renaissance-movie-lens_0
[2025-10-02T10:58:54.715Z] Running test renaissance-movie-lens_0 ...
[2025-10-02T10:58:54.715Z] ===============================================
[2025-10-02T10:58:54.715Z] renaissance-movie-lens_0 Start Time: Thu Oct 2 03:58:52 2025 Epoch Time (ms): 1759402732407
[2025-10-02T10:58:54.715Z] variation: NoOptions
[2025-10-02T10:58:54.715Z] JVM_OPTIONS:
[2025-10-02T10:58:54.715Z] { \
[2025-10-02T10:58:54.715Z] echo ""; echo "TEST SETUP:"; \
[2025-10-02T10:58:54.715Z] echo "Nothing to be done for setup."; \
[2025-10-02T10:58:54.715Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17594015997175/renaissance-movie-lens_0"; \
[2025-10-02T10:58:54.715Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17594015997175/renaissance-movie-lens_0"; \
[2025-10-02T10:58:54.715Z] echo ""; echo "TESTING:"; \
[2025-10-02T10:58:54.715Z] "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/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_x86-64_mac_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17594015997175/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-10-02T10:58:54.715Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17594015997175/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-10-02T10:58:54.715Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-10-02T10:58:54.715Z] echo "Nothing to be done for teardown."; \
[2025-10-02T10:58:54.715Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17594015997175/TestTargetResult";
[2025-10-02T10:58:54.715Z]
[2025-10-02T10:58:54.715Z] TEST SETUP:
[2025-10-02T10:58:54.715Z] Nothing to be done for setup.
[2025-10-02T10:58:54.715Z]
[2025-10-02T10:58:54.715Z] TESTING:
[2025-10-02T10:59:16.336Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2025-10-02T10:59:37.453Z] 03:59:35.120 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB.
[2025-10-02T10:59:43.811Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-10-02T10:59:45.404Z] Training: 60056, validation: 20285, test: 19854
[2025-10-02T10:59:45.404Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-10-02T10:59:45.898Z] GC before operation: completed in 383.700 ms, heap usage 296.039 MB -> 74.485 MB.
[2025-10-02T11:00:16.512Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:00:34.938Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:00:53.192Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:01:05.722Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:01:13.035Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:01:21.752Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:01:30.439Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:01:37.988Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:01:38.657Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:01:39.086Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:01:39.739Z] Top recommended movies for user id 72:
[2025-10-02T11:01:39.739Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:01:39.739Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:01:39.739Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:01:39.739Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:01:39.739Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:01:39.739Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (114110.285 ms) ======
[2025-10-02T11:01:39.739Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-10-02T11:01:40.217Z] GC before operation: completed in 498.801 ms, heap usage 300.455 MB -> 86.574 MB.
[2025-10-02T11:01:58.606Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:02:11.785Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:02:24.564Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:02:37.275Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:02:43.620Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:02:50.958Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:02:57.598Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:03:06.300Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:03:06.300Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:03:06.300Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:03:06.863Z] Top recommended movies for user id 72:
[2025-10-02T11:03:06.863Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:03:06.863Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:03:06.863Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:03:06.863Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:03:06.863Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:03:06.863Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (86586.370 ms) ======
[2025-10-02T11:03:06.863Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-10-02T11:03:07.419Z] GC before operation: completed in 543.942 ms, heap usage 130.694 MB -> 86.991 MB.
[2025-10-02T11:03:24.799Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:03:35.348Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:03:47.568Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:04:00.099Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:04:06.117Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:04:13.144Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:04:21.915Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:04:29.026Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:04:29.459Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:04:29.459Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:04:29.459Z] Top recommended movies for user id 72:
[2025-10-02T11:04:29.459Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:04:29.459Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:04:29.459Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:04:29.459Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:04:29.459Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:04:29.459Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (82218.137 ms) ======
[2025-10-02T11:04:29.459Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-10-02T11:04:30.395Z] GC before operation: completed in 465.725 ms, heap usage 397.077 MB -> 87.924 MB.
[2025-10-02T11:04:45.193Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:04:57.201Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:05:07.603Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:05:20.328Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:05:27.001Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:05:32.767Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:05:40.481Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:05:47.852Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:05:48.740Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:05:48.740Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:05:49.451Z] Top recommended movies for user id 72:
[2025-10-02T11:05:49.451Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:05:49.451Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:05:49.451Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:05:49.451Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:05:49.451Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:05:49.451Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (79135.632 ms) ======
[2025-10-02T11:05:49.451Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-10-02T11:05:49.969Z] GC before operation: completed in 782.805 ms, heap usage 107.090 MB -> 91.724 MB.
[2025-10-02T11:06:06.152Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:06:21.096Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:06:33.919Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:06:46.806Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:06:52.902Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:07:01.762Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:07:10.376Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:07:17.294Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:07:18.236Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:07:18.236Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:07:19.405Z] Top recommended movies for user id 72:
[2025-10-02T11:07:19.405Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:07:19.405Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:07:19.405Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:07:19.405Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:07:19.405Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:07:19.405Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (89103.426 ms) ======
[2025-10-02T11:07:19.405Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-10-02T11:07:19.781Z] GC before operation: completed in 519.609 ms, heap usage 177.655 MB -> 87.908 MB.
