renaissance-movie-lens_0
[2025-06-12T02:24:51.956Z] Running test renaissance-movie-lens_0 ...
[2025-06-12T02:24:51.956Z] ===============================================
[2025-06-12T02:24:51.956Z] renaissance-movie-lens_0 Start Time: Thu Jun 12 02:24:51 2025 Epoch Time (ms): 1749695091700
[2025-06-12T02:24:51.956Z] variation: NoOptions
[2025-06-12T02:24:51.956Z] JVM_OPTIONS:
[2025-06-12T02:24:51.956Z] { \
[2025-06-12T02:24:51.956Z] echo ""; echo "TEST SETUP:"; \
[2025-06-12T02:24:51.956Z] echo "Nothing to be done for setup."; \
[2025-06-12T02:24:51.956Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_1749694395965/renaissance-movie-lens_0"; \
[2025-06-12T02:24:51.956Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_1749694395965/renaissance-movie-lens_0"; \
[2025-06-12T02:24:51.956Z] echo ""; echo "TESTING:"; \
[2025-06-12T02:24:51.956Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/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_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_1749694395965/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-06-12T02:24:51.956Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_1749694395965/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-06-12T02:24:51.956Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-06-12T02:24:51.956Z] echo "Nothing to be done for teardown."; \
[2025-06-12T02:24:51.956Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_1749694395965/TestTargetResult";
[2025-06-12T02:24:51.956Z]
[2025-06-12T02:24:51.956Z] TEST SETUP:
[2025-06-12T02:24:51.956Z] Nothing to be done for setup.
[2025-06-12T02:24:51.956Z]
[2025-06-12T02:24:51.956Z] TESTING:
[2025-06-12T02:24:57.323Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-06-12T02:25:04.017Z] 02:25:03.222 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-06-12T02:25:05.970Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-06-12T02:25:05.970Z] Training: 60056, validation: 20285, test: 19854
[2025-06-12T02:25:05.970Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-06-12T02:25:05.970Z] GC before operation: completed in 122.788 ms, heap usage 204.448 MB -> 75.741 MB.
[2025-06-12T02:25:12.610Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:25:16.782Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:25:19.798Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:25:22.817Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:25:24.774Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:25:26.727Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:25:28.681Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:25:30.635Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:25:30.635Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:25:30.636Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:25:30.636Z] Top recommended movies for user id 72:
[2025-06-12T02:25:30.636Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:25:30.636Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:25:30.636Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:25:30.636Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:25:30.636Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:25:30.636Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24851.614 ms) ======
[2025-06-12T02:25:30.636Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-06-12T02:25:31.587Z] GC before operation: completed in 139.784 ms, heap usage 496.655 MB -> 87.038 MB.
[2025-06-12T02:25:34.598Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:25:37.621Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:25:39.582Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:25:42.595Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:25:43.546Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:25:45.500Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:25:46.451Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:25:48.405Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:25:48.405Z] 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.
[2025-06-12T02:25:48.405Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:25:49.357Z] Top recommended movies for user id 72:
[2025-06-12T02:25:49.357Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:25:49.358Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:25:49.358Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:25:49.358Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:25:49.358Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:25:49.358Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17780.485 ms) ======
[2025-06-12T02:25:49.358Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-06-12T02:25:49.358Z] GC before operation: completed in 159.166 ms, heap usage 452.983 MB -> 91.363 MB.
[2025-06-12T02:25:51.311Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:25:54.329Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:25:56.288Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:25:58.239Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:26:00.194Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:26:01.147Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:26:03.099Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:26:04.051Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:26:05.003Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:26:05.003Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:26:05.003Z] Top recommended movies for user id 72:
[2025-06-12T02:26:05.003Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:26:05.003Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:26:05.003Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:26:05.003Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:26:05.003Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:26:05.003Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15643.962 ms) ======
[2025-06-12T02:26:05.003Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-06-12T02:26:05.003Z] GC before operation: completed in 149.481 ms, heap usage 437.158 MB -> 93.179 MB.
