[2025-12-03T22:45:16.203Z] Running test renaissance-movie-lens_0 ... [2025-12-03T22:45:16.203Z] =============================================== [2025-12-03T22:45:16.203Z] renaissance-movie-lens_0 Start Time: Wed Dec 3 22:45:15 2025 Epoch Time (ms): 1764801915353 [2025-12-03T22:45:16.203Z] variation: NoOptions [2025-12-03T22:45:16.203Z] JVM_OPTIONS: [2025-12-03T22:45:16.203Z] { \ [2025-12-03T22:45:16.203Z] echo ""; echo "TEST SETUP:"; \ [2025-12-03T22:45:16.203Z] echo "Nothing to be done for setup."; \ [2025-12-03T22:45:16.203Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17648003548474/renaissance-movie-lens_0"; \ [2025-12-03T22:45:16.203Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17648003548474/renaissance-movie-lens_0"; \ [2025-12-03T22:45:16.203Z] echo ""; echo "TESTING:"; \ [2025-12-03T22:45:16.203Z] "/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_17648003548474/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-12-03T22:45:16.203Z] 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_17648003548474/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-12-03T22:45:16.203Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-12-03T22:45:16.203Z] echo "Nothing to be done for teardown."; \ [2025-12-03T22:45:16.203Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17648003548474/TestTargetResult"; [2025-12-03T22:45:16.203Z] [2025-12-03T22:45:16.203Z] TEST SETUP: [2025-12-03T22:45:16.203Z] Nothing to be done for setup. [2025-12-03T22:45:16.203Z] [2025-12-03T22:45:16.203Z] TESTING: [2025-12-03T22:45:21.741Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-12-03T22:45:31.639Z] 22:45:30.205 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-12-03T22:45:32.602Z] Got 100004 ratings from 671 users on 9066 movies. [2025-12-03T22:45:33.557Z] Training: 60056, validation: 20285, test: 19854 [2025-12-03T22:45:33.557Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-12-03T22:45:33.557Z] GC before operation: completed in 156.018 ms, heap usage 140.363 MB -> 76.015 MB. [2025-12-03T22:45:40.764Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:45:46.170Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:45:49.233Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:45:53.444Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:45:54.512Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:45:56.653Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:45:58.608Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:46:00.742Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:46:00.742Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:46:00.742Z] The best model improves the baseline by 14.52%. [2025-12-03T22:46:01.707Z] Top recommended movies for user id 72: [2025-12-03T22:46:01.707Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:46:01.707Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:46:01.707Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:46:01.707Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:46:01.707Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:46:01.707Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (27624.975 ms) ====== [2025-12-03T22:46:01.707Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-12-03T22:46:01.707Z] GC before operation: completed in 199.968 ms, heap usage 175.677 MB -> 88.943 MB. [2025-12-03T22:46:04.753Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:46:08.323Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:46:11.421Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:46:13.401Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:46:15.456Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:46:17.442Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:46:19.503Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:46:21.492Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:46:21.492Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:46:21.492Z] The best model improves the baseline by 14.52%. [2025-12-03T22:46:21.492Z] Top recommended movies for user id 72: [2025-12-03T22:46:21.492Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:46:21.492Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:46:21.492Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:46:21.492Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:46:21.492Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:46:21.492Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20074.730 ms) ====== [2025-12-03T22:46:21.492Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-12-03T22:46:21.492Z] GC before operation: completed in 145.045 ms, heap usage 164.277 MB -> 88.859 MB. [2025-12-03T22:46:24.532Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:46:27.560Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:46:30.604Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:46:32.809Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:46:33.774Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:46:35.746Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:46:36.703Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:46:38.691Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:46:38.691Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:46:38.691Z] The best model improves the baseline by 14.52%. [2025-12-03T22:46:38.691Z] Top recommended movies for user id 72: [2025-12-03T22:46:38.691Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:46:38.691Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:46:38.691Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:46:38.691Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:46:38.691Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:46:38.691Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17354.550 ms) ====== [2025-12-03T22:46:38.691Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-12-03T22:46:39.899Z] GC before operation: completed in 147.306 ms, heap usage 254.269 MB -> 89.468 MB. [2025-12-03T22:46:42.099Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:46:44.279Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:46:47.505Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:46:49.780Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:46:50.755Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:46:52.763Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:46:53.743Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:46:55.897Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:46:55.897Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:46:55.897Z] The best model improves the baseline by 14.52%. [2025-12-03T22:46:55.897Z] Top recommended movies for user id 72: [2025-12-03T22:46:55.897Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:46:55.897Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:46:55.897Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:46:55.897Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:46:55.897Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:46:55.897Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16726.550 ms) ====== [2025-12-03T22:46:55.897Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-12-03T22:46:55.897Z] GC