[2025-05-28T19:59:44.635Z] Running test renaissance-movie-lens_0 ... [2025-05-28T19:59:44.635Z] =============================================== [2025-05-28T19:59:44.635Z] renaissance-movie-lens_0 Start Time: Wed May 28 15:59:44 2025 Epoch Time (ms): 1748462384348 [2025-05-28T19:59:44.635Z] variation: NoOptions [2025-05-28T19:59:44.635Z] JVM_OPTIONS: [2025-05-28T19:59:44.635Z] { \ [2025-05-28T19:59:44.635Z] echo ""; echo "TEST SETUP:"; \ [2025-05-28T19:59:44.635Z] echo "Nothing to be done for setup."; \ [2025-05-28T19:59:44.635Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484618652318/renaissance-movie-lens_0"; \ [2025-05-28T19:59:44.635Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484618652318/renaissance-movie-lens_0"; \ [2025-05-28T19:59:44.635Z] echo ""; echo "TESTING:"; \ [2025-05-28T19:59:44.635Z] "/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_17484618652318/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-05-28T19:59:44.635Z] 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_17484618652318/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-05-28T19:59:44.635Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-05-28T19:59:44.635Z] echo "Nothing to be done for teardown."; \ [2025-05-28T19:59:44.635Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17484618652318/TestTargetResult"; [2025-05-28T19:59:44.635Z] [2025-05-28T19:59:44.635Z] TEST SETUP: [2025-05-28T19:59:44.635Z] Nothing to be done for setup. [2025-05-28T19:59:44.635Z] [2025-05-28T19:59:44.635Z] TESTING: [2025-05-28T19:59:47.755Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-05-28T19:59:50.170Z] 15:59:49.979 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. [2025-05-28T19:59:51.420Z] Got 100004 ratings from 671 users on 9066 movies. [2025-05-28T19:59:51.420Z] Training: 60056, validation: 20285, test: 19854 [2025-05-28T19:59:51.420Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-05-28T19:59:51.420Z] GC before operation: completed in 64.953 ms, heap usage 174.849 MB -> 75.839 MB. [2025-05-28T19:59:53.877Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T19:59:55.684Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T19:59:57.451Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T19:59:59.246Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:00:00.026Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:00:00.851Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:00:01.661Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:00:02.939Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:00:02.939Z] 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. [2025-05-28T20:00:02.939Z] The best model improves the baseline by 14.52%. [2025-05-28T20:00:02.939Z] Top recommended movies for user id 72: [2025-05-28T20:00:02.939Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:00:02.939Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:00:02.939Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:00:02.939Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:00:02.939Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:00:02.939Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (11481.446 ms) ====== [2025-05-28T20:00:02.939Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-05-28T20:00:02.939Z] GC before operation: completed in 83.057 ms, heap usage 409.836 MB -> 87.772 MB. [2025-05-28T20:00:04.764Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:00:06.019Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:00:07.836Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:00:09.080Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:00:09.853Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:00:10.729Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:00:11.493Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:00:12.262Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:00:12.626Z] 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. [2025-05-28T20:00:12.626Z] The best model improves the baseline by 14.52%. [2025-05-28T20:00:12.626Z] Top recommended movies for user id 72: [2025-05-28T20:00:12.626Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:00:12.626Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:00:12.626Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:00:12.626Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:00:12.626Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:00:12.626Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (9464.122 ms) ====== [2025-05-28T20:00:12.626Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-05-28T20:00:12.626Z] GC before operation: completed in 58.430 ms, heap usage 215.455 MB -> 88.319 MB. [2025-05-28T20:00:13.866Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:00:15.649Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:00:16.438Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:00:17.714Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:00:18.950Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:00:19.723Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:00:20.498Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:00:21.276Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:00:21.629Z] 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. [2025-05-28T20:00:21.629Z] The best model improves the baseline by 14.52%. [2025-05-28T20:00:21.629Z] Top recommended movies for user id 72: [2025-05-28T20:00:21.629Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:00:21.629Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:00:21.629Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:00:21.629Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:00:21.629Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:00:21.629Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (8997.372 ms) ====== [2025-05-28T20:00:21.629Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-05-28T20:00:21.629Z] GC before operation: completed in 53.869 ms, heap usage 113.102 MB -> 88.837 MB. [2025-05-28T20:00:22.862Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:00:24.105Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:00:25.926Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:00:27.152Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:00:27.938Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:00:28.717Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:00:29.974Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:00:30.743Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:00:30.743Z] 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. [2025-05-28T20:00:30.743Z] The best model improves the baseline by 14.52%. [2025-05-28T20:00:30.743Z] Top recommended movies for user id 72: [2025-05-28T20:00:30.744Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:00:30.744Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:00:30.744Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:00:30.744Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:00:30.744Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:00:30.744Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9115.475 ms) ====== [2025-05-28T20:00:30.744Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-05-28T20:00:30.744Z] GC