renaissance-movie-lens_0
[2025-11-20T10:13:26.642Z] Running test renaissance-movie-lens_0 ...
[2025-11-20T10:13:26.642Z] ===============================================
[2025-11-20T10:13:26.976Z] renaissance-movie-lens_0 Start Time: Thu Nov 20 10:13:26 2025 Epoch Time (ms): 1763633606633
[2025-11-20T10:13:26.976Z] variation: NoOptions
[2025-11-20T10:13:26.976Z] JVM_OPTIONS:
[2025-11-20T10:13:26.976Z] { \
[2025-11-20T10:13:26.976Z] echo ""; echo "TEST SETUP:"; \
[2025-11-20T10:13:26.976Z] echo "Nothing to be done for setup."; \
[2025-11-20T10:13:26.976Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17636291647237/renaissance-movie-lens_0"; \
[2025-11-20T10:13:26.976Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17636291647237/renaissance-movie-lens_0"; \
[2025-11-20T10:13:26.976Z] echo ""; echo "TESTING:"; \
[2025-11-20T10:13:26.976Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_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_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17636291647237/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-20T10:13:26.976Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17636291647237/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-20T10:13:26.976Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-20T10:13:26.976Z] echo "Nothing to be done for teardown."; \
[2025-11-20T10:13:26.976Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17636291647237/TestTargetResult";
[2025-11-20T10:13:26.976Z]
[2025-11-20T10:13:26.976Z] TEST SETUP:
[2025-11-20T10:13:26.976Z] Nothing to be done for setup.
[2025-11-20T10:13:26.976Z]
[2025-11-20T10:13:26.976Z] TESTING:
[2025-11-20T10:13:49.994Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-20T10:14:23.301Z] 10:14:21.669 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.
[2025-11-20T10:14:34.113Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-20T10:14:37.058Z] Training: 60056, validation: 20285, test: 19854
[2025-11-20T10:14:37.058Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-20T10:14:37.058Z] GC before operation: completed in 536.260 ms, heap usage 372.559 MB -> 77.162 MB.
[2025-11-20T10:15:10.371Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:15:26.293Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:15:39.410Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:15:50.255Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:15:57.520Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:16:04.766Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:16:12.138Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:16:18.077Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:16:18.783Z] 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.
[2025-11-20T10:16:19.484Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:16:20.626Z] Top recommended movies for user id 72:
[2025-11-20T10:16:20.626Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:16:20.626Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:16:20.626Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:16:20.626Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:16:20.626Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:16:20.626Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (103371.985 ms) ======
[2025-11-20T10:16:20.626Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-20T10:16:21.343Z] GC before operation: completed in 858.806 ms, heap usage 259.516 MB -> 90.785 MB.
[2025-11-20T10:16:34.432Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:16:43.307Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:16:54.237Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:17:03.111Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:17:10.348Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:17:16.244Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:17:22.132Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:17:26.854Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:17:27.554Z] 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.
[2025-11-20T10:17:27.554Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:17:28.713Z] Top recommended movies for user id 72:
[2025-11-20T10:17:28.713Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:17:28.713Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:17:28.713Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:17:28.713Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:17:28.713Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:17:28.713Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (67060.477 ms) ======
[2025-11-20T10:17:28.713Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-20T10:17:29.435Z] GC before operation: completed in 926.717 ms, heap usage 1.105 GB -> 94.988 MB.
[2025-11-20T10:17:40.219Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:17:49.064Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:17:59.841Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:18:07.064Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:18:12.954Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:18:18.836Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:18:24.734Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:18:29.467Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:18:30.599Z] 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.
[2025-11-20T10:18:30.599Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:18:31.297Z] Top recommended movies for user id 72:
[2025-11-20T10:18:31.297Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:18:31.297Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:18:31.297Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:18:31.297Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:18:31.297Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:18:31.297Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (61924.434 ms) ======
[2025-11-20T10:18:31.297Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-20T10:18:32.467Z] GC before operation: completed in 953.481 ms, heap usage 691.656 MB -> 94.241 MB.
[2025-11-20T10:18:43.253Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:18:50.629Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:18:59.495Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:19:08.336Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:19:14.211Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:19:20.070Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:19:24.780Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:19:30.694Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:19:31.035Z] 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.
