[2025-09-03T21:48:41.144Z] Running test renaissance-movie-lens_0 ... [2025-09-03T21:48:41.144Z] =============================================== [2025-09-03T21:48:41.144Z] renaissance-movie-lens_0 Start Time: Wed Sep 3 17:48:40 2025 Epoch Time (ms): 1756936120875 [2025-09-03T21:48:41.144Z] variation: NoOptions [2025-09-03T21:48:41.144Z] JVM_OPTIONS: [2025-09-03T21:48:41.144Z] { \ [2025-09-03T21:48:41.144Z] echo ""; echo "TEST SETUP:"; \ [2025-09-03T21:48:41.144Z] echo "Nothing to be done for setup."; \ [2025-09-03T21:48:41.144Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17569354943316/renaissance-movie-lens_0"; \ [2025-09-03T21:48:41.144Z] cd "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17569354943316/renaissance-movie-lens_0"; \ [2025-09-03T21:48:41.144Z] echo ""; echo "TESTING:"; \ [2025-09-03T21:48:41.144Z] "/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_17569354943316/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-09-03T21:48:41.144Z] 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_17569354943316/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-09-03T21:48:41.144Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-09-03T21:48:41.144Z] echo "Nothing to be done for teardown."; \ [2025-09-03T21:48:41.144Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk21_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17569354943316/TestTargetResult"; [2025-09-03T21:48:41.144Z] [2025-09-03T21:48:41.144Z] TEST SETUP: [2025-09-03T21:48:41.144Z] Nothing to be done for setup. [2025-09-03T21:48:41.144Z] [2025-09-03T21:48:41.144Z] TESTING: [2025-09-03T21:48:44.255Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads. [2025-09-03T21:48:47.377Z] 17:48:47.088 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB. [2025-09-03T21:48:48.679Z] Got 100004 ratings from 671 users on 9066 movies. [2025-09-03T21:48:48.679Z] Training: 60056, validation: 20285, test: 19854 [2025-09-03T21:48:48.679Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-09-03T21:48:48.679Z] GC before operation: completed in 73.484 ms, heap usage 270.438 MB -> 75.983 MB. [2025-09-03T21:48:51.850Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:48:53.170Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:48:55.007Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:48:56.262Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:48:57.515Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:48:58.301Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:48:59.569Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:49:00.366Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:49:00.753Z] 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. [2025-09-03T21:49:00.753Z] The best model improves the baseline by 14.52%. [2025-09-03T21:49:00.753Z] Top recommended movies for user id 72: [2025-09-03T21:49:00.753Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:49:00.753Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:49:00.753Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:49:00.753Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:49:00.753Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:49:00.753Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (11999.314 ms) ====== [2025-09-03T21:49:00.753Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-09-03T21:49:00.753Z] GC before operation: completed in 67.399 ms, heap usage 382.933 MB -> 86.698 MB. [2025-09-03T21:49:02.560Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:49:04.365Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:49:05.612Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:49:07.384Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:49:08.141Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:49:08.894Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:49:09.670Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:49:10.900Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:49:10.900Z] 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. [2025-09-03T21:49:10.900Z] The best model improves the baseline by 14.52%. [2025-09-03T21:49:10.900Z] Top recommended movies for user id 72: [2025-09-03T21:49:10.900Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:49:10.900Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:49:10.900Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:49:10.900Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:49:10.900Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:49:10.900Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (10093.476 ms) ====== [2025-09-03T21:49:10.900Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-09-03T21:49:10.900Z] GC before operation: completed in 73.806 ms, heap usage 343.746 MB -> 88.717 MB. [2025-09-03T21:49:12.667Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:49:13.956Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:49:15.769Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:49:16.990Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:49:17.754Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:49:18.996Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:49:19.759Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:49:20.532Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:49:20.900Z] 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. [2025-09-03T21:49:20.900Z] The best model improves the baseline by 14.52%. [2025-09-03T21:49:20.900Z] Top recommended movies for user id 72: [2025-09-03T21:49:20.900Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:49:20.900Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:49:20.900Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:49:20.900Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:49:20.900Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:49:20.900Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (9835.617 ms) ====== [2025-09-03T21:49:20.900Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-09-03T21:49:20.900Z] GC before operation: completed in 63.869 ms, heap usage 115.040 MB -> 89.074 MB. [2025-09-03T21:49:22.661Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:49:23.894Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:49:25.657Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:49:26.880Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:49:27.640Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:49:28.415Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:49:29.183Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:49:29.958Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:49:30.334Z] 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. [2025-09-03T21:49:30.334Z] The best model improves the baseline by 14.52%. [2025-09-03T21:49:30.334Z] Top recommended movies for user id 72: [2025-09-03T21:49:30.334Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:49:30.334Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:49:30.334Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:49:30.334Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:49:30.334Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:49:30.334Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9365.722 