[2025-11-06T10:36:46.698Z] Running test renaissance-movie-lens_0 ... [2025-11-06T10:36:46.698Z] =============================================== [2025-11-06T10:36:47.019Z] renaissance-movie-lens_0 Start Time: Thu Nov 6 10:36:46 2025 Epoch Time (ms): 1762425406729 [2025-11-06T10:36:47.019Z] variation: NoOptions [2025-11-06T10:36:47.019Z] JVM_OPTIONS: [2025-11-06T10:36:47.019Z] { \ [2025-11-06T10:36:47.019Z] echo ""; echo "TEST SETUP:"; \ [2025-11-06T10:36:47.019Z] echo "Nothing to be done for setup."; \ [2025-11-06T10:36:47.019Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17624216953227\\renaissance-movie-lens_0"; \ [2025-11-06T10:36:47.019Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17624216953227\\renaissance-movie-lens_0"; \ [2025-11-06T10:36:47.019Z] echo ""; echo "TESTING:"; \ [2025-11-06T10:36:47.019Z] "c:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\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 "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17624216953227\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-11-06T10:36:47.019Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17624216953227\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-06T10:36:47.019Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-06T10:36:47.019Z] echo "Nothing to be done for teardown."; \ [2025-11-06T10:36:47.019Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17624216953227\\TestTargetResult"; [2025-11-06T10:36:47.359Z] [2025-11-06T10:36:47.359Z] TEST SETUP: [2025-11-06T10:36:47.359Z] Nothing to be done for setup. [2025-11-06T10:36:47.359Z] [2025-11-06T10:36:47.359Z] TESTING: [2025-11-06T10:37:06.406Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-11-06T10:37:18.579Z] 10:37:17.269 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-11-06T10:37:22.146Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-06T10:37:23.284Z] Training: 60056, validation: 20285, test: 19854 [2025-11-06T10:37:23.284Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-06T10:37:23.284Z] GC before operation: completed in 241.323 ms, heap usage 235.333 MB -> 74.674 MB. [2025-11-06T10:37:40.787Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:37:52.251Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:38:03.411Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:38:13.033Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:38:19.334Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:38:25.954Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:38:32.474Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:38:36.518Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:38:37.226Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:38:37.226Z] The best model improves the baseline by 14.34%. [2025-11-06T10:38:37.781Z] Top recommended movies for user id 72: [2025-11-06T10:38:37.781Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:38:37.781Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:38:37.781Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:38:37.781Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:38:37.781Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:38:37.781Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (74360.722 ms) ====== [2025-11-06T10:38:37.781Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-06T10:38:38.110Z] GC before operation: completed in 257.432 ms, heap usage 196.171 MB -> 88.725 MB. [2025-11-06T10:38:47.556Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:38:56.938Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:39:05.106Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:39:14.485Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:39:19.752Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:39:24.594Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:39:30.002Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:39:35.621Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:39:35.968Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:39:36.406Z] The best model improves the baseline by 14.34%. [2025-11-06T10:39:36.406Z] Top recommended movies for user id 72: [2025-11-06T10:39:36.406Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:39:36.406Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:39:36.406Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:39:36.406Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:39:36.406Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:39:36.406Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (58389.344 ms) ====== [2025-11-06T10:39:36.406Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-06T10:39:36.741Z] GC before operation: completed in 236.568 ms, heap usage 211.559 MB -> 86.846 MB. [2025-11-06T10:39:45.776Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:39:55.351Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:40:04.810Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:40:12.131Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:40:18.323Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:40:22.328Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:40:28.631Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:40:33.552Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:40:33.881Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:40:33.881Z] The best model improves the baseline by 14.34%. [2025-11-06T10:40:34.222Z] Top recommended movies for user id 72: [2025-11-06T10:40:34.222Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:40:34.222Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:40:34.222Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:40:34.222Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:40:34.222Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:40:34.222Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (57765.167 ms) ====== [2025-11-06T10:40:34.222Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-06T10:40:34.564Z] GC before operation: completed in 284.186 ms, heap usage 146.606 MB -> 87.369 MB. [2025-11-06T10:40:43.605Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:40:50.885Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:40:59.820Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:41:07.533Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:41:12.126Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:41:16.579Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:41:21.645Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:41:26.691Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:41:26.692Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:41:26.692Z] The best model improves the baseline by 14.34%. [2025-11-06T10:41:27.397Z] Top recommended movies for user id 72: [2025-11-06T10:41:27.397Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:41:27.397Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:41:27.397Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:41:27.397Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:41:27.397Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:41:27.397Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (52223.966 