renaissance-movie-lens_0
[2025-09-04T02:19:44.186Z] Running test renaissance-movie-lens_0 ...
[2025-09-04T02:19:44.186Z] ===============================================
[2025-09-04T02:19:44.186Z] renaissance-movie-lens_0 Start Time: Thu Sep 4 02:19:43 2025 Epoch Time (ms): 1756952383038
[2025-09-04T02:19:44.186Z] variation: NoOptions
[2025-09-04T02:19:44.186Z] JVM_OPTIONS:
[2025-09-04T02:19:44.186Z] { \
[2025-09-04T02:19:44.186Z] echo ""; echo "TEST SETUP:"; \
[2025-09-04T02:19:44.186Z] echo "Nothing to be done for setup."; \
[2025-09-04T02:19:44.186Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569508575764/renaissance-movie-lens_0"; \
[2025-09-04T02:19:44.186Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569508575764/renaissance-movie-lens_0"; \
[2025-09-04T02:19:44.186Z] echo ""; echo "TESTING:"; \
[2025-09-04T02:19:44.186Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_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_aarch64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569508575764/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-04T02:19:44.186Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569508575764/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-04T02:19:44.186Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-04T02:19:44.186Z] echo "Nothing to be done for teardown."; \
[2025-09-04T02:19:44.186Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569508575764/TestTargetResult";
[2025-09-04T02:19:44.186Z]
[2025-09-04T02:19:44.186Z] TEST SETUP:
[2025-09-04T02:19:44.186Z] Nothing to be done for setup.
[2025-09-04T02:19:44.186Z]
[2025-09-04T02:19:44.186Z] TESTING:
[2025-09-04T02:19:52.291Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-09-04T02:20:03.778Z] 02:20:03.107 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-04T02:20:07.922Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-04T02:20:08.872Z] Training: 60056, validation: 20285, test: 19854
[2025-09-04T02:20:08.872Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-04T02:20:08.872Z] GC before operation: completed in 191.290 ms, heap usage 321.676 MB -> 75.765 MB.
[2025-09-04T02:20:21.279Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:20:27.971Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:20:33.339Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:20:38.702Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:20:40.653Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:20:43.656Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:20:46.660Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:20:48.610Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:20:49.562Z] 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.
[2025-09-04T02:20:49.562Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:20:49.562Z] Top recommended movies for user id 72:
[2025-09-04T02:20:49.562Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:20:49.562Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:20:49.562Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:20:49.562Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:20:49.562Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:20:49.562Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (40392.555 ms) ======
[2025-09-04T02:20:49.562Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-04T02:20:49.562Z] GC before operation: completed in 217.141 ms, heap usage 690.940 MB -> 96.926 MB.
[2025-09-04T02:20:54.917Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:20:59.048Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:21:03.185Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:21:07.318Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:21:09.268Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:21:13.148Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:21:14.098Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:21:17.101Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:21:17.101Z] 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.
[2025-09-04T02:21:17.101Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:21:18.050Z] Top recommended movies for user id 72:
[2025-09-04T02:21:18.050Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:21:18.050Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:21:18.050Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:21:18.050Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:21:18.050Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:21:18.050Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (27957.154 ms) ======
[2025-09-04T02:21:18.050Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-04T02:21:18.050Z] GC before operation: completed in 182.705 ms, heap usage 743.135 MB -> 92.324 MB.
[2025-09-04T02:21:22.182Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:21:26.316Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:21:30.455Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:21:33.451Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:21:36.455Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:21:38.403Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:21:41.410Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:21:43.360Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:21:43.360Z] 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.
[2025-09-04T02:21:43.360Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:21:43.360Z] Top recommended movies for user id 72:
[2025-09-04T02:21:43.360Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:21:43.360Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:21:43.360Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:21:43.360Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:21:43.360Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:21:43.360Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (25714.645 ms) ======
[2025-09-04T02:21:43.360Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-04T02:21:44.306Z] GC before operation: completed in 189.334 ms, heap usage 493.452 MB -> 96.263 MB.