before operation: completed in 157.247 ms, heap usage 379.345 MB -> 89.934 MB. [2025-12-03T22:46:58.457Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:47:01.581Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:47:03.601Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:47:06.696Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:47:07.653Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:47:09.809Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:47:11.837Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:47:12.804Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:47:12.804Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:47:12.804Z] The best model improves the baseline by 14.52%. [2025-12-03T22:47:13.756Z] Top recommended movies for user id 72: [2025-12-03T22:47:13.756Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:47:13.756Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:47:13.756Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:47:13.756Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:47:13.756Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:47:13.756Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17299.199 ms) ====== [2025-12-03T22:47:13.756Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-12-03T22:47:13.756Z] GC before operation: completed in 150.995 ms, heap usage 123.590 MB -> 89.587 MB. [2025-12-03T22:47:15.903Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:47:19.058Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:47:22.089Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:47:25.653Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:47:26.620Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:47:27.573Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:47:28.538Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:47:30.568Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:47:30.568Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:47:30.568Z] The best model improves the baseline by 14.52%. [2025-12-03T22:47:30.568Z] Top recommended movies for user id 72: [2025-12-03T22:47:30.568Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:47:30.568Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:47:30.568Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:47:30.568Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:47:30.568Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:47:30.568Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16996.647 ms) ====== [2025-12-03T22:47:30.568Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-12-03T22:47:30.568Z] GC before operation: completed in 132.441 ms, heap usage 439.668 MB -> 90.355 MB. [2025-12-03T22:47:32.531Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:47:34.486Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:47:36.442Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:47:38.405Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:47:39.359Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:47:41.327Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:47:42.281Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:47:43.236Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:47:44.366Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:47:44.366Z] The best model improves the baseline by 14.52%. [2025-12-03T22:47:44.366Z] Top recommended movies for user id 72: [2025-12-03T22:47:44.366Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:47:44.366Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:47:44.366Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:47:44.366Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:47:44.366Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:47:44.366Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (13317.317 ms) ====== [2025-12-03T22:47:44.367Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-12-03T22:47:44.367Z] GC before operation: completed in 124.830 ms, heap usage 400.551 MB -> 90.243 MB. [2025-12-03T22:47:47.132Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:47:48.091Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:47:50.052Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:47:52.009Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:47:52.966Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:47:53.960Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:47:55.926Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:47:56.885Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:47:56.885Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:47:56.885Z] The best model improves the baseline by 14.52%. [2025-12-03T22:47:56.885Z] Top recommended movies for user id 72: [2025-12-03T22:47:56.885Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:47:56.885Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:47:56.885Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:47:56.885Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:47:56.885Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:47:56.885Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13194.362 ms) ====== [2025-12-03T22:47:56.885Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-12-03T22:47:57.843Z] GC before operation: completed in 144.386 ms, heap usage 184.191 MB -> 90.176 MB. [2025-12-03T22:47:59.802Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:48:01.776Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:48:03.787Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:48:04.742Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:48:06.699Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:48:07.657Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:48:08.694Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:48:09.648Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:48:09.648Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:48:09.648Z] The best model improves the baseline by 14.52%. [2025-12-03T22:48:10.603Z] Top recommended movies for user id 72: [2025-12-03T22:48:10.603Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:48:10.603Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:48:10.603Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:48:10.603Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:48:10.603Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:48:10.603Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (12705.043 ms) ====== [2025-12-03T22:48:10.603Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-12-03T22:48:10.603Z] GC before operation: completed in 186.601 ms, heap usage 283.501 MB -> 90.240 MB. [2025-12-03T22:48:12.567Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:48:13.860Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:48:15.822Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:48:17.780Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:48:18.736Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:48:20.695Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:48:21.647Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:48:22.603Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:48:22.603Z] 