[2025-11-26T23:06:27.320Z] Running test renaissance-movie-lens_0 ... [2025-11-26T23:06:27.320Z] =============================================== [2025-11-26T23:06:27.320Z] renaissance-movie-lens_0 Start Time: Wed Nov 26 23:06:26 2025 Epoch Time (ms): 1764198386214 [2025-11-26T23:06:27.320Z] variation: NoOptions [2025-11-26T23:06:27.320Z] JVM_OPTIONS: [2025-11-26T23:06:27.320Z] { \ [2025-11-26T23:06:27.320Z] echo ""; echo "TEST SETUP:"; \ [2025-11-26T23:06:27.320Z] echo "Nothing to be done for setup."; \ [2025-11-26T23:06:27.320Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17641969269689/renaissance-movie-lens_0"; \ [2025-11-26T23:06:27.320Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17641969269689/renaissance-movie-lens_0"; \ [2025-11-26T23:06:27.320Z] echo ""; echo "TESTING:"; \ [2025-11-26T23:06:27.320Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_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_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17641969269689/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-11-26T23:06:27.320Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17641969269689/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-11-26T23:06:27.320Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-11-26T23:06:27.320Z] echo "Nothing to be done for teardown."; \ [2025-11-26T23:06:27.320Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17641969269689/TestTargetResult"; [2025-11-26T23:06:27.320Z] [2025-11-26T23:06:27.320Z] TEST SETUP: [2025-11-26T23:06:27.320Z] Nothing to be done for setup. [2025-11-26T23:06:27.320Z] [2025-11-26T23:06:27.320Z] TESTING: [2025-11-26T23:06:31.469Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-11-26T23:06:39.628Z] 23:06:38.126 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-11-26T23:06:40.588Z] Got 100004 ratings from 671 users on 9066 movies. [2025-11-26T23:06:41.560Z] Training: 60056, validation: 20285, test: 19854 [2025-11-26T23:06:41.560Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-11-26T23:06:41.560Z] GC before operation: completed in 162.350 ms, heap usage 263.859 MB -> 75.807 MB. [2025-11-26T23:06:46.931Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:06:51.083Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:06:54.107Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:06:57.128Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:06:59.089Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:07:01.053Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:07:03.226Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:07:04.178Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:07:05.135Z] 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. [2025-11-26T23:07:05.135Z] The best model improves the baseline by 14.52%. [2025-11-26T23:07:05.135Z] Top recommended movies for user id 72: [2025-11-26T23:07:05.135Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:07:05.135Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:07:05.135Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:07:05.135Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:07:05.135Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:07:05.135Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23788.015 ms) ====== [2025-11-26T23:07:05.135Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-11-26T23:07:05.135Z] GC before operation: completed in 158.830 ms, heap usage 152.688 MB -> 87.557 MB. [2025-11-26T23:07:08.154Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:07:11.350Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:07:14.369Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:07:16.329Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:07:18.284Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:07:19.237Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:07:21.192Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:07:23.147Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:07:23.147Z] 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. [2025-11-26T23:07:23.147Z] The best model improves the baseline by 14.52%. [2025-11-26T23:07:23.147Z] Top recommended movies for user id 72: [2025-11-26T23:07:23.147Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:07:23.147Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:07:23.147Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:07:23.147Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:07:23.147Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:07:23.147Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18035.289 ms) ====== [2025-11-26T23:07:23.147Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-11-26T23:07:23.147Z] GC before operation: completed in 143.942 ms, heap usage 104.927 MB -> 88.593 MB. [2025-11-26T23:07:26.172Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:07:29.194Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:07:31.153Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:07:34.172Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:07:35.125Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:07:37.082Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:07:39.040Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:07:39.995Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:07:40.948Z] 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. [2025-11-26T23:07:40.948Z] The best model improves the baseline by 14.52%. [2025-11-26T23:07:40.948Z] Top recommended movies for user id 72: [2025-11-26T23:07:40.948Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:07:40.948Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:07:40.948Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:07:40.948Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:07:40.948Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:07:40.948Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17385.225 ms) ====== [2025-11-26T23:07:40.948Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-11-26T23:07:40.948Z] GC before operation: completed in 150.450 ms, heap usage 149.463 MB -> 89.330 MB. [2025-11-26T23:07:43.966Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:07:45.921Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:07:48.942Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:07:51.965Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:07:52.919Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:07:54.877Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:07:57.904Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:07:57.904Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:07:58.857Z] 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. [2025-11-26T23:07:58.857Z] The best model improves the baseline by 14.52%. [2025-11-26T23:07:58.857Z] Top recommended movies for user id 72: [2025-11-26T23:07:58.857Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:07:58.857Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:07:58.857Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:07:58.857Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:07:58.857Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:07:58.857Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17728.872 