[2025-09-04T02:21:47.312Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:21:51.445Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:21:55.582Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:21:58.591Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:22:00.540Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:22:03.541Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:22:05.668Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:22:08.128Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:22:08.128Z] 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.
[2025-09-04T02:22:08.128Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:22:08.128Z] Top recommended movies for user id 72:
[2025-09-04T02:22:08.128Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:22:08.128Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:22:08.128Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:22:08.128Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:22:08.128Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:22:08.128Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (24577.112 ms) ======
[2025-09-04T02:22:08.128Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-04T02:22:09.075Z] GC before operation: completed in 191.042 ms, heap usage 752.645 MB -> 96.651 MB.
[2025-09-04T02:22:12.077Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:22:16.216Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:22:19.230Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:22:23.362Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:22:25.311Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:22:27.300Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:22:30.303Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:22:32.245Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:22:32.246Z] 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.
[2025-09-04T02:22:32.246Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:22:33.195Z] Top recommended movies for user id 72:
[2025-09-04T02:22:33.195Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:22:33.195Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:22:33.195Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:22:33.195Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:22:33.195Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:22:33.195Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (24230.456 ms) ======
[2025-09-04T02:22:33.195Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-04T02:22:33.195Z] GC before operation: completed in 185.011 ms, heap usage 485.577 MB -> 91.931 MB.
[2025-09-04T02:22:37.341Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:22:41.483Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:22:45.621Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:22:48.629Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:22:50.573Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:22:52.519Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:22:55.517Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:22:57.464Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:22:57.464Z] 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.
[2025-09-04T02:22:57.464Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:22:58.413Z] Top recommended movies for user id 72:
[2025-09-04T02:22:58.413Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:22:58.413Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:22:58.413Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:22:58.413Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:22:58.413Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:22:58.413Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (24908.570 ms) ======
[2025-09-04T02:22:58.413Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-04T02:22:58.413Z] GC before operation: completed in 182.295 ms, heap usage 260.911 MB -> 96.653 MB.
[2025-09-04T02:23:02.114Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:23:05.116Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:23:09.258Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:23:12.261Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:23:14.206Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:23:16.149Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:23:18.099Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:23:20.047Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:23:20.047Z] 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.
[2025-09-04T02:23:20.996Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:23:20.996Z] Top recommended movies for user id 72:
[2025-09-04T02:23:20.996Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:23:20.996Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:23:20.996Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:23:20.996Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:23:20.996Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:23:20.996Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (22664.387 ms) ======
[2025-09-04T02:23:20.996Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-04T02:23:20.996Z] GC before operation: completed in 190.629 ms, heap usage 210.579 MB -> 94.055 MB.
[2025-09-04T02:23:25.128Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:23:28.300Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:23:31.313Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:23:34.318Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:23:36.264Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:23:38.206Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:23:40.149Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:23:42.101Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:23:43.055Z] 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.
[2025-09-04T02:23:43.055Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:23:43.055Z] Top recommended movies for user id 72:
[2025-09-04T02:23:43.055Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:23:43.055Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:23:43.055Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:23:43.055Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:23:43.055Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:23:43.055Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21929.518 ms) ======
[2025-09-04T02:23:43.055Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-04T02:23:43.055Z] GC before operation: completed in 192.870 ms, heap usage 671.875 MB -> 93.735 MB.
[2025-09-04T02:23:47.204Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:23:50.212Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:23:55.050Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:23:56.999Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:23:58.949Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:24:00.898Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:24:02.850Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:24:05.877Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:24:05.877Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-04T02:24:05.877Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:24:05.877Z] Top recommended movies for user id 72:
[2025-09-04T02:24:05.877Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:24:05.877Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:24:05.877Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:24:05.877Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:24:05.877Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:24:05.877Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (22848.375 ms) ======
[2025-09-04T02:24:05.877Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-04T02:24:05.877Z] GC before operation: completed in 188.733 ms, heap usage 263.823 MB -> 89.814 MB.
