[2025-06-27T20:57:22.281Z] Running test renaissance-movie-lens_0 ... [2025-06-27T20:57:22.281Z] =============================================== [2025-06-27T20:57:22.281Z] renaissance-movie-lens_0 Start Time: Fri Jun 27 13:57:21 2025 Epoch Time (ms): 1751057841798 [2025-06-27T20:57:22.281Z] variation: NoOptions [2025-06-27T20:57:22.281Z] JVM_OPTIONS: [2025-06-27T20:57:22.281Z] { \ [2025-06-27T20:57:22.281Z] echo ""; echo "TEST SETUP:"; \ [2025-06-27T20:57:22.281Z] echo "Nothing to be done for setup."; \ [2025-06-27T20:57:22.281Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17510549304772/renaissance-movie-lens_0"; \ [2025-06-27T20:57:22.281Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17510549304772/renaissance-movie-lens_0"; \ [2025-06-27T20:57:22.281Z] echo ""; echo "TESTING:"; \ [2025-06-27T20:57:22.281Z] "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_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_x86-64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17510549304772/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-27T20:57:22.281Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17510549304772/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-27T20:57:22.281Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-27T20:57:22.281Z] echo "Nothing to be done for teardown."; \ [2025-06-27T20:57:22.281Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17510549304772/TestTargetResult"; [2025-06-27T20:57:22.281Z] [2025-06-27T20:57:22.281Z] TEST SETUP: [2025-06-27T20:57:22.281Z] Nothing to be done for setup. [2025-06-27T20:57:22.281Z] [2025-06-27T20:57:22.281Z] TESTING: [2025-06-27T20:57:40.020Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-06-27T20:58:01.281Z] 13:57:58.102 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. [2025-06-27T20:58:05.423Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-27T20:58:06.709Z] Training: 60056, validation: 20285, test: 19854 [2025-06-27T20:58:06.709Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-27T20:58:07.125Z] GC before operation: completed in 486.584 ms, heap usage 436.020 MB -> 75.983 MB. [2025-06-27T20:58:30.878Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T20:58:49.257Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T20:59:04.470Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T20:59:17.283Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T20:59:26.758Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T20:59:35.742Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T20:59:44.263Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T20:59:51.744Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T20:59:52.565Z] 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. [2025-06-27T20:59:53.133Z] The best model improves the baseline by 14.52%. [2025-06-27T20:59:54.160Z] Top recommended movies for user id 72: [2025-06-27T20:59:54.160Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T20:59:54.160Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T20:59:54.160Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T20:59:54.160Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T20:59:54.160Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T20:59:54.160Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (106706.596 ms) ====== [2025-06-27T20:59:54.160Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-27T20:59:54.160Z] GC before operation: completed in 294.357 ms, heap usage 289.734 MB -> 87.553 MB. [2025-06-27T21:00:07.153Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:00:22.056Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:00:37.254Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:00:52.913Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:00:59.880Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:01:08.834Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:01:17.270Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:01:26.264Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:01:26.838Z] 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. [2025-06-27T21:01:26.838Z] The best model improves the baseline by 14.52%. [2025-06-27T21:01:28.050Z] Top recommended movies for user id 72: [2025-06-27T21:01:28.050Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:01:28.050Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:01:28.050Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:01:28.050Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:01:28.050Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:01:28.050Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (93550.163 ms) ====== [2025-06-27T21:01:28.050Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-27T21:01:28.618Z] GC before operation: completed in 655.729 ms, heap usage 151.847 MB -> 88.252 MB. [2025-06-27T21:01:41.475Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:01:56.053Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:02:09.063Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:02:23.635Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:02:31.862Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:02:39.193Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:02:48.090Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:02:53.814Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:02:55.287Z] 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. [2025-06-27T21:02:55.287Z] The best model improves the baseline by 14.52%. [2025-06-27T21:02:55.287Z] Top recommended movies for user id 72: [2025-06-27T21:02:55.287Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:02:55.287Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:02:55.287Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:02:55.287Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:02:55.287Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:02:55.287Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (87048.551 ms) ====== [2025-06-27T21:02:55.287Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-27T21:02:55.833Z] GC before operation: completed in 289.357 ms, heap usage 929.535 MB -> 94.019 MB. [2025-06-27T21:03:08.567Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:03:23.490Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:03:36.031Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:03:48.386Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:03:54.157Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:04:01.303Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:04:08.171Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:04:16.835Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:04:18.232Z] 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. [2025-06-27T21:04:18.232Z] The best model improves the baseline by 14.52%. [2025-06-27T21:04:18.232Z] Top recommended movies for user id 72: [2025-06-27T21:04:18.232Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:04:18.232Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:04:18.232Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:04:18.232Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:04:18.232Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:04:18.232Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (82671.026 