[2025-10-04T02:49:11.377Z] Running test renaissance-movie-lens_0 ... [2025-10-04T02:49:11.377Z] =============================================== [2025-10-04T02:49:11.377Z] renaissance-movie-lens_0 Start Time: Sat Oct 4 02:49:11 2025 Epoch Time (ms): 1759546151234 [2025-10-04T02:49:11.377Z] variation: NoOptions [2025-10-04T02:49:11.377Z] JVM_OPTIONS: [2025-10-04T02:49:11.377Z] { \ [2025-10-04T02:49:11.377Z] echo ""; echo "TEST SETUP:"; \ [2025-10-04T02:49:11.377Z] echo "Nothing to be done for setup."; \ [2025-10-04T02:49:11.377Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17595456555949/renaissance-movie-lens_0"; \ [2025-10-04T02:49:11.377Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17595456555949/renaissance-movie-lens_0"; \ [2025-10-04T02:49:11.377Z] echo ""; echo "TESTING:"; \ [2025-10-04T02:49:11.377Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/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_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17595456555949/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-10-04T02:49:11.377Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17595456555949/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-10-04T02:49:11.377Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-10-04T02:49:11.377Z] echo "Nothing to be done for teardown."; \ [2025-10-04T02:49:11.377Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17595456555949/TestTargetResult"; [2025-10-04T02:49:11.377Z] [2025-10-04T02:49:11.377Z] TEST SETUP: [2025-10-04T02:49:11.377Z] Nothing to be done for setup. [2025-10-04T02:49:11.377Z] [2025-10-04T02:49:11.377Z] TESTING: [2025-10-04T02:49:16.693Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-10-04T02:49:25.157Z] 02:49:24.736 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-10-04T02:49:27.498Z] Got 100004 ratings from 671 users on 9066 movies. [2025-10-04T02:49:28.231Z] Training: 60056, validation: 20285, test: 19854 [2025-10-04T02:49:28.231Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-10-04T02:49:28.231Z] GC before operation: completed in 122.383 ms, heap usage 176.851 MB -> 75.776 MB. [2025-10-04T02:49:34.804Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:49:39.074Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:49:43.330Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:49:46.640Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:49:48.144Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:49:50.487Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:49:51.994Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:49:54.330Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:49:54.330Z] 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. [2025-10-04T02:49:54.330Z] The best model improves the baseline by 14.52%. [2025-10-04T02:49:54.330Z] Top recommended movies for user id 72: [2025-10-04T02:49:54.330Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:49:54.330Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:49:54.330Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:49:54.330Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:49:54.330Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:49:54.330Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (26223.135 ms) ====== [2025-10-04T02:49:54.330Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-10-04T02:49:54.330Z] GC before operation: completed in 115.232 ms, heap usage 416.971 MB -> 86.752 MB. [2025-10-04T02:49:57.591Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:50:00.836Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:50:04.092Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:50:06.419Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:50:07.923Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:50:10.265Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:50:11.771Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:50:13.278Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:50:13.278Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-10-04T02:50:13.278Z] The best model improves the baseline by 14.52%. [2025-10-04T02:50:14.226Z] Top recommended movies for user id 72: [2025-10-04T02:50:14.226Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:50:14.226Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:50:14.226Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:50:14.226Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:50:14.226Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:50:14.226Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (19006.631 ms) ====== [2025-10-04T02:50:14.226Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-10-04T02:50:14.226Z] GC before operation: completed in 124.187 ms, heap usage 125.152 MB -> 88.546 MB. [2025-10-04T02:50:16.562Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:50:19.812Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:50:22.173Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:50:24.512Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:50:26.852Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:50:28.335Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:50:29.819Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:50:31.316Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:50:31.316Z] 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. [2025-10-04T02:50:31.316Z] The best model improves the baseline by 14.52%. [2025-10-04T02:50:31.316Z] Top recommended movies for user id 72: [2025-10-04T02:50:31.316Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:50:31.316Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:50:31.316Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:50:31.316Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:50:31.316Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:50:31.316Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17891.349 ms) ====== [2025-10-04T02:50:31.316Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-10-04T02:50:32.028Z] GC before operation: completed in 128.554 ms, heap usage 236.103 MB -> 89.385 MB. [2025-10-04T02:50:34.347Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:50:36.682Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:50:39.896Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:50:42.207Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:50:43.696Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:50:46.016Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:50:47.498Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:50:48.986Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:50:48.986Z] 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. [2025-10-04T02:50:48.986Z] The best model improves the baseline by 14.52%. [2025-10-04T02:50:48.986Z] Top recommended movies for user id 72: [2025-10-04T02:50:48.986Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:50:48.986Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:50:48.986Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:50:48.986Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:50:48.986Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:50:48.986Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17480.145 