before operation: completed in 61.970 ms, heap usage 514.691 MB -> 92.980 MB. [2025-05-28T20:00:31.999Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:00:33.257Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:00:35.039Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:00:36.302Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:00:37.110Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:00:37.884Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:00:38.651Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:00:39.417Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:00:39.417Z] 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. [2025-05-28T20:00:39.417Z] The best model improves the baseline by 14.52%. [2025-05-28T20:00:39.417Z] Top recommended movies for user id 72: [2025-05-28T20:00:39.417Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:00:39.417Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:00:39.417Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:00:39.417Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:00:39.417Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:00:39.417Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8700.699 ms) ====== [2025-05-28T20:00:39.417Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-05-28T20:00:39.771Z] GC before operation: completed in 61.347 ms, heap usage 458.786 MB -> 89.621 MB. [2025-05-28T20:00:41.004Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:00:42.252Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:00:43.511Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:00:44.761Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:00:45.532Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:00:46.311Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:00:47.099Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:00:47.892Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:00:47.892Z] 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. [2025-05-28T20:00:47.892Z] The best model improves the baseline by 14.52%. [2025-05-28T20:00:47.892Z] Top recommended movies for user id 72: [2025-05-28T20:00:47.892Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:00:47.892Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:00:47.892Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:00:47.892Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:00:47.892Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:00:47.892Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8306.813 ms) ====== [2025-05-28T20:00:47.893Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-05-28T20:00:47.893Z] GC before operation: completed in 71.736 ms, heap usage 242.422 MB -> 90.955 MB. [2025-05-28T20:00:49.135Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:00:50.413Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:00:51.651Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:00:52.886Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:00:53.667Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:00:54.021Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:00:55.327Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:00:55.750Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:00:56.104Z] 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. [2025-05-28T20:00:56.104Z] The best model improves the baseline by 14.52%. [2025-05-28T20:00:56.104Z] Top recommended movies for user id 72: [2025-05-28T20:00:56.104Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:00:56.104Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:00:56.104Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:00:56.104Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:00:56.104Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:00:56.104Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (8028.600 ms) ====== [2025-05-28T20:00:56.104Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-05-28T20:00:56.104Z] GC before operation: completed in 58.253 ms, heap usage 137.675 MB -> 92.329 MB. [2025-05-28T20:00:57.352Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:00:58.590Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:00:59.856Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:01:01.150Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:01:01.961Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:01:02.750Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:01:03.587Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:01:04.394Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:01:04.394Z] 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. [2025-05-28T20:01:04.394Z] The best model improves the baseline by 14.52%. [2025-05-28T20:01:04.394Z] Top recommended movies for user id 72: [2025-05-28T20:01:04.394Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:01:04.394Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:01:04.394Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:01:04.394Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:01:04.394Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:01:04.394Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (8476.276 ms) ====== [2025-05-28T20:01:04.394Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-05-28T20:01:04.757Z] GC before operation: completed in 60.627 ms, heap usage 397.341 MB -> 90.177 MB. [2025-05-28T20:01:06.032Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:01:07.311Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:01:08.545Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:01:09.782Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:01:10.557Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:01:11.335Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:01:12.115Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:01:12.897Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:01:12.897Z] 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. [2025-05-28T20:01:12.897Z] The best model improves the baseline by 14.52%. [2025-05-28T20:01:12.897Z] Top recommended movies for user id 72: [2025-05-28T20:01:12.897Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:01:12.897Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:01:12.897Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:01:12.897Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:01:12.897Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:01:12.897Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8443.641 ms) ====== [2025-05-28T20:01:12.897Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-05-28T20:01:13.261Z] GC before operation: completed in 60.251 ms, heap usage 321.342 MB -> 89.799 MB. [2025-05-28T20:01:14.529Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:01:15.769Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:01:17.008Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:01:18.248Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:01:19.014Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:01:19.799Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:01:20.580Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:01:21.352Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:01:21.352Z] 