renaissance-movie-lens_0
[2025-10-03T20:41:53.341Z] Running test renaissance-movie-lens_0 ...
[2025-10-03T20:41:53.341Z] ===============================================
[2025-10-03T20:41:53.341Z] renaissance-movie-lens_0 Start Time: Fri Oct 3 16:41:52 2025 Epoch Time (ms): 1759524112984
[2025-10-03T20:41:53.341Z] variation: NoOptions
[2025-10-03T20:41:53.341Z] JVM_OPTIONS:
[2025-10-03T20:41:53.341Z] { \
[2025-10-03T20:41:53.341Z] echo ""; echo "TEST SETUP:"; \
[2025-10-03T20:41:53.341Z] echo "Nothing to be done for setup."; \
[2025-10-03T20:41:53.341Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17595234413722/renaissance-movie-lens_0"; \
[2025-10-03T20:41:53.341Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17595234413722/renaissance-movie-lens_0"; \
[2025-10-03T20:41:53.341Z] echo ""; echo "TESTING:"; \
[2025-10-03T20:41:53.341Z] "/Users/admin/workspace/workspace/Test_openjdk21_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_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17595234413722/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-10-03T20:41:53.341Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17595234413722/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-10-03T20:41:53.341Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-10-03T20:41:53.341Z] echo "Nothing to be done for teardown."; \
[2025-10-03T20:41:53.341Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17595234413722/TestTargetResult";
[2025-10-03T20:41:53.341Z]
[2025-10-03T20:41:53.341Z] TEST SETUP:
[2025-10-03T20:41:53.341Z] Nothing to be done for setup.
[2025-10-03T20:41:53.341Z]
[2025-10-03T20:41:53.341Z] TESTING:
[2025-10-03T20:41:56.469Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2025-10-03T20:41:59.630Z] 16:41:59.370 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB.
[2025-10-03T20:42:00.877Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-10-03T20:42:00.877Z] Training: 60056, validation: 20285, test: 19854
[2025-10-03T20:42:00.877Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-10-03T20:42:01.257Z] GC before operation: completed in 71.351 ms, heap usage 127.630 MB -> 76.036 MB.
[2025-10-03T20:42:04.519Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:42:06.295Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:42:08.120Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:42:09.906Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:42:11.138Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:42:12.464Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:42:13.234Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:42:14.479Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:42:14.479Z] 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.
[2025-10-03T20:42:14.479Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:42:14.835Z] Top recommended movies for user id 72:
[2025-10-03T20:42:14.835Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:42:14.835Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:42:14.835Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:42:14.835Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:42:14.835Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:42:14.835Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (13650.042 ms) ======
[2025-10-03T20:42:14.835Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-10-03T20:42:14.835Z] GC before operation: completed in 82.193 ms, heap usage 418.147 MB -> 86.742 MB.
[2025-10-03T20:42:16.683Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:42:17.934Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:42:19.722Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:42:20.960Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:42:22.250Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:42:23.038Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:42:23.846Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:42:24.648Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:42:25.058Z] 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.
[2025-10-03T20:42:25.058Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:42:25.058Z] Top recommended movies for user id 72:
[2025-10-03T20:42:25.058Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:42:25.058Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:42:25.058Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:42:25.058Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:42:25.058Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:42:25.058Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (10191.603 ms) ======
[2025-10-03T20:42:25.058Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-10-03T20:42:25.058Z] GC before operation: completed in 81.045 ms, heap usage 342.774 MB -> 88.651 MB.
[2025-10-03T20:42:26.855Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:42:28.146Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:42:30.025Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:42:31.263Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:42:32.024Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:42:33.293Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:42:34.105Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:42:34.909Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:42:34.909Z] 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.
[2025-10-03T20:42:35.264Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:42:35.264Z] Top recommended movies for user id 72:
[2025-10-03T20:42:35.264Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:42:35.264Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:42:35.264Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:42:35.264Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:42:35.264Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:42:35.264Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (10097.569 ms) ======
[2025-10-03T20:42:35.264Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-10-03T20:42:35.264Z] GC before operation: completed in 67.291 ms, heap usage 340.419 MB -> 89.339 MB.