ms) ====== [2025-09-03T21:49:30.334Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-09-03T21:49:30.334Z] GC before operation: completed in 72.546 ms, heap usage 227.290 MB -> 89.481 MB. [2025-09-03T21:49:32.130Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:49:32.925Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:49:34.703Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:49:35.952Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:49:36.740Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:49:37.527Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:49:38.310Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:49:39.110Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:49:39.110Z] 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. [2025-09-03T21:49:39.110Z] The best model improves the baseline by 14.52%. [2025-09-03T21:49:39.110Z] Top recommended movies for user id 72: [2025-09-03T21:49:39.110Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:49:39.110Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:49:39.110Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:49:39.110Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:49:39.110Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:49:39.110Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8719.021 ms) ====== [2025-09-03T21:49:39.110Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-09-03T21:49:39.110Z] GC before operation: completed in 92.072 ms, heap usage 334.315 MB -> 89.657 MB. [2025-09-03T21:49:40.336Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:49:42.118Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:49:43.362Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:49:44.232Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:49:45.001Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:49:45.771Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:49:46.551Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:49:47.352Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:49:47.711Z] 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. [2025-09-03T21:49:47.711Z] The best model improves the baseline by 14.52%. [2025-09-03T21:49:47.711Z] Top recommended movies for user id 72: [2025-09-03T21:49:47.711Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:49:47.711Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:49:47.711Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:49:47.711Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:49:47.711Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:49:47.711Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8426.362 ms) ====== [2025-09-03T21:49:47.711Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-09-03T21:49:47.711Z] GC before operation: completed in 73.166 ms, heap usage 231.208 MB -> 89.723 MB. [2025-09-03T21:49:48.941Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:49:50.726Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:49:51.501Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:49:53.312Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:49:54.085Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:49:54.971Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:49:55.774Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:49:56.582Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:49:56.582Z] 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. [2025-09-03T21:49:56.582Z] The best model improves the baseline by 14.52%. [2025-09-03T21:49:56.582Z] Top recommended movies for user id 72: [2025-09-03T21:49:56.582Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:49:56.582Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:49:56.582Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:49:56.582Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:49:56.582Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:49:56.582Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (8887.514 ms) ====== [2025-09-03T21:49:56.582Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-09-03T21:49:56.582Z] GC before operation: completed in 66.092 ms, heap usage 165.121 MB -> 89.655 MB. [2025-09-03T21:49:57.864Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:49:59.131Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:50:00.520Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:50:01.807Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:50:02.488Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:50:03.834Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:50:04.239Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:50:05.063Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:50:05.429Z] 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. [2025-09-03T21:50:05.429Z] The best model improves the baseline by 14.52%. [2025-09-03T21:50:05.429Z] Top recommended movies for user id 72: [2025-09-03T21:50:05.429Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:50:05.429Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:50:05.429Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:50:05.429Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:50:05.429Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:50:05.429Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (8751.569 ms) ====== [2025-09-03T21:50:05.429Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-09-03T21:50:05.429Z] GC before operation: completed in 77.119 ms, heap usage 339.295 MB -> 90.113 MB. [2025-09-03T21:50:06.696Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:50:08.474Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:50:09.702Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:50:10.982Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:50:11.796Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:50:12.549Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:50:13.310Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:50:14.062Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:50:14.062Z] 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. [2025-09-03T21:50:14.062Z] The best model improves the baseline by 14.52%. [2025-09-03T21:50:14.062Z] Top recommended movies for user id 72: [2025-09-03T21:50:14.062Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:50:14.062Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:50:14.062Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:50:14.062Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:50:14.062Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:50:14.062Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8570.914 ms) ====== [2025-09-03T21:50:14.063Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-09-03T21:50:14.063Z] GC before operation: completed in 63.849 ms, heap usage 195.273 MB -> 89.823 MB. [2025-09-03T21:50:15.291Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:50:16.580Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:50:18.361Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:50:19.610Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:50:20.389Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:50:20.750Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:50:21.509Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:50:22.268Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:50:22.268Z] 