[2025-06-12T02:26:07.708Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:26:09.691Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:26:12.724Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:26:14.679Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:26:15.636Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:26:17.589Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:26:18.541Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:26:20.531Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:26:20.531Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:26:20.531Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:26:20.531Z] Top recommended movies for user id 72:
[2025-06-12T02:26:20.531Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:26:20.531Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:26:20.531Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:26:20.531Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:26:20.531Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:26:20.531Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15663.932 ms) ======
[2025-06-12T02:26:20.531Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-06-12T02:26:20.531Z] GC before operation: completed in 142.302 ms, heap usage 768.583 MB -> 96.034 MB.
[2025-06-12T02:26:23.549Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:26:25.501Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:26:27.454Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:26:30.468Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:26:31.418Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:26:32.369Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:26:34.323Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:26:35.273Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:26:36.223Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:26:36.223Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:26:36.223Z] Top recommended movies for user id 72:
[2025-06-12T02:26:36.223Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:26:36.223Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:26:36.223Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:26:36.223Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:26:36.223Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:26:36.223Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15386.157 ms) ======
[2025-06-12T02:26:36.223Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-06-12T02:26:36.223Z] GC before operation: completed in 124.197 ms, heap usage 279.359 MB -> 94.367 MB.
[2025-06-12T02:26:39.238Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:26:41.191Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:26:43.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:26:46.163Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:26:47.113Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:26:49.068Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:26:50.019Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:26:51.970Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:26:51.970Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:26:51.970Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:26:51.970Z] Top recommended movies for user id 72:
[2025-06-12T02:26:51.970Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:26:51.970Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:26:51.970Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:26:51.970Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:26:51.970Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:26:51.970Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15709.517 ms) ======
[2025-06-12T02:26:51.970Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-06-12T02:26:51.970Z] GC before operation: completed in 156.175 ms, heap usage 522.422 MB -> 95.895 MB.
[2025-06-12T02:26:53.949Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:26:56.969Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:26:58.922Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:27:00.879Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:27:03.532Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:27:04.662Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:27:05.636Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:27:06.585Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:27:07.546Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:27:07.546Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:27:07.546Z] Top recommended movies for user id 72:
[2025-06-12T02:27:07.546Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:27:07.546Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:27:07.546Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:27:07.546Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:27:07.546Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:27:07.546Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15374.565 ms) ======
[2025-06-12T02:27:07.546Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-06-12T02:27:07.546Z] GC before operation: completed in 135.984 ms, heap usage 766.310 MB -> 93.772 MB.
[2025-06-12T02:27:10.560Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:27:12.511Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:27:14.461Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:27:17.478Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:27:18.429Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:27:19.379Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:27:21.350Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:27:22.312Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:27:22.312Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:27:22.312Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:27:22.312Z] Top recommended movies for user id 72:
[2025-06-12T02:27:22.312Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:27:22.312Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:27:22.312Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:27:22.312Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:27:22.312Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:27:22.312Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14921.048 ms) ======
[2025-06-12T02:27:22.312Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-06-12T02:27:22.312Z] GC before operation: completed in 111.862 ms, heap usage 227.077 MB -> 93.729 MB.
[2025-06-12T02:27:25.335Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:27:27.300Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:27:29.257Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:27:31.256Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:27:32.209Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:27:34.166Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:27:35.117Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:27:36.067Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:27:37.021Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:27:37.021Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:27:37.021Z] Top recommended movies for user id 72:
[2025-06-12T02:27:37.021Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:27:37.021Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:27:37.021Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:27:37.021Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:27:37.021Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:27:37.021Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14238.179 ms) ======
[2025-06-12T02:27:37.021Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-06-12T02:27:37.021Z] GC before operation: completed in 126.114 ms, heap usage 439.605 MB -> 93.650 MB.