ms) ====== [2025-11-26T23:07:58.857Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-11-26T23:07:58.857Z] GC before operation: completed in 136.642 ms, heap usage 291.015 MB -> 89.754 MB. [2025-11-26T23:08:01.881Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:08:03.836Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:08:05.793Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:08:08.828Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:08:09.789Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:08:11.765Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:08:13.738Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:08:14.691Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:08:14.691Z] 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. [2025-11-26T23:08:14.691Z] The best model improves the baseline by 14.52%. [2025-11-26T23:08:15.647Z] Top recommended movies for user id 72: [2025-11-26T23:08:15.647Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:08:15.647Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:08:15.647Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:08:15.647Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:08:15.647Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:08:15.647Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16347.127 ms) ====== [2025-11-26T23:08:15.647Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-11-26T23:08:15.647Z] GC before operation: completed in 137.056 ms, heap usage 343.912 MB -> 89.704 MB. [2025-11-26T23:08:17.604Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:08:20.637Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:08:22.602Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:08:25.628Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:08:26.581Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:08:28.540Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:08:29.497Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:08:31.455Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:08:31.455Z] 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. [2025-11-26T23:08:31.455Z] The best model improves the baseline by 14.52%. [2025-11-26T23:08:31.455Z] Top recommended movies for user id 72: [2025-11-26T23:08:31.455Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:08:31.455Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:08:31.455Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:08:31.455Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:08:31.455Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:08:31.455Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16434.207 ms) ====== [2025-11-26T23:08:31.455Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-11-26T23:08:32.411Z] GC before operation: completed in 148.327 ms, heap usage 363.253 MB -> 90.079 MB. [2025-11-26T23:08:34.368Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:08:37.386Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:08:39.343Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:08:41.302Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:08:43.259Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:08:45.217Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:08:46.172Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:08:48.128Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:08:48.128Z] 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. [2025-11-26T23:08:48.128Z] The best model improves the baseline by 14.52%. [2025-11-26T23:08:48.128Z] Top recommended movies for user id 72: [2025-11-26T23:08:48.128Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:08:48.128Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:08:48.128Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:08:48.128Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:08:48.128Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:08:48.128Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16437.117 ms) ====== [2025-11-26T23:08:48.128Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-11-26T23:08:49.081Z] GC before operation: completed in 211.602 ms, heap usage 107.502 MB -> 89.630 MB. [2025-11-26T23:08:52.083Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:08:53.035Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:08:56.059Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:08:58.013Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:08:59.978Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:09:00.930Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:09:02.888Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:09:04.842Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:09:04.842Z] 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. [2025-11-26T23:09:04.842Z] The best model improves the baseline by 14.52%. [2025-11-26T23:09:04.842Z] Top recommended movies for user id 72: [2025-11-26T23:09:04.842Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:09:04.842Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:09:04.842Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:09:04.842Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:09:04.842Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:09:04.842Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16453.525 ms) ====== [2025-11-26T23:09:04.842Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-11-26T23:09:04.842Z] GC before operation: completed in 162.382 ms, heap usage 139.258 MB -> 89.954 MB. [2025-11-26T23:09:07.865Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:09:09.823Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:09:13.003Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:09:14.955Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:09:16.908Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:09:17.862Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:09:19.823Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:09:20.774Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:09:20.774Z] 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. [2025-11-26T23:09:21.731Z] The best model improves the baseline by 14.52%. [2025-11-26T23:09:21.731Z] Top recommended movies for user id 72: [2025-11-26T23:09:21.731Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:09:21.731Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:09:21.731Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:09:21.731Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:09:21.731Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:09:21.731Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16205.586 ms) ====== [2025-11-26T23:09:21.731Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-11-26T23:09:21.731Z] GC before operation: completed in 149.786 ms, heap usage 199.814 MB -> 89.996 MB. [2025-11-26T23:09:23.688Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:09:26.710Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:09:28.668Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:09:30.624Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:09:31.581Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:09:33.534Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:09:34.486Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:09:35.438Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:09:36.397Z] 