[2025-06-11T20:31:37.369Z] Running test renaissance-movie-lens_0 ... [2025-06-11T20:31:37.369Z] =============================================== [2025-06-11T20:31:37.369Z] renaissance-movie-lens_0 Start Time: Wed Jun 11 20:31:36 2025 Epoch Time (ms): 1749673896872 [2025-06-11T20:31:37.369Z] variation: NoOptions [2025-06-11T20:31:37.369Z] JVM_OPTIONS: [2025-06-11T20:31:37.369Z] { \ [2025-06-11T20:31:37.369Z] echo ""; echo "TEST SETUP:"; \ [2025-06-11T20:31:37.369Z] echo "Nothing to be done for setup."; \ [2025-06-11T20:31:37.369Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17496724797197/renaissance-movie-lens_0"; \ [2025-06-11T20:31:37.369Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17496724797197/renaissance-movie-lens_0"; \ [2025-06-11T20:31:37.369Z] echo ""; echo "TESTING:"; \ [2025-06-11T20:31:37.369Z] "/home/jenkins/workspace/Test_openjdk21_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_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17496724797197/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-11T20:31:37.369Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17496724797197/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-11T20:31:37.369Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-11T20:31:37.369Z] echo "Nothing to be done for teardown."; \ [2025-06-11T20:31:37.369Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17496724797197/TestTargetResult"; [2025-06-11T20:31:37.369Z] [2025-06-11T20:31:37.369Z] TEST SETUP: [2025-06-11T20:31:37.369Z] Nothing to be done for setup. [2025-06-11T20:31:37.369Z] [2025-06-11T20:31:37.369Z] TESTING: [2025-06-11T20:31:45.234Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-11T20:31:54.708Z] 20:31:53.882 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-06-11T20:31:57.238Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-11T20:31:57.623Z] Training: 60056, validation: 20285, test: 19854 [2025-06-11T20:31:57.623Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-11T20:31:58.048Z] GC before operation: completed in 164.690 ms, heap usage 181.620 MB -> 76.112 MB. [2025-06-11T20:32:07.648Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:32:12.918Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:32:18.104Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:32:22.395Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:32:24.385Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:32:26.239Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:32:28.732Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:32:30.595Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:32:30.988Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:32:30.988Z] The best model improves the baseline by 14.52%. [2025-06-11T20:32:31.372Z] Top recommended movies for user id 72: [2025-06-11T20:32:31.372Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:32:31.372Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:32:31.372Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:32:31.372Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:32:31.372Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:32:31.372Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (33560.032 ms) ====== [2025-06-11T20:32:31.372Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-11T20:32:31.788Z] GC before operation: completed in 154.087 ms, heap usage 380.790 MB -> 98.059 MB. [2025-06-11T20:32:35.979Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:32:39.307Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:32:42.601Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:32:46.785Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:32:48.814Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:32:50.658Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:32:53.239Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:32:55.173Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:32:55.601Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:32:55.601Z] The best model improves the baseline by 14.52%. [2025-06-11T20:32:55.601Z] Top recommended movies for user id 72: [2025-06-11T20:32:55.601Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:32:55.601Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:32:55.601Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:32:55.601Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:32:55.601Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:32:55.601Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (24163.930 ms) ====== [2025-06-11T20:32:55.601Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-11T20:32:55.980Z] GC before operation: completed in 147.034 ms, heap usage 434.043 MB -> 88.912 MB. [2025-06-11T20:32:59.269Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:33:03.483Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:33:06.739Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:33:09.279Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:33:11.199Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:33:13.059Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:33:15.094Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:33:17.008Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:33:17.399Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:33:17.399Z] The best model improves the baseline by 14.52%. [2025-06-11T20:33:17.799Z] Top recommended movies for user id 72: [2025-06-11T20:33:17.799Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:33:17.799Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:33:17.799Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:33:17.799Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:33:17.799Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:33:17.799Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21670.416 ms) ====== [2025-06-11T20:33:17.799Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-11T20:33:17.799Z] GC before operation: completed in 136.923 ms, heap usage 169.005 MB -> 90.649 MB. [2025-06-11T20:33:21.048Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:33:23.567Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:33:26.906Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:33:30.144Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:33:31.437Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:33:33.294Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:33:35.209Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:33:37.088Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:33:37.479Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:33:37.479Z] The best model improves the baseline by 14.52%. [2025-06-11T20:33:37.479Z] Top recommended movies for user id 72: [2025-06-11T20:33:37.