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. [2025-05-28T20:01:21.352Z] The best model improves the baseline by 14.52%. [2025-05-28T20:01:21.713Z] Top recommended movies for user id 72: [2025-05-28T20:01:21.713Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:01:21.713Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:01:21.713Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:01:21.713Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:01:21.713Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:01:21.713Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (8459.032 ms) ====== [2025-05-28T20:01:21.713Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-05-28T20:01:21.713Z] GC before operation: completed in 68.369 ms, heap usage 182.695 MB -> 89.851 MB. [2025-05-28T20:01:22.964Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:01:24.205Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:01:25.428Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:01:26.671Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:01:27.029Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:01:27.811Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:01:28.582Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:01:29.348Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:01:29.702Z] 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. [2025-05-28T20:01:29.702Z] The best model improves the baseline by 14.52%. [2025-05-28T20:01:29.702Z] Top recommended movies for user id 72: [2025-05-28T20:01:29.702Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:01:29.702Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:01:29.702Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:01:29.702Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:01:29.702Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:01:29.702Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (7958.685 ms) ====== [2025-05-28T20:01:29.702Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-05-28T20:01:29.702Z] GC before operation: completed in 67.967 ms, heap usage 194.579 MB -> 89.533 MB. [2025-05-28T20:01:30.939Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:01:32.169Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:01:33.409Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:01:34.188Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:01:34.971Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:01:35.742Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:01:36.513Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:01:37.277Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:01:37.277Z] 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. [2025-05-28T20:01:37.277Z] The best model improves the baseline by 14.52%. [2025-05-28T20:01:37.641Z] Top recommended movies for user id 72: [2025-05-28T20:01:37.641Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:01:37.641Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:01:37.641Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:01:37.641Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:01:37.641Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:01:37.642Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (7815.605 ms) ====== [2025-05-28T20:01:37.642Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-05-28T20:01:37.642Z] GC before operation: completed in 64.933 ms, heap usage 247.665 MB -> 90.027 MB. [2025-05-28T20:01:38.874Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:01:39.744Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:01:40.997Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:01:42.245Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:01:43.010Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:01:43.787Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:01:44.550Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:01:45.328Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:01:45.328Z] 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. [2025-05-28T20:01:45.328Z] The best model improves the baseline by 14.52%. [2025-05-28T20:01:45.328Z] Top recommended movies for user id 72: [2025-05-28T20:01:45.328Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:01:45.328Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:01:45.328Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:01:45.328Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:01:45.328Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:01:45.328Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (7886.027 ms) ====== [2025-05-28T20:01:45.328Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-05-28T20:01:45.328Z] GC before operation: completed in 60.300 ms, heap usage 193.924 MB -> 89.932 MB. [2025-05-28T20:01:46.554Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:01:47.785Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:01:49.029Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:01:50.262Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:01:51.027Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:01:51.799Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:01:52.570Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:01:53.347Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:01:53.347Z] 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. [2025-05-28T20:01:53.347Z] The best model improves the baseline by 14.52%. [2025-05-28T20:01:53.347Z] Top recommended movies for user id 72: [2025-05-28T20:01:53.347Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:01:53.347Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:01:53.347Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:01:53.347Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:01:53.347Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:01:53.347Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (7859.949 ms) ====== [2025-05-28T20:01:53.347Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-05-28T20:01:53.347Z] GC before operation: completed in 59.596 ms, heap usage 163.276 MB -> 89.747 MB. [2025-05-28T20:01:54.577Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:01:55.823Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:01:57.059Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:01:58.318Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:01:59.086Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:01:59.850Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:02:00.217Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:02:01.013Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:02:01.013Z] 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. [2025-05-28T20:02:01.013Z] The best model improves the baseline by 14.52%. [2025-05-28T20:02:01.013Z] Top recommended movies for user id 72: [2025-05-28T20:02:01.013Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:02:01.013Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:02:01.013Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:02:01.013Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:02:01.013Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:02:01.013Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (7711.020 