renaissance-movie-lens_0
[2025-11-28T05:00:15.876Z] Running test renaissance-movie-lens_0 ...
[2025-11-28T05:00:15.876Z] ===============================================
[2025-11-28T05:00:15.876Z] renaissance-movie-lens_0 Start Time: Fri Nov 28 05:00:15 2025 Epoch Time (ms): 1764306015439
[2025-11-28T05:00:15.876Z] variation: NoOptions
[2025-11-28T05:00:15.876Z] JVM_OPTIONS:
[2025-11-28T05:00:15.876Z] { \
[2025-11-28T05:00:15.876Z] echo ""; echo "TEST SETUP:"; \
[2025-11-28T05:00:15.876Z] echo "Nothing to be done for setup."; \
[2025-11-28T05:00:15.876Z] mkdir -p "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17643048823248/renaissance-movie-lens_0"; \
[2025-11-28T05:00:15.876Z] cd "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17643048823248/renaissance-movie-lens_0"; \
[2025-11-28T05:00:15.876Z] echo ""; echo "TESTING:"; \
[2025-11-28T05:00:15.876Z] "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1_rerun/jdkbinary/j2sdk-image/Contents/Home/bin/..//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 "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17643048823248/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-28T05:00:15.876Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/..; rm -f -r "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17643048823248/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-28T05:00:15.876Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-28T05:00:15.876Z] echo "Nothing to be done for teardown."; \
[2025-11-28T05:00:15.876Z] } 2>&1 | tee -a "/Users/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_1_rerun/aqa-tests/TKG/../TKG/output_17643048823248/TestTargetResult";
[2025-11-28T05:00:15.876Z]
[2025-11-28T05:00:15.876Z] TEST SETUP:
[2025-11-28T05:00:15.876Z] Nothing to be done for setup.
[2025-11-28T05:00:15.876Z]
[2025-11-28T05:00:15.876Z] TESTING:
[2025-11-28T05:00:21.991Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2025-11-28T05:00:31.148Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-28T05:00:31.503Z] Training: 60056, validation: 20285, test: 19854
[2025-11-28T05:00:31.504Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-28T05:00:31.504Z] GC before operation: completed in 106.350 ms, heap usage 970.833 MB -> 76.300 MB.
[2025-11-28T05:00:59.684Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:01:19.201Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:01:38.750Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:01:58.267Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:02:05.784Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:02:14.949Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:02:28.394Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:02:35.915Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:02:35.915Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:02:35.915Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:02:36.269Z] Top recommended movies for user id 72:
[2025-11-28T05:02:36.269Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:02:36.269Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:02:36.269Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:02:36.269Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:02:36.269Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:02:36.269Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (124552.151 ms) ======
[2025-11-28T05:02:36.269Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-28T05:02:36.269Z] GC before operation: completed in 117.283 ms, heap usage 1.053 GB -> 113.601 MB.
[2025-11-28T05:02:55.787Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:03:15.297Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:03:38.812Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:03:55.071Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:04:04.229Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:04:11.784Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:04:25.222Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:04:34.382Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:04:34.382Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:04:34.382Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:04:34.382Z] Top recommended movies for user id 72:
[2025-11-28T05:04:34.382Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:04:34.382Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:04:34.382Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:04:34.382Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:04:34.382Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:04:34.382Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (117736.315 ms) ======
[2025-11-28T05:04:34.382Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-28T05:04:34.382Z] GC before operation: completed in 118.319 ms, heap usage 373.189 MB -> 119.181 MB.
[2025-11-28T05:04:53.900Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:05:13.462Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:05:36.914Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:05:50.390Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:06:01.568Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:06:09.083Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:06:22.535Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:06:30.134Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:06:30.134Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:06:30.134Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:06:30.134Z] Top recommended movies for user id 72:
[2025-11-28T05:06:30.134Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:06:30.134Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:06:30.134Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:06:30.134Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:06:30.134Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:06:30.134Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (115903.525 ms) ======
[2025-11-28T05:06:30.134Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-28T05:06:30.134Z] GC before operation: completed in 111.952 ms, heap usage 261.742 MB -> 120.059 MB.