ms) ====== [2025-11-06T10:41:27.397Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-06T10:41:27.397Z] GC before operation: completed in 261.083 ms, heap usage 331.202 MB -> 87.895 MB. [2025-11-06T10:41:36.687Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:41:45.201Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:41:52.850Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:42:01.426Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:42:07.424Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:42:12.554Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:42:17.942Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:42:23.439Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:42:23.439Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:42:23.439Z] The best model improves the baseline by 14.34%. [2025-11-06T10:42:23.846Z] Top recommended movies for user id 72: [2025-11-06T10:42:23.846Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:42:23.846Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:42:23.846Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:42:23.846Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:42:23.846Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:42:23.846Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (56478.834 ms) ====== [2025-11-06T10:42:23.846Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-06T10:42:23.846Z] GC before operation: completed in 265.594 ms, heap usage 168.561 MB -> 87.687 MB. [2025-11-06T10:42:33.533Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:42:41.213Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:42:49.220Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:42:58.543Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:43:02.590Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:43:07.761Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:43:13.696Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:43:17.533Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:43:18.262Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:43:18.262Z] The best model improves the baseline by 14.34%. [2025-11-06T10:43:18.737Z] Top recommended movies for user id 72: [2025-11-06T10:43:18.737Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:43:18.737Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:43:18.737Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:43:18.737Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:43:18.737Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:43:18.737Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (54617.591 ms) ====== [2025-11-06T10:43:18.737Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-06T10:43:19.068Z] GC before operation: completed in 240.350 ms, heap usage 260.785 MB -> 88.069 MB. [2025-11-06T10:43:28.174Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:43:35.651Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:43:45.210Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:43:52.364Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:43:58.461Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:44:03.370Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:44:08.345Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:44:14.214Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:44:14.214Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:44:14.214Z] The best model improves the baseline by 14.34%. [2025-11-06T10:44:14.990Z] Top recommended movies for user id 72: [2025-11-06T10:44:14.990Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:44:14.990Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:44:14.990Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:44:14.990Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:44:14.990Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:44:14.990Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (56050.110 ms) ====== [2025-11-06T10:44:14.990Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-06T10:44:14.990Z] GC before operation: completed in 266.990 ms, heap usage 169.703 MB -> 87.885 MB. [2025-11-06T10:44:24.113Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:44:30.726Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:44:38.575Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:44:46.791Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:45:07.703Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:45:07.703Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:45:07.703Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:45:07.703Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:45:07.703Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:45:07.703Z] The best model improves the baseline by 14.34%. [2025-11-06T10:45:07.703Z] Top recommended movies for user id 72: [2025-11-06T10:45:07.703Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:45:07.703Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:45:07.703Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:45:07.703Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:45:07.703Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:45:07.703Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (51548.873 ms) ====== [2025-11-06T10:45:07.703Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-06T10:45:07.703Z] GC before operation: completed in 228.585 ms, heap usage 178.546 MB -> 88.085 MB. [2025-11-06T10:45:15.085Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:45:24.119Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:45:31.736Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:45:40.801Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:45:44.852Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:45:50.052Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:45:55.071Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:46:00.364Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:46:00.364Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:46:00.364Z] The best model improves the baseline by 14.34%. [2025-11-06T10:46:00.851Z] Top recommended movies for user id 72: [2025-11-06T10:46:00.851Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:46:00.851Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:46:00.851Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:46:00.851Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:46:00.851Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:46:00.851Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (53954.278 ms) ====== [2025-11-06T10:46:00.851Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-06T10:46:01.267Z] GC before operation: completed in 244.150 ms, heap usage 145.123 MB -> 87.953 MB. [2025-11-06T10:46:10.552Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:46:16.746Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:46:25.704Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:46:32.082Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:46:37.455Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:46:41.393Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:46:46.718Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:46:50.801Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:46:51.779Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:46:51.779Z] The