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:33:37.479Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:33:37.479Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:33:37.479Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:33:37.479Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:33:37.479Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19900.197 ms) ====== [2025-06-11T20:33:37.479Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-11T20:33:37.854Z] GC before operation: completed in 141.492 ms, heap usage 264.413 MB -> 89.795 MB. [2025-06-11T20:33:41.352Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:33:43.918Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:33:47.192Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:33:50.488Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:33:52.391Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:33:54.271Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:33:56.148Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:33:58.711Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:33:58.711Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:33:58.711Z] The best model improves the baseline by 14.52%. [2025-06-11T20:33:59.083Z] Top recommended movies for user id 72: [2025-06-11T20:33:59.083Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:33:59.083Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:33:59.083Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:33:59.083Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:33:59.083Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:33:59.083Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (21219.562 ms) ====== [2025-06-11T20:33:59.083Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-11T20:33:59.083Z] GC before operation: completed in 127.467 ms, heap usage 315.384 MB -> 89.780 MB. [2025-06-11T20:34:02.372Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:34:05.645Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:34:09.029Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:34:11.562Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:34:14.047Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:34:15.359Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:34:17.908Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:34:19.839Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:34:19.839Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:34:19.839Z] The best model improves the baseline by 14.52%. [2025-06-11T20:34:20.234Z] Top recommended movies for user id 72: [2025-06-11T20:34:20.234Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:34:20.234Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:34:20.234Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:34:20.234Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:34:20.234Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:34:20.234Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (20914.737 ms) ====== [2025-06-11T20:34:20.234Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-11T20:34:20.234Z] GC before operation: completed in 127.878 ms, heap usage 410.105 MB -> 90.253 MB. [2025-06-11T20:34:23.500Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:34:25.998Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:34:29.297Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:34:32.602Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:34:34.531Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:34:35.872Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:34:38.397Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:34:39.714Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:34:40.088Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:34:40.088Z] The best model improves the baseline by 14.52%. [2025-06-11T20:34:40.471Z] Top recommended movies for user id 72: [2025-06-11T20:34:40.471Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:34:40.471Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:34:40.471Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:34:40.471Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:34:40.471Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:34:40.471Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20247.379 ms) ====== [2025-06-11T20:34:40.471Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-11T20:34:40.471Z] GC before operation: completed in 127.569 ms, heap usage 341.323 MB -> 90.118 MB. [2025-06-11T20:34:43.773Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:34:47.074Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:34:49.617Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:34:52.852Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:34:54.767Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:34:56.652Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:34:58.544Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:35:00.419Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:35:00.809Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:35:00.809Z] The best model improves the baseline by 14.52%. [2025-06-11T20:35:00.809Z] Top recommended movies for user id 72: [2025-06-11T20:35:00.809Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:35:00.809Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:35:00.809Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:35:00.809Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:35:00.809Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:35:00.809Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20380.887 ms) ====== [2025-06-11T20:35:00.809Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-11T20:35:01.239Z] GC before operation: completed in 140.511 ms, heap usage 430.308 MB -> 90.442 MB. [2025-06-11T20:35:04.522Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:35:07.050Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:35:10.349Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:35:13.672Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:35:14.991Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:35:16.882Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:35:18.738Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:35:20.600Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:35:20.993Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:35:20.993Z] The best model improves the baseline by 14.52%. [2025-06-11T20:35:21.367Z] Top recommended movies for user id 72: [2025-06-11T20:35:21.367Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:35:21.367Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:35:21.367Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:35:21.367Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:35:21.367Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:35:21.367Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20135.961 ms) ====== [2025-06-11T20:35:21.367Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-11T20:35:21.367Z] GC before operation: completed in 130.595 ms, heap usage 401.599 MB -> 90.312 MB. [2025-06-11T20:35:24.610Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:35:27.904Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:35:31.156Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:35:33.694Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:35:35.532Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:35:37.368Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:35:39.254Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:35:41.159Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:35:41.532Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:35:41.532Z] The