[2025-10-03T20:42:37.082Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:42:38.364Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:42:39.620Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:42:41.391Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:42:42.158Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:42:42.954Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:42:44.220Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:42:44.987Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:42:44.987Z] 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.
[2025-10-03T20:42:44.987Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:42:44.987Z] Top recommended movies for user id 72:
[2025-10-03T20:42:44.987Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:42:44.987Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:42:44.987Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:42:44.987Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:42:44.987Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:42:44.987Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9795.041 ms) ======
[2025-10-03T20:42:44.987Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-10-03T20:42:44.987Z] GC before operation: completed in 68.896 ms, heap usage 127.677 MB -> 89.281 MB.
[2025-10-03T20:42:46.759Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:42:48.005Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:42:49.795Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:42:51.032Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:42:51.802Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:42:53.047Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:42:53.814Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:42:54.589Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:42:54.589Z] 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.
[2025-10-03T20:42:54.589Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:42:54.952Z] Top recommended movies for user id 72:
[2025-10-03T20:42:54.952Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:42:54.952Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:42:54.952Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:42:54.952Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:42:54.952Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:42:54.952Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (9684.865 ms) ======
[2025-10-03T20:42:54.952Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-10-03T20:42:54.952Z] GC before operation: completed in 77.476 ms, heap usage 332.276 MB -> 89.523 MB.
[2025-10-03T20:42:56.200Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:42:58.008Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:42:59.349Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:43:00.121Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:43:00.898Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:43:01.293Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:43:02.084Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:43:02.897Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:43:03.286Z] 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.
[2025-10-03T20:43:03.286Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:43:03.286Z] Top recommended movies for user id 72:
[2025-10-03T20:43:03.286Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:43:03.286Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:43:03.286Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:43:03.286Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:43:03.286Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:43:03.287Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8341.131 ms) ======
[2025-10-03T20:43:03.287Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-10-03T20:43:03.287Z] GC before operation: completed in 73.124 ms, heap usage 189.474 MB -> 89.623 MB.
[2025-10-03T20:43:04.559Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:43:06.344Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:43:07.583Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:43:08.817Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:43:09.617Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:43:10.879Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:43:11.651Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:43:12.439Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:43:12.439Z] 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.
[2025-10-03T20:43:12.439Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:43:12.439Z] Top recommended movies for user id 72:
[2025-10-03T20:43:12.439Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:43:12.439Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:43:12.439Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:43:12.439Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:43:12.439Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:43:12.439Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (9230.559 ms) ======
[2025-10-03T20:43:12.439Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-10-03T20:43:12.439Z] GC before operation: completed in 69.756 ms, heap usage 250.394 MB -> 89.830 MB.
[2025-10-03T20:43:14.216Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:43:15.535Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:43:16.786Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:43:18.021Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:43:19.263Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:43:20.035Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:43:20.801Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:43:21.587Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:43:21.587Z] 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.
[2025-10-03T20:43:21.587Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:43:21.587Z] Top recommended movies for user id 72:
[2025-10-03T20:43:21.587Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:43:21.587Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:43:21.587Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:43:21.587Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:43:21.587Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:43:21.587Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (9108.291 ms) ======
[2025-10-03T20:43:21.587Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-10-03T20:43:21.943Z] GC before operation: completed in 78.095 ms, heap usage 562.262 MB -> 93.757 MB.
[2025-10-03T20:43:23.191Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:43:24.434Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:43:25.716Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:43:27.538Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:43:27.905Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:43:28.694Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:43:29.932Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:43:30.304Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:43:30.687Z] 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.
[2025-10-03T20:43:30.687Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:43:30.687Z] Top recommended movies for user id 72:
[2025-10-03T20:43:30.687Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:43:30.687Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:43:30.687Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:43:30.687Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:43:30.687Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:43:30.687Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8926.248 ms) ======
[2025-10-03T20:43:30.687Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-10-03T20:43:30.687Z] GC before operation: completed in 62.318 ms, heap usage 268.749 MB -> 89.870 MB.
