[2025-06-19T11:33:36.538Z] Running test renaissance-movie-lens_0 ... [2025-06-19T11:33:36.538Z] =============================================== [2025-06-19T11:33:36.538Z] renaissance-movie-lens_0 Start Time: Thu Jun 19 11:33:36 2025 Epoch Time (ms): 1750332816408 [2025-06-19T11:33:36.863Z] variation: NoOptions [2025-06-19T11:33:36.863Z] JVM_OPTIONS: [2025-06-19T11:33:36.863Z] { \ [2025-06-19T11:33:36.863Z] echo ""; echo "TEST SETUP:"; \ [2025-06-19T11:33:36.863Z] echo "Nothing to be done for setup."; \ [2025-06-19T11:33:36.863Z] mkdir -p "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17503312181534\\renaissance-movie-lens_0"; \ [2025-06-19T11:33:36.863Z] cd "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17503312181534\\renaissance-movie-lens_0"; \ [2025-06-19T11:33:36.863Z] echo ""; echo "TESTING:"; \ [2025-06-19T11:33:36.863Z] "c:/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17503312181534\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2025-06-19T11:33:36.863Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17503312181534\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-19T11:33:36.863Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-19T11:33:36.863Z] echo "Nothing to be done for teardown."; \ [2025-06-19T11:33:36.863Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17503312181534\\TestTargetResult"; [2025-06-19T11:33:36.863Z] [2025-06-19T11:33:36.863Z] TEST SETUP: [2025-06-19T11:33:36.863Z] Nothing to be done for setup. [2025-06-19T11:33:36.863Z] [2025-06-19T11:33:36.863Z] TESTING: [2025-06-19T11:33:49.758Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-19T11:33:56.916Z] 11:33:55.645 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-06-19T11:33:58.076Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-19T11:33:58.484Z] Training: 60056, validation: 20285, test: 19854 [2025-06-19T11:33:58.484Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-19T11:33:58.823Z] GC before operation: completed in 98.572 ms, heap usage 130.371 MB -> 75.890 MB. [2025-06-19T11:34:12.116Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:34:20.932Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:34:29.689Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:34:38.435Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:34:42.114Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:34:46.749Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:34:50.477Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:34:55.196Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:34:55.196Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:34:55.532Z] The best model improves the baseline by 14.52%. [2025-06-19T11:34:55.897Z] Top recommended movies for user id 72: [2025-06-19T11:34:55.897Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:34:55.897Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:34:55.897Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:34:55.897Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:34:55.897Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:34:55.897Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (57054.100 ms) ====== [2025-06-19T11:34:55.897Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-19T11:34:55.897Z] GC before operation: completed in 113.223 ms, heap usage 186.519 MB -> 93.324 MB. [2025-06-19T11:35:03.061Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:35:10.244Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:35:17.338Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:35:24.457Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:35:28.153Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:35:31.823Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:35:36.484Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:35:40.177Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:35:40.504Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:35:40.504Z] The best model improves the baseline by 14.52%. [2025-06-19T11:35:40.827Z] Top recommended movies for user id 72: [2025-06-19T11:35:40.827Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:35:40.827Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:35:40.827Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:35:40.827Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:35:40.827Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:35:40.827Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (44968.671 ms) ====== [2025-06-19T11:35:40.827Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-19T11:35:40.827Z] GC before operation: completed in 99.111 ms, heap usage 235.172 MB -> 89.748 MB. [2025-06-19T11:35:47.938Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:35:55.064Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:36:02.207Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:36:09.301Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:36:12.172Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:36:15.935Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:36:20.191Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:36:23.870Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:36:24.196Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:36:24.196Z] The best model improves the baseline by 14.52%. [2025-06-19T11:36:24.513Z] Top recommended movies for user id 72: [2025-06-19T11:36:24.513Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:36:24.513Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:36:24.513Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:36:24.513Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:36:24.513Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:36:24.513Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (43641.937 ms) ====== [2025-06-19T11:36:24.513Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-19T11:36:24.513Z] GC before operation: completed in 110.841 ms, heap usage 232.270 MB -> 91.097 MB. [2025-06-19T11:36:31.653Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:36:38.755Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:36:45.902Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:36:51.778Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:36:55.450Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:36:59.133Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:37:03.790Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:37:06.649Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:37:07.333Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:37:07.333Z] The best model improves the baseline by 14.52%. [2025-06-19T11:37:07.656Z] Top recommended movies for user id 72: [2025-06-19T11:37:07.656Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:37:07.656Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:37:07.656Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:37:07.656Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:37:07.656Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:37:07.656Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (42892.853 