best model improves the baseline by 14.52%. [2025-06-11T20:35:41.532Z] Top recommended movies for user id 72: [2025-06-11T20:35:41.532Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:35:41.532Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:35:41.532Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:35:41.532Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:35:41.532Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:35:41.532Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20300.044 ms) ====== [2025-06-11T20:35:41.532Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-11T20:35:41.927Z] GC before operation: completed in 135.462 ms, heap usage 373.486 MB -> 90.449 MB. [2025-06-11T20:35:45.202Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:35:48.449Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:35:51.177Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:35:54.459Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:35:55.769Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:35:57.643Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:35:59.569Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:36:01.467Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:36:01.865Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:36:01.865Z] The best model improves the baseline by 14.52%. [2025-06-11T20:36:02.267Z] Top recommended movies for user id 72: [2025-06-11T20:36:02.267Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:36:02.267Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:36:02.267Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:36:02.267Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:36:02.267Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:36:02.267Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (20404.935 ms) ====== [2025-06-11T20:36:02.267Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-11T20:36:02.267Z] GC before operation: completed in 133.740 ms, heap usage 296.192 MB -> 90.118 MB. [2025-06-11T20:36:05.555Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:36:08.060Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:36:11.372Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:36:13.944Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:36:15.833Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:36:17.693Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:36:19.573Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:36:21.509Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:36:21.882Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:36:21.882Z] The best model improves the baseline by 14.52%. [2025-06-11T20:36:22.253Z] Top recommended movies for user id 72: [2025-06-11T20:36:22.253Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:36:22.253Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:36:22.253Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:36:22.253Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:36:22.253Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:36:22.253Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19884.365 ms) ====== [2025-06-11T20:36:22.253Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-11T20:36:22.253Z] GC before operation: completed in 128.267 ms, heap usage 157.698 MB -> 93.140 MB. [2025-06-11T20:36:25.516Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:36:28.049Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:36:31.300Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:36:33.902Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:36:35.774Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:36:37.639Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:36:39.617Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:36:41.518Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:36:41.930Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:36:41.930Z] The best model improves the baseline by 14.52%. [2025-06-11T20:36:42.335Z] Top recommended movies for user id 72: [2025-06-11T20:36:42.335Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:36:42.335Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:36:42.335Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:36:42.335Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:36:42.335Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:36:42.335Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (19798.629 ms) ====== [2025-06-11T20:36:42.335Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-11T20:36:42.335Z] GC before operation: completed in 131.961 ms, heap usage 402.060 MB -> 90.528 MB. [2025-06-11T20:36:45.605Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:36:48.142Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:36:51.404Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:36:54.766Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:36:56.078Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:36:57.961Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:37:00.464Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:37:01.899Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:37:02.276Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:37:02.276Z] The best model improves the baseline by 14.52%. [2025-06-11T20:37:02.669Z] Top recommended movies for user id 72: [2025-06-11T20:37:02.669Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:37:02.669Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:37:02.669Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:37:02.669Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:37:02.669Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:37:02.669Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20259.174 ms) ====== [2025-06-11T20:37:02.669Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-11T20:37:02.669Z] GC before operation: completed in 133.225 ms, heap usage 296.691 MB -> 90.235 MB. [2025-06-11T20:37:05.960Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:37:08.477Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:37:11.784Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:37:15.144Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:37:16.445Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:37:18.337Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:37:20.226Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:37:22.104Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:37:22.489Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:37:22.489Z] The best model improves the baseline by 14.52%. [2025-06-11T20:37:22.869Z] Top recommended movies for user id 72: [2025-06-11T20:37:22.869Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:37:22.869Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:37:22.869Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:37:22.869Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:37:22.869Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:37:22.869Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20051.802 