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. [2025-12-03T22:48:22.603Z] The best model improves the baseline by 14.52%. [2025-12-03T22:48:22.603Z] Top recommended movies for user id 72: [2025-12-03T22:48:22.603Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:48:22.603Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:48:22.603Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:48:22.603Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:48:22.603Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:48:22.603Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (12729.501 ms) ====== [2025-12-03T22:48:22.603Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-12-03T22:48:23.619Z] GC before operation: completed in 140.757 ms, heap usage 201.489 MB -> 90.262 MB. [2025-12-03T22:48:25.619Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:48:27.579Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:48:28.570Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:48:30.558Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:48:32.521Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:48:33.477Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:48:35.439Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:48:36.396Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:48:36.396Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:48:36.396Z] The best model improves the baseline by 14.52%. [2025-12-03T22:48:36.396Z] Top recommended movies for user id 72: [2025-12-03T22:48:36.396Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:48:36.396Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:48:36.396Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:48:36.396Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:48:36.396Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:48:36.396Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (13358.787 ms) ====== [2025-12-03T22:48:36.396Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-12-03T22:48:36.396Z] GC before operation: completed in 139.371 ms, heap usage 501.979 MB -> 90.413 MB. [2025-12-03T22:48:40.130Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:48:41.091Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:48:43.195Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:48:45.168Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:48:46.121Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:48:48.091Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:48:49.046Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:48:50.005Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:48:50.005Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:48:50.005Z] The best model improves the baseline by 14.52%. [2025-12-03T22:48:50.005Z] Top recommended movies for user id 72: [2025-12-03T22:48:50.005Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:48:50.005Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:48:50.005Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:48:50.005Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:48:50.005Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:48:50.005Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (13719.156 ms) ====== [2025-12-03T22:48:50.005Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-12-03T22:48:50.957Z] GC before operation: completed in 152.788 ms, heap usage 224.831 MB -> 90.179 MB. [2025-12-03T22:48:52.989Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:48:55.058Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:48:57.018Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:48:59.173Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:49:00.134Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:49:01.090Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:49:03.053Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:49:04.545Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:49:04.545Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:49:04.545Z] The best model improves the baseline by 14.52%. [2025-12-03T22:49:04.545Z] Top recommended movies for user id 72: [2025-12-03T22:49:04.545Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:49:04.545Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:49:04.545Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:49:04.545Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:49:04.545Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:49:04.545Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (13911.065 ms) ====== [2025-12-03T22:49:04.545Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-12-03T22:49:04.545Z] GC before operation: completed in 168.222 ms, heap usage 239.430 MB -> 90.406 MB. [2025-12-03T22:49:06.508Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:49:08.473Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:49:10.439Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:49:12.454Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:49:14.464Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:49:15.421Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:49:16.381Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:49:17.337Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:49:18.297Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:49:18.297Z] The best model improves the baseline by 14.52%. [2025-12-03T22:49:18.297Z] Top recommended movies for user id 72: [2025-12-03T22:49:18.297Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:49:18.297Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:49:18.297Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:49:18.297Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:49:18.297Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:49:18.297Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (13522.213 ms) ====== [2025-12-03T22:49:18.297Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-12-03T22:49:18.297Z] GC before operation: completed in 160.148 ms, heap usage 211.601 MB -> 90.120 MB. [2025-12-03T22:49:20.432Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:49:22.561Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:49:24.519Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:49:26.484Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:49:27.674Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:49:28.745Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:49:30.707Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:49:31.667Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:49:31.667Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:49:31.667Z] The best model improves the baseline by 14.52%. [2025-12-03T22:49:31.667Z] Top recommended movies for user id 72: [2025-12-03T22:49:31.667Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:49:31.667Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:49:31.667Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:49:31.667Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:49:31.667Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:49:31.667Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (13763.645 