best model improves the baseline by 14.34%. [2025-11-06T10:46:51.779Z] Top recommended movies for user id 72: [2025-11-06T10:46:51.779Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:46:51.779Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:46:51.779Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:46:51.779Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:46:51.779Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:46:51.779Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (50699.080 ms) ====== [2025-11-06T10:46:51.779Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-06T10:46:52.176Z] GC before operation: completed in 235.230 ms, heap usage 309.551 MB -> 88.309 MB. [2025-11-06T10:47:00.789Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:47:08.830Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:47:17.176Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:47:25.329Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:47:31.183Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:47:36.356Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:47:41.544Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:47:46.979Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:47:46.979Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:47:46.979Z] The best model improves the baseline by 14.34%. [2025-11-06T10:47:47.795Z] Top recommended movies for user id 72: [2025-11-06T10:47:47.795Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:47:47.795Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:47:47.795Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:47:47.795Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:47:47.795Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:47:47.795Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (55177.622 ms) ====== [2025-11-06T10:47:47.796Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-06T10:47:47.796Z] GC before operation: completed in 247.132 ms, heap usage 169.350 MB -> 87.894 MB. [2025-11-06T10:47:56.093Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:48:03.473Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:48:11.272Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:48:18.939Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:48:23.241Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:48:27.288Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:48:32.397Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:48:37.195Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:48:37.693Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:48:37.693Z] The best model improves the baseline by 14.34%. [2025-11-06T10:48:37.693Z] Top recommended movies for user id 72: [2025-11-06T10:48:37.693Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:48:37.693Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:48:37.693Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:48:37.693Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:48:37.693Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:48:37.693Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (50249.419 ms) ====== [2025-11-06T10:48:37.693Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-06T10:48:38.091Z] GC before operation: completed in 237.234 ms, heap usage 330.952 MB -> 88.350 MB. [2025-11-06T10:48:45.788Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:48:55.195Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:49:03.144Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:49:11.181Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:49:16.752Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:49:22.215Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:49:27.060Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:49:32.581Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:49:32.995Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:49:32.995Z] The best model improves the baseline by 14.34%. [2025-11-06T10:49:33.424Z] Top recommended movies for user id 72: [2025-11-06T10:49:33.424Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:49:33.424Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:49:33.424Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:49:33.424Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:49:33.424Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:49:33.424Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (55291.018 ms) ====== [2025-11-06T10:49:33.424Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-06T10:49:33.424Z] GC before operation: completed in 233.165 ms, heap usage 183.128 MB -> 88.219 MB. [2025-11-06T10:49:43.572Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:49:51.858Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:50:00.173Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:50:08.475Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:50:12.857Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:50:18.176Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:50:23.570Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:50:28.502Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:50:29.273Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:50:29.273Z] The best model improves the baseline by 14.34%. [2025-11-06T10:50:29.273Z] Top recommended movies for user id 72: [2025-11-06T10:50:29.273Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:50:29.273Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:50:29.273Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:50:29.273Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:50:29.273Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:50:29.273Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (55713.311 ms) ====== [2025-11-06T10:50:29.273Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-06T10:50:29.273Z] GC before operation: completed in 239.889 ms, heap usage 199.181 MB -> 88.054 MB. [2025-11-06T10:50:38.355Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:50:45.675Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:50:54.665Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:51:02.131Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:51:07.764Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:51:11.995Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:51:18.211Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:51:22.704Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:51:23.477Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:51:23.477Z] The best model improves the baseline by 14.34%. [2025-11-06T10:51:23.800Z] Top recommended movies for user id 72: [2025-11-06T10:51:23.800Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:51:23.800Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:51:23.800Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:51:23.800Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:51:23.800Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:51:23.800Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (54295.332 