[2025-09-04T02:24:10.017Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:24:13.020Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:24:17.154Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:24:20.154Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:24:22.100Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:24:24.219Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:24:26.208Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:24:28.160Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:24:28.160Z] 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.
[2025-09-04T02:24:28.160Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:24:28.160Z] Top recommended movies for user id 72:
[2025-09-04T02:24:28.160Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:24:28.160Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:24:28.160Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:24:28.160Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:24:28.160Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:24:28.160Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (22300.661 ms) ======
[2025-09-04T02:24:28.160Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-04T02:24:29.111Z] GC before operation: completed in 182.795 ms, heap usage 126.577 MB -> 93.757 MB.
[2025-09-04T02:24:32.118Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:24:36.246Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:24:39.253Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:24:42.258Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:24:44.207Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:24:46.152Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:24:48.959Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:24:50.904Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:24:50.904Z] 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.
[2025-09-04T02:24:50.904Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:24:50.904Z] Top recommended movies for user id 72:
[2025-09-04T02:24:50.904Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:24:50.904Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:24:50.904Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:24:50.904Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:24:50.904Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:24:50.904Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (22493.192 ms) ======
[2025-09-04T02:24:50.904Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-04T02:24:50.904Z] GC before operation: completed in 186.770 ms, heap usage 244.616 MB -> 95.362 MB.
[2025-09-04T02:24:55.046Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:24:58.058Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:25:02.191Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:25:05.245Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:25:07.188Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:25:09.134Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:25:11.075Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:25:13.027Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:25:13.027Z] 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.
[2025-09-04T02:25:13.027Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:25:13.975Z] Top recommended movies for user id 72:
[2025-09-04T02:25:13.975Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:25:13.975Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:25:13.975Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:25:13.975Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:25:13.975Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:25:13.975Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (22367.713 ms) ======
[2025-09-04T02:25:13.975Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-04T02:25:13.975Z] GC before operation: completed in 188.350 ms, heap usage 195.719 MB -> 94.288 MB.
[2025-09-04T02:25:16.986Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:25:21.124Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:25:24.124Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:25:26.221Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:25:28.173Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:25:30.113Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:25:33.120Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:25:35.069Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:25:35.069Z] 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.
[2025-09-04T02:25:35.069Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:25:35.069Z] Top recommended movies for user id 72:
[2025-09-04T02:25:35.069Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:25:35.069Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:25:35.069Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:25:35.069Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:25:35.069Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:25:35.069Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (21527.393 ms) ======
[2025-09-04T02:25:35.069Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-04T02:25:36.015Z] GC before operation: completed in 185.130 ms, heap usage 201.989 MB -> 92.423 MB.
[2025-09-04T02:25:39.010Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:25:44.245Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:25:46.188Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:25:49.197Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:25:51.137Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:25:53.087Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:25:55.031Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:25:56.989Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:25:56.989Z] 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.
[2025-09-04T02:25:56.989Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:25:56.989Z] Top recommended movies for user id 72:
[2025-09-04T02:25:56.989Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:25:56.989Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:25:56.989Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:25:56.989Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:25:56.989Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:25:56.989Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (21742.346 ms) ======
[2025-09-04T02:25:56.989Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-04T02:25:57.935Z] GC before operation: completed in 188.985 ms, heap usage 785.745 MB -> 93.944 MB.
[2025-09-04T02:26:00.944Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:26:05.081Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:26:08.084Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:26:12.220Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:26:13.166Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:26:16.175Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:26:18.123Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:26:20.071Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:26:20.071Z] 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.
[2025-09-04T02:26:20.071Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:26:21.020Z] Top recommended movies for user id 72:
[2025-09-04T02:26:21.020Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:26:21.020Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:26:21.020Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:26:21.020Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:26:21.020Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:26:21.020Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (23031.918 ms) ======
[2025-09-04T02:26:21.020Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-04T02:26:21.020Z] GC before operation: completed in 186.401 ms, heap usage 290.752 MB -> 90.220 MB.