[2025-10-02T11:07:37.841Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:07:50.788Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:08:06.370Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:08:17.520Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:08:26.088Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:08:33.711Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:08:42.982Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:08:52.049Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:08:52.049Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:08:52.049Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:08:52.527Z] Top recommended movies for user id 72:
[2025-10-02T11:08:52.527Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:08:52.527Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:08:52.527Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:08:52.527Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:08:52.527Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:08:52.527Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (92644.452 ms) ======
[2025-10-02T11:08:52.527Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-10-02T11:08:53.069Z] GC before operation: completed in 465.686 ms, heap usage 415.738 MB -> 88.597 MB.
[2025-10-02T11:09:11.745Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:09:26.703Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:09:38.844Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:09:51.637Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:09:59.054Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:10:07.951Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:10:16.742Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:10:25.623Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:10:26.576Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:10:26.576Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:10:27.025Z] Top recommended movies for user id 72:
[2025-10-02T11:10:27.025Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:10:27.025Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:10:27.025Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:10:27.025Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:10:27.025Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:10:27.025Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (94188.488 ms) ======
[2025-10-02T11:10:27.025Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-10-02T11:10:27.447Z] GC before operation: completed in 537.133 ms, heap usage 320.174 MB -> 88.340 MB.
[2025-10-02T11:10:43.236Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:10:57.977Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:11:09.240Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:11:21.799Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:11:27.506Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:11:36.678Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:11:43.853Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:11:49.614Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:11:50.574Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:11:50.574Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:11:52.006Z] Top recommended movies for user id 72:
[2025-10-02T11:11:52.006Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:11:52.006Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:11:52.006Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:11:52.006Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:11:52.006Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:11:52.006Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (83719.867 ms) ======
[2025-10-02T11:11:52.006Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-10-02T11:11:52.006Z] GC before operation: completed in 508.984 ms, heap usage 135.932 MB -> 91.869 MB.
[2025-10-02T11:12:04.545Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:12:14.930Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:12:23.359Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:12:31.608Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:12:36.595Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:12:42.300Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:12:47.039Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:12:54.283Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:12:54.283Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:12:54.283Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:12:54.760Z] Top recommended movies for user id 72:
[2025-10-02T11:12:54.760Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:12:54.760Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:12:54.760Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:12:54.760Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:12:54.760Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:12:54.760Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (62929.330 ms) ======
[2025-10-02T11:12:54.760Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-10-02T11:12:55.181Z] GC before operation: completed in 426.841 ms, heap usage 128.075 MB -> 92.208 MB.
[2025-10-02T11:13:10.224Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:13:22.563Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:13:37.361Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:13:48.495Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:13:57.456Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:14:03.568Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:14:10.858Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:14:18.143Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:14:18.143Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:14:18.594Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:14:19.049Z] Top recommended movies for user id 72:
[2025-10-02T11:14:19.049Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:14:19.049Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:14:19.049Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:14:19.049Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:14:19.049Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:14:19.049Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (83702.342 ms) ======
[2025-10-02T11:14:19.049Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-10-02T11:14:19.591Z] GC before operation: completed in 466.032 ms, heap usage 377.975 MB -> 88.710 MB.
[2025-10-02T11:14:34.911Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:14:47.427Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:14:59.847Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:15:12.354Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:15:18.067Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:15:26.657Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:15:35.902Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:15:41.495Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:15:41.985Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:15:41.985Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:15:42.606Z] Top recommended movies for user id 72:
[2025-10-02T11:15:42.606Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:15:42.606Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:15:42.606Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:15:42.606Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:15:42.606Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:15:42.606Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (83292.590 ms) ======
[2025-10-02T11:15:42.606Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-10-02T11:15:43.074Z] GC before operation: completed in 451.469 ms, heap usage 216.651 MB -> 88.203 MB.
[2025-10-02T11:15:58.260Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:16:10.658Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:16:23.000Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:16:33.381Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:16:39.406Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:16:46.936Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:16:54.379Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:17:01.420Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:17:02.468Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:17:02.468Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:17:02.978Z] Top recommended movies for user id 72:
[2025-10-02T11:17:02.978Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:17:02.978Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:17:02.978Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:17:02.978Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:17:02.978Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:17:02.978Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (79915.225 ms) ======
[2025-10-02T11:17:02.978Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-10-02T11:17:03.364Z] GC before operation: completed in 440.512 ms, heap usage 120.930 MB -> 92.156 MB.
[2025-10-02T11:17:22.365Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:17:34.814Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:17:50.188Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:18:00.604Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:18:08.402Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:18:16.129Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:18:26.780Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:18:32.966Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:18:34.115Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:18:34.115Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:18:35.203Z] Top recommended movies for user id 72:
[2025-10-02T11:18:35.203Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:18:35.203Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:18:35.203Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:18:35.203Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:18:35.203Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:18:35.203Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (91856.650 ms) ======
[2025-10-02T11:18:35.203Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-10-02T11:18:35.662Z] GC before operation: completed in 398.692 ms, heap usage 410.727 MB -> 88.945 MB.
