[2025-06-12T04:51:40.480Z] Running test renaissance-movie-lens_0 ... [2025-06-12T04:51:40.480Z] =============================================== [2025-06-12T04:51:40.480Z] renaissance-movie-lens_0 Start Time: Thu Jun 12 04:51:40 2025 Epoch Time (ms): 1749703900378 [2025-06-12T04:51:40.480Z] variation: NoOptions [2025-06-12T04:51:40.480Z] JVM_OPTIONS: [2025-06-12T04:51:40.480Z] { \ [2025-06-12T04:51:40.480Z] echo ""; echo "TEST SETUP:"; \ [2025-06-12T04:51:40.480Z] echo "Nothing to be done for setup."; \ [2025-06-12T04:51:40.480Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17497039005216/renaissance-movie-lens_0"; \ [2025-06-12T04:51:40.480Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17497039005216/renaissance-movie-lens_0"; \ [2025-06-12T04:51:40.480Z] echo ""; echo "TESTING:"; \ [2025-06-12T04:51:40.481Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/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 "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17497039005216/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-12T04:51:40.481Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17497039005216/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-12T04:51:40.481Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-12T04:51:40.481Z] echo "Nothing to be done for teardown."; \ [2025-06-12T04:51:40.481Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17497039005216/TestTargetResult"; [2025-06-12T04:51:40.481Z] [2025-06-12T04:51:40.481Z] TEST SETUP: [2025-06-12T04:51:40.481Z] Nothing to be done for setup. [2025-06-12T04:51:40.481Z] [2025-06-12T04:51:40.481Z] TESTING: [2025-06-12T04:51:49.712Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-06-12T04:52:00.148Z] 04:51:59.919 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. [2025-06-12T04:52:07.119Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-12T04:52:07.119Z] Training: 60056, validation: 20285, test: 19854 [2025-06-12T04:52:07.119Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-12T04:52:07.767Z] GC before operation: completed in 359.477 ms, heap usage 174.081 MB -> 75.849 MB. [2025-06-12T04:52:21.725Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:52:35.379Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:52:44.654Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:52:50.986Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:52:56.643Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:53:01.844Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T04:53:05.906Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T04:53:10.136Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T04:53:11.506Z] 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. [2025-06-12T04:53:11.506Z] The best model improves the baseline by 14.34%. [2025-06-12T04:53:12.189Z] Top recommended movies for user id 72: [2025-06-12T04:53:12.189Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T04:53:12.189Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T04:53:12.189Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T04:53:12.189Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T04:53:12.189Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T04:53:12.189Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (64126.008 ms) ====== [2025-06-12T04:53:12.189Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-12T04:53:12.189Z] GC before operation: completed in 329.031 ms, heap usage 241.950 MB -> 90.128 MB. [2025-06-12T04:53:20.291Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:53:24.195Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:53:30.531Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:53:35.540Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:53:38.711Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:53:42.762Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T04:53:46.749Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T04:53:50.870Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T04:53:51.546Z] 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. [2025-06-12T04:53:51.546Z] The best model improves the baseline by 14.34%. [2025-06-12T04:53:52.282Z] Top recommended movies for user id 72: [2025-06-12T04:53:52.282Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T04:53:52.282Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T04:53:52.282Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T04:53:52.282Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T04:53:52.282Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T04:53:52.282Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (39959.835 ms) ====== [2025-06-12T04:53:52.282Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-12T04:53:52.282Z] GC before operation: completed in 431.044 ms, heap usage 309.951 MB -> 88.112 MB. [2025-06-12T04:53:59.982Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:54:06.188Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:54:12.481Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:54:19.104Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:54:22.126Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:54:26.376Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T04:54:29.638Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T04:54:33.668Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T04:54:33.668Z] 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. [2025-06-12T04:54:33.668Z] The best model improves the baseline by 14.34%. [2025-06-12T04:54:34.366Z] Top recommended movies for user id 72: [2025-06-12T04:54:34.366Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T04:54:34.366Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T04:54:34.366Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T04:54:34.366Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T04:54:34.366Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T04:54:34.366Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (41437.135 ms) ====== [2025-06-12T04:54:34.366Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-12T04:54:34.366Z] GC before operation: completed in 287.606 ms, heap usage 108.406 MB -> 88.779 MB. [2025-06-12T04:54:42.239Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:54:48.776Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:54:55.042Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:55:00.430Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:55:03.598Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:55:06.787Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T04:55:10.994Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T04:55:14.997Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T04:55:14.997Z] 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. [2025-06-12T04:55:14.997Z] The best model improves the baseline by 14.34%. [2025-06-12T04:55:15.750Z] Top recommended movies for user id 72: [2025-06-12T04:55:15.750Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T04:55:15.750Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T04:55:15.750Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T04:55:15.750Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T04:55:15.750Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T04:55:15.750Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (41235.903 ms) ====== [2025-06-12T04:55:15.750Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-12T04:55:16.405Z] GC