[2025-07-31T04:55:14.347Z] Running test renaissance-movie-lens_0 ... [2025-07-31T04:55:14.347Z] =============================================== [2025-07-31T04:55:14.347Z] renaissance-movie-lens_0 Start Time: Thu Jul 31 04:55:13 2025 Epoch Time (ms): 1753937713946 [2025-07-31T04:55:14.347Z] variation: NoOptions [2025-07-31T04:55:14.347Z] JVM_OPTIONS: [2025-07-31T04:55:14.347Z] { \ [2025-07-31T04:55:14.347Z] echo ""; echo "TEST SETUP:"; \ [2025-07-31T04:55:14.347Z] echo "Nothing to be done for setup."; \ [2025-07-31T04:55:14.347Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17539367384728/renaissance-movie-lens_0"; \ [2025-07-31T04:55:14.347Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17539367384728/renaissance-movie-lens_0"; \ [2025-07-31T04:55:14.347Z] echo ""; echo "TESTING:"; \ [2025-07-31T04:55:14.347Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-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_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17539367384728/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-07-31T04:55:14.347Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17539367384728/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-07-31T04:55:14.347Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-07-31T04:55:14.347Z] echo "Nothing to be done for teardown."; \ [2025-07-31T04:55:14.347Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17539367384728/TestTargetResult"; [2025-07-31T04:55:14.347Z] [2025-07-31T04:55:14.347Z] TEST SETUP: [2025-07-31T04:55:14.347Z] Nothing to be done for setup. [2025-07-31T04:55:14.347Z] [2025-07-31T04:55:14.347Z] TESTING: [2025-07-31T04:55:21.006Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-07-31T04:55:27.719Z] 04:55:27.384 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. [2025-07-31T04:55:29.657Z] Got 100004 ratings from 671 users on 9066 movies. [2025-07-31T04:55:30.622Z] Training: 60056, validation: 20285, test: 19854 [2025-07-31T04:55:30.622Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-07-31T04:55:30.622Z] GC before operation: completed in 128.015 ms, heap usage 376.696 MB -> 75.859 MB. [2025-07-31T04:55:38.090Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:55:42.393Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:55:46.529Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:55:50.680Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:55:52.619Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:55:53.612Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:55:55.553Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:55:57.504Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:55:57.504Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-07-31T04:55:58.447Z] The best model improves the baseline by 14.52%. [2025-07-31T04:55:58.447Z] Top recommended movies for user id 72: [2025-07-31T04:55:58.447Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:55:58.447Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:55:58.447Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:55:58.447Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:55:58.447Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:55:58.447Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (27858.507 ms) ====== [2025-07-31T04:55:58.447Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-07-31T04:55:58.447Z] GC before operation: completed in 150.920 ms, heap usage 164.962 MB -> 86.905 MB. [2025-07-31T04:56:02.569Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:56:05.565Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:56:09.730Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:56:12.781Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:56:14.752Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:56:17.776Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:56:19.723Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:56:21.659Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:56:22.603Z] 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. [2025-07-31T04:56:22.603Z] The best model improves the baseline by 14.52%. [2025-07-31T04:56:22.603Z] Top recommended movies for user id 72: [2025-07-31T04:56:22.603Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:56:22.603Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:56:22.603Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:56:22.603Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:56:22.603Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:56:22.603Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23989.663 ms) ====== [2025-07-31T04:56:22.603Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-07-31T04:56:22.603Z] GC before operation: completed in 191.103 ms, heap usage 239.057 MB -> 88.564 MB. [2025-07-31T04:56:27.260Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:56:30.251Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:56:33.254Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:56:37.369Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:56:38.410Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:56:41.504Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:56:43.468Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:56:45.404Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:56:45.404Z] 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. [2025-07-31T04:56:45.404Z] The best model improves the baseline by 14.52%. [2025-07-31T04:56:46.353Z] Top recommended movies for user id 72: [2025-07-31T04:56:46.353Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:56:46.353Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:56:46.353Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:56:46.353Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:56:46.353Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:56:46.353Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23270.547 ms) ====== [2025-07-31T04:56:46.353Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-07-31T04:56:46.353Z] GC before operation: completed in 145.963 ms, heap usage 283.964 MB -> 89.516 MB. [2025-07-31T04:56:49.340Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:56:52.332Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:56:56.484Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:56:59.489Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:57:01.424Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:57:03.364Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:57:06.389Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:57:08.346Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:57:08.346Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-07-31T04:57:08.346Z] The best model improves the baseline by 14.52%. [2025-07-31T04:57:08.346Z] Top recommended movies for user id 72: [2025-07-31T04:57:08.346Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:57:08.346Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:57:08.346Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:57:08.346Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:57:08.346Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:57:08.346Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22249.225 