[2025-10-03T20:43:31.975Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:43:33.780Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:43:35.018Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:43:36.309Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:43:37.075Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:43:37.853Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:43:38.698Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:43:39.488Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:43:39.842Z] 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.
[2025-10-03T20:43:39.842Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:43:39.842Z] Top recommended movies for user id 72:
[2025-10-03T20:43:39.842Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:43:39.842Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:43:39.842Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:43:39.842Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:43:39.842Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:43:39.842Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (8987.694 ms) ======
[2025-10-03T20:43:39.842Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-10-03T20:43:39.842Z] GC before operation: completed in 72.083 ms, heap usage 391.861 MB -> 90.279 MB.
[2025-10-03T20:43:41.088Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:43:42.338Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:43:44.160Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:43:45.394Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:43:46.184Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:43:46.985Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:43:47.769Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:43:48.561Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:43:48.561Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-03T20:43:48.561Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:43:48.561Z] Top recommended movies for user id 72:
[2025-10-03T20:43:48.561Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:43:48.561Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:43:48.561Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:43:48.561Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:43:48.561Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:43:48.561Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (8805.906 ms) ======
[2025-10-03T20:43:48.561Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-10-03T20:43:48.561Z] GC before operation: completed in 68.669 ms, heap usage 153.619 MB -> 89.736 MB.
[2025-10-03T20:43:50.380Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:43:51.161Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:43:52.443Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:43:53.679Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:43:54.445Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:43:55.225Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:43:56.061Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:43:56.853Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:43:57.212Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-03T20:43:57.212Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:43:57.212Z] Top recommended movies for user id 72:
[2025-10-03T20:43:57.212Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:43:57.212Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:43:57.212Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:43:57.212Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:43:57.212Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:43:57.212Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (8394.867 ms) ======
[2025-10-03T20:43:57.212Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-10-03T20:43:57.212Z] GC before operation: completed in 69.564 ms, heap usage 436.386 MB -> 90.253 MB.
[2025-10-03T20:43:58.463Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:43:59.728Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:44:01.026Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:44:02.331Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:44:03.214Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:44:04.007Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:44:04.797Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:44:05.574Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:44:05.574Z] 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.
[2025-10-03T20:44:05.574Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:44:05.574Z] Top recommended movies for user id 72:
[2025-10-03T20:44:05.574Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:44:05.574Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:44:05.574Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:44:05.574Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:44:05.574Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:44:05.574Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (8490.427 ms) ======
[2025-10-03T20:44:05.574Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-10-03T20:44:05.574Z] GC before operation: completed in 64.433 ms, heap usage 242.151 MB -> 90.113 MB.
[2025-10-03T20:44:06.819Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:44:08.611Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:44:09.872Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:44:10.644Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:44:11.431Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:44:12.251Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:44:13.026Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:44:13.827Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:44:14.184Z] 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.
[2025-10-03T20:44:14.184Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:44:14.184Z] Top recommended movies for user id 72:
[2025-10-03T20:44:14.184Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:44:14.184Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:44:14.184Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:44:14.184Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:44:14.184Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:44:14.184Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (8346.530 ms) ======
[2025-10-03T20:44:14.184Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-10-03T20:44:14.184Z] GC before operation: completed in 78.432 ms, heap usage 185.000 MB -> 89.757 MB.
[2025-10-03T20:44:15.424Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:44:16.690Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:44:18.038Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:44:19.275Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:44:20.045Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:44:20.818Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:44:21.595Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:44:22.365Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:44:22.365Z] 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.
[2025-10-03T20:44:22.731Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:44:22.731Z] Top recommended movies for user id 72:
[2025-10-03T20:44:22.731Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:44:22.731Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:44:22.731Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:44:22.731Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:44:22.731Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:44:22.731Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8441.252 ms) ======
[2025-10-03T20:44:22.731Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-10-03T20:44:22.731Z] GC before operation: completed in 60.309 ms, heap usage 274.845 MB -> 90.313 MB.