ms) ====== [2025-06-27T21:04:18.232Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-27T21:04:18.768Z] GC before operation: completed in 374.374 ms, heap usage 670.690 MB -> 93.153 MB. [2025-06-27T21:04:31.110Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:04:43.697Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:04:55.880Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:05:08.449Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:05:16.734Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:05:22.712Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:05:29.867Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:05:36.831Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:05:37.251Z] 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. [2025-06-27T21:05:37.706Z] The best model improves the baseline by 14.52%. [2025-06-27T21:05:38.165Z] Top recommended movies for user id 72: [2025-06-27T21:05:38.165Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:05:38.165Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:05:38.165Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:05:38.165Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:05:38.165Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:05:38.165Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (79201.463 ms) ====== [2025-06-27T21:05:38.165Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-27T21:05:38.165Z] GC before operation: completed in 364.092 ms, heap usage 453.168 MB -> 89.612 MB. [2025-06-27T21:05:51.151Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:06:01.689Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:06:15.411Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:06:26.063Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:06:33.106Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:06:40.068Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:06:48.784Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:06:54.326Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:06:55.395Z] 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. [2025-06-27T21:06:55.395Z] The best model improves the baseline by 14.52%. [2025-06-27T21:06:55.395Z] Top recommended movies for user id 72: [2025-06-27T21:06:55.395Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:06:55.395Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:06:55.395Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:06:55.395Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:06:55.395Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:06:55.395Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (77167.496 ms) ====== [2025-06-27T21:06:55.395Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-27T21:06:55.871Z] GC before operation: completed in 369.104 ms, heap usage 676.299 MB -> 93.345 MB. [2025-06-27T21:07:10.910Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:07:23.539Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:07:35.858Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:07:48.148Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:07:52.772Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:08:00.220Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:08:07.140Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:08:14.312Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:08:15.871Z] 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. [2025-06-27T21:08:15.871Z] The best model improves the baseline by 14.52%. [2025-06-27T21:08:16.357Z] Top recommended movies for user id 72: [2025-06-27T21:08:16.357Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:08:16.357Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:08:16.357Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:08:16.357Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:08:16.357Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:08:16.357Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (80481.383 ms) ====== [2025-06-27T21:08:16.357Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-27T21:08:17.046Z] GC before operation: completed in 452.980 ms, heap usage 509.636 MB -> 93.035 MB. [2025-06-27T21:08:32.225Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:08:44.945Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:08:57.180Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:09:07.696Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:09:16.214Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:09:21.787Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:09:27.441Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:09:34.582Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:09:35.100Z] 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. [2025-06-27T21:09:35.490Z] The best model improves the baseline by 14.52%. [2025-06-27T21:09:35.903Z] Top recommended movies for user id 72: [2025-06-27T21:09:35.903Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:09:35.903Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:09:35.903Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:09:35.903Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:09:35.903Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:09:35.903Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (78923.827 ms) ====== [2025-06-27T21:09:35.903Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-27T21:09:36.384Z] GC before operation: completed in 300.333 ms, heap usage 284.273 MB -> 89.743 MB. [2025-06-27T21:09:48.814Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:10:01.242Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:10:16.177Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:10:25.180Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:10:31.267Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:10:38.252Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:10:43.998Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:10:51.308Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:10:51.308Z] 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. [2025-06-27T21:10:51.861Z] The best model improves the baseline by 14.52%. [2025-06-27T21:10:52.284Z] Top recommended movies for user id 72: [2025-06-27T21:10:52.284Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:10:52.284Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:10:52.284Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:10:52.284Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:10:52.284Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:10:52.284Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (76236.803 ms) ====== [2025-06-27T21:10:52.284Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-27T21:10:52.868Z] GC before operation: completed in 333.791 ms, heap usage 241.327 MB -> 89.569 MB. [2025-06-27T21:11:05.485Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:11:17.643Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:11:29.998Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:11:38.226Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:11:45.568Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:11:51.226Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:11:56.962Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:12:02.848Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:12:03.844Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-06-27T21:12:03.844Z] The