[2025-06-12T02:27:38.974Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:27:40.925Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:27:43.938Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:27:45.910Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:27:46.860Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:27:47.810Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:27:49.765Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:27:50.716Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:27:50.716Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:27:50.716Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:27:50.716Z] Top recommended movies for user id 72:
[2025-06-12T02:27:50.716Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:27:50.716Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:27:50.716Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:27:50.716Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:27:50.716Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:27:50.716Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14128.473 ms) ======
[2025-06-12T02:27:50.716Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-06-12T02:27:51.668Z] GC before operation: completed in 138.183 ms, heap usage 543.447 MB -> 93.849 MB.
[2025-06-12T02:27:53.623Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:27:55.575Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:27:57.525Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:28:00.052Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:28:01.025Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:28:02.979Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:28:03.931Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:28:05.883Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:28:05.883Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:28:05.883Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:28:05.883Z] Top recommended movies for user id 72:
[2025-06-12T02:28:05.883Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:28:05.883Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:28:05.883Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:28:05.883Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:28:05.883Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:28:05.883Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14582.330 ms) ======
[2025-06-12T02:28:05.883Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-06-12T02:28:05.883Z] GC before operation: completed in 137.829 ms, heap usage 519.191 MB -> 90.378 MB.
[2025-06-12T02:28:07.842Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:28:10.897Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:28:12.858Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:28:14.810Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:28:15.763Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:28:17.930Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:28:18.885Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:28:19.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:28:20.788Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:28:20.788Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:28:20.788Z] Top recommended movies for user id 72:
[2025-06-12T02:28:20.788Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:28:20.788Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:28:20.788Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:28:20.788Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:28:20.788Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:28:20.788Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14616.230 ms) ======
[2025-06-12T02:28:20.788Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-06-12T02:28:20.788Z] GC before operation: completed in 132.471 ms, heap usage 282.587 MB -> 92.592 MB.
[2025-06-12T02:28:22.745Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:28:25.761Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:28:28.775Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:28:30.739Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:28:31.691Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:28:33.643Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:28:34.594Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:28:36.544Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:28:36.544Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:28:36.544Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:28:36.544Z] Top recommended movies for user id 72:
[2025-06-12T02:28:36.544Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:28:36.544Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:28:36.544Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:28:36.544Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:28:36.544Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:28:36.544Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15848.737 ms) ======
[2025-06-12T02:28:36.544Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-06-12T02:28:36.544Z] GC before operation: completed in 128.193 ms, heap usage 193.887 MB -> 91.489 MB.
[2025-06-12T02:28:39.563Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:28:42.573Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:28:44.526Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:28:47.546Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:28:48.498Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:28:49.486Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:28:51.439Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:28:52.394Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:28:52.394Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:28:52.394Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:28:52.394Z] Top recommended movies for user id 72:
[2025-06-12T02:28:52.394Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:28:52.394Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:28:52.394Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:28:52.394Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:28:52.394Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:28:52.394Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16093.226 ms) ======
[2025-06-12T02:28:52.394Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-06-12T02:28:53.368Z] GC before operation: completed in 133.637 ms, heap usage 229.014 MB -> 93.497 MB.
[2025-06-12T02:28:55.196Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:28:57.149Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:29:00.176Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:29:02.126Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:29:03.078Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:29:04.029Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:29:05.981Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:29:07.088Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:29:07.088Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:29:07.088Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:29:08.039Z] Top recommended movies for user id 72:
[2025-06-12T02:29:08.039Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:29:08.039Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:29:08.039Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:29:08.039Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:29:08.039Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:29:08.039Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14680.587 ms) ======
[2025-06-12T02:29:08.039Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-06-12T02:29:08.039Z] GC before operation: completed in 118.931 ms, heap usage 505.424 MB -> 92.900 MB.
