:58:03.510Z] 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. [2025-12-04T01:58:03.510Z] The best model improves the baseline by 14.52%. [2025-12-04T01:58:03.510Z] Top recommended movies for user id 72: [2025-12-04T01:58:03.510Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T01:58:03.510Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T01:58:03.510Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T01:58:03.510Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T01:58:03.510Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T01:58:03.510Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20681.191 ms) ====== [2025-12-04T01:58:03.510Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-04T01:58:04.462Z] GC before operation: completed in 185.290 ms, heap usage 379.584 MB -> 88.573 MB. [2025-12-04T01:58:07.627Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:58:10.493Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:58:13.511Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:58:16.537Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T01:58:18.493Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T01:58:20.448Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T01:58:22.406Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T01:58:24.362Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T01:58:24.362Z] 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. [2025-12-04T01:58:24.362Z] The best model improves the baseline by 14.52%. [2025-12-04T01:58:24.362Z] Top recommended movies for user id 72: [2025-12-04T01:58:24.362Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T01:58:24.362Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T01:58:24.362Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T01:58:24.362Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T01:58:24.362Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T01:58:24.362Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20300.778 ms) ====== [2025-12-04T01:58:24.362Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-04T01:58:24.362Z] GC before operation: completed in 195.642 ms, heap usage 386.220 MB -> 88.901 MB. [2025-12-04T01:58:27.427Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:58:30.446Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:58:33.460Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:58:36.742Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T01:58:38.798Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T01:58:40.814Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T01:58:42.767Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T01:58:44.725Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T01:58:44.725Z] 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. [2025-12-04T01:58:44.725Z] The best model improves the baseline by 14.52%. [2025-12-04T01:58:44.725Z] Top recommended movies for user id 72: [2025-12-04T01:58:44.725Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T01:58:44.725Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T01:58:44.725Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T01:58:44.725Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T01:58:44.725Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T01:58:44.725Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20159.891 ms) ====== [2025-12-04T01:58:44.725Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-04T01:58:44.725Z] GC before operation: completed in 184.241 ms, heap usage 395.934 MB -> 88.843 MB. [2025-12-04T01:58:47.912Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:58:50.818Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:58:54.970Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:58:56.934Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T01:58:58.890Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T01:59:00.848Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T01:59:02.809Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T01:59:04.783Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T01:59:04.783Z] 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. [2025-12-04T01:59:05.901Z] The best model improves the baseline by 14.52%. [2025-12-04T01:59:05.902Z] Top recommended movies for user id 72: [2025-12-04T01:59:05.902Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T01:59:05.902Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T01:59:05.902Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T01:59:05.902Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T01:59:05.902Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T01:59:05.902Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20469.725 ms) ====== [2025-12-04T01:59:05.902Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-04T01:59:05.902Z] GC before operation: completed in 190.753 ms, heap usage 425.572 MB -> 89.054 MB. [2025-12-04T01:59:08.919Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:59:11.935Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:59:14.951Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:59:17.968Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T01:59:20.176Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T01:59:21.147Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T01:59:23.104Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T01:59:25.111Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T01:59:26.064Z] 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. [2025-12-04T01:59:26.064Z] The best model improves the baseline by 14.52%. [2025-12-04T01:59:26.064Z] Top recommended movies for user id 72: [2025-12-04T01:59:26.064Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T01:59:26.064Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T01:59:26.064Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T01:59:26.064Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T01:59:26.064Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T01:59:26.064Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20367.206 ms) ====== [2025-12-04T01:59:26.064Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-04T01:59:26.064Z] GC before operation: completed in 190.211 ms, heap usage 405.013 MB -> 88.927 MB. [2025-12-04T01:59:29.082Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:59:32.098Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:59:35.528Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:59:38.544Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T01:59:40.498Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T01:59:42.451Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T01:59:44.405Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T01:59:46.477Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T01:59:46.477Z] 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. [2025-12-04T01:59:46.477Z] The best model improves the baseline by 14.52%. [2025-12-04T01:59:46.477Z] Top recommended movies for user id 72: [2025-12-04T01:59:46.477Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T01:59:46.477Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T01:59:46.477Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T01:59:46.477Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T01:59:46.477Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T01:59:46.477Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20232.893 ms) ====== [2025-12-04T01:59:46.477Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-04T01:59:46.477Z] GC before operation: completed in 200.143 ms, heap usage 384.134 MB -> 89.131 MB. [2025-12-04T01:59:49.612Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T01:59:52.633Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T01:59:55.791Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T01:59:58.810Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:00:00.762Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:00:02.824Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:00:05.238Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:00:06.200Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:00:07.153Z] 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. [2025-12-04T02:00:07.153Z] The best model improves the baseline by 14.52%. [2025-12-04T02:00:07.153Z] Top recommended movies for user id 72: [2025-12-04T02:00:07.153Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:00:07.153Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:00:07.153Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:00:07.153Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:00:07.153Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:00:07.153Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20315.571 ms) ====== [2025-12-04T02:00:07.153Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-04T02:00:07.153Z] GC before operation: completed in 193.846 ms, heap usage 381.403 MB -> 88.859 MB. [2025-12-04T02:00:10.181Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:00:13.198Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:00:16.217Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:00:19.936Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:00:20.889Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:00:22.862Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:00:24.974Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:00:26.934Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:00:26.934Z] 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. [2025-12-04T02:00:26.934Z] The best model improves the baseline by 14.52%. [2025-12-04T02:00:26.934Z] Top recommended movies for user id 72: [2025-12-04T02:00:26.934Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:00:26.934Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:00:26.934Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:00:26.934Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:00:26.934Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:00:26.934Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20200.390 ms) ====== [2025-12-04T02:00:26.934Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-04T02:00:27.941Z] GC before operation: completed in 200.845 ms, heap usage 476.315 MB -> 89.207 MB. [2025-12-04T02:00:30.956Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:00:33.972Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:00:36.988Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:00:40.005Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:00:41.964Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:00:42.914Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:00:44.872Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:00:46.829Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:00:47.781Z] 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. [2025-12-04T02:00:47.781Z] The best model improves the baseline by 14.52%. [2025-12-04T02:00:47.781Z] Top recommended movies for user id 72: [2025-12-04T02:00:47.781Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:00:47.781Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:00:47.781Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:00:47.781Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:00:47.781Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:00:47.781Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20048.651 ms) ====== [2025-12-04T02:00:47.781Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-04T02:00:47.781Z] GC before operation: completed in 188.016 ms, heap usage 381.071 MB -> 89.182 MB. [2025-12-04T02:00:50.795Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:00:53.981Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:00:56.994Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:01:00.007Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:01:02.139Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:01:04.006Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:01:05.974Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:01:06.924Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:01:07.957Z] 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. [2025-12-04T02:01:07.957Z] The best model improves the baseline by 14.52%. [2025-12-04T02:01:07.957Z] Top recommended movies for user id 72: [2025-12-04T02:01:07.957Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:01:07.957Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:01:07.957Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:01:07.957Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:01:07.957Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:01:07.957Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19970.579 ms) ====== [2025-12-04T02:01:07.957Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-04T02:01:07.957Z] GC before operation: completed in 184.983 ms, heap usage 324.350 MB -> 88.917 MB. [2025-12-04T02:01:10.987Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:01:14.011Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:01:17.025Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:01:20.093Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:01:22.045Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:01:23.128Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:01:25.084Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:01:27.046Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:01:28.166Z] 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. [2025-12-04T02:01:28.166Z] The best model improves the baseline by 14.52%. [2025-12-04T02:01:28.166Z] Top recommended movies for user id 72: [2025-12-04T02:01:28.166Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:01:28.166Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:01:28.166Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:01:28.166Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:01:28.166Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:01:28.166Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19857.834 