best model improves the baseline by 14.52%. [2025-06-27T21:12:04.310Z] Top recommended movies for user id 72: [2025-06-27T21:12:04.310Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:12:04.310Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:12:04.310Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:12:04.310Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:12:04.310Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:12:04.310Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (71716.602 ms) ====== [2025-06-27T21:12:04.310Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-27T21:12:04.722Z] GC before operation: completed in 428.004 ms, heap usage 792.983 MB -> 94.026 MB. [2025-06-27T21:12:17.081Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:12:29.875Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:12:40.277Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:12:51.145Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:12:58.291Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:13:04.480Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:13:12.833Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:13:18.560Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:13:19.605Z] 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. [2025-06-27T21:13:19.605Z] The best model improves the baseline by 14.52%. [2025-06-27T21:13:20.487Z] Top recommended movies for user id 72: [2025-06-27T21:13:20.487Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:13:20.487Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:13:20.487Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:13:20.487Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:13:20.487Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:13:20.487Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (75615.247 ms) ====== [2025-06-27T21:13:20.487Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-27T21:13:21.436Z] GC before operation: completed in 456.556 ms, heap usage 193.036 MB -> 89.489 MB. [2025-06-27T21:13:32.277Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:13:42.559Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:13:54.890Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:14:04.132Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:14:11.344Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:14:18.398Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:14:25.550Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:14:31.206Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:14:31.891Z] 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. [2025-06-27T21:14:32.344Z] The best model improves the baseline by 14.52%. [2025-06-27T21:14:32.344Z] Top recommended movies for user id 72: [2025-06-27T21:14:32.344Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:14:32.344Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:14:32.344Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:14:32.344Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:14:32.344Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:14:32.344Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (71595.577 ms) ====== [2025-06-27T21:14:32.344Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-27T21:14:32.899Z] GC before operation: completed in 400.619 ms, heap usage 126.043 MB -> 90.713 MB. [2025-06-27T21:14:44.913Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:14:56.830Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:15:06.847Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:15:19.397Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:15:23.837Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:15:28.850Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:15:36.263Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:15:42.393Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:15:43.645Z] 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. [2025-06-27T21:15:43.645Z] The best model improves the baseline by 14.52%. [2025-06-27T21:15:43.645Z] Top recommended movies for user id 72: [2025-06-27T21:15:43.645Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:15:43.645Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:15:43.645Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:15:43.645Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:15:43.645Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:15:43.645Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (70892.760 ms) ====== [2025-06-27T21:15:43.645Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-27T21:15:44.157Z] GC before operation: completed in 297.710 ms, heap usage 190.997 MB -> 89.836 MB. [2025-06-27T21:15:56.546Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:16:09.242Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:16:21.576Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:16:32.505Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:16:36.963Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:16:44.246Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:16:52.860Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:16:55.226Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:16:56.252Z] 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. [2025-06-27T21:16:56.252Z] The best model improves the baseline by 14.52%. [2025-06-27T21:16:56.709Z] Top recommended movies for user id 72: [2025-06-27T21:16:56.710Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:16:56.710Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:16:56.710Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:16:56.710Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:16:56.710Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:16:56.710Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (72636.869 ms) ====== [2025-06-27T21:16:56.710Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-27T21:16:57.195Z] GC before operation: completed in 419.571 ms, heap usage 405.064 MB -> 89.989 MB. [2025-06-27T21:17:09.914Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:17:22.395Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:17:31.365Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:17:43.833Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:17:48.502Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:17:54.422Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:18:01.321Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:18:06.390Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:18:07.595Z] 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. [2025-06-27T21:18:07.595Z] The best model improves the baseline by 14.52%. [2025-06-27T21:18:08.175Z] Top recommended movies for user id 72: [2025-06-27T21:18:08.175Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:18:08.175Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:18:08.175Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:18:08.175Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:18:08.175Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:18:08.175Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (70937.487 