[2025-10-02T04:28:43.261Z] Running test renaissance-movie-lens_0 ... [2025-10-02T04:28:43.261Z] =============================================== [2025-10-02T04:28:43.261Z] renaissance-movie-lens_0 Start Time: Thu Oct 2 04:28:42 2025 Epoch Time (ms): 1759379322234 [2025-10-02T04:28:43.261Z] variation: NoOptions [2025-10-02T04:28:43.261Z] JVM_OPTIONS: [2025-10-02T04:28:43.261Z] { \ [2025-10-02T04:28:43.261Z] echo ""; echo "TEST SETUP:"; \ [2025-10-02T04:28:43.261Z] echo "Nothing to be done for setup."; \ [2025-10-02T04:28:43.261Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17593772234129/renaissance-movie-lens_0"; \ [2025-10-02T04:28:43.261Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17593772234129/renaissance-movie-lens_0"; \ [2025-10-02T04:28:43.261Z] echo ""; echo "TESTING:"; \ [2025-10-02T04:28:43.261Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17593772234129/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-10-02T04:28:43.261Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17593772234129/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-10-02T04:28:43.261Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-10-02T04:28:43.261Z] echo "Nothing to be done for teardown."; \ [2025-10-02T04:28:43.261Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17593772234129/TestTargetResult"; [2025-10-02T04:28:43.261Z] [2025-10-02T04:28:43.261Z] TEST SETUP: [2025-10-02T04:28:43.261Z] Nothing to be done for setup. [2025-10-02T04:28:43.261Z] [2025-10-02T04:28:43.261Z] TESTING: [2025-10-02T04:28:51.584Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-10-02T04:29:03.510Z] 04:29:02.143 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-10-02T04:29:06.567Z] Got 100004 ratings from 671 users on 9066 movies. [2025-10-02T04:29:07.522Z] Training: 60056, validation: 20285, test: 19854 [2025-10-02T04:29:07.522Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-10-02T04:29:07.522Z] GC before operation: completed in 174.291 ms, heap usage 421.108 MB -> 75.933 MB. [2025-10-02T04:29:19.105Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:29:25.817Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:29:29.983Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:29:34.749Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:29:37.784Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:29:39.743Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:29:42.760Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:29:45.786Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:29:45.787Z] 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. [2025-10-02T04:29:45.787Z] The best model improves the baseline by 14.52%. [2025-10-02T04:29:45.787Z] Top recommended movies for user id 72: [2025-10-02T04:29:45.787Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:29:45.787Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:29:45.787Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:29:45.787Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:29:45.787Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:29:45.787Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (38480.573 ms) ====== [2025-10-02T04:29:45.787Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-10-02T04:29:46.738Z] GC before operation: completed in 197.173 ms, heap usage 683.816 MB -> 98.389 MB. [2025-10-02T04:29:50.902Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:29:55.066Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:29:59.220Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:30:03.421Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:30:10.735Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:30:10.735Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:30:10.735Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:30:11.686Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:30:12.643Z] 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. [2025-10-02T04:30:12.643Z] The best model improves the baseline by 14.52%. [2025-10-02T04:30:12.643Z] Top recommended movies for user id 72: [2025-10-02T04:30:12.643Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:30:12.643Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:30:12.643Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:30:12.643Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:30:12.643Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:30:12.643Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (26627.223 ms) ====== [2025-10-02T04:30:12.643Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-10-02T04:30:12.643Z] GC before operation: completed in 167.654 ms, heap usage 513.380 MB -> 91.366 MB. [2025-10-02T04:30:18.022Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:30:22.182Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:30:25.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:30:28.219Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:30:30.178Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:30:33.209Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:30:35.170Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:30:36.120Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:30:37.073Z] 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. [2025-10-02T04:30:37.073Z] The best model improves the baseline by 14.52%. [2025-10-02T04:30:37.073Z] Top recommended movies for user id 72: [2025-10-02T04:30:37.073Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:30:37.073Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:30:37.073Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:30:37.073Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:30:37.073Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:30:37.073Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (24206.628 ms) ====== [2025-10-02T04:30:37.073Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-10-02T04:30:37.073Z] GC before operation: completed in 165.317 ms, heap usage 673.895 MB -> 93.155 MB. [2025-10-02T04:30:41.215Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:30:44.259Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:30:48.407Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:30:51.420Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:30:53.375Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:30:55.332Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:30:57.282Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:30:59.243Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:30:59.243Z] 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. [2025-10-02T04:30:59.243Z] The best model improves the baseline by 14.52%. [2025-10-02T04:30:59.243Z] Top recommended movies for user id 72: [2025-10-02T04:30:59.243Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:30:59.243Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:30:59.243Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:30:59.243Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:30:59.243Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:30:59.243Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22119.921 ms) ====== [2025-10-02T04:30:59.243Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-10-02T04:31:00.192Z] GC before