renaissance-movie-lens_0
[2026-04-14T02:11:29.855Z] Running test renaissance-movie-lens_0 ...
[2026-04-14T02:11:29.855Z] ===============================================
[2026-04-14T02:11:29.855Z] renaissance-movie-lens_0 Start Time: Mon Apr 13 22:11:29 2026 Epoch Time (ms): 1776132689563
[2026-04-14T02:11:29.855Z] variation: NoOptions
[2026-04-14T02:11:29.855Z] JVM_OPTIONS:
[2026-04-14T02:11:29.855Z] { \
[2026-04-14T02:11:29.855Z] echo ""; echo "TEST SETUP:"; \
[2026-04-14T02:11:29.855Z] echo "Nothing to be done for setup."; \
[2026-04-14T02:11:29.855Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17761322395178/renaissance-movie-lens_0"; \
[2026-04-14T02:11:29.855Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17761322395178/renaissance-movie-lens_0"; \
[2026-04-14T02:11:29.855Z] echo ""; echo "TESTING:"; \
[2026-04-14T02:11:29.856Z] "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/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/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17761322395178/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2026-04-14T02:11:29.856Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17761322395178/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2026-04-14T02:11:29.856Z] echo ""; echo "TEST TEARDOWN:"; \
[2026-04-14T02:11:29.856Z] echo "Nothing to be done for teardown."; \
[2026-04-14T02:11:29.856Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17761322395178/TestTargetResult";
[2026-04-14T02:11:29.856Z]
[2026-04-14T02:11:29.856Z] TEST SETUP:
[2026-04-14T02:11:29.856Z] Nothing to be done for setup.
[2026-04-14T02:11:29.856Z]
[2026-04-14T02:11:29.856Z] TESTING:
[2026-04-14T02:11:33.792Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2026-04-14T02:11:37.716Z] 22:11:37.372 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2026-04-14T02:11:38.470Z] Got 100004 ratings from 671 users on 9066 movies.
[2026-04-14T02:11:38.828Z] Training: 60056, validation: 20285, test: 19854
[2026-04-14T02:11:38.828Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2026-04-14T02:11:38.828Z] GC before operation: completed in 66.747 ms, heap usage 197.779 MB -> 74.660 MB.
[2026-04-14T02:11:41.967Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:11:44.406Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:11:46.202Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:11:48.011Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:11:49.236Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:11:50.469Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:11:51.228Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:11:52.443Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:11:52.443Z] 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.
[2026-04-14T02:11:52.443Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:11:52.800Z] Top recommended movies for user id 72:
[2026-04-14T02:11:52.800Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:11:52.800Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:11:52.800Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:11:52.800Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:11:52.800Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:11:52.800Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (13764.112 ms) ======
[2026-04-14T02:11:52.800Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2026-04-14T02:11:52.800Z] GC before operation: completed in 74.420 ms, heap usage 572.538 MB -> 92.219 MB.
[2026-04-14T02:11:54.580Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:11:56.370Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:11:58.154Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:11:59.968Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:12:01.199Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:12:02.471Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:12:03.233Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:12:04.461Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:12:04.815Z] 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.
[2026-04-14T02:12:04.815Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:12:04.815Z] Top recommended movies for user id 72:
[2026-04-14T02:12:04.815Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:12:04.815Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:12:04.815Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:12:04.815Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:12:04.815Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:12:04.815Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (12033.437 ms) ======
[2026-04-14T02:12:04.815Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2026-04-14T02:12:04.815Z] GC before operation: completed in 79.620 ms, heap usage 185.785 MB -> 87.678 MB.
[2026-04-14T02:12:06.588Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:12:08.979Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:12:10.224Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:12:12.620Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:12:13.380Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:12:14.592Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:12:15.823Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:12:16.600Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:12:16.950Z] 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.