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. [2025-09-03T21:50:22.268Z] The best model improves the baseline by 14.52%. [2025-09-03T21:50:22.627Z] Top recommended movies for user id 72: [2025-09-03T21:50:22.627Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:50:22.627Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:50:22.627Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:50:22.627Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:50:22.627Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:50:22.627Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (8353.137 ms) ====== [2025-09-03T21:50:22.627Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-09-03T21:50:22.627Z] GC before operation: completed in 50.620 ms, heap usage 334.876 MB -> 90.312 MB. [2025-09-03T21:50:23.856Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:50:25.080Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:50:26.314Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:50:27.542Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:50:27.905Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:50:28.662Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:50:29.023Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:50:29.800Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:50:29.800Z] 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. [2025-09-03T21:50:29.800Z] The best model improves the baseline by 14.52%. [2025-09-03T21:50:29.800Z] Top recommended movies for user id 72: [2025-09-03T21:50:29.800Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:50:29.800Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:50:29.800Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:50:29.800Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:50:29.800Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:50:29.800Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (7404.754 ms) ====== [2025-09-03T21:50:29.800Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-09-03T21:50:30.154Z] GC before operation: completed in 52.027 ms, heap usage 180.188 MB -> 89.745 MB. [2025-09-03T21:50:30.917Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:50:32.160Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:50:33.379Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:50:34.135Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:50:34.909Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:50:35.259Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:50:36.069Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:50:36.430Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:50:36.795Z] 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. [2025-09-03T21:50:36.795Z] The best model improves the baseline by 14.52%. [2025-09-03T21:50:36.795Z] Top recommended movies for user id 72: [2025-09-03T21:50:36.795Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:50:36.795Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:50:36.795Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:50:36.795Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:50:36.795Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:50:36.795Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (6708.900 ms) ====== [2025-09-03T21:50:36.795Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-09-03T21:50:36.795Z] GC before operation: completed in 56.197 ms, heap usage 340.333 MB -> 90.183 MB. [2025-09-03T21:50:38.018Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:50:38.772Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:50:40.010Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:50:40.763Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:50:41.526Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:50:42.287Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:50:43.054Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:50:43.826Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:50:43.826Z] 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. [2025-09-03T21:50:43.826Z] The best model improves the baseline by 14.52%. [2025-09-03T21:50:43.826Z] Top recommended movies for user id 72: [2025-09-03T21:50:43.826Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:50:43.826Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:50:43.826Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:50:43.826Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:50:43.826Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:50:43.826Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (7115.543 ms) ====== [2025-09-03T21:50:43.826Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-09-03T21:50:43.826Z] GC before operation: completed in 54.646 ms, heap usage 272.641 MB -> 90.335 MB. [2025-09-03T21:50:45.062Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:50:46.277Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:50:47.041Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:50:48.275Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:50:49.037Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:50:49.806Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:50:50.586Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:50:51.372Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:50:51.372Z] 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. [2025-09-03T21:50:51.372Z] The best model improves the baseline by 14.52%. [2025-09-03T21:50:51.728Z] Top recommended movies for user id 72: [2025-09-03T21:50:51.728Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:50:51.729Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:50:51.729Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:50:51.729Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:50:51.729Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:50:51.729Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (7675.300 ms) ====== [2025-09-03T21:50:51.729Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-09-03T21:50:51.729Z] GC before operation: completed in 78.901 ms, heap usage 400.225 MB -> 90.267 MB. [2025-09-03T21:50:52.986Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:50:54.760Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:50:56.035Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:50:57.266Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:50:58.045Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:50:58.809Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:51:00.046Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:51:00.813Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:51:00.813Z] 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. [2025-09-03T21:51:00.813Z] The best model improves the baseline by 14.52%. [2025-09-03T21:51:00.813Z] Top recommended movies for user id 72: [2025-09-03T21:51:00.813Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:51:00.813Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:51:00.813Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:51:00.813Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:51:00.813Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:51:00.813Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (9083.499 