ms) ====== [2025-06-19T11:37:07.656Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-19T11:37:07.656Z] GC before operation: completed in 109.016 ms, heap usage 283.099 MB -> 89.740 MB. [2025-06-19T11:37:14.773Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:37:21.875Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:37:29.012Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:37:36.135Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:37:39.016Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:37:43.678Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:37:47.359Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:37:52.086Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:37:52.086Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:37:52.086Z] The best model improves the baseline by 14.52%. [2025-06-19T11:37:52.086Z] Top recommended movies for user id 72: [2025-06-19T11:37:52.086Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:37:52.086Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:37:52.086Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:37:52.086Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:37:52.086Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:37:52.086Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (44501.562 ms) ====== [2025-06-19T11:37:52.086Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-19T11:37:52.414Z] GC before operation: completed in 113.335 ms, heap usage 447.203 MB -> 92.110 MB. [2025-06-19T11:37:59.541Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:38:06.650Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:38:13.785Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:38:19.542Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:38:23.229Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:38:27.871Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:38:31.567Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:38:35.219Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:38:35.549Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:38:35.962Z] The best model improves the baseline by 14.52%. [2025-06-19T11:38:35.962Z] Top recommended movies for user id 72: [2025-06-19T11:38:35.962Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:38:35.962Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:38:35.962Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:38:35.962Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:38:35.962Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:38:35.962Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (43663.948 ms) ====== [2025-06-19T11:38:35.962Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-19T11:38:36.299Z] GC before operation: completed in 115.126 ms, heap usage 263.226 MB -> 93.180 MB. [2025-06-19T11:38:43.403Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:38:49.161Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:38:56.294Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:39:02.054Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:39:05.734Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:39:09.404Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:39:14.211Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:39:17.076Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:39:17.846Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:39:17.846Z] The best model improves the baseline by 14.52%. [2025-06-19T11:39:17.846Z] Top recommended movies for user id 72: [2025-06-19T11:39:17.846Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:39:17.846Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:39:17.846Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:39:17.846Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:39:17.846Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:39:17.846Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (41869.284 ms) ====== [2025-06-19T11:39:17.846Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-19T11:39:18.178Z] GC before operation: completed in 105.958 ms, heap usage 120.493 MB -> 89.775 MB. [2025-06-19T11:39:25.273Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:39:31.047Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:39:38.167Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:39:45.261Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:39:48.158Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:39:51.836Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:39:56.464Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:40:00.207Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:40:00.531Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:40:00.531Z] The best model improves the baseline by 14.52%. [2025-06-19T11:40:00.868Z] Top recommended movies for user id 72: [2025-06-19T11:40:00.868Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:40:00.868Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:40:00.868Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:40:00.868Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:40:00.868Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:40:00.868Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (42719.288 ms) ====== [2025-06-19T11:40:00.868Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-19T11:40:00.868Z] GC before operation: completed in 102.022 ms, heap usage 302.600 MB -> 90.289 MB. [2025-06-19T11:40:07.989Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:40:15.124Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:40:22.242Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:40:29.351Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:40:33.025Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:40:36.705Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:40:41.334Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:40:44.194Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:40:44.891Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:40:44.891Z] The best model improves the baseline by 14.52%. [2025-06-19T11:40:45.231Z] Top recommended movies for user id 72: [2025-06-19T11:40:45.231Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:40:45.231Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:40:45.231Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:40:45.231Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:40:45.231Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:40:45.231Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (44264.178 ms) ====== [2025-06-19T11:40:45.231Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-19T11:40:45.231Z] GC before operation: completed in 98.934 ms, heap usage 135.369 MB -> 92.086 MB. [2025-06-19T11:40:52.358Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:40:59.475Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:41:06.592Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:41:13.692Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:41:16.551Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:41:20.273Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:41:23.944Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:41:27.623Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:41:28.420Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:41:28.420Z] The