[2025-06-29T20:51:10.775Z] Running test renaissance-movie-lens_0 ... [2025-06-29T20:51:10.775Z] =============================================== [2025-06-29T20:51:10.775Z] renaissance-movie-lens_0 Start Time: Sun Jun 29 20:51:09 2025 Epoch Time (ms): 1751230269880 [2025-06-29T20:51:10.775Z] variation: NoOptions [2025-06-29T20:51:10.775Z] JVM_OPTIONS: [2025-06-29T20:51:10.775Z] { \ [2025-06-29T20:51:10.775Z] echo ""; echo "TEST SETUP:"; \ [2025-06-29T20:51:10.775Z] echo "Nothing to be done for setup."; \ [2025-06-29T20:51:10.775Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17512288609013/renaissance-movie-lens_0"; \ [2025-06-29T20:51:10.775Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17512288609013/renaissance-movie-lens_0"; \ [2025-06-29T20:51:10.775Z] echo ""; echo "TESTING:"; \ [2025-06-29T20:51:10.775Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17512288609013/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-29T20:51:10.775Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17512288609013/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-29T20:51:10.775Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-29T20:51:10.775Z] echo "Nothing to be done for teardown."; \ [2025-06-29T20:51:10.775Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17512288609013/TestTargetResult"; [2025-06-29T20:51:10.775Z] [2025-06-29T20:51:10.775Z] TEST SETUP: [2025-06-29T20:51:10.775Z] Nothing to be done for setup. [2025-06-29T20:51:10.775Z] [2025-06-29T20:51:10.775Z] TESTING: [2025-06-29T20:51:16.073Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-29T20:51:22.671Z] 20:51:21.499 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-06-29T20:51:23.604Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-29T20:51:24.552Z] Training: 60056, validation: 20285, test: 19854 [2025-06-29T20:51:24.552Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-29T20:51:24.552Z] GC before operation: completed in 157.974 ms, heap usage 203.227 MB -> 75.769 MB. [2025-06-29T20:51:31.166Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:51:34.143Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:51:37.151Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:51:40.118Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:51:41.054Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:51:42.976Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:51:44.898Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:51:46.823Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:51:46.823Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:51:46.823Z] The best model improves the baseline by 14.52%. [2025-06-29T20:51:47.757Z] Top recommended movies for user id 72: [2025-06-29T20:51:47.757Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:51:47.757Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:51:47.757Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:51:47.757Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:51:47.757Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:51:47.757Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22611.742 ms) ====== [2025-06-29T20:51:47.757Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-29T20:51:47.757Z] GC before operation: completed in 145.175 ms, heap usage 201.015 MB -> 90.452 MB. [2025-06-29T20:51:50.398Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:51:52.329Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:51:55.318Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:51:58.302Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:51:59.250Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:52:01.180Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:52:03.140Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:52:05.143Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:52:05.143Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:52:05.143Z] The best model improves the baseline by 14.52%. [2025-06-29T20:52:05.143Z] Top recommended movies for user id 72: [2025-06-29T20:52:05.143Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:52:05.143Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:52:05.143Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:52:05.143Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:52:05.143Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:52:05.143Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17891.303 ms) ====== [2025-06-29T20:52:05.143Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-29T20:52:05.143Z] GC before operation: completed in 164.095 ms, heap usage 245.429 MB -> 88.689 MB. [2025-06-29T20:52:08.120Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:52:10.051Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:52:13.027Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:52:14.948Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:52:16.871Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:52:17.808Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:52:19.753Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:52:21.698Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:52:21.698Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:52:21.698Z] The best model improves the baseline by 14.52%. [2025-06-29T20:52:21.698Z] Top recommended movies for user id 72: [2025-06-29T20:52:21.698Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:52:21.698Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:52:21.698Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:52:21.698Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:52:21.698Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:52:21.698Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16155.508 ms) ====== [2025-06-29T20:52:21.698Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-29T20:52:21.698Z] GC before operation: completed in 189.868 ms, heap usage 344.706 MB -> 89.562 MB. [2025-06-29T20:52:24.673Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:52:26.611Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:52:29.591Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:52:31.674Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:52:33.599Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:52:35.524Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:52:36.457Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:52:38.376Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:52:38.376Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:52:38.376Z] The best model improves the baseline by 14.52%. [2025-06-29T20:52:39.310Z] Top recommended movies for user id 72: [2025-06-29T20:52:39.310Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:52:39.310Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:52:39.310Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:52:39.310Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:52:39.310Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:52:39.310Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17125.595 ms) ====== [2025-06-29T20:52:39.311Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-29T20:52:39.311Z] GC