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. [2025-11-26T23:09:36.398Z] The best model improves the baseline by 14.52%. [2025-11-26T23:09:36.398Z] Top recommended movies for user id 72: [2025-11-26T23:09:36.398Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:09:36.398Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:09:36.398Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:09:36.398Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:09:36.398Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:09:36.398Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14825.960 ms) ====== [2025-11-26T23:09:36.398Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-11-26T23:09:36.398Z] GC before operation: completed in 131.137 ms, heap usage 430.298 MB -> 90.496 MB. [2025-11-26T23:09:39.426Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:09:41.387Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:09:44.417Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:09:47.128Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:09:48.107Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:09:49.108Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:09:51.089Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:09:52.042Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:09:52.042Z] 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. [2025-11-26T23:09:52.042Z] The best model improves the baseline by 14.52%. [2025-11-26T23:09:53.013Z] Top recommended movies for user id 72: [2025-11-26T23:09:53.013Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:09:53.013Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:09:53.013Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:09:53.013Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:09:53.013Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:09:53.013Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16097.296 ms) ====== [2025-11-26T23:09:53.013Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-11-26T23:09:53.013Z] GC before operation: completed in 135.691 ms, heap usage 181.429 MB -> 89.904 MB. [2025-11-26T23:09:54.971Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:09:57.998Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:09:59.961Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:10:03.050Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:10:04.004Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:10:05.960Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:10:06.914Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:10:08.886Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:10:08.886Z] 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. [2025-11-26T23:10:08.886Z] The best model improves the baseline by 14.52%. [2025-11-26T23:10:08.886Z] Top recommended movies for user id 72: [2025-11-26T23:10:08.886Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:10:08.886Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:10:08.886Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:10:08.886Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:10:08.886Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:10:08.886Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16384.788 ms) ====== [2025-11-26T23:10:08.886Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-11-26T23:10:08.886Z] GC before operation: completed in 143.317 ms, heap usage 122.768 MB -> 90.008 MB. [2025-11-26T23:10:12.013Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:10:13.967Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:10:15.925Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:10:18.961Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:10:19.917Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:10:20.870Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:10:22.827Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:10:23.779Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:10:24.788Z] 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. [2025-11-26T23:10:24.788Z] The best model improves the baseline by 14.52%. [2025-11-26T23:10:24.788Z] Top recommended movies for user id 72: [2025-11-26T23:10:24.788Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:10:24.788Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:10:24.788Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:10:24.788Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:10:24.788Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:10:24.788Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15108.698 ms) ====== [2025-11-26T23:10:24.788Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-11-26T23:10:24.788Z] GC before operation: completed in 149.137 ms, heap usage 481.826 MB -> 90.633 MB. [2025-11-26T23:10:26.750Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:10:29.764Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:10:31.721Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:10:33.683Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:10:34.648Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:10:36.603Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:10:37.554Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:10:39.519Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:10:39.519Z] 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. [2025-11-26T23:10:39.519Z] The best model improves the baseline by 14.52%. [2025-11-26T23:10:39.519Z] Top recommended movies for user id 72: [2025-11-26T23:10:39.519Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:10:39.519Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:10:39.519Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:10:39.519Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:10:39.519Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:10:39.519Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15165.086 ms) ====== [2025-11-26T23:10:39.519Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-11-26T23:10:39.519Z] GC before operation: completed in 162.497 ms, heap usage 370.381 MB -> 90.297 MB. [2025-11-26T23:10:42.355Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:10:47.527Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:10:47.527Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:10:49.479Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:10:50.432Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:10:52.386Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:10:53.339Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:10:55.313Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:10:55.313Z] 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. [2025-11-26T23:10:55.313Z] The best model improves the baseline by 14.52%. [2025-11-26T23:10:55.313Z] Top recommended movies for user id 72: [2025-11-26T23:10:55.313Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:10:55.313Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:10:55.313Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:10:55.313Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:10:55.313Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:10:55.313Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15728.087 