ms) ====== [2025-09-03T21:51:00.813Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-09-03T21:51:00.813Z] GC before operation: completed in 56.495 ms, heap usage 321.226 MB -> 90.277 MB. [2025-09-03T21:51:02.069Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:51:03.352Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:51:04.637Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:51:05.903Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:51:06.701Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:51:07.484Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:51:08.239Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:51:09.013Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:51:09.365Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983. [2025-09-03T21:51:09.365Z] The best model improves the baseline by 14.52%. [2025-09-03T21:51:09.365Z] Top recommended movies for user id 72: [2025-09-03T21:51:09.365Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:51:09.365Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:51:09.365Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:51:09.365Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:51:09.365Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:51:09.365Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (8469.945 ms) ====== [2025-09-03T21:51:09.365Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-09-03T21:51:09.365Z] GC before operation: completed in 84.864 ms, heap usage 304.809 MB -> 90.142 MB. [2025-09-03T21:51:10.596Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:51:11.840Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:51:13.066Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:51:14.305Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:51:15.066Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:51:15.834Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:51:16.620Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:51:17.386Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:51:17.386Z] 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. [2025-09-03T21:51:17.386Z] The best model improves the baseline by 14.52%. [2025-09-03T21:51:17.747Z] Top recommended movies for user id 72: [2025-09-03T21:51:17.747Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:51:17.747Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:51:17.747Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:51:17.747Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:51:17.747Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:51:17.747Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (8183.850 ms) ====== [2025-09-03T21:51:17.747Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-09-03T21:51:17.747Z] GC before operation: completed in 96.139 ms, heap usage 339.045 MB -> 90.314 MB. [2025-09-03T21:51:18.968Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:51:20.202Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:51:21.966Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:51:23.204Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:51:23.988Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:51:24.770Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:51:26.006Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:51:26.766Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:51:26.766Z] 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. [2025-09-03T21:51:26.766Z] The best model improves the baseline by 14.52%. [2025-09-03T21:51:27.143Z] Top recommended movies for user id 72: [2025-09-03T21:51:27.143Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:51:27.143Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:51:27.143Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:51:27.143Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:51:27.143Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:51:27.143Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (9332.152 ms) ====== [2025-09-03T21:51:27.143Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-09-03T21:51:27.143Z] GC before operation: completed in 71.449 ms, heap usage 412.409 MB -> 90.191 MB. [2025-09-03T21:51:28.378Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:51:29.600Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:51:30.830Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:51:32.592Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:51:33.371Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:51:34.165Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:51:35.398Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:51:36.207Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:51:36.207Z] 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. [2025-09-03T21:51:36.207Z] The best model improves the baseline by 14.52%. [2025-09-03T21:51:36.571Z] Top recommended movies for user id 72: [2025-09-03T21:51:36.571Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:51:36.571Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:51:36.571Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:51:36.571Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:51:36.571Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:51:36.571Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (9328.590 ms) ====== [2025-09-03T21:51:36.571Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-09-03T21:51:36.571Z] GC before operation: completed in 74.207 ms, heap usage 414.534 MB -> 90.311 MB. [2025-09-03T21:51:37.813Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-09-03T21:51:38.579Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-09-03T21:51:39.813Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-09-03T21:51:41.050Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-09-03T21:51:41.427Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-09-03T21:51:42.196Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-09-03T21:51:42.980Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-09-03T21:51:43.349Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-09-03T21:51:43.349Z] 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. [2025-09-03T21:51:43.349Z] The best model improves the baseline by 14.52%. [2025-09-03T21:51:43.702Z] Top recommended movies for user id 72: [2025-09-03T21:51:43.702Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504) [2025-09-03T21:51:43.702Z] 2: Goat, The (1921) (rating: 4.677, id: 83318) [2025-09-03T21:51:43.702Z] 3: Play House, The (1921) (rating: 4.677, id: 83359) [2025-09-03T21:51:43.702Z] 4: Cops (1922) (rating: 4.677, id: 83411) [2025-09-03T21:51:43.702Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530) [2025-09-03T21:51:43.702Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (7119.516 ms) ====== [2025-09-03T21:51:43.702Z] ----------------------------------- [2025-09-03T21:51:43.702Z] renaissance-movie-lens_0_PASSED [2025-09-03T21:51:43.702Z] ----------------------------------- [2025-09-03T21:51:43.702Z] [2025-09-03T21:51:43.702Z] TEST TEARDOWN: [2025-09-03T21:51:43.702Z] Nothing to be done for teardown. [2025-09-03T21:51:43.702Z] renaissance-movie-lens_0 Finish Time: Wed Sep 3 17:51:43 2025 Epoch Time (ms): 1756936303587