before operation: completed in 681.465 ms, heap usage 141.713 MB -> 88.836 MB. [2025-06-12T04:55:24.208Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:55:30.746Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:55:35.845Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:55:40.906Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:55:46.107Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:55:49.295Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T04:55:53.360Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T04:55:56.430Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T04:55:56.430Z] 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. [2025-06-12T04:55:56.430Z] The best model improves the baseline by 14.34%. [2025-06-12T04:55:57.122Z] Top recommended movies for user id 72: [2025-06-12T04:55:57.122Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T04:55:57.122Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T04:55:57.122Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T04:55:57.122Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T04:55:57.122Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T04:55:57.122Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (40722.163 ms) ====== [2025-06-12T04:55:57.122Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-12T04:55:57.122Z] GC before operation: completed in 309.832 ms, heap usage 141.172 MB -> 89.120 MB. [2025-06-12T04:56:02.149Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:56:08.673Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:56:23.141Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:56:31.286Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:56:35.942Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:56:40.033Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T04:56:44.285Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T04:56:47.368Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T04:56:48.058Z] 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. [2025-06-12T04:56:48.058Z] The best model improves the baseline by 14.34%. [2025-06-12T04:56:48.058Z] Top recommended movies for user id 72: [2025-06-12T04:56:48.058Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T04:56:48.058Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T04:56:48.058Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T04:56:48.058Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T04:56:48.058Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T04:56:48.058Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (50826.689 ms) ====== [2025-06-12T04:56:48.058Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-12T04:56:48.058Z] GC before operation: completed in 270.113 ms, heap usage 171.799 MB -> 89.119 MB. [2025-06-12T04:56:53.356Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:56:59.632Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:57:06.561Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:57:12.543Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:57:15.615Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:57:17.802Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T04:57:21.778Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T04:57:24.866Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T04:57:24.866Z] 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. [2025-06-12T04:57:24.866Z] The best model improves the baseline by 14.34%. [2025-06-12T04:57:25.542Z] Top recommended movies for user id 72: [2025-06-12T04:57:25.542Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T04:57:25.542Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T04:57:25.542Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T04:57:25.542Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T04:57:25.542Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T04:57:25.542Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (37028.979 ms) ====== [2025-06-12T04:57:25.542Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-12T04:57:25.542Z] GC before operation: completed in 328.458 ms, heap usage 177.142 MB -> 88.987 MB. [2025-06-12T04:57:31.922Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:57:37.034Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:57:43.306Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:57:47.545Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:57:50.580Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:57:55.888Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T04:57:58.929Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T04:58:02.927Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T04:58:02.927Z] 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. [2025-06-12T04:58:02.927Z] The best model improves the baseline by 14.34%. [2025-06-12T04:58:03.617Z] Top recommended movies for user id 72: [2025-06-12T04:58:03.617Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T04:58:03.617Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T04:58:03.617Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T04:58:03.617Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T04:58:03.617Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T04:58:03.617Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (37612.321 ms) ====== [2025-06-12T04:58:03.617Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-12T04:58:03.617Z] GC before operation: completed in 269.087 ms, heap usage 214.340 MB -> 91.129 MB. [2025-06-12T04:58:08.643Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:58:13.906Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:58:20.227Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:58:24.348Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:58:27.394Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:58:32.918Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T04:58:36.047Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T04:58:39.190Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T04:58:39.878Z] 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. [2025-06-12T04:58:39.878Z] The best model improves the baseline by 14.34%. [2025-06-12T04:58:39.878Z] Top recommended movies for user id 72: [2025-06-12T04:58:39.878Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T04:58:39.878Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T04:58:39.878Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T04:58:39.878Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T04:58:39.878Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T04:58:39.878Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (36357.273 ms) ====== [2025-06-12T04:58:39.878Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-12T04:58:41.067Z] GC before operation: completed in 249.247 ms, heap usage 361.533 MB -> 89.409 MB. [2025-06-12T04:58:46.472Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:58:52.793Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:58:59.313Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:59:05.621Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:59:08.759Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:59:11.931Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T04:59:17.199Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T04:59:20.278Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T04:59:20.278Z] 