before operation: completed in 195.070 ms, heap usage 299.239 MB -> 89.762 MB. [2025-06-29T20:52:42.274Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:52:44.369Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:52:46.297Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:52:48.939Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:52:50.863Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:52:51.797Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:52:53.719Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:52:54.655Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:52:55.640Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:52:55.640Z] The best model improves the baseline by 14.52%. [2025-06-29T20:52:55.640Z] Top recommended movies for user id 72: [2025-06-29T20:52:55.640Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:52:55.640Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:52:55.640Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:52:55.640Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:52:55.640Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:52:55.640Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16246.504 ms) ====== [2025-06-29T20:52:55.640Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-29T20:52:55.640Z] GC before operation: completed in 160.600 ms, heap usage 356.048 MB -> 89.810 MB. [2025-06-29T20:52:57.574Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:53:00.588Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:53:03.585Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:53:05.536Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:53:07.454Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:53:08.388Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:53:10.314Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:53:11.255Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:53:12.192Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:53:12.192Z] The best model improves the baseline by 14.52%. [2025-06-29T20:53:12.192Z] Top recommended movies for user id 72: [2025-06-29T20:53:12.192Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:53:12.192Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:53:12.192Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:53:12.192Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:53:12.192Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:53:12.192Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16339.670 ms) ====== [2025-06-29T20:53:12.192Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-29T20:53:12.192Z] GC before operation: completed in 127.646 ms, heap usage 290.529 MB -> 90.242 MB. [2025-06-29T20:53:14.113Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:53:17.078Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:53:20.051Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:53:21.971Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:53:23.899Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:53:24.833Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:53:26.783Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:53:27.723Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:53:28.664Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:53:28.664Z] The best model improves the baseline by 14.52%. [2025-06-29T20:53:28.664Z] Top recommended movies for user id 72: [2025-06-29T20:53:28.664Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:53:28.664Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:53:28.664Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:53:28.664Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:53:28.664Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:53:28.664Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16449.475 ms) ====== [2025-06-29T20:53:28.664Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-29T20:53:28.664Z] GC before operation: completed in 151.046 ms, heap usage 559.243 MB -> 93.591 MB. [2025-06-29T20:53:30.688Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:53:33.782Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:53:35.726Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:53:37.657Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:53:38.601Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:53:40.535Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:53:41.477Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:53:43.424Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:53:43.424Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:53:43.424Z] The best model improves the baseline by 14.52%. [2025-06-29T20:53:44.371Z] Top recommended movies for user id 72: [2025-06-29T20:53:44.371Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:53:44.371Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:53:44.371Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:53:44.371Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:53:44.371Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:53:44.371Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15198.373 ms) ====== [2025-06-29T20:53:44.371Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-29T20:53:44.371Z] GC before operation: completed in 148.096 ms, heap usage 720.684 MB -> 93.988 MB. [2025-06-29T20:53:46.011Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:53:48.995Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:53:50.912Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:53:53.877Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:53:55.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:53:56.746Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:53:58.663Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:53:59.607Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:54:00.552Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:54:00.552Z] The best model improves the baseline by 14.52%. [2025-06-29T20:54:00.552Z] Top recommended movies for user id 72: [2025-06-29T20:54:00.552Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:54:00.552Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:54:00.552Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:54:00.552Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:54:00.552Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:54:00.552Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (16526.130 ms) ====== [2025-06-29T20:54:00.552Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-29T20:54:00.552Z] GC before operation: completed in 143.413 ms, heap usage 395.760 MB -> 90.173 MB. [2025-06-29T20:54:03.593Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:54:05.515Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:54:07.446Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:54:10.526Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:54:11.472Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:54:13.397Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:54:14.351Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:54:16.280Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:54:16.280Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:54:16.280Z] The