[2025-11-28T05:06:49.652Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:07:09.234Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:07:28.758Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:07:45.011Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:07:56.125Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:08:03.637Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:08:17.109Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:08:24.631Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:08:24.631Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:08:24.631Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:08:24.984Z] Top recommended movies for user id 72:
[2025-11-28T05:08:24.984Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:08:24.984Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:08:24.984Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:08:24.984Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:08:24.984Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:08:24.984Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (114752.812 ms) ======
[2025-11-28T05:08:24.984Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-28T05:08:24.984Z] GC before operation: completed in 111.495 ms, heap usage 260.824 MB -> 120.253 MB.
[2025-11-28T05:08:44.518Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:09:04.034Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:09:27.493Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:09:40.931Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:09:52.057Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:09:59.568Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:10:13.049Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:10:20.561Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:10:20.561Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:10:20.561Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:10:20.917Z] Top recommended movies for user id 72:
[2025-11-28T05:10:20.917Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:10:20.917Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:10:20.917Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:10:20.917Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:10:20.917Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:10:20.917Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (115795.959 ms) ======
[2025-11-28T05:10:20.917Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-28T05:10:20.917Z] GC before operation: completed in 111.705 ms, heap usage 249.915 MB -> 120.264 MB.
[2025-11-28T05:10:40.420Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:10:59.963Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:11:23.420Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:11:39.650Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:11:48.827Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:11:56.332Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:12:09.776Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:12:17.307Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:12:17.307Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:12:17.307Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:12:17.307Z] Top recommended movies for user id 72:
[2025-11-28T05:12:17.307Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:12:17.307Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:12:17.307Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:12:17.307Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:12:17.307Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:12:17.307Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (116393.708 ms) ======
[2025-11-28T05:12:17.307Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-28T05:12:17.307Z] GC before operation: completed in 118.205 ms, heap usage 1.026 GB -> 120.969 MB.
[2025-11-28T05:12:36.829Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:12:56.351Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:13:19.810Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:13:33.260Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:13:44.382Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:13:53.552Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:14:04.668Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:14:13.830Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:14:13.830Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:14:13.830Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:14:13.830Z] Top recommended movies for user id 72:
[2025-11-28T05:14:13.830Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:14:13.830Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:14:13.830Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:14:13.830Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:14:13.830Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:14:13.830Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (116298.655 ms) ======
[2025-11-28T05:14:13.830Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-28T05:14:13.830Z] GC before operation: completed in 110.218 ms, heap usage 241.707 MB -> 120.455 MB.
[2025-11-28T05:14:33.350Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:14:52.857Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:15:16.325Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:15:32.550Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:15:41.719Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:15:49.235Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:16:02.687Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:16:10.212Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:16:10.566Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:16:10.566Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:16:10.566Z] Top recommended movies for user id 72:
[2025-11-28T05:16:10.566Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:16:10.566Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:16:10.566Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:16:10.566Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:16:10.566Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:16:10.566Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (116844.266 ms) ======
[2025-11-28T05:16:10.566Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-28T05:16:10.920Z] GC before operation: completed in 113.796 ms, heap usage 268.882 MB -> 120.851 MB.
[2025-11-28T05:16:30.476Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:16:49.989Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:17:13.442Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:17:26.885Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:17:38.007Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:17:47.168Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:17:58.291Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:18:07.448Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:18:07.448Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:18:07.448Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:18:07.448Z] Top recommended movies for user id 72:
[2025-11-28T05:18:07.448Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:18:07.448Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:18:07.448Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:18:07.448Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:18:07.448Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:18:07.448Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (116429.201 ms) ======
[2025-11-28T05:18:07.448Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-28T05:18:07.448Z] GC before operation: completed in 115.914 ms, heap usage 242.625 MB -> 120.573 MB.