[2025-06-12T02:29:10.889Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:29:12.838Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:29:15.850Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:29:17.803Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:29:18.754Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:29:20.706Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:29:21.656Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:29:22.606Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:29:23.557Z] 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.
[2025-06-12T02:29:23.557Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:29:23.557Z] Top recommended movies for user id 72:
[2025-06-12T02:29:23.557Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:29:23.558Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:29:23.558Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:29:23.558Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:29:23.558Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:29:23.558Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15740.757 ms) ======
[2025-06-12T02:29:23.558Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-06-12T02:29:23.558Z] GC before operation: completed in 134.450 ms, heap usage 388.140 MB -> 92.681 MB.
[2025-06-12T02:29:26.577Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:29:28.530Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:29:30.488Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:29:32.439Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:29:34.480Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:29:35.432Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:29:36.384Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:29:38.337Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:29:38.337Z] 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.
[2025-06-12T02:29:38.337Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:29:38.337Z] Top recommended movies for user id 72:
[2025-06-12T02:29:38.337Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:29:38.337Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:29:38.337Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:29:38.337Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:29:38.337Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:29:38.337Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14813.236 ms) ======
[2025-06-12T02:29:38.337Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-06-12T02:29:38.337Z] GC before operation: completed in 140.214 ms, heap usage 437.674 MB -> 94.337 MB.
[2025-06-12T02:29:40.286Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:29:43.298Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:29:45.250Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:29:47.202Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:29:48.154Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:29:50.107Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:29:51.063Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:29:52.016Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:29:53.601Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:29:53.601Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:29:53.601Z] Top recommended movies for user id 72:
[2025-06-12T02:29:53.601Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:29:53.601Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:29:53.601Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:29:53.601Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:29:53.601Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:29:53.601Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14157.429 ms) ======
[2025-06-12T02:29:53.601Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-06-12T02:29:53.601Z] GC before operation: completed in 176.767 ms, heap usage 437.463 MB -> 90.424 MB.
[2025-06-12T02:29:54.558Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:29:57.575Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:29:59.529Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:30:01.484Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:30:02.436Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:30:04.534Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:30:05.484Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:30:06.487Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:30:06.487Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:30:06.487Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:30:07.441Z] Top recommended movies for user id 72:
[2025-06-12T02:30:07.441Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:30:07.441Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:30:07.441Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:30:07.441Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:30:07.441Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:30:07.441Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14166.148 ms) ======
[2025-06-12T02:30:07.441Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-06-12T02:30:07.441Z] GC before operation: completed in 116.230 ms, heap usage 488.661 MB -> 94.356 MB.
[2025-06-12T02:30:09.395Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-12T02:30:11.349Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-12T02:30:14.363Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-12T02:30:16.318Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-12T02:30:17.271Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-12T02:30:18.226Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-12T02:30:20.182Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-12T02:30:21.133Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-12T02:30:21.133Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-06-12T02:30:21.133Z] The best model improves the baseline by 14.52%.
[2025-06-12T02:30:22.087Z] Top recommended movies for user id 72:
[2025-06-12T02:30:22.087Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-06-12T02:30:22.087Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-06-12T02:30:22.087Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-06-12T02:30:22.087Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-06-12T02:30:22.087Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-06-12T02:30:22.087Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14439.212 ms) ======
[2025-06-12T02:30:22.087Z] -----------------------------------
[2025-06-12T02:30:22.087Z] renaissance-movie-lens_0_PASSED
[2025-06-12T02:30:22.087Z] -----------------------------------
[2025-06-12T02:30:22.087Z]
[2025-06-12T02:30:22.087Z] TEST TEARDOWN:
[2025-06-12T02:30:22.087Z] Nothing to be done for teardown.
[2025-06-12T02:30:22.087Z] renaissance-movie-lens_0 Finish Time: Thu Jun 12 02:30:21 2025 Epoch Time (ms): 1749695421614