ms) ====== [2025-07-31T04:57:08.346Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-07-31T04:57:08.346Z] GC before operation: completed in 173.157 ms, heap usage 253.606 MB -> 89.591 MB. [2025-07-31T04:57:11.344Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:57:15.483Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:57:18.129Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:57:21.133Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:57:22.075Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:57:24.023Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:57:24.980Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:57:25.924Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:57:26.865Z] 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. [2025-07-31T04:57:26.865Z] The best model improves the baseline by 14.52%. [2025-07-31T04:57:26.865Z] Top recommended movies for user id 72: [2025-07-31T04:57:26.865Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:57:26.865Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:57:26.865Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:57:26.865Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:57:26.865Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:57:26.865Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17998.439 ms) ====== [2025-07-31T04:57:26.865Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-07-31T04:57:26.865Z] GC before operation: completed in 143.169 ms, heap usage 196.474 MB -> 89.603 MB. [2025-07-31T04:57:28.842Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:57:30.779Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:57:32.741Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:57:34.694Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:57:35.651Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:57:37.589Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:57:38.533Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:57:39.475Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:57:39.476Z] 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. [2025-07-31T04:57:39.476Z] The best model improves the baseline by 14.52%. [2025-07-31T04:57:39.476Z] Top recommended movies for user id 72: [2025-07-31T04:57:39.476Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:57:39.476Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:57:39.476Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:57:39.476Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:57:39.476Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:57:39.476Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (13186.414 ms) ====== [2025-07-31T04:57:39.476Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-07-31T04:57:40.422Z] GC before operation: completed in 131.022 ms, heap usage 166.548 MB -> 90.659 MB. [2025-07-31T04:57:42.398Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:57:46.096Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:57:46.096Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:57:48.029Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:57:48.970Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:57:50.908Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:57:51.853Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:57:52.794Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:57:53.738Z] 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. [2025-07-31T04:57:53.738Z] The best model improves the baseline by 14.52%. [2025-07-31T04:57:53.738Z] Top recommended movies for user id 72: [2025-07-31T04:57:53.738Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:57:53.738Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:57:53.738Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:57:53.738Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:57:53.738Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:57:53.738Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13496.904 ms) ====== [2025-07-31T04:57:53.738Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-07-31T04:57:53.738Z] GC before operation: completed in 119.730 ms, heap usage 98.375 MB -> 92.993 MB. [2025-07-31T04:57:55.677Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:57:57.609Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:57:59.550Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:58:01.513Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:58:03.449Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:58:04.394Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:58:05.342Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:58:07.282Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:58:07.282Z] 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. [2025-07-31T04:58:07.282Z] The best model improves the baseline by 14.52%. [2025-07-31T04:58:07.282Z] Top recommended movies for user id 72: [2025-07-31T04:58:07.282Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:58:07.282Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:58:07.282Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:58:07.282Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:58:07.282Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:58:07.282Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13669.106 ms) ====== [2025-07-31T04:58:07.282Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-07-31T04:58:07.282Z] GC before operation: completed in 132.941 ms, heap usage 496.012 MB -> 90.519 MB. [2025-07-31T04:58:09.904Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:58:11.839Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:58:13.781Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:58:15.750Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:58:16.698Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:58:18.639Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:58:19.579Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:58:20.524Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:58:20.524Z] 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. [2025-07-31T04:58:20.524Z] The best model improves the baseline by 14.52%. [2025-07-31T04:58:20.524Z] Top recommended movies for user id 72: [2025-07-31T04:58:20.524Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:58:20.524Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:58:20.524Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:58:20.524Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:58:20.524Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:58:20.524Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13470.998 ms) ====== [2025-07-31T04:58:20.524Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-07-31T04:58:21.656Z] GC before operation: completed in 130.815 ms, heap usage 446.873 MB -> 90.240 MB. [2025-07-31T04:58:23.598Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:58:25.535Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:58:27.469Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:58:29.409Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:58:30.352Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:58:31.294Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:58:33.232Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:58:34.182Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:58:34.182Z] 