ms) ====== [2025-12-04T02:01:28.166Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-04T02:01:28.166Z] GC before operation: completed in 179.058 ms, heap usage 356.832 MB -> 89.145 MB. [2025-12-04T02:01:31.327Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:01:34.340Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:01:37.352Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:01:40.448Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:01:43.280Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:01:44.235Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:01:46.194Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:01:47.145Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:01:48.227Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T02:01:48.227Z] The best model improves the baseline by 14.52%. [2025-12-04T02:01:48.227Z] Top recommended movies for user id 72: [2025-12-04T02:01:48.227Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:01:48.227Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:01:48.227Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:01:48.227Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:01:48.227Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:01:48.227Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20075.516 ms) ====== [2025-12-04T02:01:48.227Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-04T02:01:48.227Z] GC before operation: completed in 196.271 ms, heap usage 385.214 MB -> 89.083 MB. [2025-12-04T02:01:51.246Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:01:54.284Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:01:57.305Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:02:00.327Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:02:02.285Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:02:04.239Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:02:06.192Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:02:08.254Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:02:08.254Z] 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. [2025-12-04T02:02:08.254Z] The best model improves the baseline by 14.52%. [2025-12-04T02:02:08.254Z] Top recommended movies for user id 72: [2025-12-04T02:02:08.254Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:02:08.254Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:02:08.254Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:02:08.254Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:02:08.254Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:02:08.254Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20084.860 ms) ====== [2025-12-04T02:02:08.254Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-04T02:02:08.254Z] GC before operation: completed in 189.051 ms, heap usage 384.009 MB -> 89.124 MB. [2025-12-04T02:02:11.273Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:02:14.364Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:02:17.395Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:02:20.416Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:02:22.372Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:02:24.916Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:02:26.871Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:02:27.828Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:02:28.780Z] 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. [2025-12-04T02:02:28.780Z] The best model improves the baseline by 14.52%. [2025-12-04T02:02:28.780Z] Top recommended movies for user id 72: [2025-12-04T02:02:28.780Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:02:28.780Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:02:28.780Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:02:28.780Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:02:28.780Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:02:28.780Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20250.002 ms) ====== [2025-12-04T02:02:28.780Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-04T02:02:28.780Z] GC before operation: completed in 192.126 ms, heap usage 345.969 MB -> 88.865 MB. [2025-12-04T02:02:31.991Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:02:35.058Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:02:38.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:02:41.162Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:02:43.130Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:02:45.090Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:02:47.055Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:02:49.010Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:02:49.010Z] 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. [2025-12-04T02:02:49.010Z] The best model improves the baseline by 14.52%. [2025-12-04T02:02:49.010Z] Top recommended movies for user id 72: [2025-12-04T02:02:49.010Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:02:49.010Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:02:49.010Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:02:49.010Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:02:49.010Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:02:49.010Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (20095.222 ms) ====== [2025-12-04T02:02:49.010Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-04T02:02:49.010Z] GC before operation: completed in 187.807 ms, heap usage 423.779 MB -> 89.073 MB. [2025-12-04T02:02:52.034Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:02:55.051Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:02:58.249Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:03:01.350Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:03:03.351Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:03:04.302Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:03:06.869Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:03:08.828Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:03:08.828Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T02:03:08.829Z] The best model improves the baseline by 14.52%. [2025-12-04T02:03:08.829Z] Top recommended movies for user id 72: [2025-12-04T02:03:08.829Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:03:08.829Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:03:08.829Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:03:08.829Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:03:08.829Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:03:08.829Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19780.268 ms) ====== [2025-12-04T02:03:09.781Z] ----------------------------------- [2025-12-04T02:03:09.781Z] renaissance-movie-lens_0_PASSED [2025-12-04T02:03:09.781Z] ----------------------------------- [2025-12-04T02:03:09.781Z] [2025-12-04T02:03:09.781Z] TEST TEARDOWN: [2025-12-04T02:03:09.781Z] Nothing to be done for teardown. [2025-12-04T02:03:09.781Z] renaissance-movie-lens_0 Finish Time: Thu Dec 4 02:03:09 2025 Epoch Time (ms): 1764813789109