best model improves the baseline by 14.52%. [2025-06-29T20:54:16.280Z] Top recommended movies for user id 72: [2025-06-29T20:54:16.280Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:54:16.280Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:54:16.280Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:54:16.280Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:54:16.280Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:54:16.280Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15952.993 ms) ====== [2025-06-29T20:54:16.280Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-29T20:54:17.224Z] GC before operation: completed in 154.603 ms, heap usage 251.844 MB -> 90.147 MB. [2025-06-29T20:54:19.156Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:54:21.135Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:54:24.127Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:54:26.051Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:54:27.976Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:54:28.932Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:54:30.866Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:54:31.821Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:54:32.769Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:54:32.770Z] The best model improves the baseline by 14.52%. [2025-06-29T20:54:32.770Z] Top recommended movies for user id 72: [2025-06-29T20:54:32.770Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:54:32.770Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:54:32.770Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:54:32.770Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:54:32.770Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:54:32.770Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15873.249 ms) ====== [2025-06-29T20:54:32.770Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-29T20:54:32.770Z] GC before operation: completed in 163.404 ms, heap usage 362.555 MB -> 90.083 MB. [2025-06-29T20:54:35.765Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:54:37.783Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:54:40.763Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:54:43.104Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:54:44.051Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:54:45.975Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:54:46.910Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:54:48.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:54:48.836Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:54:48.836Z] The best model improves the baseline by 14.52%. [2025-06-29T20:54:48.836Z] Top recommended movies for user id 72: [2025-06-29T20:54:48.836Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:54:48.836Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:54:48.836Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:54:48.836Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:54:48.836Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:54:48.836Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16335.791 ms) ====== [2025-06-29T20:54:48.836Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-29T20:54:49.775Z] GC before operation: completed in 142.710 ms, heap usage 483.371 MB -> 90.526 MB. [2025-06-29T20:54:51.721Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:54:53.656Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:54:56.647Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:54:58.565Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:55:00.492Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:55:01.428Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:55:03.344Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:55:04.284Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:55:04.284Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:55:04.284Z] The best model improves the baseline by 14.52%. [2025-06-29T20:55:05.389Z] Top recommended movies for user id 72: [2025-06-29T20:55:05.389Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:55:05.389Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:55:05.389Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:55:05.389Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:55:05.389Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:55:05.389Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15573.320 ms) ====== [2025-06-29T20:55:05.389Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-29T20:55:05.389Z] GC before operation: completed in 170.560 ms, heap usage 235.634 MB -> 90.158 MB. [2025-06-29T20:55:07.312Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:55:09.414Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:55:12.388Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:55:14.307Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:55:15.245Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:55:16.181Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:55:18.117Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:55:19.056Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:55:19.998Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:55:19.998Z] The best model improves the baseline by 14.52%. [2025-06-29T20:55:19.998Z] Top recommended movies for user id 72: [2025-06-29T20:55:19.998Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:55:19.998Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:55:19.998Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:55:19.998Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:55:19.998Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:55:19.998Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14719.579 ms) ====== [2025-06-29T20:55:19.998Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-29T20:55:19.998Z] GC before operation: completed in 131.460 ms, heap usage 251.706 MB -> 90.087 MB. [2025-06-29T20:55:21.935Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:55:23.862Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:55:26.828Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:55:28.754Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:55:30.684Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:55:31.623Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:55:33.594Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:55:34.530Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:55:34.530Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:55:34.530Z] The best model improves the baseline by 14.52%. [2025-06-29T20:55:35.466Z] Top recommended movies for user id 72: [2025-06-29T20:55:35.466Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:55:35.466Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:55:35.466Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:55:35.466Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:55:35.466Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:55:35.466Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15188.084 