[2026-04-14T02:12:16.950Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:12:16.950Z] Top recommended movies for user id 72:
[2026-04-14T02:12:16.950Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:12:16.950Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:12:16.950Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:12:16.950Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:12:16.950Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:12:16.950Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (12130.332 ms) ======
[2026-04-14T02:12:16.950Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2026-04-14T02:12:16.950Z] GC before operation: completed in 78.926 ms, heap usage 490.718 MB -> 88.695 MB.
[2026-04-14T02:12:19.354Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:12:21.124Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:12:22.885Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:12:24.659Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:12:25.428Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:12:26.642Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:12:27.399Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:12:28.614Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:12:28.614Z] 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.
[2026-04-14T02:12:28.614Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:12:28.971Z] Top recommended movies for user id 72:
[2026-04-14T02:12:28.971Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:12:28.971Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:12:28.971Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:12:28.971Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:12:28.971Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:12:28.971Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (11782.906 ms) ======
[2026-04-14T02:12:28.971Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2026-04-14T02:12:28.971Z] GC before operation: completed in 75.462 ms, heap usage 212.114 MB -> 88.659 MB.
[2026-04-14T02:12:30.730Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:12:32.486Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:12:34.250Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:12:36.016Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:12:37.282Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:12:38.053Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:12:39.262Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:12:40.530Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:12:40.530Z] 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.
[2026-04-14T02:12:40.530Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:12:40.530Z] Top recommended movies for user id 72:
[2026-04-14T02:12:40.530Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:12:40.530Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:12:40.530Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:12:40.530Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:12:40.530Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:12:40.530Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (11545.153 ms) ======
[2026-04-14T02:12:40.530Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2026-04-14T02:12:40.530Z] GC before operation: completed in 74.284 ms, heap usage 265.915 MB -> 88.714 MB.
[2026-04-14T02:12:42.283Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:12:44.062Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:12:45.853Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:12:47.618Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:12:48.847Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:12:50.072Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:12:51.308Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:12:52.127Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:12:52.127Z] 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.
[2026-04-14T02:12:52.127Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:12:52.480Z] Top recommended movies for user id 72:
[2026-04-14T02:12:52.480Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:12:52.480Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:12:52.480Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:12:52.480Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:12:52.480Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:12:52.480Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (11796.887 ms) ======
[2026-04-14T02:12:52.480Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2026-04-14T02:12:52.480Z] GC before operation: completed in 94.829 ms, heap usage 456.019 MB -> 89.184 MB.
[2026-04-14T02:12:54.232Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:12:55.989Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:12:57.770Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:13:00.165Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:13:00.979Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:13:01.744Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:13:02.977Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:13:04.203Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:13:04.203Z] 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.
[2026-04-14T02:13:04.203Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:13:04.203Z] Top recommended movies for user id 72:
[2026-04-14T02:13:04.203Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:13:04.203Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:13:04.203Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:13:04.203Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:13:04.203Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:13:04.203Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (11717.610 ms) ======
[2026-04-14T02:13:04.203Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2026-04-14T02:13:04.203Z] GC before operation: completed in 92.325 ms, heap usage 135.037 MB -> 88.708 MB.
[2026-04-14T02:13:05.962Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:13:07.716Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:13:09.473Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:13:11.244Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:13:12.026Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:13:12.794Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:13:14.099Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:13:15.322Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:13:15.322Z] 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.
[2026-04-14T02:13:15.322Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:13:15.679Z] Top recommended movies for user id 72:
[2026-04-14T02:13:15.679Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:13:15.679Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:13:15.679Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:13:15.679Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:13:15.679Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:13:15.679Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (11296.586 ms) ======
[2026-04-14T02:13:15.679Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2026-04-14T02:13:15.679Z] GC before operation: completed in 72.536 ms, heap usage 430.074 MB -> 89.290 MB.
[2026-04-14T02:13:17.443Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:13:19.841Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:13:21.611Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:13:23.377Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:13:24.141Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:13:25.362Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:13:26.603Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:13:27.405Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:13:27.405Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-04-14T02:13:27.405Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:13:27.764Z] Top recommended movies for user id 72:
[2026-04-14T02:13:27.764Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:13:27.764Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:13:27.764Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:13:27.764Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:13:27.764Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:13:27.764Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (11936.596 ms) ======
[2026-04-14T02:13:27.764Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2026-04-14T02:13:27.764Z] GC before operation: completed in 80.320 ms, heap usage 333.819 MB -> 89.085 MB.