[2025-11-20T10:19:31.363Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:19:32.059Z] Top recommended movies for user id 72:
[2025-11-20T10:19:32.059Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:19:32.059Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:19:32.059Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:19:32.059Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:19:32.059Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:19:32.059Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (59721.549 ms) ======
[2025-11-20T10:19:32.059Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-20T10:19:32.806Z] GC before operation: completed in 937.586 ms, heap usage 705.946 MB -> 94.675 MB.
[2025-11-20T10:19:43.585Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:19:52.441Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:20:01.302Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:20:10.160Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:20:14.882Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:20:19.612Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:20:25.497Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:20:31.359Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:20:32.066Z] 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.
[2025-11-20T10:20:32.066Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:20:32.764Z] Top recommended movies for user id 72:
[2025-11-20T10:20:32.764Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:20:32.764Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:20:32.764Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:20:32.764Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:20:32.764Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:20:32.764Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (59894.320 ms) ======
[2025-11-20T10:20:32.764Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-20T10:20:33.938Z] GC before operation: completed in 949.366 ms, heap usage 367.707 MB -> 90.922 MB.
[2025-11-20T10:20:44.815Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:20:52.046Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:21:00.904Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:21:08.153Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:21:14.024Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:21:18.875Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:21:23.655Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:21:29.535Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:21:29.535Z] 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.
[2025-11-20T10:21:29.535Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:21:30.235Z] Top recommended movies for user id 72:
[2025-11-20T10:21:30.235Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:21:30.235Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:21:30.235Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:21:30.235Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:21:30.235Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:21:30.235Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (56455.730 ms) ======
[2025-11-20T10:21:30.235Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-20T10:21:31.412Z] GC before operation: completed in 962.455 ms, heap usage 830.475 MB -> 95.296 MB.
[2025-11-20T10:21:40.262Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:21:49.108Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:21:56.348Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:22:05.235Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:22:09.951Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:22:14.671Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:22:19.417Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:22:24.149Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:22:25.284Z] 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.
[2025-11-20T10:22:25.284Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:22:25.991Z] Top recommended movies for user id 72:
[2025-11-20T10:22:25.991Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:22:25.991Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:22:25.991Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:22:25.991Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:22:25.991Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:22:25.991Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (54646.091 ms) ======
[2025-11-20T10:22:25.991Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-20T10:22:26.715Z] GC before operation: completed in 975.824 ms, heap usage 278.379 MB -> 91.074 MB.
[2025-11-20T10:22:35.729Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:22:42.966Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:22:51.812Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:22:59.079Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:23:03.814Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:23:09.687Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:23:14.480Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:23:19.201Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:23:19.528Z] 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.
[2025-11-20T10:23:19.853Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:23:20.176Z] Top recommended movies for user id 72:
[2025-11-20T10:23:20.176Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:23:20.176Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:23:20.176Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:23:20.176Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:23:20.176Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:23:20.176Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (53438.499 ms) ======
[2025-11-20T10:23:20.176Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-20T10:23:21.345Z] GC before operation: completed in 981.321 ms, heap usage 547.582 MB -> 94.859 MB.
[2025-11-20T10:23:30.194Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:23:39.045Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:23:46.277Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:23:53.619Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:23:58.344Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:24:03.061Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:24:07.792Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:24:12.557Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:24:13.260Z] 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.
[2025-11-20T10:24:13.586Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:24:14.300Z] Top recommended movies for user id 72:
[2025-11-20T10:24:14.300Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:24:14.300Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:24:14.300Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:24:14.300Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:24:14.300Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:24:14.300Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (52920.509 ms) ======
[2025-11-20T10:24:14.300Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-20T10:24:15.028Z] GC before operation: completed in 982.074 ms, heap usage 978.831 MB -> 95.975 MB.
[2025-11-20T10:24:24.017Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:24:32.884Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:24:40.118Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:24:47.344Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:24:52.054Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:24:56.775Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:25:01.543Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:25:06.277Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:25:06.980Z] 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.
[2025-11-20T10:25:06.980Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:25:07.680Z] Top recommended movies for user id 72:
[2025-11-20T10:25:07.680Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:25:07.680Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:25:07.680Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:25:07.680Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:25:07.680Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:25:07.680Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (52525.490 ms) ======
[2025-11-20T10:25:07.680Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-20T10:25:08.833Z] GC before operation: completed in 984.200 ms, heap usage 237.730 MB -> 91.253 MB.