[2025-09-04T02:26:25.155Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:26:29.414Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:26:33.550Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:26:39.665Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:26:39.665Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:26:41.613Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:26:43.571Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:26:46.593Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:26:46.593Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-04T02:26:46.593Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:26:46.593Z] Top recommended movies for user id 72:
[2025-09-04T02:26:46.593Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:26:46.593Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:26:46.593Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:26:46.593Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:26:46.593Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:26:46.593Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (25990.845 ms) ======
[2025-09-04T02:26:46.593Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-04T02:26:46.593Z] GC before operation: completed in 207.413 ms, heap usage 717.642 MB -> 93.901 MB.
[2025-09-04T02:26:50.730Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:26:54.880Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:26:57.890Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:27:00.898Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:27:02.844Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:27:04.792Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:27:07.805Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:27:08.751Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:27:09.701Z] 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.
[2025-09-04T02:27:09.701Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:27:09.701Z] Top recommended movies for user id 72:
[2025-09-04T02:27:09.701Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:27:09.701Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:27:09.701Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:27:09.701Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:27:09.701Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:27:09.701Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (22859.314 ms) ======
[2025-09-04T02:27:09.701Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-04T02:27:09.701Z] GC before operation: completed in 197.557 ms, heap usage 748.224 MB -> 97.537 MB.
[2025-09-04T02:27:13.844Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:27:16.851Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:27:20.996Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:27:24.002Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:27:24.951Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:27:27.052Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:27:30.060Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:27:32.013Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:27:32.013Z] 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.
[2025-09-04T02:27:32.013Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:27:32.013Z] Top recommended movies for user id 72:
[2025-09-04T02:27:32.013Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:27:32.013Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:27:32.013Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:27:32.013Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:27:32.013Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:27:32.013Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (22161.466 ms) ======
[2025-09-04T02:27:32.013Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-04T02:27:32.013Z] GC before operation: completed in 184.162 ms, heap usage 220.123 MB -> 89.841 MB.
[2025-09-04T02:27:36.143Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:27:39.151Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:27:43.288Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:27:46.295Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:27:47.240Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:27:50.246Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:27:52.193Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:27:54.148Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:27:54.148Z] 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.
[2025-09-04T02:27:54.148Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:27:55.101Z] Top recommended movies for user id 72:
[2025-09-04T02:27:55.101Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:27:55.101Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:27:55.101Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:27:55.101Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:27:55.101Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:27:55.101Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (22491.690 ms) ======
[2025-09-04T02:27:55.101Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-04T02:27:55.101Z] GC before operation: completed in 199.010 ms, heap usage 286.408 MB -> 90.148 MB.
[2025-09-04T02:27:59.262Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T02:28:02.268Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T02:28:06.417Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T02:28:09.418Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T02:28:11.369Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T02:28:13.312Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T02:28:15.263Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T02:28:18.269Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T02:28:18.269Z] 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.
[2025-09-04T02:28:18.269Z] The best model improves the baseline by 14.52%.
[2025-09-04T02:28:18.269Z] Top recommended movies for user id 72:
[2025-09-04T02:28:18.269Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T02:28:18.269Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T02:28:18.269Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T02:28:18.269Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T02:28:18.269Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T02:28:18.269Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (23372.255 ms) ======
[2025-09-04T02:28:20.212Z] -----------------------------------
[2025-09-04T02:28:20.212Z] renaissance-movie-lens_0_PASSED
[2025-09-04T02:28:20.212Z] -----------------------------------
[2025-09-04T02:28:20.212Z]
[2025-09-04T02:28:20.212Z] TEST TEARDOWN:
[2025-09-04T02:28:20.212Z] Nothing to be done for teardown.
[2025-09-04T02:28:20.212Z] renaissance-movie-lens_0 Finish Time: Thu Sep 4 02:28:19 2025 Epoch Time (ms): 1756952899376