[2025-12-04T02:26:23.561Z] Running test renaissance-movie-lens_0 ... [2025-12-04T02:26:23.561Z] =============================================== [2025-12-04T02:26:23.561Z] renaissance-movie-lens_0 Start Time: Thu Dec 4 02:26:22 2025 Epoch Time (ms): 1764815182413 [2025-12-04T02:26:23.561Z] variation: NoOptions [2025-12-04T02:26:23.561Z] JVM_OPTIONS: [2025-12-04T02:26:23.561Z] { \ [2025-12-04T02:26:23.561Z] echo ""; echo "TEST SETUP:"; \ [2025-12-04T02:26:23.561Z] echo "Nothing to be done for setup."; \ [2025-12-04T02:26:23.561Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17648129404803/renaissance-movie-lens_0"; \ [2025-12-04T02:26:23.561Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17648129404803/renaissance-movie-lens_0"; \ [2025-12-04T02:26:23.561Z] echo ""; echo "TESTING:"; \ [2025-12-04T02:26:23.561Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/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_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17648129404803/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-04T02:26:23.561Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17648129404803/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-04T02:26:23.561Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-04T02:26:23.561Z] echo "Nothing to be done for teardown."; \ [2025-12-04T02:26:23.561Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17648129404803/TestTargetResult"; [2025-12-04T02:26:23.561Z] [2025-12-04T02:26:23.561Z] TEST SETUP: [2025-12-04T02:26:23.561Z] Nothing to be done for setup. [2025-12-04T02:26:23.561Z] [2025-12-04T02:26:23.561Z] TESTING: [2025-12-04T02:26:32.477Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-04T02:26:46.097Z] 02:26:45.923 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. [2025-12-04T02:26:51.573Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-04T02:26:52.555Z] Training: 60056, validation: 20285, test: 19854 [2025-12-04T02:26:52.555Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-04T02:26:52.555Z] GC before operation: completed in 256.715 ms, heap usage 233.907 MB -> 75.780 MB. [2025-12-04T02:27:07.100Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:27:15.408Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:27:23.726Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:27:30.593Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:27:34.415Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:27:37.486Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:27:40.570Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:27:43.631Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:27:44.596Z] 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. [2025-12-04T02:27:44.596Z] The best model improves the baseline by 14.52%. [2025-12-04T02:27:44.596Z] Top recommended movies for user id 72: [2025-12-04T02:27:44.596Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:27:44.596Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:27:44.596Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:27:44.596Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:27:44.596Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:27:44.596Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (52040.232 ms) ====== [2025-12-04T02:27:44.596Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-04T02:27:45.557Z] GC before operation: completed in 251.265 ms, heap usage 242.936 MB -> 88.212 MB. [2025-12-04T02:27:49.741Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:27:55.190Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:27:59.384Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:28:03.574Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:28:06.766Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:28:08.758Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:28:11.819Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:28:13.798Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:28:13.798Z] 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. [2025-12-04T02:28:13.798Z] The best model improves the baseline by 14.52%. [2025-12-04T02:28:14.761Z] Top recommended movies for user id 72: [2025-12-04T02:28:14.761Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:28:14.761Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:28:14.761Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:28:14.761Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:28:14.761Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:28:14.761Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (29328.791 ms) ====== [2025-12-04T02:28:14.761Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-04T02:28:14.761Z] GC before operation: completed in 176.500 ms, heap usage 519.605 MB -> 89.021 MB. [2025-12-04T02:28:19.032Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:28:23.746Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:28:27.312Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:28:31.516Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:28:33.487Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:28:36.524Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:28:38.494Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:28:40.471Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:28:41.430Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T02:28:41.430Z] The best model improves the baseline by 14.52%. [2025-12-04T02:28:41.430Z] Top recommended movies for user id 72: [2025-12-04T02:28:41.430Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:28:41.430Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:28:41.430Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:28:41.430Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:28:41.430Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:28:41.430Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (26800.094 ms) ====== [2025-12-04T02:28:41.430Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-04T02:28:41.430Z] GC before operation: completed in 181.418 ms, heap usage 198.357 MB -> 89.210 MB. [2025-12-04T02:28:45.630Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:28:49.848Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:28:52.930Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:28:57.203Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:28:59.198Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:29:02.261Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:29:04.234Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:29:06.278Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:29:06.278Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T02:29:07.264Z] The best model improves the baseline by 14.52%. [2025-12-04T02:29:07.264Z] Top recommended movies for user id 72: [2025-12-04T02:29:07.264Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:29:07.264Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:29:07.264Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:29:07.264Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:29:07.264Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:29:07.264Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (25491.827 