ms) ====== [2025-10-04T02:50:48.986Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-10-04T02:50:49.700Z] GC before operation: completed in 114.036 ms, heap usage 396.017 MB -> 89.876 MB. [2025-10-04T02:50:52.012Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:50:54.329Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:50:57.646Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:50:59.954Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:51:01.645Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:51:03.126Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:51:04.615Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:51:06.115Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:51:06.831Z] 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. [2025-10-04T02:51:06.831Z] The best model improves the baseline by 14.52%. [2025-10-04T02:51:06.831Z] Top recommended movies for user id 72: [2025-10-04T02:51:06.831Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:51:06.831Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:51:06.831Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:51:06.831Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:51:06.831Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:51:06.831Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17467.353 ms) ====== [2025-10-04T02:51:06.831Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-10-04T02:51:06.831Z] GC before operation: completed in 124.023 ms, heap usage 97.293 MB -> 89.360 MB. [2025-10-04T02:51:10.044Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:51:12.358Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:51:14.728Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:51:17.933Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:51:19.423Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:51:20.905Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:51:22.388Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:51:23.874Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:51:24.588Z] 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. [2025-10-04T02:51:24.588Z] The best model improves the baseline by 14.52%. [2025-10-04T02:51:24.588Z] Top recommended movies for user id 72: [2025-10-04T02:51:24.588Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:51:24.588Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:51:24.588Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:51:24.588Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:51:24.588Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:51:24.588Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17568.275 ms) ====== [2025-10-04T02:51:24.588Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-10-04T02:51:24.588Z] GC before operation: completed in 115.128 ms, heap usage 363.587 MB -> 90.172 MB. [2025-10-04T02:51:27.804Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:51:30.629Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:51:32.942Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:51:35.259Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:51:36.759Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:51:38.256Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:51:40.559Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:51:42.051Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:51:42.051Z] 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. [2025-10-04T02:51:42.051Z] The best model improves the baseline by 14.52%. [2025-10-04T02:51:42.051Z] Top recommended movies for user id 72: [2025-10-04T02:51:42.051Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:51:42.051Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:51:42.051Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:51:42.051Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:51:42.051Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:51:42.051Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17369.625 ms) ====== [2025-10-04T02:51:42.051Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-10-04T02:51:42.051Z] GC before operation: completed in 121.974 ms, heap usage 410.387 MB -> 90.066 MB. [2025-10-04T02:51:44.367Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:51:47.686Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:51:49.999Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:51:52.308Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:51:53.793Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:51:55.277Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:51:56.768Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:51:58.255Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:51:58.255Z] 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. [2025-10-04T02:51:58.255Z] The best model improves the baseline by 14.52%. [2025-10-04T02:51:58.255Z] Top recommended movies for user id 72: [2025-10-04T02:51:58.255Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:51:58.255Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:51:58.255Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:51:58.255Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:51:58.255Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:51:58.255Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16342.543 ms) ====== [2025-10-04T02:51:58.255Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-10-04T02:51:58.255Z] GC before operation: completed in 113.388 ms, heap usage 471.413 MB -> 90.537 MB. [2025-10-04T02:52:01.472Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:52:03.778Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:52:06.090Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:52:08.404Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:52:09.887Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:52:10.607Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:52:12.095Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:52:13.584Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:52:13.584Z] 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. [2025-10-04T02:52:13.584Z] The best model improves the baseline by 14.52%. [2025-10-04T02:52:14.299Z] Top recommended movies for user id 72: [2025-10-04T02:52:14.299Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:52:14.299Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:52:14.299Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:52:14.299Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:52:14.299Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:52:14.299Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15343.876 ms) ====== [2025-10-04T02:52:14.299Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-10-04T02:52:14.299Z] GC before operation: completed in 117.515 ms, heap usage 279.011 MB -> 90.064 MB. [2025-10-04T02:52:17.088Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:52:18.567Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:52:20.886Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:52:23.194Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:52:24.675Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:52:26.158Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:52:27.642Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:52:29.129Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:52:29.129Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-10-04T02:52:29.129Z] The