[2025-10-02T11:18:51.667Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:19:04.241Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:19:14.874Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:19:27.300Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:19:34.516Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:19:40.016Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:19:48.793Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:19:56.087Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:19:56.508Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:19:56.508Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:19:57.016Z] Top recommended movies for user id 72:
[2025-10-02T11:19:57.016Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:19:57.016Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:19:57.016Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:19:57.016Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:19:57.016Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:19:57.016Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (81494.830 ms) ======
[2025-10-02T11:19:57.016Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-10-02T11:19:58.012Z] GC before operation: completed in 455.841 ms, heap usage 219.049 MB -> 88.364 MB.
[2025-10-02T11:20:16.835Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:20:29.391Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:20:42.111Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:20:55.056Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:21:02.313Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:21:08.317Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:21:15.550Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:21:24.600Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:21:25.572Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:21:25.572Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:21:25.572Z] Top recommended movies for user id 72:
[2025-10-02T11:21:25.572Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:21:25.572Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:21:25.572Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:21:25.572Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:21:25.572Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:21:25.572Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (88186.226 ms) ======
[2025-10-02T11:21:25.572Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-10-02T11:21:26.455Z] GC before operation: completed in 515.469 ms, heap usage 488.780 MB -> 89.034 MB.
[2025-10-02T11:21:44.420Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:21:57.347Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:22:10.178Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:22:22.796Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:22:31.630Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:22:39.186Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:22:46.313Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:22:56.979Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:22:56.979Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:22:56.979Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:22:57.970Z] Top recommended movies for user id 72:
[2025-10-02T11:22:57.970Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:22:57.970Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:22:57.970Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:22:57.970Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:22:57.970Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:22:57.970Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (91329.239 ms) ======
[2025-10-02T11:22:57.970Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-10-02T11:22:57.970Z] GC before operation: completed in 536.175 ms, heap usage 305.511 MB -> 88.578 MB.
[2025-10-02T11:23:16.114Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:23:28.633Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:23:43.855Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:23:56.468Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:24:04.417Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:24:13.212Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:24:21.949Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:24:27.917Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:24:28.987Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:24:29.451Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:24:30.063Z] Top recommended movies for user id 72:
[2025-10-02T11:24:30.063Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:24:30.063Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:24:30.063Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:24:30.063Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:24:30.063Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:24:30.063Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (91684.880 ms) ======
[2025-10-02T11:24:30.063Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-10-02T11:24:31.106Z] GC before operation: completed in 1039.175 ms, heap usage 282.847 MB -> 88.765 MB.
[2025-10-02T11:24:49.961Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:25:05.196Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:25:18.493Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:25:30.640Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:25:37.019Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:25:43.429Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:25:53.982Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:26:00.055Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:26:00.569Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:26:00.569Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:26:01.032Z] Top recommended movies for user id 72:
[2025-10-02T11:26:01.032Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:26:01.032Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:26:01.032Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:26:01.032Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:26:01.032Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:26:01.033Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (89978.071 ms) ======
[2025-10-02T11:26:01.033Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-10-02T11:26:01.521Z] GC before operation: completed in 466.834 ms, heap usage 335.080 MB -> 88.484 MB.
[2025-10-02T11:26:15.035Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:26:29.987Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:26:45.091Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:26:55.572Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:27:05.486Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:27:11.459Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:27:20.098Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:27:25.813Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:27:26.787Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:27:26.787Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:27:27.874Z] Top recommended movies for user id 72:
[2025-10-02T11:27:27.874Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:27:27.874Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:27:27.874Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:27:27.874Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:27:27.874Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:27:27.874Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (86349.967 ms) ======
[2025-10-02T11:27:27.874Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-10-02T11:27:28.332Z] GC before operation: completed in 570.074 ms, heap usage 220.792 MB -> 88.454 MB.
[2025-10-02T11:27:43.302Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-02T11:27:55.550Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-02T11:28:08.969Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-02T11:28:21.632Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-02T11:28:27.780Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-02T11:28:34.723Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-02T11:28:43.553Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-02T11:28:51.444Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-02T11:28:51.860Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-02T11:28:51.860Z] The best model improves the baseline by 14.52%.
[2025-10-02T11:28:52.303Z] Top recommended movies for user id 72:
[2025-10-02T11:28:52.303Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-02T11:28:52.303Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-02T11:28:52.303Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-02T11:28:52.303Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-02T11:28:52.303Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-02T11:28:52.303Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (84203.668 ms) ======
[2025-10-02T11:28:57.719Z] -----------------------------------
[2025-10-02T11:28:57.719Z] renaissance-movie-lens_0_PASSED
[2025-10-02T11:28:57.719Z] -----------------------------------
[2025-10-02T11:28:57.719Z]
[2025-10-02T11:28:57.719Z] TEST TEARDOWN:
[2025-10-02T11:28:57.719Z] Nothing to be done for teardown.
[2025-10-02T11:28:57.719Z] renaissance-movie-lens_0 Finish Time: Thu Oct 2 04:28:55 2025 Epoch Time (ms): 1759404535201