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. [2025-06-12T04:59:20.278Z] The best model improves the baseline by 14.34%. [2025-06-12T04:59:20.932Z] Top recommended movies for user id 72: [2025-06-12T04:59:20.932Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T04:59:20.932Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T04:59:20.932Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T04:59:20.932Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T04:59:20.932Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T04:59:20.932Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (40515.787 ms) ====== [2025-06-12T04:59:20.932Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-12T04:59:20.932Z] GC before operation: completed in 173.319 ms, heap usage 109.935 MB -> 89.535 MB. [2025-06-12T04:59:27.521Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T04:59:36.400Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T04:59:42.686Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T04:59:49.305Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T04:59:54.747Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T04:59:59.899Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T05:00:05.282Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T05:00:07.497Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T05:00:08.155Z] 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. [2025-06-12T05:00:08.155Z] The best model improves the baseline by 14.34%. [2025-06-12T05:00:08.155Z] Top recommended movies for user id 72: [2025-06-12T05:00:08.155Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T05:00:08.155Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T05:00:08.155Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T05:00:08.155Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T05:00:08.155Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T05:00:08.155Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (47535.329 ms) ====== [2025-06-12T05:00:08.155Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-12T05:00:08.824Z] GC before operation: completed in 180.211 ms, heap usage 221.874 MB -> 89.088 MB. [2025-06-12T05:00:14.081Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T05:00:19.718Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T05:00:23.698Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T05:00:30.170Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T05:00:33.290Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T05:00:36.354Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T05:00:40.332Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T05:00:43.602Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T05:00:44.265Z] 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. [2025-06-12T05:00:44.265Z] The best model improves the baseline by 14.34%. [2025-06-12T05:00:44.265Z] Top recommended movies for user id 72: [2025-06-12T05:00:44.265Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T05:00:44.265Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T05:00:44.265Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T05:00:44.265Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T05:00:44.265Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T05:00:44.265Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (35939.398 ms) ====== [2025-06-12T05:00:44.265Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-12T05:00:45.034Z] GC before operation: completed in 257.356 ms, heap usage 222.091 MB -> 91.568 MB. [2025-06-12T05:00:50.168Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T05:00:56.588Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T05:01:02.950Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T05:01:08.296Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T05:01:11.357Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T05:01:13.484Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T05:01:18.647Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T05:01:24.076Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T05:01:24.076Z] 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. [2025-06-12T05:01:24.750Z] The best model improves the baseline by 14.34%. [2025-06-12T05:01:24.750Z] Top recommended movies for user id 72: [2025-06-12T05:01:24.750Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T05:01:24.750Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T05:01:24.750Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T05:01:24.750Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T05:01:24.750Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T05:01:24.750Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (40170.489 ms) ====== [2025-06-12T05:01:24.750Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-12T05:01:25.401Z] GC before operation: completed in 291.869 ms, heap usage 207.824 MB -> 89.375 MB. [2025-06-12T05:01:31.661Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T05:01:38.159Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T05:01:44.684Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T05:01:48.675Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T05:01:53.353Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T05:01:56.548Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T05:01:59.819Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T05:02:03.242Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T05:02:03.891Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-12T05:02:04.572Z] The best model improves the baseline by 14.34%. [2025-06-12T05:02:04.572Z] Top recommended movies for user id 72: [2025-06-12T05:02:04.572Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T05:02:04.572Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T05:02:04.572Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T05:02:04.572Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T05:02:04.572Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T05:02:04.572Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (39337.168 ms) ====== [2025-06-12T05:02:04.572Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-12T05:02:05.278Z] GC before operation: completed in 501.747 ms, heap usage 238.403 MB -> 89.282 MB. [2025-06-12T05:02:11.608Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T05:02:17.845Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T05:02:24.082Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T05:02:30.403Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T05:02:33.481Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T05:02:39.126Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T05:02:41.341Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T05:02:44.569Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T05:02:45.296Z] 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. [2025-06-12T05:02:45.296Z] The best model improves the baseline by 14.34%. [2025-06-12T05:02:45.980Z] Top recommended movies for user id 72: [2025-06-12T05:02:45.980Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T05:02:45.980Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T05:02:45.980Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T05:02:45.980Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T05:02:45.980Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T05:02:45.980Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (40875.737 