[2026-04-14T02:13:29.548Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:13:31.327Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:13:33.098Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:13:34.324Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:13:35.551Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:13:36.810Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:13:37.591Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:13:38.832Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:13:39.212Z] 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.
[2026-04-14T02:13:39.212Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:13:39.212Z] Top recommended movies for user id 72:
[2026-04-14T02:13:39.212Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:13:39.212Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:13:39.212Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:13:39.212Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:13:39.212Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:13:39.212Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (11652.822 ms) ======
[2026-04-14T02:13:39.212Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2026-04-14T02:13:39.563Z] GC before operation: completed in 99.697 ms, heap usage 201.526 MB -> 89.145 MB.
[2026-04-14T02:13:41.338Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:13:43.725Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:13:46.154Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:13:47.927Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:13:48.686Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:13:49.914Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:13:51.178Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:13:52.452Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:13:52.452Z] 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.
[2026-04-14T02:13:52.452Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:13:52.452Z] Top recommended movies for user id 72:
[2026-04-14T02:13:52.452Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:13:52.452Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:13:52.452Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:13:52.452Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:13:52.452Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:13:52.452Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13011.428 ms) ======
[2026-04-14T02:13:52.452Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2026-04-14T02:13:52.452Z] GC before operation: completed in 77.504 ms, heap usage 111.724 MB -> 88.699 MB.
[2026-04-14T02:13:54.860Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:13:56.627Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:13:58.385Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:14:00.776Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:14:01.992Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:14:03.218Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:14:04.491Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:14:05.714Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:14:05.714Z] 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.
[2026-04-14T02:14:05.714Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:14:05.714Z] Top recommended movies for user id 72:
[2026-04-14T02:14:05.714Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:14:05.714Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:14:05.714Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:14:05.714Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:14:05.714Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:14:05.714Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13264.030 ms) ======
[2026-04-14T02:14:05.714Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2026-04-14T02:14:05.714Z] GC before operation: completed in 82.601 ms, heap usage 487.502 MB -> 89.389 MB.
[2026-04-14T02:14:08.118Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:14:09.901Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:14:11.718Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:14:14.117Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:14:14.902Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:14:16.228Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:14:17.494Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:14:18.745Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:14:19.117Z] 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.
[2026-04-14T02:14:19.117Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:14:19.117Z] Top recommended movies for user id 72:
[2026-04-14T02:14:19.117Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:14:19.117Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:14:19.117Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:14:19.117Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:14:19.117Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:14:19.117Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13379.490 ms) ======
[2026-04-14T02:14:19.117Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2026-04-14T02:14:19.471Z] GC before operation: completed in 91.906 ms, heap usage 120.975 MB -> 89.067 MB.
[2026-04-14T02:14:21.906Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:14:23.698Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:14:25.478Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:14:27.266Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:14:28.500Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:14:29.748Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:14:30.966Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:14:31.724Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:14:32.094Z] 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.
[2026-04-14T02:14:32.094Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:14:32.094Z] Top recommended movies for user id 72:
[2026-04-14T02:14:32.094Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:14:32.094Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:14:32.094Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:14:32.094Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:14:32.094Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:14:32.094Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (12892.127 ms) ======
[2026-04-14T02:14:32.094Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2026-04-14T02:14:32.443Z] GC before operation: completed in 94.193 ms, heap usage 166.727 MB -> 88.923 MB.
[2026-04-14T02:14:34.229Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:14:36.636Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:14:38.421Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:14:40.219Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:14:41.469Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:14:42.251Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:14:43.519Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:14:44.783Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:14:45.135Z] 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.
[2026-04-14T02:14:45.135Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:14:45.135Z] Top recommended movies for user id 72:
[2026-04-14T02:14:45.135Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:14:45.135Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:14:45.135Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:14:45.135Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:14:45.135Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:14:45.135Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (12838.319 ms) ======
[2026-04-14T02:14:45.135Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2026-04-14T02:14:45.135Z] GC before operation: completed in 92.276 ms, heap usage 271.752 MB -> 89.295 MB.