best model improves the baseline by 14.52%. [2025-10-04T02:52:29.129Z] Top recommended movies for user id 72: [2025-10-04T02:52:29.129Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:52:29.129Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:52:29.129Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:52:29.129Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:52:29.129Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:52:29.129Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15321.421 ms) ====== [2025-10-04T02:52:29.129Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-10-04T02:52:29.844Z] GC before operation: completed in 110.071 ms, heap usage 288.942 MB -> 90.308 MB. [2025-10-04T02:52:32.151Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:52:34.477Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:52:36.785Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:52:39.101Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:52:39.817Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:52:41.303Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:52:42.792Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:52:44.278Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:52:44.996Z] 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. [2025-10-04T02:52:44.996Z] The best model improves the baseline by 14.52%. [2025-10-04T02:52:44.996Z] Top recommended movies for user id 72: [2025-10-04T02:52:44.996Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:52:44.996Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:52:44.996Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:52:44.996Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:52:44.996Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:52:44.996Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15446.493 ms) ====== [2025-10-04T02:52:44.996Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-10-04T02:52:44.996Z] GC before operation: completed in 108.668 ms, heap usage 150.503 MB -> 89.754 MB. [2025-10-04T02:52:47.315Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:52:49.631Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:52:52.833Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:52:54.774Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:52:56.247Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:52:57.760Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:52:59.241Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:53:00.731Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:53:00.731Z] 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. [2025-10-04T02:53:00.731Z] The best model improves the baseline by 14.52%. [2025-10-04T02:53:01.451Z] Top recommended movies for user id 72: [2025-10-04T02:53:01.451Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:53:01.451Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:53:01.451Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:53:01.451Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:53:01.451Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:53:01.451Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16106.074 ms) ====== [2025-10-04T02:53:01.451Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-10-04T02:53:01.451Z] GC before operation: completed in 114.947 ms, heap usage 453.973 MB -> 90.443 MB. [2025-10-04T02:53:03.767Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:53:06.080Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:53:08.392Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:53:11.608Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:53:12.327Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:53:14.635Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:53:16.126Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:53:17.614Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:53:17.614Z] 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. [2025-10-04T02:53:17.614Z] The best model improves the baseline by 14.52%. [2025-10-04T02:53:17.614Z] Top recommended movies for user id 72: [2025-10-04T02:53:17.614Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:53:17.614Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:53:17.614Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:53:17.614Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:53:17.614Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:53:17.614Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16387.412 ms) ====== [2025-10-04T02:53:17.614Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-10-04T02:53:17.614Z] GC before operation: completed in 108.987 ms, heap usage 103.205 MB -> 90.032 MB. [2025-10-04T02:53:20.829Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:53:23.150Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:53:25.458Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:53:27.773Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:53:29.259Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:53:30.734Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:53:32.216Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:53:33.700Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:53:33.700Z] 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. [2025-10-04T02:53:33.700Z] The best model improves the baseline by 14.52%. [2025-10-04T02:53:34.416Z] Top recommended movies for user id 72: [2025-10-04T02:53:34.416Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:53:34.416Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:53:34.416Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:53:34.416Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:53:34.416Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:53:34.416Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16374.061 ms) ====== [2025-10-04T02:53:34.416Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-10-04T02:53:34.416Z] GC before operation: completed in 117.988 ms, heap usage 97.211 MB -> 89.849 MB. [2025-10-04T02:53:36.725Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:53:39.508Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:53:41.847Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:53:44.169Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:53:45.707Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:53:47.191Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:53:48.673Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:53:50.158Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:53:50.158Z] 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. [2025-10-04T02:53:50.873Z] The best model improves the baseline by 14.52%. [2025-10-04T02:53:50.873Z] Top recommended movies for user id 72: [2025-10-04T02:53:50.873Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:53:50.873Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:53:50.873Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:53:50.873Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:53:50.873Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:53:50.873Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16417.829 