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. [2025-07-31T04:58:34.182Z] The best model improves the baseline by 14.52%. [2025-07-31T04:58:35.124Z] Top recommended movies for user id 72: [2025-07-31T04:58:35.124Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:58:35.124Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:58:35.124Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:58:35.124Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:58:35.124Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:58:35.124Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13742.009 ms) ====== [2025-07-31T04:58:35.124Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-07-31T04:58:35.124Z] GC before operation: completed in 119.275 ms, heap usage 194.290 MB -> 90.156 MB. [2025-07-31T04:58:37.063Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:58:38.998Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:58:40.934Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:58:42.874Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:58:44.893Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:58:45.838Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:58:46.782Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:58:48.717Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:58:48.717Z] 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. [2025-07-31T04:58:48.717Z] The best model improves the baseline by 14.52%. [2025-07-31T04:58:48.717Z] Top recommended movies for user id 72: [2025-07-31T04:58:48.717Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:58:48.717Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:58:48.717Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:58:48.717Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:58:48.717Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:58:48.717Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13704.420 ms) ====== [2025-07-31T04:58:48.717Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-07-31T04:58:48.717Z] GC before operation: completed in 127.332 ms, heap usage 375.092 MB -> 90.055 MB. [2025-07-31T04:58:50.814Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:58:52.750Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:58:54.692Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:58:57.681Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:58:58.629Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:59:00.014Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:59:01.137Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:59:02.083Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:59:02.083Z] 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. [2025-07-31T04:59:02.083Z] The best model improves the baseline by 14.52%. [2025-07-31T04:59:02.083Z] Top recommended movies for user id 72: [2025-07-31T04:59:02.083Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:59:02.083Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:59:02.083Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:59:02.083Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:59:02.083Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:59:02.083Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13403.965 ms) ====== [2025-07-31T04:59:02.083Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-07-31T04:59:02.083Z] GC before operation: completed in 132.731 ms, heap usage 372.768 MB -> 90.453 MB. [2025-07-31T04:59:04.025Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:59:05.961Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:59:08.957Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:59:10.893Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:59:11.837Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:59:12.785Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:59:14.796Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:59:15.757Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:59:15.757Z] 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. [2025-07-31T04:59:15.757Z] The best model improves the baseline by 14.52%. [2025-07-31T04:59:15.757Z] Top recommended movies for user id 72: [2025-07-31T04:59:15.757Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:59:15.757Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:59:15.757Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:59:15.757Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:59:15.757Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:59:15.757Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13730.921 ms) ====== [2025-07-31T04:59:15.757Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-07-31T04:59:15.757Z] GC before operation: completed in 135.360 ms, heap usage 520.841 MB -> 90.659 MB. [2025-07-31T04:59:18.748Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:59:20.684Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:59:22.623Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:59:24.559Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:59:25.513Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:59:26.527Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:59:28.464Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:59:29.412Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:59:29.412Z] 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. [2025-07-31T04:59:29.412Z] The best model improves the baseline by 14.52%. [2025-07-31T04:59:29.412Z] Top recommended movies for user id 72: [2025-07-31T04:59:29.412Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:59:29.412Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:59:29.412Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:59:29.412Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:59:29.412Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:59:29.412Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13594.878 ms) ====== [2025-07-31T04:59:29.412Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-07-31T04:59:29.412Z] GC before operation: completed in 120.612 ms, heap usage 460.331 MB -> 90.347 MB. [2025-07-31T04:59:32.409Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:59:34.348Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:59:36.283Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:59:38.215Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:59:39.159Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:59:40.102Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:59:42.036Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:59:42.978Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:59:42.978Z] 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. [2025-07-31T04:59:42.978Z] The best model improves the baseline by 14.52%. [2025-07-31T04:59:42.978Z] Top recommended movies for user id 72: [2025-07-31T04:59:42.978Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:59:42.978Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:59:42.978Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:59:42.978Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:59:42.978Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:59:42.978Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13412.757 