ms) ====== [2025-12-03T22:49:31.667Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-12-03T22:49:32.626Z] GC before operation: completed in 148.968 ms, heap usage 102.650 MB -> 90.459 MB. [2025-12-03T22:49:34.598Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:49:36.554Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:49:38.550Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:49:39.504Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:49:41.559Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:49:42.680Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:49:43.633Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:49:44.592Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:49:44.592Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:49:44.592Z] The best model improves the baseline by 14.52%. [2025-12-03T22:49:45.545Z] Top recommended movies for user id 72: [2025-12-03T22:49:45.545Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:49:45.545Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:49:45.545Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:49:45.545Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:49:45.545Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:49:45.545Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (12824.997 ms) ====== [2025-12-03T22:49:45.545Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-12-03T22:49:45.545Z] GC before operation: completed in 172.794 ms, heap usage 257.308 MB -> 90.323 MB. [2025-12-03T22:49:47.502Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:49:49.476Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:49:51.443Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:49:53.925Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:49:54.889Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:49:55.842Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:49:56.797Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:49:58.850Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:49:58.850Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:49:58.850Z] The best model improves the baseline by 14.52%. [2025-12-03T22:49:58.850Z] Top recommended movies for user id 72: [2025-12-03T22:49:58.850Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:49:58.850Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:49:58.850Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:49:58.850Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:49:58.850Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:49:58.850Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13414.711 ms) ====== [2025-12-03T22:49:58.850Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-12-03T22:49:58.850Z] GC before operation: completed in 139.190 ms, heap usage 103.110 MB -> 90.059 MB. [2025-12-03T22:50:00.809Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:50:02.820Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:50:04.780Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:50:06.740Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:50:07.848Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:50:09.830Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:50:10.786Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:50:11.750Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:50:11.750Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:50:11.750Z] The best model improves the baseline by 14.52%. [2025-12-03T22:50:12.797Z] Top recommended movies for user id 72: [2025-12-03T22:50:12.797Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:50:12.797Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:50:12.797Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:50:12.797Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:50:12.797Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:50:12.797Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13451.651 ms) ====== [2025-12-03T22:50:12.797Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-12-03T22:50:12.797Z] GC before operation: completed in 148.994 ms, heap usage 278.636 MB -> 90.233 MB. [2025-12-03T22:50:14.765Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:50:16.724Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:50:18.777Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:50:20.750Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:50:22.236Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:50:23.198Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:50:24.155Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:50:25.113Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:50:25.113Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:50:25.113Z] The best model improves the baseline by 14.52%. [2025-12-03T22:50:26.069Z] Top recommended movies for user id 72: [2025-12-03T22:50:26.069Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:50:26.069Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:50:26.069Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:50:26.069Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:50:26.069Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:50:26.069Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (13259.568 ms) ====== [2025-12-03T22:50:26.069Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-12-03T22:50:26.069Z] GC before operation: completed in 141.871 ms, heap usage 517.975 MB -> 90.717 MB. [2025-12-03T22:50:28.217Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-12-03T22:50:30.204Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-12-03T22:50:32.165Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-12-03T22:50:34.132Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-12-03T22:50:35.084Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-12-03T22:50:36.079Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-12-03T22:50:38.047Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-12-03T22:50:39.004Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-12-03T22:50:39.004Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-12-03T22:50:39.004Z] The best model improves the baseline by 14.52%. [2025-12-03T22:50:39.004Z] Top recommended movies for user id 72: [2025-12-03T22:50:39.004Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-12-03T22:50:39.004Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-12-03T22:50:39.004Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-12-03T22:50:39.004Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-12-03T22:50:39.004Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-12-03T22:50:39.004Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (13350.118 ms) ====== [2025-12-03T22:50:39.957Z] ----------------------------------- [2025-12-03T22:50:39.957Z] renaissance-movie-lens_0_PASSED [2025-12-03T22:50:39.957Z] ----------------------------------- [2025-12-03T22:50:39.957Z] [2025-12-03T22:50:39.957Z] TEST TEARDOWN: [2025-12-03T22:50:39.957Z] Nothing to be done for teardown. [2025-12-03T22:50:39.957Z] renaissance-movie-lens_0 Finish Time: Wed Dec 3 22:50:39 2025 Epoch Time (ms): 1764802239325