[2025-10-03T20:44:23.967Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:44:25.208Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:44:26.469Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:44:27.700Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:44:28.513Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:44:29.293Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:44:30.079Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:44:30.852Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:44:30.852Z] 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.
[2025-10-03T20:44:31.212Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:44:31.212Z] Top recommended movies for user id 72:
[2025-10-03T20:44:31.212Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:44:31.212Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:44:31.212Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:44:31.212Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:44:31.212Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:44:31.212Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (8427.214 ms) ======
[2025-10-03T20:44:31.212Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-10-03T20:44:31.212Z] GC before operation: completed in 60.668 ms, heap usage 232.158 MB -> 90.075 MB.
[2025-10-03T20:44:32.453Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:44:33.732Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:44:34.970Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:44:36.211Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:44:37.030Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:44:37.828Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:44:38.616Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:44:39.384Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:44:39.384Z] 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.
[2025-10-03T20:44:39.384Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:44:39.384Z] Top recommended movies for user id 72:
[2025-10-03T20:44:39.384Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:44:39.384Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:44:39.384Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:44:39.384Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:44:39.384Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:44:39.384Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (8228.749 ms) ======
[2025-10-03T20:44:39.384Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-10-03T20:44:39.384Z] GC before operation: completed in 72.774 ms, heap usage 199.183 MB -> 90.024 MB.
[2025-10-03T20:44:40.623Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:44:41.870Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:44:43.125Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:44:44.374Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:44:45.143Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:44:45.923Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:44:46.690Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:44:47.465Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:44:47.828Z] 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.
[2025-10-03T20:44:47.828Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:44:47.828Z] Top recommended movies for user id 72:
[2025-10-03T20:44:47.828Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:44:47.828Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:44:47.828Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:44:47.828Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:44:47.828Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:44:47.828Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8357.731 ms) ======
[2025-10-03T20:44:47.828Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-10-03T20:44:47.828Z] GC before operation: completed in 63.723 ms, heap usage 177.783 MB -> 89.975 MB.
[2025-10-03T20:44:49.068Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:44:50.328Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:44:51.577Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:44:52.813Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:44:53.588Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:44:54.364Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:44:55.151Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:44:55.927Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:44:56.290Z] 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.
[2025-10-03T20:44:56.290Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:44:56.290Z] Top recommended movies for user id 72:
[2025-10-03T20:44:56.290Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:44:56.290Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:44:56.290Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:44:56.290Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:44:56.290Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:44:56.290Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8364.432 ms) ======
[2025-10-03T20:44:56.290Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-10-03T20:44:56.290Z] GC before operation: completed in 66.683 ms, heap usage 442.116 MB -> 90.395 MB.
[2025-10-03T20:44:57.564Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-10-03T20:44:58.815Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-10-03T20:45:00.644Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-10-03T20:45:01.430Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-10-03T20:45:02.691Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-10-03T20:45:03.080Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-10-03T20:45:03.889Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-10-03T20:45:04.714Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-10-03T20:45:05.071Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-10-03T20:45:05.071Z] The best model improves the baseline by 14.52%.
[2025-10-03T20:45:05.071Z] Top recommended movies for user id 72:
[2025-10-03T20:45:05.071Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-10-03T20:45:05.071Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-10-03T20:45:05.071Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-10-03T20:45:05.071Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-10-03T20:45:05.071Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-10-03T20:45:05.071Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (8716.350 ms) ======
[2025-10-03T20:45:05.428Z] -----------------------------------
[2025-10-03T20:45:05.428Z] renaissance-movie-lens_0_PASSED
[2025-10-03T20:45:05.428Z] -----------------------------------
[2025-10-03T20:45:05.428Z]
[2025-10-03T20:45:05.428Z] TEST TEARDOWN:
[2025-10-03T20:45:05.428Z] Nothing to be done for teardown.
[2025-10-03T20:45:05.428Z] renaissance-movie-lens_0 Finish Time: Fri Oct 3 16:45:05 2025 Epoch Time (ms): 1759524305079