[2025-11-28T05:18:26.943Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:18:46.452Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:19:09.957Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:19:26.191Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:19:35.344Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:19:44.502Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:19:55.615Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:20:04.877Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:20:04.877Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:20:04.877Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:20:04.877Z] Top recommended movies for user id 72:
[2025-11-28T05:20:04.877Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:20:04.877Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:20:04.877Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:20:04.877Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:20:04.877Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:20:04.877Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (117263.561 ms) ======
[2025-11-28T05:20:04.877Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-28T05:20:04.877Z] GC before operation: completed in 112.289 ms, heap usage 1.024 GB -> 121.187 MB.
[2025-11-28T05:20:24.457Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:20:43.978Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:21:07.428Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:21:23.631Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:21:32.817Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:21:41.973Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:21:53.081Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:22:02.269Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:22:02.269Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:22:02.269Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:22:02.269Z] Top recommended movies for user id 72:
[2025-11-28T05:22:02.269Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:22:02.269Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:22:02.269Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:22:02.269Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:22:02.269Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:22:02.269Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (117384.766 ms) ======
[2025-11-28T05:22:02.269Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-28T05:22:02.269Z] GC before operation: completed in 117.202 ms, heap usage 1.025 GB -> 120.805 MB.
[2025-11-28T05:22:21.815Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:22:41.348Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:23:04.804Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:23:21.055Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:23:30.206Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:23:39.355Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:23:50.531Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:23:59.683Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:23:59.683Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:23:59.683Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:23:59.683Z] Top recommended movies for user id 72:
[2025-11-28T05:23:59.683Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:23:59.683Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:23:59.683Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:23:59.683Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:23:59.683Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:23:59.683Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (117560.092 ms) ======
[2025-11-28T05:23:59.683Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-28T05:23:59.683Z] GC before operation: completed in 113.547 ms, heap usage 940.269 MB -> 116.165 MB.
[2025-11-28T05:24:19.215Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:24:38.714Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:25:02.403Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:25:18.836Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:25:29.966Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:25:39.133Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:26:08.306Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:26:15.844Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:26:15.844Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:26:15.844Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:26:16.204Z] Top recommended movies for user id 72:
[2025-11-28T05:26:16.204Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:26:16.204Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:26:16.204Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:26:16.204Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:26:16.204Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:26:16.204Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (136399.330 ms) ======
[2025-11-28T05:26:16.204Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-28T05:26:16.204Z] GC before operation: completed in 120.777 ms, heap usage 466.265 MB -> 120.944 MB.
[2025-11-28T05:26:35.766Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:26:55.312Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:27:18.758Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:27:32.209Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:27:41.429Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:27:50.587Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:28:04.029Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:28:11.548Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:28:11.548Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:28:11.548Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:28:11.548Z] Top recommended movies for user id 72:
[2025-11-28T05:28:11.548Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:28:11.548Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:28:11.548Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:28:11.548Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:28:11.548Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:28:11.548Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (114877.373 ms) ======
[2025-11-28T05:28:11.548Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-28T05:28:11.548Z] GC before operation: completed in 113.362 ms, heap usage 1.037 GB -> 121.042 MB.
[2025-11-28T05:28:35.007Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:29:07.109Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:29:26.686Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:29:42.951Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:29:52.121Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:30:01.289Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:30:12.462Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:30:21.684Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:30:22.050Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:30:22.050Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:30:22.403Z] Top recommended movies for user id 72:
[2025-11-28T05:30:22.403Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:30:22.403Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:30:22.403Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:30:22.403Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:30:22.403Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:30:22.403Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (130939.983 ms) ======
[2025-11-28T05:30:22.403Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-28T05:30:22.403Z] GC before operation: completed in 92.662 ms, heap usage 580.293 MB -> 92.444 MB.