best model improves the baseline by 14.52%. [2025-06-19T11:41:28.420Z] Top recommended movies for user id 72: [2025-06-19T11:41:28.420Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:41:28.420Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:41:28.420Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:41:28.420Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:41:28.420Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:41:28.420Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (43277.346 ms) ====== [2025-06-19T11:41:28.420Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-19T11:41:28.746Z] GC before operation: completed in 106.901 ms, heap usage 134.616 MB -> 92.490 MB. [2025-06-19T11:41:35.842Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:41:41.613Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:41:48.725Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:41:55.823Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:41:58.706Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:42:02.389Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:42:06.058Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:42:09.740Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:42:10.435Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:42:10.435Z] The best model improves the baseline by 14.52%. [2025-06-19T11:42:10.435Z] Top recommended movies for user id 72: [2025-06-19T11:42:10.435Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:42:10.435Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:42:10.435Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:42:10.435Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:42:10.435Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:42:10.435Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (41867.870 ms) ====== [2025-06-19T11:42:10.435Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-19T11:42:10.435Z] GC before operation: completed in 112.903 ms, heap usage 533.105 MB -> 90.324 MB. [2025-06-19T11:42:19.159Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:42:26.270Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:42:33.429Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:42:39.236Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:42:42.911Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:42:46.563Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:42:50.233Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:42:53.913Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:42:54.657Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:42:54.657Z] The best model improves the baseline by 14.52%. [2025-06-19T11:42:54.657Z] Top recommended movies for user id 72: [2025-06-19T11:42:54.657Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:42:54.657Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:42:54.657Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:42:54.657Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:42:54.657Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:42:54.657Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (44148.758 ms) ====== [2025-06-19T11:42:54.657Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-19T11:42:54.987Z] GC before operation: completed in 105.016 ms, heap usage 260.858 MB -> 93.748 MB. [2025-06-19T11:43:02.086Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:43:09.199Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:43:16.357Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:43:22.125Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:43:25.794Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:43:30.424Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:43:34.095Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:43:38.725Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:43:38.725Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:43:38.725Z] The best model improves the baseline by 14.52%. [2025-06-19T11:43:38.725Z] Top recommended movies for user id 72: [2025-06-19T11:43:38.725Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:43:38.725Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:43:38.725Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:43:38.725Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:43:38.725Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:43:38.725Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (43881.209 ms) ====== [2025-06-19T11:43:38.725Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-19T11:43:38.725Z] GC before operation: completed in 104.426 ms, heap usage 458.908 MB -> 93.882 MB. [2025-06-19T11:43:45.823Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:43:51.625Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:44:00.407Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:44:06.163Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:44:09.843Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:44:13.504Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:44:17.185Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:44:20.851Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:44:21.643Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:44:21.643Z] The best model improves the baseline by 14.52%. [2025-06-19T11:44:21.643Z] Top recommended movies for user id 72: [2025-06-19T11:44:21.643Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:44:21.643Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:44:21.643Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:44:21.643Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:44:21.643Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:44:21.643Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (42883.164 ms) ====== [2025-06-19T11:44:21.643Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-19T11:44:21.974Z] GC before operation: completed in 116.365 ms, heap usage 448.785 MB -> 93.666 MB. [2025-06-19T11:44:29.071Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:44:34.861Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:44:43.598Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:44:49.376Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:44:53.038Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:44:56.694Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:45:01.325Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:45:05.002Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:45:05.002Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:45:05.002Z] The best model improves the baseline by 14.52%. [2025-06-19T11:45:05.320Z] Top recommended movies for user id 72: [2025-06-19T11:45:05.320Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:45:05.320Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:45:05.320Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:45:05.320Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:45:05.320Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:45:05.320Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (43438.409 