ms) ====== [2025-12-04T02:29:07.264Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-04T02:29:07.264Z] GC before operation: completed in 183.401 ms, heap usage 184.777 MB -> 89.427 MB. [2025-12-04T02:29:11.638Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:29:16.572Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:29:19.006Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:29:23.190Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:29:25.166Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:29:27.144Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:29:30.192Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:29:32.170Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:29:33.129Z] 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. [2025-12-04T02:29:33.129Z] The best model improves the baseline by 14.52%. [2025-12-04T02:29:33.129Z] Top recommended movies for user id 72: [2025-12-04T02:29:33.129Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:29:33.129Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:29:33.129Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:29:33.129Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:29:33.129Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:29:33.129Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (25874.205 ms) ====== [2025-12-04T02:29:33.129Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-04T02:29:33.129Z] GC before operation: completed in 189.478 ms, heap usage 627.865 MB -> 93.213 MB. [2025-12-04T02:29:38.571Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:29:41.618Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:29:45.805Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:29:48.851Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:29:51.903Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:29:53.879Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:29:56.941Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:29:58.912Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:29:58.912Z] 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. [2025-12-04T02:29:58.912Z] The best model improves the baseline by 14.52%. [2025-12-04T02:29:59.870Z] Top recommended movies for user id 72: [2025-12-04T02:29:59.870Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:29:59.870Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:29:59.870Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:29:59.870Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:29:59.870Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:29:59.870Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (26238.522 ms) ====== [2025-12-04T02:29:59.870Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-04T02:29:59.870Z] GC before operation: completed in 182.740 ms, heap usage 198.888 MB -> 95.500 MB. [2025-12-04T02:30:04.229Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:30:08.102Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:30:14.915Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:30:15.874Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:30:17.867Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:30:19.838Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:30:22.887Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:30:26.554Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:30:26.554Z] 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. [2025-12-04T02:30:26.554Z] The best model improves the baseline by 14.52%. [2025-12-04T02:30:26.554Z] Top recommended movies for user id 72: [2025-12-04T02:30:26.554Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:30:26.554Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:30:26.554Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:30:26.554Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:30:26.554Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:30:26.554Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (25870.248 ms) ====== [2025-12-04T02:30:26.554Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-04T02:30:26.554Z] GC before operation: completed in 181.206 ms, heap usage 861.602 MB -> 94.069 MB. [2025-12-04T02:30:30.781Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:30:35.009Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:30:39.218Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:30:42.270Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:30:45.314Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:30:47.284Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:30:49.254Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:30:52.302Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:30:52.302Z] 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. [2025-12-04T02:30:52.302Z] The best model improves the baseline by 14.52%. [2025-12-04T02:30:52.302Z] Top recommended movies for user id 72: [2025-12-04T02:30:52.302Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:30:52.302Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:30:52.302Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:30:52.302Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:30:52.302Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:30:52.302Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (26662.915 ms) ====== [2025-12-04T02:30:52.302Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-04T02:30:52.302Z] GC before operation: completed in 190.530 ms, heap usage 233.079 MB -> 93.246 MB. [2025-12-04T02:30:56.509Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:31:00.695Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:31:03.755Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:31:07.536Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:31:09.528Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:31:11.508Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:31:15.169Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:31:16.136Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:31:17.100Z] 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. [2025-12-04T02:31:17.100Z] The best model improves the baseline by 14.52%. [2025-12-04T02:31:17.100Z] Top recommended movies for user id 72: [2025-12-04T02:31:17.100Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:31:17.100Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:31:17.100Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:31:17.100Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:31:17.100Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:31:17.100Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (24485.205 ms) ====== [2025-12-04T02:31:17.100Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-04T02:31:17.100Z] GC before operation: completed in 186.858 ms, heap usage 453.401 MB -> 93.626 MB. [2025-12-04T02:31:21.286Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:31:24.362Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:31:28.591Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:31:32.785Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:31:34.777Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:31:36.758Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:31:39.809Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:31:41.786Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:31:41.786Z] 