ms) ====== [2025-06-12T05:02:45.980Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-12T05:02:45.980Z] GC before operation: completed in 240.483 ms, heap usage 181.399 MB -> 91.693 MB. [2025-06-12T05:02:52.589Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T05:02:58.914Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T05:03:04.024Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T05:03:09.208Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T05:03:12.316Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T05:03:15.632Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T05:03:19.742Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T05:03:22.980Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T05:03:23.744Z] 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. [2025-06-12T05:03:23.744Z] The best model improves the baseline by 14.34%. [2025-06-12T05:03:24.985Z] Top recommended movies for user id 72: [2025-06-12T05:03:24.985Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T05:03:24.985Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T05:03:24.985Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T05:03:24.985Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T05:03:24.985Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T05:03:24.985Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (38010.951 ms) ====== [2025-06-12T05:03:24.985Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-12T05:03:24.985Z] GC before operation: completed in 388.120 ms, heap usage 144.375 MB -> 89.201 MB. [2025-06-12T05:03:30.326Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T05:03:35.502Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T05:03:42.002Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T05:03:47.197Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T05:03:50.313Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T05:03:53.368Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T05:03:57.550Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T05:04:01.518Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T05:04:02.249Z] 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. [2025-06-12T05:04:02.249Z] The best model improves the baseline by 14.34%. [2025-06-12T05:04:02.939Z] Top recommended movies for user id 72: [2025-06-12T05:04:02.939Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T05:04:02.939Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T05:04:02.939Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T05:04:02.939Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T05:04:02.940Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T05:04:02.940Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (38114.274 ms) ====== [2025-06-12T05:04:02.940Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-12T05:04:02.940Z] GC before operation: completed in 324.565 ms, heap usage 212.277 MB -> 89.384 MB. [2025-06-12T05:04:08.132Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T05:04:13.730Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T05:04:19.002Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T05:04:24.093Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T05:04:28.259Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T05:04:31.237Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T05:04:33.462Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T05:04:36.534Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T05:04:37.278Z] 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. [2025-06-12T05:04:37.278Z] The best model improves the baseline by 14.34%. [2025-06-12T05:04:37.278Z] Top recommended movies for user id 72: [2025-06-12T05:04:37.279Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T05:04:37.279Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T05:04:37.279Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T05:04:37.279Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T05:04:37.279Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T05:04:37.279Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (34241.102 ms) ====== [2025-06-12T05:04:37.279Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-12T05:04:37.935Z] GC before operation: completed in 355.915 ms, heap usage 219.483 MB -> 89.291 MB. [2025-06-12T05:04:44.170Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T05:04:49.317Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T05:04:57.108Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T05:05:02.734Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T05:05:05.919Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T05:05:08.329Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T05:05:12.519Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T05:05:15.717Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T05:05:16.389Z] 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. [2025-06-12T05:05:16.389Z] The best model improves the baseline by 14.34%. [2025-06-12T05:05:17.073Z] Top recommended movies for user id 72: [2025-06-12T05:05:17.073Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T05:05:17.073Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T05:05:17.073Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T05:05:17.073Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T05:05:17.073Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T05:05:17.073Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (39052.657 ms) ====== [2025-06-12T05:05:17.073Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-12T05:05:17.073Z] GC before operation: completed in 245.644 ms, heap usage 223.357 MB -> 89.323 MB. [2025-06-12T05:05:22.144Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-12T05:05:27.364Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-12T05:05:33.727Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-12T05:05:37.789Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-12T05:05:41.734Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-12T05:05:44.533Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-12T05:05:48.488Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-12T05:05:51.591Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-12T05:05:52.291Z] 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. [2025-06-12T05:05:52.291Z] The best model improves the baseline by 14.34%. [2025-06-12T05:05:52.291Z] Top recommended movies for user id 72: [2025-06-12T05:05:52.291Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-12T05:05:52.291Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-12T05:05:52.291Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-12T05:05:52.291Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-12T05:05:52.291Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-12T05:05:52.291Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (35444.869 ms) ====== [2025-06-12T05:05:52.934Z] ----------------------------------- [2025-06-12T05:05:52.934Z] renaissance-movie-lens_0_PASSED [2025-06-12T05:05:52.934Z] ----------------------------------- [2025-06-12T05:05:52.934Z] [2025-06-12T05:05:52.934Z] TEST TEARDOWN: [2025-06-12T05:05:52.934Z] Nothing to be done for teardown. [2025-06-12T05:05:52.934Z] renaissance-movie-lens_0 Finish Time: Thu Jun 12 05:05:52 2025 Epoch Time (ms): 1749704752580