ms) ====== [2025-05-28T20:02:01.013Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-05-28T20:02:01.013Z] GC before operation: completed in 63.260 ms, heap usage 262.790 MB -> 90.040 MB. [2025-05-28T20:02:02.320Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:02:03.593Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:02:04.406Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:02:05.679Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:02:06.443Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:02:07.212Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:02:07.979Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:02:08.764Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:02:08.764Z] 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. [2025-05-28T20:02:08.764Z] The best model improves the baseline by 14.52%. [2025-05-28T20:02:08.764Z] Top recommended movies for user id 72: [2025-05-28T20:02:08.764Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:02:08.764Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:02:08.764Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:02:08.764Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:02:08.764Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:02:08.764Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (7711.685 ms) ====== [2025-05-28T20:02:08.764Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-05-28T20:02:09.122Z] GC before operation: completed in 61.657 ms, heap usage 274.052 MB -> 89.969 MB. [2025-05-28T20:02:10.367Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:02:11.623Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:02:12.884Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:02:14.127Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:02:14.499Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:02:15.291Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:02:16.065Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:02:16.838Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:02:17.194Z] 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. [2025-05-28T20:02:17.194Z] The best model improves the baseline by 14.52%. [2025-05-28T20:02:17.194Z] Top recommended movies for user id 72: [2025-05-28T20:02:17.194Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:02:17.194Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:02:17.194Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:02:17.194Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:02:17.194Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:02:17.194Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (8206.627 ms) ====== [2025-05-28T20:02:17.194Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-05-28T20:02:17.194Z] GC before operation: completed in 56.343 ms, heap usage 480.239 MB -> 93.622 MB. [2025-05-28T20:02:18.443Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:02:19.698Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:02:20.948Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:02:22.188Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:02:22.969Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:02:23.855Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:02:24.628Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:02:25.421Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:02:25.421Z] 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. [2025-05-28T20:02:25.421Z] The best model improves the baseline by 14.52%. [2025-05-28T20:02:25.421Z] Top recommended movies for user id 72: [2025-05-28T20:02:25.421Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:02:25.421Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:02:25.421Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:02:25.421Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:02:25.421Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:02:25.421Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8350.903 ms) ====== [2025-05-28T20:02:25.421Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-05-28T20:02:25.777Z] GC before operation: completed in 59.864 ms, heap usage 398.504 MB -> 90.245 MB. [2025-05-28T20:02:27.017Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:02:28.263Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:02:29.503Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:02:30.748Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:02:31.517Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:02:32.301Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:02:33.089Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:02:33.465Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:02:33.826Z] 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. [2025-05-28T20:02:33.826Z] The best model improves the baseline by 14.52%. [2025-05-28T20:02:33.826Z] Top recommended movies for user id 72: [2025-05-28T20:02:33.827Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:02:33.827Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:02:33.827Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:02:33.827Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:02:33.827Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:02:33.827Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8141.151 ms) ====== [2025-05-28T20:02:33.827Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-05-28T20:02:33.827Z] GC before operation: completed in 54.945 ms, heap usage 263.348 MB -> 89.946 MB. [2025-05-28T20:02:35.071Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-05-28T20:02:36.322Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-05-28T20:02:37.566Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-05-28T20:02:38.799Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-05-28T20:02:39.571Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-05-28T20:02:40.360Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-05-28T20:02:41.132Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-05-28T20:02:41.916Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-05-28T20:02:41.917Z] 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. [2025-05-28T20:02:41.917Z] The best model improves the baseline by 14.52%. [2025-05-28T20:02:41.917Z] Top recommended movies for user id 72: [2025-05-28T20:02:41.917Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-05-28T20:02:41.917Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-05-28T20:02:41.917Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-05-28T20:02:41.917Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-05-28T20:02:41.917Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-05-28T20:02:41.917Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (8072.652 ms) ====== [2025-05-28T20:02:42.273Z] ----------------------------------- [2025-05-28T20:02:42.273Z] renaissance-movie-lens_0_PASSED [2025-05-28T20:02:42.273Z] ----------------------------------- [2025-05-28T20:02:42.273Z] [2025-05-28T20:02:42.273Z] TEST TEARDOWN: [2025-05-28T20:02:42.273Z] Nothing to be done for teardown. [2025-05-28T20:02:42.273Z] renaissance-movie-lens_0 Finish Time: Wed May 28 16:02:41 2025 Epoch Time (ms): 1748462561892