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. [2025-12-04T02:31:41.786Z] The best model improves the baseline by 14.52%. [2025-12-04T02:31:42.766Z] Top recommended movies for user id 72: [2025-12-04T02:31:42.766Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:31:42.766Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:31:42.766Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:31:42.766Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:31:42.766Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:31:42.766Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (25040.281 ms) ====== [2025-12-04T02:31:42.766Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-04T02:31:42.766Z] GC before operation: completed in 177.095 ms, heap usage 169.268 MB -> 91.225 MB. [2025-12-04T02:31:48.214Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:31:52.429Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:31:56.693Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:32:00.615Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:32:02.912Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:32:03.889Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:32:09.597Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:32:09.597Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:32:09.597Z] 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. [2025-12-04T02:32:09.597Z] The best model improves the baseline by 14.52%. [2025-12-04T02:32:09.597Z] Top recommended movies for user id 72: [2025-12-04T02:32:09.597Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:32:09.597Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:32:09.597Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:32:09.597Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:32:09.597Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:32:09.597Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (27034.669 ms) ====== [2025-12-04T02:32:09.597Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-04T02:32:09.597Z] GC before operation: completed in 191.222 ms, heap usage 530.969 MB -> 95.882 MB. [2025-12-04T02:32:15.886Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:32:17.877Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:32:22.063Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:32:25.641Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:32:27.642Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:32:29.766Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:32:38.799Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:32:38.799Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:32:38.799Z] 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. [2025-12-04T02:32:38.799Z] The best model improves the baseline by 14.52%. [2025-12-04T02:32:38.799Z] Top recommended movies for user id 72: [2025-12-04T02:32:38.799Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:32:38.799Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:32:38.799Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:32:38.799Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:32:38.799Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:32:38.799Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (25784.018 ms) ====== [2025-12-04T02:32:38.799Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-04T02:32:38.799Z] GC before operation: completed in 181.533 ms, heap usage 518.403 MB -> 94.101 MB. [2025-12-04T02:32:39.779Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:32:44.188Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:32:47.312Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:32:51.501Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:32:55.444Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:32:56.415Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:33:00.960Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:33:00.960Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:33:00.960Z] 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. [2025-12-04T02:33:00.960Z] The best model improves the baseline by 14.52%. [2025-12-04T02:33:00.960Z] Top recommended movies for user id 72: [2025-12-04T02:33:00.960Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:33:00.960Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:33:00.960Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:33:00.960Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:33:00.960Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:33:00.960Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (25532.259 ms) ====== [2025-12-04T02:33:00.960Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-04T02:33:01.923Z] GC before operation: completed in 181.760 ms, heap usage 722.070 MB -> 96.460 MB. [2025-12-04T02:33:05.797Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:33:13.641Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:33:17.145Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:33:17.145Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:33:20.193Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:33:22.172Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:33:25.780Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:33:26.771Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:33:27.734Z] 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. [2025-12-04T02:33:27.734Z] The best model improves the baseline by 14.52%. [2025-12-04T02:33:27.734Z] Top recommended movies for user id 72: [2025-12-04T02:33:27.734Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:33:27.734Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:33:27.734Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:33:27.734Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:33:27.734Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:33:27.734Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (26252.401 ms) ====== [2025-12-04T02:33:27.734Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-04T02:33:27.734Z] GC before operation: completed in 182.519 ms, heap usage 157.229 MB -> 93.079 MB. [2025-12-04T02:33:37.229Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:33:38.191Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:33:40.172Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:33:43.539Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:33:47.188Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:33:48.152Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:33:51.220Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:33:58.634Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:33:58.634Z] 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. [2025-12-04T02:33:58.634Z] The best model improves the baseline by 14.52%. [2025-12-04T02:33:58.634Z] Top recommended movies for user id 72: [2025-12-04T02:33:58.634Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:33:58.634Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:33:58.634Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:33:58.634Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:33:58.634Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:33:58.634Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (25821.374 