ms) ====== [2025-07-31T04:59:42.978Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-07-31T04:59:42.978Z] GC before operation: completed in 113.076 ms, heap usage 446.694 MB -> 90.619 MB. [2025-07-31T04:59:45.970Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T04:59:47.908Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T04:59:50.022Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T04:59:51.995Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T04:59:53.619Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T04:59:54.562Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T04:59:56.496Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T04:59:57.438Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T04:59:57.438Z] 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. [2025-07-31T04:59:57.438Z] The best model improves the baseline by 14.52%. [2025-07-31T04:59:57.438Z] Top recommended movies for user id 72: [2025-07-31T04:59:57.438Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T04:59:57.438Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T04:59:57.438Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T04:59:57.438Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T04:59:57.438Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T04:59:57.438Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14450.439 ms) ====== [2025-07-31T04:59:57.438Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-07-31T04:59:58.382Z] GC before operation: completed in 125.834 ms, heap usage 471.276 MB -> 90.463 MB. [2025-07-31T05:00:00.318Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T05:00:02.273Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T05:00:05.323Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T05:00:07.260Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T05:00:08.201Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T05:00:09.142Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T05:00:11.078Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T05:00:12.023Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T05:00:12.023Z] 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. [2025-07-31T05:00:12.023Z] The best model improves the baseline by 14.52%. [2025-07-31T05:00:12.023Z] Top recommended movies for user id 72: [2025-07-31T05:00:12.023Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T05:00:12.023Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T05:00:12.023Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T05:00:12.023Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T05:00:12.023Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T05:00:12.023Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14318.794 ms) ====== [2025-07-31T05:00:12.023Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-07-31T05:00:12.023Z] GC before operation: completed in 121.921 ms, heap usage 429.593 MB -> 90.430 MB. [2025-07-31T05:00:15.011Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T05:00:16.957Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T05:00:18.893Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T05:00:20.841Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T05:00:21.788Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T05:00:23.723Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T05:00:24.669Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T05:00:25.610Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T05:00:25.610Z] 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. [2025-07-31T05:00:25.610Z] The best model improves the baseline by 14.52%. [2025-07-31T05:00:25.610Z] Top recommended movies for user id 72: [2025-07-31T05:00:25.610Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T05:00:25.610Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T05:00:25.610Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T05:00:25.610Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T05:00:25.610Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T05:00:25.610Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13554.066 ms) ====== [2025-07-31T05:00:25.610Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-07-31T05:00:25.610Z] GC before operation: completed in 137.708 ms, heap usage 515.263 MB -> 90.461 MB. [2025-07-31T05:00:28.604Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T05:00:30.543Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T05:00:32.490Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T05:00:33.435Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T05:00:35.375Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T05:00:36.316Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T05:00:37.259Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T05:00:38.203Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T05:00:38.203Z] 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. [2025-07-31T05:00:38.203Z] The best model improves the baseline by 14.52%. [2025-07-31T05:00:38.203Z] Top recommended movies for user id 72: [2025-07-31T05:00:38.203Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T05:00:38.203Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T05:00:38.203Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T05:00:38.203Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T05:00:38.203Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T05:00:38.203Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (12565.652 ms) ====== [2025-07-31T05:00:38.203Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-07-31T05:00:39.147Z] GC before operation: completed in 125.249 ms, heap usage 120.460 MB -> 89.997 MB. [2025-07-31T05:00:41.793Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-31T05:00:42.734Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-31T05:00:44.674Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-31T05:00:46.608Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-31T05:00:47.555Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-31T05:00:48.496Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-31T05:00:49.440Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-31T05:00:50.383Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-31T05:00:51.323Z] 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. [2025-07-31T05:00:51.323Z] The best model improves the baseline by 14.52%. [2025-07-31T05:00:51.323Z] Top recommended movies for user id 72: [2025-07-31T05:00:51.323Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-31T05:00:51.323Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-31T05:00:51.323Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-31T05:00:51.323Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-31T05:00:51.323Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-31T05:00:51.323Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (12349.199 ms) ====== [2025-07-31T05:00:51.323Z] ----------------------------------- [2025-07-31T05:00:51.323Z] renaissance-movie-lens_0_PASSED [2025-07-31T05:00:51.323Z] ----------------------------------- [2025-07-31T05:00:51.323Z] [2025-07-31T05:00:51.323Z] TEST TEARDOWN: [2025-07-31T05:00:51.323Z] Nothing to be done for teardown. [2025-07-31T05:00:51.323Z] renaissance-movie-lens_0 Finish Time: Thu Jul 31 05:00:51 2025 Epoch Time (ms): 1753938051165