[2026-04-14T02:14:47.548Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:14:49.330Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:14:51.093Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:14:53.519Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:14:54.287Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:14:55.539Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:14:56.786Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:14:58.025Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:14:58.025Z] 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.
[2026-04-14T02:14:58.025Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:14:58.025Z] Top recommended movies for user id 72:
[2026-04-14T02:14:58.025Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:14:58.025Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:14:58.025Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:14:58.025Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:14:58.025Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:14:58.025Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12777.172 ms) ======
[2026-04-14T02:14:58.025Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2026-04-14T02:14:58.025Z] GC before operation: completed in 83.467 ms, heap usage 332.406 MB -> 89.211 MB.
[2026-04-14T02:14:59.789Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:15:02.184Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:15:03.978Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:15:06.368Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:15:07.611Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:15:08.400Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:15:09.650Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:15:10.878Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:15:11.242Z] 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.
[2026-04-14T02:15:11.242Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:15:11.242Z] Top recommended movies for user id 72:
[2026-04-14T02:15:11.242Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:15:11.242Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:15:11.242Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:15:11.242Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:15:11.242Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:15:11.242Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13194.629 ms) ======
[2026-04-14T02:15:11.242Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2026-04-14T02:15:11.242Z] GC before operation: completed in 87.450 ms, heap usage 119.481 MB -> 89.071 MB.
[2026-04-14T02:15:13.630Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:15:15.447Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:15:17.824Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:15:20.256Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:15:21.028Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:15:22.265Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:15:23.505Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:15:24.723Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:15:25.086Z] 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.
[2026-04-14T02:15:25.086Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:15:25.086Z] Top recommended movies for user id 72:
[2026-04-14T02:15:25.086Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:15:25.086Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:15:25.086Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:15:25.086Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:15:25.087Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:15:25.087Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13733.457 ms) ======
[2026-04-14T02:15:25.087Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2026-04-14T02:15:25.087Z] GC before operation: completed in 99.074 ms, heap usage 119.998 MB -> 88.855 MB.
[2026-04-14T02:15:27.498Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:15:29.337Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:15:31.110Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:15:32.923Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:15:34.183Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:15:35.469Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:15:36.702Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:15:37.952Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:15:37.952Z] 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.
[2026-04-14T02:15:37.952Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:15:37.952Z] Top recommended movies for user id 72:
[2026-04-14T02:15:37.952Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:15:37.952Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:15:37.952Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:15:37.952Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:15:37.952Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:15:37.952Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12740.676 ms) ======
[2026-04-14T02:15:37.952Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2026-04-14T02:15:38.308Z] GC before operation: completed in 93.670 ms, heap usage 351.568 MB -> 89.248 MB.
[2026-04-14T02:15:40.776Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-04-14T02:15:42.587Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-04-14T02:15:44.358Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-04-14T02:15:46.752Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-04-14T02:15:47.991Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-04-14T02:15:49.241Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-04-14T02:15:50.488Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-04-14T02:15:51.729Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-04-14T02:15:51.729Z] 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.
[2026-04-14T02:15:51.729Z] The best model improves the baseline by 14.52%.
[2026-04-14T02:15:52.132Z] Top recommended movies for user id 72:
[2026-04-14T02:15:52.132Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-04-14T02:15:52.132Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-04-14T02:15:52.132Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-04-14T02:15:52.132Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-04-14T02:15:52.132Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-04-14T02:15:52.132Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13894.976 ms) ======
[2026-04-14T02:15:52.482Z] -----------------------------------
[2026-04-14T02:15:52.482Z] renaissance-movie-lens_0_PASSED
[2026-04-14T02:15:52.482Z] -----------------------------------
[2026-04-14T02:15:52.482Z]
[2026-04-14T02:15:52.482Z] TEST TEARDOWN:
[2026-04-14T02:15:52.482Z] Nothing to be done for teardown.
[2026-04-14T02:15:52.482Z] renaissance-movie-lens_0 Finish Time: Mon Apr 13 22:15:52 2026 Epoch Time (ms): 1776132952406