ms) ====== [2025-06-27T21:18:08.175Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-27T21:18:08.705Z] GC before operation: completed in 499.040 ms, heap usage 463.139 MB -> 90.291 MB. [2025-06-27T21:18:21.477Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:18:32.190Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:18:44.707Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:18:54.278Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:19:01.437Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:19:07.038Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:19:14.336Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:19:19.260Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:19:19.731Z] 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. [2025-06-27T21:19:19.731Z] The best model improves the baseline by 14.52%. [2025-06-27T21:19:20.226Z] Top recommended movies for user id 72: [2025-06-27T21:19:20.226Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:19:20.226Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:19:20.226Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:19:20.226Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:19:20.226Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:19:20.226Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (71671.700 ms) ====== [2025-06-27T21:19:20.226Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-27T21:19:20.687Z] GC before operation: completed in 310.869 ms, heap usage 839.914 MB -> 94.387 MB. [2025-06-27T21:19:33.034Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:19:43.043Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:19:58.328Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:20:07.098Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:20:13.478Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:20:20.286Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:20:26.355Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:20:32.387Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:20:32.858Z] 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. [2025-06-27T21:20:32.858Z] The best model improves the baseline by 14.52%. [2025-06-27T21:20:33.357Z] Top recommended movies for user id 72: [2025-06-27T21:20:33.357Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:20:33.357Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:20:33.357Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:20:33.357Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:20:33.357Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:20:33.357Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (73014.017 ms) ====== [2025-06-27T21:20:33.357Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-27T21:20:33.870Z] GC before operation: completed in 300.038 ms, heap usage 260.684 MB -> 90.022 MB. [2025-06-27T21:20:46.510Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:20:59.285Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:21:06.671Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:21:16.911Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:21:24.225Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:21:29.287Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:21:36.449Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:21:41.272Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:21:41.847Z] 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. [2025-06-27T21:21:42.307Z] The best model improves the baseline by 14.52%. [2025-06-27T21:21:42.833Z] Top recommended movies for user id 72: [2025-06-27T21:21:42.834Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:21:42.834Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:21:42.834Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:21:42.834Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:21:42.834Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:21:42.834Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (68807.411 ms) ====== [2025-06-27T21:21:42.834Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-27T21:21:42.834Z] GC before operation: completed in 327.399 ms, heap usage 351.507 MB -> 89.910 MB. [2025-06-27T21:21:55.772Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:22:06.747Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:22:17.478Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:22:26.535Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:22:32.843Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:22:40.222Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:22:50.632Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:22:55.182Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:22:57.275Z] 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. [2025-06-27T21:22:57.275Z] The best model improves the baseline by 14.52%. [2025-06-27T21:22:57.967Z] Top recommended movies for user id 72: [2025-06-27T21:22:57.967Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:22:57.967Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:22:57.967Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:22:57.967Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:22:57.967Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:22:57.967Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (74346.934 ms) ====== [2025-06-27T21:22:57.967Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-27T21:22:57.967Z] GC before operation: completed in 369.549 ms, heap usage 763.203 MB -> 94.229 MB. [2025-06-27T21:23:10.452Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:23:22.718Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:23:35.174Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:23:45.350Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:23:51.959Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:23:58.120Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:24:04.979Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:24:10.215Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:24:11.437Z] 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. [2025-06-27T21:24:11.437Z] The best model improves the baseline by 14.52%. [2025-06-27T21:24:11.906Z] Top recommended movies for user id 72: [2025-06-27T21:24:11.906Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-06-27T21:24:11.906Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-06-27T21:24:11.906Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-06-27T21:24:11.906Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-06-27T21:24:11.906Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-06-27T21:24:11.906Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (74164.113 ms) ====== [2025-06-27T21:24:15.451Z] ----------------------------------- [2025-06-27T21:24:15.451Z] renaissance-movie-lens_0_PASSED [2025-06-27T21:24:15.451Z] ----------------------------------- [2025-06-27T21:24:15.451Z] [2025-06-27T21:24:15.451Z] TEST TEARDOWN: [2025-06-27T21:24:15.451Z] Nothing to be done for teardown. [2025-06-27T21:24:15.451Z] renaissance-movie-lens_0 Finish Time: Fri Jun 27 14:24:14 2025 Epoch Time (ms): 1751059454868