[2025-11-20T10:25:17.679Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:25:24.911Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:25:33.763Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:25:41.015Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:25:45.734Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:25:50.458Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:25:55.232Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:25:59.959Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:26:00.656Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-20T10:26:00.656Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:26:01.356Z] Top recommended movies for user id 72:
[2025-11-20T10:26:01.356Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:26:01.356Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:26:01.356Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:26:01.356Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:26:01.356Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:26:01.356Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (52611.181 ms) ======
[2025-11-20T10:26:01.356Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-20T10:26:02.514Z] GC before operation: completed in 973.292 ms, heap usage 505.250 MB -> 91.410 MB.
[2025-11-20T10:26:11.361Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:26:18.657Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:26:27.510Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:26:34.749Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:26:40.617Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:26:46.492Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:26:51.223Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:26:57.164Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:26:57.485Z] 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.
[2025-11-20T10:26:57.485Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:26:58.182Z] Top recommended movies for user id 72:
[2025-11-20T10:26:58.182Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:26:58.182Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:26:58.182Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:26:58.182Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:26:58.182Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:26:58.182Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (55925.341 ms) ======
[2025-11-20T10:26:58.182Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-20T10:26:59.318Z] GC before operation: completed in 1010.118 ms, heap usage 872.852 MB -> 95.510 MB.
[2025-11-20T10:27:10.099Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:27:20.875Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:27:29.717Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:27:38.637Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:27:43.358Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:27:49.227Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:27:53.996Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:27:58.722Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:27:59.422Z] 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.
[2025-11-20T10:27:59.422Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:28:00.121Z] Top recommended movies for user id 72:
[2025-11-20T10:28:00.121Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:28:00.121Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:28:00.121Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:28:00.121Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:28:00.121Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:28:00.121Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (60983.227 ms) ======
[2025-11-20T10:28:00.121Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-20T10:28:01.295Z] GC before operation: completed in 971.425 ms, heap usage 916.951 MB -> 100.047 MB.
[2025-11-20T10:28:10.135Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:28:19.294Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:28:26.537Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:28:33.762Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:28:39.626Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:28:44.339Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:28:49.207Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:28:53.921Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:28:54.247Z] 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.
[2025-11-20T10:28:54.247Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:28:55.395Z] Top recommended movies for user id 72:
[2025-11-20T10:28:55.395Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:28:55.395Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:28:55.395Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:28:55.395Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:28:55.395Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:28:55.395Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (53966.584 ms) ======
[2025-11-20T10:28:55.395Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-20T10:28:56.120Z] GC before operation: completed in 940.938 ms, heap usage 178.201 MB -> 91.127 MB.
[2025-11-20T10:29:06.937Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:29:14.154Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:29:22.988Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:29:29.067Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:29:33.808Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:29:38.539Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:29:43.259Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:29:47.979Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:29:49.113Z] 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.
[2025-11-20T10:29:49.113Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:29:49.817Z] Top recommended movies for user id 72:
[2025-11-20T10:29:49.817Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:29:49.817Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:29:49.817Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:29:49.817Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:29:49.817Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:29:49.817Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (53639.183 ms) ======
[2025-11-20T10:29:49.817Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-20T10:29:50.973Z] GC before operation: completed in 999.132 ms, heap usage 248.124 MB -> 91.357 MB.
[2025-11-20T10:29:59.809Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:30:08.686Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:30:15.913Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:30:23.124Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:30:28.978Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:30:33.686Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:30:41.039Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:30:41.373Z] Exception in thread "Executor task launch worker for task 3.0 in stage 24534.0 (TID 23856)" java.lang.AssertionError: assertion failed: task count shouldn't below 0
[2025-11-20T10:30:41.373Z] at scala.Predef$.assert(Predef.scala:279)
[2025-11-20T10:30:41.373Z] at org.apache.spark.executor.ExecutorMetricsPoller.decrementCount$1(ExecutorMetricsPoller.scala:133)
[2025-11-20T10:30:41.373Z] at org.apache.spark.executor.ExecutorMetricsPoller.$anonfun$onTaskCompletion$3(ExecutorMetricsPoller.scala:138)
[2025-11-20T10:30:41.373Z] at java.base/java.util.concurrent.ConcurrentHashMap.computeIfPresent(ConcurrentHashMap.java:1828)
[2025-11-20T10:30:41.373Z] at org.apache.spark.executor.ExecutorMetricsPoller.onTaskCompletion(ExecutorMetricsPoller.scala:138)
[2025-11-20T10:30:41.373Z] at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:834)
[2025-11-20T10:30:41.373Z] at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136)
[2025-11-20T10:30:41.373Z] at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
[2025-11-20T10:30:41.373Z] at java.base/java.lang.Thread.run(Thread.java:840)
[2025-11-20T10:30:46.083Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:30:46.778Z] 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.