ms) ====== [2025-06-19T11:45:05.320Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-19T11:45:05.320Z] GC before operation: completed in 99.696 ms, heap usage 152.016 MB -> 93.460 MB. [2025-06-19T11:45:12.448Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:45:19.611Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:45:26.739Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:45:33.848Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:45:36.714Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:45:40.392Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:45:45.070Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:45:48.754Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:45:49.086Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:45:49.086Z] The best model improves the baseline by 14.52%. [2025-06-19T11:45:49.414Z] Top recommended movies for user id 72: [2025-06-19T11:45:49.414Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:45:49.414Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:45:49.414Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:45:49.414Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:45:49.414Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:45:49.414Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (43927.890 ms) ====== [2025-06-19T11:45:49.414Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-19T11:45:49.414Z] GC before operation: completed in 105.262 ms, heap usage 193.469 MB -> 93.324 MB. [2025-06-19T11:45:56.531Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:46:02.333Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:46:11.067Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:46:16.854Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:46:20.524Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:46:24.218Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:46:27.877Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:46:31.555Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:46:32.275Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:46:32.275Z] The best model improves the baseline by 14.52%. [2025-06-19T11:46:32.275Z] Top recommended movies for user id 72: [2025-06-19T11:46:32.275Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:46:32.275Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:46:32.275Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:46:32.275Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:46:32.275Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:46:32.275Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (42948.802 ms) ====== [2025-06-19T11:46:32.275Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-19T11:46:32.601Z] GC before operation: completed in 107.003 ms, heap usage 286.663 MB -> 92.744 MB. [2025-06-19T11:46:39.718Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:46:46.817Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:46:53.917Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:46:59.669Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:47:03.347Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:47:07.014Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:47:10.680Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:47:14.343Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:47:14.661Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:47:14.661Z] The best model improves the baseline by 14.52%. [2025-06-19T11:47:14.988Z] Top recommended movies for user id 72: [2025-06-19T11:47:14.988Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:47:14.988Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:47:14.988Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:47:14.988Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:47:14.988Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:47:14.988Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (42435.756 ms) ====== [2025-06-19T11:47:14.988Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-19T11:47:14.988Z] GC before operation: completed in 111.987 ms, heap usage 296.534 MB -> 90.210 MB. [2025-06-19T11:47:22.165Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:47:27.932Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:47:35.040Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:47:42.156Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:47:45.847Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:47:49.513Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:47:53.204Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:47:56.902Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:47:57.599Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:47:57.599Z] The best model improves the baseline by 14.52%. [2025-06-19T11:47:57.955Z] Top recommended movies for user id 72: [2025-06-19T11:47:57.955Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:47:57.955Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:47:57.955Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:47:57.955Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:47:57.955Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:47:57.955Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (42793.839 ms) ====== [2025-06-19T11:47:57.955Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-19T11:47:57.955Z] GC before operation: completed in 99.331 ms, heap usage 275.622 MB -> 93.572 MB. [2025-06-19T11:48:05.061Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T11:48:10.818Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T11:48:17.966Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T11:48:25.072Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T11:48:27.939Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T11:48:31.601Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T11:48:36.234Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T11:48:39.119Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T11:48:39.799Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-19T11:48:39.799Z] The best model improves the baseline by 14.52%. [2025-06-19T11:48:39.799Z] Top recommended movies for user id 72: [2025-06-19T11:48:39.799Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T11:48:39.799Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T11:48:39.799Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T11:48:39.799Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T11:48:39.799Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T11:48:39.799Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (41958.130 ms) ====== [2025-06-19T11:48:40.485Z] ----------------------------------- [2025-06-19T11:48:40.485Z] renaissance-movie-lens_0_PASSED [2025-06-19T11:48:40.485Z] ----------------------------------- [2025-06-19T11:48:41.152Z] [2025-06-19T11:48:41.152Z] TEST TEARDOWN: [2025-06-19T11:48:41.152Z] Nothing to be done for teardown. [2025-06-19T11:48:41.152Z] renaissance-movie-lens_0 Finish Time: Thu Jun 19 11:48:41 2025 Epoch Time (ms): 1750333721001