ms) ====== [2025-12-04T02:33:58.634Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-04T02:33:58.634Z] GC before operation: completed in 179.841 ms, heap usage 460.597 MB -> 92.897 MB. [2025-12-04T02:33:58.634Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:34:06.370Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:34:06.370Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:34:10.027Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:34:16.693Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:34:16.693Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:34:16.693Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:34:20.378Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:34:21.346Z] 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. [2025-12-04T02:34:21.346Z] The best model improves the baseline by 14.52%. [2025-12-04T02:34:21.346Z] Top recommended movies for user id 72: [2025-12-04T02:34:21.346Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:34:21.346Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:34:21.346Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:34:21.346Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:34:21.346Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:34:21.346Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (24669.161 ms) ====== [2025-12-04T02:34:21.346Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-04T02:34:21.346Z] GC before operation: completed in 180.675 ms, heap usage 376.639 MB -> 93.769 MB. [2025-12-04T02:34:27.334Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:34:27.334Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:34:29.317Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:34:34.987Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:34:34.987Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:34:36.969Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:34:41.267Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:34:41.268Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:34:41.268Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-04T02:34:41.268Z] The best model improves the baseline by 14.52%. [2025-12-04T02:34:41.268Z] Top recommended movies for user id 72: [2025-12-04T02:34:41.268Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:34:41.268Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:34:41.268Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:34:41.268Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:34:41.268Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:34:41.268Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (22896.013 ms) ====== [2025-12-04T02:34:41.268Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-04T02:34:44.781Z] GC before operation: completed in 176.808 ms, heap usage 113.814 MB -> 89.999 MB. [2025-12-04T02:34:45.745Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:34:49.126Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:34:55.230Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:34:58.780Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:34:58.780Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:34:59.744Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:35:16.550Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:35:16.550Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:35:16.550Z] 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. [2025-12-04T02:35:16.550Z] The best model improves the baseline by 14.52%. [2025-12-04T02:35:16.550Z] Top recommended movies for user id 72: [2025-12-04T02:35:16.550Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:35:16.550Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:35:16.550Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:35:16.550Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:35:16.550Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:35:16.550Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (23251.222 ms) ====== [2025-12-04T02:35:16.550Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-04T02:35:16.550Z] GC before operation: completed in 189.166 ms, heap usage 916.382 MB -> 94.554 MB. [2025-12-04T02:35:16.550Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:35:16.550Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:35:20.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:35:20.199Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:35:27.281Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:35:27.281Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:35:28.255Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:35:29.224Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:35:29.224Z] 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. [2025-12-04T02:35:29.224Z] The best model improves the baseline by 14.52%. [2025-12-04T02:35:29.224Z] Top recommended movies for user id 72: [2025-12-04T02:35:29.224Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:35:29.224Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:35:29.224Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:35:29.224Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:35:29.224Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:35:29.224Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (24202.473 ms) ====== [2025-12-04T02:35:29.224Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-04T02:35:29.224Z] GC before operation: completed in 184.973 ms, heap usage 707.777 MB -> 94.128 MB. [2025-12-04T02:35:37.486Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-04T02:35:44.016Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-04T02:35:44.016Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-04T02:35:49.999Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-04T02:35:49.999Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-04T02:35:49.999Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-04T02:36:02.150Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-04T02:36:02.150Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-04T02:36:02.150Z] 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. [2025-12-04T02:36:02.150Z] The best model improves the baseline by 14.52%. [2025-12-04T02:36:02.150Z] Top recommended movies for user id 72: [2025-12-04T02:36:02.150Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-04T02:36:02.150Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-04T02:36:02.150Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-04T02:36:02.150Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-04T02:36:02.150Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-04T02:36:02.150Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (25018.291 ms) ====== [2025-12-04T02:36:02.150Z] ----------------------------------- [2025-12-04T02:36:02.150Z] renaissance-movie-lens_0_PASSED [2025-12-04T02:36:02.150Z] ----------------------------------- [2025-12-04T02:36:02.150Z] [2025-12-04T02:36:02.150Z] TEST TEARDOWN: [2025-12-04T02:36:02.150Z] Nothing to be done for teardown. [2025-12-04T02:36:02.150Z] renaissance-movie-lens_0 Finish Time: Thu Dec 4 02:35:55 2025 Epoch Time (ms): 1764815755739