operation: completed in 173.369 ms, heap usage 723.211 MB -> 93.591 MB. [2025-10-02T04:31:03.208Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:31:06.388Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:31:11.193Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:31:14.222Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:31:16.199Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:31:18.158Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:31:21.183Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:31:23.139Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:31:24.089Z] 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. [2025-10-02T04:31:24.089Z] The best model improves the baseline by 14.52%. [2025-10-02T04:31:24.089Z] Top recommended movies for user id 72: [2025-10-02T04:31:24.089Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:31:24.089Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:31:24.089Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:31:24.089Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:31:24.089Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:31:24.089Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (24419.949 ms) ====== [2025-10-02T04:31:24.089Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-10-02T04:31:24.089Z] GC before operation: completed in 168.473 ms, heap usage 534.212 MB -> 90.038 MB. [2025-10-02T04:31:29.463Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:31:33.626Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:31:38.311Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:31:41.322Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:31:43.307Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:31:45.264Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:31:47.226Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:31:50.256Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:31:50.256Z] 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. [2025-10-02T04:31:50.256Z] The best model improves the baseline by 14.52%. [2025-10-02T04:31:50.256Z] Top recommended movies for user id 72: [2025-10-02T04:31:50.256Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:31:50.256Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:31:50.256Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:31:50.256Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:31:50.256Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:31:50.256Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (26036.786 ms) ====== [2025-10-02T04:31:50.256Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-10-02T04:31:50.256Z] GC before operation: completed in 178.634 ms, heap usage 276.905 MB -> 95.791 MB. [2025-10-02T04:31:54.423Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:31:57.468Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:32:01.629Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:32:04.641Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:32:06.602Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:32:08.559Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:32:10.514Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:32:12.470Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:32:13.429Z] 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. [2025-10-02T04:32:13.430Z] The best model improves the baseline by 14.52%. [2025-10-02T04:32:13.430Z] Top recommended movies for user id 72: [2025-10-02T04:32:13.430Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:32:13.430Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:32:13.430Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:32:13.430Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:32:13.430Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:32:13.430Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (22685.968 ms) ====== [2025-10-02T04:32:13.430Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-10-02T04:32:13.430Z] GC before operation: completed in 175.863 ms, heap usage 646.298 MB -> 93.956 MB. [2025-10-02T04:32:21.288Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:32:21.288Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:32:24.371Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:32:28.555Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:32:30.511Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:32:32.466Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:32:34.422Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:32:36.378Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:32:36.378Z] 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. [2025-10-02T04:32:36.378Z] The best model improves the baseline by 14.52%. [2025-10-02T04:32:37.335Z] Top recommended movies for user id 72: [2025-10-02T04:32:37.335Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:32:37.335Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:32:37.335Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:32:37.335Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:32:37.335Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:32:37.335Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (23480.019 ms) ====== [2025-10-02T04:32:37.335Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-10-02T04:32:37.335Z] GC before operation: completed in 181.672 ms, heap usage 228.495 MB -> 95.848 MB. [2025-10-02T04:32:40.347Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:32:44.496Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:32:47.538Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:32:50.553Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:32:52.515Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:32:54.477Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:32:57.488Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:32:59.449Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:32:59.449Z] 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. [2025-10-02T04:32:59.449Z] The best model improves the baseline by 14.52%. [2025-10-02T04:32:59.449Z] Top recommended movies for user id 72: [2025-10-02T04:32:59.449Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:32:59.449Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:32:59.449Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:32:59.449Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:32:59.449Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:32:59.449Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (22758.461 ms) ====== [2025-10-02T04:32:59.449Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-10-02T04:33:00.400Z] GC before operation: completed in 182.962 ms, heap usage 311.410 MB -> 92.394 MB. [2025-10-02T04:33:04.557Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:33:07.627Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:33:11.791Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:33:14.811Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:33:16.769Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:33:18.739Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:33:20.691Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:33:22.651Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:33:24.566Z] 