ms) ====== [2025-11-06T10:51:23.800Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-06T10:51:23.800Z] GC before operation: completed in 243.865 ms, heap usage 182.283 MB -> 88.260 MB. [2025-11-06T10:51:33.006Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:51:40.336Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:51:49.744Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:51:57.640Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:52:02.705Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:52:07.549Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:52:12.550Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:52:18.088Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:52:18.462Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:52:18.462Z] The best model improves the baseline by 14.34%. [2025-11-06T10:52:18.853Z] Top recommended movies for user id 72: [2025-11-06T10:52:18.853Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:52:18.853Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:52:18.853Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:52:18.853Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:52:18.853Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:52:18.853Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (54867.566 ms) ====== [2025-11-06T10:52:18.853Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-06T10:52:19.286Z] GC before operation: completed in 239.165 ms, heap usage 187.761 MB -> 88.102 MB. [2025-11-06T10:52:28.251Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:52:35.480Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:52:43.255Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:52:50.836Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:52:54.677Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:52:59.025Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:53:03.935Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:53:07.801Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:53:08.577Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:53:08.577Z] The best model improves the baseline by 14.34%. [2025-11-06T10:53:08.918Z] Top recommended movies for user id 72: [2025-11-06T10:53:08.918Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:53:08.918Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:53:08.918Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:53:08.918Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:53:08.918Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:53:08.918Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (49829.371 ms) ====== [2025-11-06T10:53:08.918Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-06T10:53:09.703Z] GC before operation: completed in 228.458 ms, heap usage 306.740 MB -> 88.354 MB. [2025-11-06T10:53:17.612Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:53:25.544Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:53:34.663Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:53:42.704Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:53:48.065Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:53:53.060Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:53:57.992Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:54:03.210Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:54:03.733Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:54:03.733Z] The best model improves the baseline by 14.34%. [2025-11-06T10:54:03.733Z] Top recommended movies for user id 72: [2025-11-06T10:54:03.733Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:54:03.733Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:54:03.733Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:54:03.733Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:54:03.733Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:54:03.733Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (54445.587 ms) ====== [2025-11-06T10:54:03.733Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-06T10:54:04.484Z] GC before operation: completed in 238.083 ms, heap usage 183.668 MB -> 88.048 MB. [2025-11-06T10:54:12.041Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:54:20.119Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:54:28.031Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:54:36.397Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:54:41.098Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:54:45.573Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:54:50.518Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:54:56.282Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:54:56.827Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:54:57.180Z] The best model improves the baseline by 14.34%. [2025-11-06T10:54:57.180Z] Top recommended movies for user id 72: [2025-11-06T10:54:57.180Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:54:57.180Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:54:57.180Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:54:57.180Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:54:57.180Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:54:57.180Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (53324.690 ms) ====== [2025-11-06T10:54:57.180Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-06T10:54:57.997Z] GC before operation: completed in 239.781 ms, heap usage 111.156 MB -> 88.030 MB. [2025-11-06T10:55:05.809Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-06T10:55:15.114Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-06T10:55:22.387Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-06T10:55:31.711Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-06T10:55:36.138Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-06T10:55:41.776Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-06T10:55:46.855Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-06T10:55:51.131Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-06T10:55:51.840Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-11-06T10:55:51.840Z] The best model improves the baseline by 14.34%. [2025-11-06T10:55:51.840Z] Top recommended movies for user id 72: [2025-11-06T10:55:51.840Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-11-06T10:55:51.840Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-11-06T10:55:51.840Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-11-06T10:55:51.840Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-11-06T10:55:51.840Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-11-06T10:55:51.840Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (54646.762 ms) ====== [2025-11-06T10:55:52.546Z] ----------------------------------- [2025-11-06T10:55:52.546Z] renaissance-movie-lens_0_PASSED [2025-11-06T10:55:52.546Z] ----------------------------------- [2025-11-06T10:55:52.877Z] [2025-11-06T10:55:52.877Z] TEST TEARDOWN: [2025-11-06T10:55:52.877Z] Nothing to be done for teardown. [2025-11-06T10:55:53.196Z] renaissance-movie-lens_0 Finish Time: Thu Nov 6 10:55:52 2025 Epoch Time (ms): 1762426552934