ms) ====== [2025-10-04T02:53:50.873Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-10-04T02:53:50.873Z] GC before operation: completed in 110.404 ms, heap usage 361.467 MB -> 90.466 MB. [2025-10-04T02:53:53.187Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:53:55.498Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:53:58.712Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:54:00.192Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:54:01.684Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:54:03.172Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:54:04.664Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:54:06.149Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:54:06.875Z] 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. [2025-10-04T02:54:06.875Z] The best model improves the baseline by 14.52%. [2025-10-04T02:54:06.876Z] Top recommended movies for user id 72: [2025-10-04T02:54:06.876Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:54:06.876Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:54:06.876Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:54:06.876Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:54:06.876Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:54:06.876Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15973.215 ms) ====== [2025-10-04T02:54:06.876Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-10-04T02:54:06.876Z] GC before operation: completed in 112.407 ms, heap usage 442.776 MB -> 90.463 MB. [2025-10-04T02:54:09.201Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:54:11.520Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:54:14.733Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:54:16.703Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:54:18.199Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:54:19.686Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:54:21.176Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:54:22.663Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:54:22.663Z] 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. [2025-10-04T02:54:22.663Z] The best model improves the baseline by 14.52%. [2025-10-04T02:54:22.663Z] Top recommended movies for user id 72: [2025-10-04T02:54:22.663Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:54:22.663Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:54:22.663Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:54:22.663Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:54:22.663Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:54:22.663Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16110.851 ms) ====== [2025-10-04T02:54:22.663Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-10-04T02:54:23.392Z] GC before operation: completed in 116.113 ms, heap usage 371.110 MB -> 90.441 MB. [2025-10-04T02:54:25.704Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:54:28.015Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:54:31.232Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:54:32.717Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:54:34.198Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:54:35.684Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:54:37.168Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:54:38.658Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:54:39.373Z] 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. [2025-10-04T02:54:39.373Z] The best model improves the baseline by 14.52%. [2025-10-04T02:54:39.373Z] Top recommended movies for user id 72: [2025-10-04T02:54:39.373Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:54:39.373Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:54:39.373Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:54:39.373Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:54:39.373Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:54:39.373Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16252.021 ms) ====== [2025-10-04T02:54:39.373Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-10-04T02:54:39.374Z] GC before operation: completed in 111.722 ms, heap usage 126.068 MB -> 89.948 MB. [2025-10-04T02:54:41.689Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:54:44.008Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:54:46.417Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:54:48.725Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:54:50.208Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:54:51.688Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:54:52.403Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:54:53.889Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:54:53.889Z] 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. [2025-10-04T02:54:54.607Z] The best model improves the baseline by 14.52%. [2025-10-04T02:54:54.607Z] Top recommended movies for user id 72: [2025-10-04T02:54:54.607Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:54:54.607Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:54:54.607Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:54:54.607Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:54:54.607Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:54:54.607Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14908.727 ms) ====== [2025-10-04T02:54:54.607Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-10-04T02:54:54.607Z] GC before operation: completed in 117.669 ms, heap usage 123.893 MB -> 91.089 MB. [2025-10-04T02:54:57.376Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-04T02:54:58.879Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-04T02:55:01.198Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-04T02:55:03.510Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-04T02:55:04.991Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-04T02:55:06.475Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-04T02:55:07.957Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-04T02:55:08.684Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-04T02:55:09.402Z] 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. [2025-10-04T02:55:09.402Z] The best model improves the baseline by 14.52%. [2025-10-04T02:55:09.402Z] Top recommended movies for user id 72: [2025-10-04T02:55:09.402Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-04T02:55:09.402Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-04T02:55:09.402Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-04T02:55:09.402Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-04T02:55:09.402Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-04T02:55:09.402Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14816.740 ms) ====== [2025-10-04T02:55:10.119Z] ----------------------------------- [2025-10-04T02:55:10.119Z] renaissance-movie-lens_0_PASSED [2025-10-04T02:55:10.119Z] ----------------------------------- [2025-10-04T02:55:10.119Z] [2025-10-04T02:55:10.119Z] TEST TEARDOWN: [2025-10-04T02:55:10.119Z] Nothing to be done for teardown. [2025-10-04T02:55:10.119Z] renaissance-movie-lens_0 Finish Time: Sat Oct 4 02:55:09 2025 Epoch Time (ms): 1759546509429