[2025-11-28T05:30:41.943Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:31:01.453Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:31:29.636Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:31:49.297Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:31:58.449Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:32:07.613Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:32:21.080Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:32:28.677Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:32:28.677Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:32:28.677Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:32:29.034Z] Top recommended movies for user id 72:
[2025-11-28T05:32:29.034Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:32:29.034Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:32:29.034Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:32:29.034Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:32:29.034Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:32:29.034Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (126462.632 ms) ======
[2025-11-28T05:32:29.034Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-28T05:32:29.034Z] GC before operation: completed in 114.884 ms, heap usage 501.315 MB -> 120.858 MB.
[2025-11-28T05:32:52.503Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:33:12.016Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:33:40.209Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:33:53.662Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:34:02.933Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:34:12.116Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:34:25.562Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:34:33.085Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:34:33.085Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:34:33.085Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:34:33.085Z] Top recommended movies for user id 72:
[2025-11-28T05:34:33.085Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:34:33.085Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:34:33.085Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:34:33.085Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:34:33.085Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:34:33.085Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (124099.780 ms) ======
[2025-11-28T05:34:33.085Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-28T05:34:33.085Z] GC before operation: completed in 118.762 ms, heap usage 259.981 MB -> 120.844 MB.
[2025-11-28T05:34:56.570Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:35:23.522Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:35:46.980Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:36:00.446Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:36:11.570Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:36:19.112Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:36:32.588Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:36:40.107Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:36:40.464Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:36:40.464Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:36:40.464Z] Top recommended movies for user id 72:
[2025-11-28T05:36:40.464Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:36:40.464Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:36:40.464Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:36:40.464Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:36:40.464Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:36:40.464Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (127394.265 ms) ======
[2025-11-28T05:36:40.464Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-28T05:36:40.818Z] GC before operation: completed in 113.671 ms, heap usage 649.843 MB -> 120.842 MB.
[2025-11-28T05:37:00.338Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:37:19.856Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:37:43.312Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:37:59.522Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:38:10.677Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:38:19.831Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:38:33.310Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:38:44.426Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:38:44.426Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:38:44.426Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:38:44.426Z] Top recommended movies for user id 72:
[2025-11-28T05:38:44.426Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:38:44.426Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:38:44.426Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:38:44.426Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:38:44.426Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:38:44.426Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (123070.981 ms) ======
[2025-11-28T05:38:44.426Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-28T05:38:44.426Z] GC before operation: completed in 118.643 ms, heap usage 377.624 MB -> 108.484 MB.
[2025-11-28T05:39:11.689Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-28T05:39:35.148Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-28T05:39:58.626Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-28T05:40:14.844Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-28T05:40:24.028Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-28T05:40:35.146Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-28T05:41:04.784Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-28T05:41:12.307Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-28T05:41:12.307Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2025-11-28T05:41:12.307Z] The best model improves the baseline by 14.43%.
[2025-11-28T05:41:12.307Z] Top recommended movies for user id 72:
[2025-11-28T05:41:12.307Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.674, id: 67504)
[2025-11-28T05:41:12.307Z] 2: Goat, The (1921) (rating: 4.674, id: 83318)
[2025-11-28T05:41:12.307Z] 3: Play House, The (1921) (rating: 4.674, id: 83359)
[2025-11-28T05:41:12.307Z] 4: Cops (1922) (rating: 4.674, id: 83411)
[2025-11-28T05:41:12.307Z] 5: Dear Frankie (2004) (rating: 4.256, id: 8530)
[2025-11-28T05:41:12.307Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (148356.379 ms) ======
[2025-11-28T05:41:13.526Z] -----------------------------------
[2025-11-28T05:41:13.526Z] renaissance-movie-lens_0_PASSED
[2025-11-28T05:41:13.526Z] -----------------------------------
[2025-11-28T05:41:13.526Z]
[2025-11-28T05:41:13.526Z] TEST TEARDOWN:
[2025-11-28T05:41:13.526Z] Nothing to be done for teardown.
[2025-11-28T05:41:13.526Z] renaissance-movie-lens_0 Finish Time: Fri Nov 28 05:41:13 2025 Epoch Time (ms): 1764308473334