ms) ====== [2025-06-29T20:55:35.466Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-29T20:55:35.466Z] GC before operation: completed in 179.163 ms, heap usage 415.921 MB -> 90.536 MB. [2025-06-29T20:55:37.390Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:55:40.770Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:55:42.699Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:55:44.622Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:55:46.543Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:55:47.477Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:55:49.398Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:55:50.331Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:55:50.331Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:55:50.331Z] The best model improves the baseline by 14.52%. [2025-06-29T20:55:51.269Z] Top recommended movies for user id 72: [2025-06-29T20:55:51.269Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:55:51.269Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:55:51.269Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:55:51.269Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:55:51.269Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:55:51.269Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15624.297 ms) ====== [2025-06-29T20:55:51.269Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-29T20:55:51.269Z] GC before operation: completed in 123.705 ms, heap usage 415.936 MB -> 90.382 MB. [2025-06-29T20:55:53.200Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:55:56.185Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:55:58.109Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:56:00.049Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:56:00.985Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:56:02.907Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:56:03.842Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:56:05.801Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:56:05.802Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:56:05.802Z] The best model improves the baseline by 14.52%. [2025-06-29T20:56:05.802Z] Top recommended movies for user id 72: [2025-06-29T20:56:05.802Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:56:05.802Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:56:05.802Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:56:05.802Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:56:05.802Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:56:05.802Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14742.845 ms) ====== [2025-06-29T20:56:05.802Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-29T20:56:05.802Z] GC before operation: completed in 188.176 ms, heap usage 289.477 MB -> 90.343 MB. [2025-06-29T20:56:08.768Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:56:10.687Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:56:13.662Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:56:15.585Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:56:16.520Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:56:18.465Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:56:20.395Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:56:21.329Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:56:21.330Z] 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. [2025-06-29T20:56:21.330Z] The best model improves the baseline by 14.52%. [2025-06-29T20:56:22.266Z] Top recommended movies for user id 72: [2025-06-29T20:56:22.266Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:56:22.266Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:56:22.266Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:56:22.266Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:56:22.266Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:56:22.266Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15852.192 ms) ====== [2025-06-29T20:56:22.266Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-29T20:56:22.266Z] GC before operation: completed in 172.526 ms, heap usage 343.395 MB -> 90.211 MB. [2025-06-29T20:56:24.187Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:56:27.168Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:56:29.087Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:56:31.018Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:56:32.944Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:56:34.312Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:56:35.249Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:56:37.171Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:56:37.171Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-06-29T20:56:37.171Z] The best model improves the baseline by 14.52%. [2025-06-29T20:56:37.171Z] Top recommended movies for user id 72: [2025-06-29T20:56:37.171Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:56:37.171Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:56:37.171Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:56:37.171Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:56:37.171Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:56:37.171Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15577.117 ms) ====== [2025-06-29T20:56:37.171Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-29T20:56:38.108Z] GC before operation: completed in 189.410 ms, heap usage 648.694 MB -> 93.915 MB. [2025-06-29T20:56:40.036Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-29T20:56:43.010Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-29T20:56:44.930Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-29T20:56:46.852Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-29T20:56:48.782Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-29T20:56:49.715Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-29T20:56:51.647Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-29T20:56:52.592Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-29T20:56:53.584Z] 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. [2025-06-29T20:56:53.584Z] The best model improves the baseline by 14.52%. [2025-06-29T20:56:53.584Z] Top recommended movies for user id 72: [2025-06-29T20:56:53.584Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-29T20:56:53.584Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-29T20:56:53.584Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-29T20:56:53.584Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-29T20:56:53.584Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-29T20:56:53.584Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15566.894 ms) ====== [2025-06-29T20:56:53.584Z] ----------------------------------- [2025-06-29T20:56:53.584Z] renaissance-movie-lens_0_PASSED [2025-06-29T20:56:53.584Z] ----------------------------------- [2025-06-29T20:56:53.584Z] [2025-06-29T20:56:53.584Z] TEST TEARDOWN: [2025-06-29T20:56:53.584Z] Nothing to be done for teardown. [2025-06-29T20:56:53.584Z] renaissance-movie-lens_0 Finish Time: Sun Jun 29 20:56:53 2025 Epoch Time (ms): 1751230613332