[2025-11-20T10:30:47.105Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:30:47.815Z] Top recommended movies for user id 72:
[2025-11-20T10:30:47.815Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:30:47.815Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:30:47.815Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:30:47.815Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:30:47.815Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:30:47.815Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (56921.466 ms) ======
[2025-11-20T10:30:47.815Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-20T10:30:48.547Z] GC before operation: completed in 952.238 ms, heap usage 713.151 MB -> 95.129 MB.
[2025-11-20T10:30:59.375Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:31:08.217Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:31:17.057Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:31:25.979Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:31:30.690Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:31:35.430Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:31:40.141Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:31:46.002Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:31:46.002Z] 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.
[2025-11-20T10:31:46.002Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:31:46.698Z] Top recommended movies for user id 72:
[2025-11-20T10:31:46.698Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:31:46.698Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:31:46.698Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:31:46.698Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:31:46.698Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:31:46.698Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (58125.423 ms) ======
[2025-11-20T10:31:46.698Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-20T10:31:47.873Z] GC before operation: completed in 957.740 ms, heap usage 341.405 MB -> 92.765 MB.
[2025-11-20T10:31:56.718Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:32:04.043Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:32:11.279Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:32:20.177Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:32:24.159Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:32:28.887Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:32:33.609Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:32:38.413Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:32:38.737Z] 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.
[2025-11-20T10:32:38.737Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:32:39.445Z] Top recommended movies for user id 72:
[2025-11-20T10:32:39.445Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:32:39.445Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:32:39.445Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:32:39.445Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:32:39.445Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:32:39.445Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (51656.695 ms) ======
[2025-11-20T10:32:39.445Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-20T10:32:40.181Z] GC before operation: completed in 979.491 ms, heap usage 696.383 MB -> 95.034 MB.
[2025-11-20T10:32:50.982Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:32:58.233Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:33:07.082Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:33:14.351Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:33:18.271Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:33:22.990Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:33:28.868Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:33:33.592Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:33:33.592Z] 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.
[2025-11-20T10:33:33.920Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:33:34.620Z] Top recommended movies for user id 72:
[2025-11-20T10:33:34.620Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:33:34.620Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:33:34.620Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:33:34.620Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:33:34.620Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:33:34.620Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (54276.550 ms) ======
[2025-11-20T10:33:34.620Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-20T10:33:35.780Z] GC before operation: completed in 984.978 ms, heap usage 909.131 MB -> 95.846 MB.
[2025-11-20T10:33:44.639Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T10:33:51.893Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T10:33:59.145Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T10:34:07.994Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T10:34:11.743Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T10:34:16.465Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T10:34:21.182Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T10:34:25.916Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T10:34:26.662Z] 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.
[2025-11-20T10:34:26.662Z] The best model improves the baseline by 14.52%.
[2025-11-20T10:34:27.365Z] Top recommended movies for user id 72:
[2025-11-20T10:34:27.365Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T10:34:27.365Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T10:34:27.365Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T10:34:27.365Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T10:34:27.365Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T10:34:27.365Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (51708.298 ms) ======
[2025-11-20T10:34:31.117Z] -----------------------------------
[2025-11-20T10:34:31.117Z] renaissance-movie-lens_0_PASSED
[2025-11-20T10:34:31.117Z] -----------------------------------
[2025-11-20T10:34:31.117Z]
[2025-11-20T10:34:31.117Z] TEST TEARDOWN:
[2025-11-20T10:34:31.117Z] Nothing to be done for teardown.
[2025-11-20T10:34:31.117Z] renaissance-movie-lens_0 Finish Time: Thu Nov 20 10:34:30 2025 Epoch Time (ms): 1763634870823