ms) ====== [2025-06-11T20:37:22.869Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-11T20:37:22.869Z] GC before operation: completed in 133.937 ms, heap usage 414.334 MB -> 90.583 MB. [2025-06-11T20:37:26.140Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:37:28.784Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:37:32.066Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:37:34.593Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:37:36.470Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:37:37.778Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:37:39.685Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:37:41.568Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:37:41.940Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:37:41.940Z] The best model improves the baseline by 14.52%. [2025-06-11T20:37:41.940Z] Top recommended movies for user id 72: [2025-06-11T20:37:41.940Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:37:41.940Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:37:41.940Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:37:41.940Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:37:41.940Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:37:41.940Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (19145.629 ms) ====== [2025-06-11T20:37:41.940Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-11T20:37:41.940Z] GC before operation: completed in 136.658 ms, heap usage 170.311 MB -> 91.260 MB. [2025-06-11T20:37:45.221Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:37:47.790Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:37:51.308Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:37:53.848Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:37:55.695Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:37:57.658Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:37:59.553Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:38:01.406Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:38:01.839Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:38:01.839Z] The best model improves the baseline by 14.52%. [2025-06-11T20:38:01.839Z] Top recommended movies for user id 72: [2025-06-11T20:38:01.839Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:38:01.839Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:38:01.839Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:38:01.839Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:38:01.839Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:38:01.839Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19839.834 ms) ====== [2025-06-11T20:38:01.839Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-11T20:38:02.223Z] GC before operation: completed in 130.612 ms, heap usage 421.694 MB -> 90.557 MB. [2025-06-11T20:38:05.473Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:38:08.709Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:38:11.334Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:38:14.609Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:38:15.948Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:38:18.426Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:38:20.319Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:38:21.758Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:38:22.162Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:38:22.162Z] The best model improves the baseline by 14.52%. [2025-06-11T20:38:22.542Z] Top recommended movies for user id 72: [2025-06-11T20:38:22.542Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:38:22.542Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:38:22.542Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:38:22.542Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:38:22.542Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:38:22.542Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20396.784 ms) ====== [2025-06-11T20:38:22.542Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-11T20:38:22.542Z] GC before operation: completed in 129.120 ms, heap usage 374.131 MB -> 90.377 MB. [2025-06-11T20:38:25.782Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:38:28.274Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:38:31.527Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:38:34.768Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:38:36.064Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:38:37.939Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:38:39.779Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:38:41.658Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:38:42.035Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:38:42.035Z] The best model improves the baseline by 14.52%. [2025-06-11T20:38:42.035Z] Top recommended movies for user id 72: [2025-06-11T20:38:42.035Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:38:42.035Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:38:42.035Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:38:42.035Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:38:42.035Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:38:42.035Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19490.322 ms) ====== [2025-06-11T20:38:42.035Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-11T20:38:42.408Z] GC before operation: completed in 135.996 ms, heap usage 281.254 MB -> 90.313 MB. [2025-06-11T20:38:45.673Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-11T20:38:48.186Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-11T20:38:51.617Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-11T20:38:54.148Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-11T20:38:56.093Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-11T20:38:57.967Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-11T20:38:59.832Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-11T20:39:01.172Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-11T20:39:01.564Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-11T20:39:01.564Z] The best model improves the baseline by 14.52%. [2025-06-11T20:39:01.939Z] Top recommended movies for user id 72: [2025-06-11T20:39:01.939Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-11T20:39:01.939Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-11T20:39:01.939Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-11T20:39:01.939Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-11T20:39:01.939Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-11T20:39:01.939Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19640.853 ms) ====== [2025-06-11T20:39:02.741Z] ----------------------------------- [2025-06-11T20:39:02.741Z] renaissance-movie-lens_0_PASSED [2025-06-11T20:39:02.741Z] ----------------------------------- [2025-06-11T20:39:02.741Z] [2025-06-11T20:39:02.741Z] TEST TEARDOWN: [2025-06-11T20:39:02.741Z] Nothing to be done for teardown. [2025-06-11T20:39:02.741Z] renaissance-movie-lens_0 Finish Time: Wed Jun 11 20:39:02 2025 Epoch Time (ms): 1749674342387