ms) ====== [2025-11-26T23:10:55.313Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-11-26T23:10:56.270Z] GC before operation: completed in 138.834 ms, heap usage 365.548 MB -> 90.518 MB. [2025-11-26T23:10:58.224Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:11:02.090Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:11:03.042Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:11:05.006Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:11:06.963Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:11:07.918Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:11:09.889Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:11:10.950Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:11:11.903Z] 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. [2025-11-26T23:11:11.903Z] The best model improves the baseline by 14.52%. [2025-11-26T23:11:11.903Z] Top recommended movies for user id 72: [2025-11-26T23:11:11.903Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:11:11.903Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:11:11.903Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:11:11.903Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:11:11.903Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:11:11.903Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15826.322 ms) ====== [2025-11-26T23:11:11.903Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-11-26T23:11:11.903Z] GC before operation: completed in 137.732 ms, heap usage 99.664 MB -> 89.990 MB. [2025-11-26T23:11:13.863Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:11:15.820Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:11:18.837Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:11:20.791Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:11:21.743Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:11:22.695Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:11:24.654Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:11:25.607Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:11:26.560Z] 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. [2025-11-26T23:11:26.560Z] The best model improves the baseline by 14.52%. [2025-11-26T23:11:26.560Z] Top recommended movies for user id 72: [2025-11-26T23:11:26.560Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:11:26.560Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:11:26.560Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:11:26.560Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:11:26.560Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:11:26.560Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14570.914 ms) ====== [2025-11-26T23:11:26.560Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-11-26T23:11:26.560Z] GC before operation: completed in 144.808 ms, heap usage 425.262 MB -> 90.534 MB. [2025-11-26T23:11:28.581Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:11:30.551Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:11:33.572Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:11:35.528Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:11:36.480Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:11:38.433Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:11:39.389Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:11:41.389Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:11:41.389Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:11:41.389Z] The best model improves the baseline by 14.52%. [2025-11-26T23:11:42.341Z] Top recommended movies for user id 72: [2025-11-26T23:11:42.341Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:11:42.341Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:11:42.341Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:11:42.341Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:11:42.341Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:11:42.341Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15173.534 ms) ====== [2025-11-26T23:11:42.341Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-11-26T23:11:42.341Z] GC before operation: completed in 155.014 ms, heap usage 303.322 MB -> 90.238 MB. [2025-11-26T23:11:44.300Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:11:46.254Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:11:49.292Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:11:51.254Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:11:52.205Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:11:54.161Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:11:55.113Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:11:57.072Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:11:57.072Z] 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. [2025-11-26T23:11:57.072Z] The best model improves the baseline by 14.52%. [2025-11-26T23:11:57.072Z] Top recommended movies for user id 72: [2025-11-26T23:11:57.072Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:11:57.072Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:11:57.072Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:11:57.072Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:11:57.072Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:11:57.072Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15259.668 ms) ====== [2025-11-26T23:11:57.072Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-11-26T23:11:57.072Z] GC before operation: completed in 169.106 ms, heap usage 170.661 MB -> 90.140 MB. [2025-11-26T23:12:00.091Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-11-26T23:12:02.048Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-11-26T23:12:04.012Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-11-26T23:12:05.970Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-11-26T23:12:07.934Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-11-26T23:12:08.899Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-11-26T23:12:09.852Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-11-26T23:12:12.109Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-11-26T23:12:12.110Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-11-26T23:12:12.110Z] The best model improves the baseline by 14.52%. [2025-11-26T23:12:12.110Z] Top recommended movies for user id 72: [2025-11-26T23:12:12.110Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-11-26T23:12:12.110Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-11-26T23:12:12.110Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-11-26T23:12:12.110Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-11-26T23:12:12.110Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-11-26T23:12:12.110Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14863.735 ms) ====== [2025-11-26T23:12:13.062Z] ----------------------------------- [2025-11-26T23:12:13.062Z] renaissance-movie-lens_0_PASSED [2025-11-26T23:12:13.062Z] ----------------------------------- [2025-11-26T23:12:13.062Z] [2025-11-26T23:12:13.062Z] TEST TEARDOWN: [2025-11-26T23:12:13.062Z] Nothing to be done for teardown. [2025-11-26T23:12:13.062Z] renaissance-movie-lens_0 Finish Time: Wed Nov 26 23:12:12 2025 Epoch Time (ms): 1764198732090