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. [2025-10-02T04:33:24.566Z] The best model improves the baseline by 14.52%. [2025-10-02T04:33:24.566Z] Top recommended movies for user id 72: [2025-10-02T04:33:24.566Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:33:24.566Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:33:24.566Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:33:24.566Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:33:24.566Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:33:24.566Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (23603.227 ms) ====== [2025-10-02T04:33:24.566Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-10-02T04:33:24.566Z] GC before operation: completed in 194.833 ms, heap usage 130.311 MB -> 96.134 MB. [2025-10-02T04:33:27.595Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:33:31.755Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:33:35.919Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:33:38.943Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:33:40.924Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:33:42.880Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:33:44.836Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:33:46.792Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:33:47.747Z] 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. [2025-10-02T04:33:47.747Z] The best model improves the baseline by 14.52%. [2025-10-02T04:33:47.747Z] Top recommended movies for user id 72: [2025-10-02T04:33:47.747Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:33:47.747Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:33:47.747Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:33:47.747Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:33:47.747Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:33:47.747Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (24132.757 ms) ====== [2025-10-02T04:33:47.747Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-10-02T04:33:47.747Z] GC before operation: completed in 176.735 ms, heap usage 385.370 MB -> 92.444 MB. [2025-10-02T04:33:52.076Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:33:55.103Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:33:59.257Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:34:02.310Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:34:04.266Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:34:06.390Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:34:07.343Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:34:09.298Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:34:10.247Z] 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. [2025-10-02T04:34:10.247Z] The best model improves the baseline by 14.52%. [2025-10-02T04:34:10.247Z] Top recommended movies for user id 72: [2025-10-02T04:34:10.247Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:34:10.247Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:34:10.247Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:34:10.247Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:34:10.247Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:34:10.247Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (22137.042 ms) ====== [2025-10-02T04:34:10.247Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-10-02T04:34:10.247Z] GC before operation: completed in 180.167 ms, heap usage 494.303 MB -> 94.756 MB. [2025-10-02T04:34:14.400Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:34:17.418Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:34:20.446Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:34:23.459Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:34:25.413Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:34:28.077Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:34:30.031Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:34:32.000Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:34:32.000Z] 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. [2025-10-02T04:34:32.000Z] The best model improves the baseline by 14.52%. [2025-10-02T04:34:32.000Z] Top recommended movies for user id 72: [2025-10-02T04:34:32.000Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:34:32.000Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:34:32.000Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:34:32.000Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:34:32.000Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:34:32.000Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (21971.087 ms) ====== [2025-10-02T04:34:32.000Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-10-02T04:34:32.951Z] GC before operation: completed in 172.922 ms, heap usage 433.203 MB -> 93.063 MB. [2025-10-02T04:34:35.972Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:34:38.992Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:34:42.054Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:34:45.076Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:34:47.052Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:34:49.013Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:34:50.969Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:34:52.924Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:34:52.924Z] 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. [2025-10-02T04:34:52.924Z] The best model improves the baseline by 14.52%. [2025-10-02T04:34:53.877Z] Top recommended movies for user id 72: [2025-10-02T04:34:53.877Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:34:53.877Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:34:53.877Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:34:53.877Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:34:53.877Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:34:53.877Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20975.857 ms) ====== [2025-10-02T04:34:53.877Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-10-02T04:34:53.877Z] GC before operation: completed in 185.379 ms, heap usage 769.686 MB -> 94.184 MB. [2025-10-02T04:34:56.903Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:35:00.003Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:35:03.028Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:35:06.043Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:35:07.999Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:35:09.955Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:35:11.937Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:35:13.894Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:35:13.894Z] 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. [2025-10-02T04:35:13.894Z] The best model improves the baseline by 14.52%. [2025-10-02T04:35:14.843Z] Top recommended movies for user id 72: [2025-10-02T04:35:14.843Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:35:14.843Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:35:14.843Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:35:14.843Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:35:14.843Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:35:14.843Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20657.553 ms) ====== [2025-10-02T04:35:14.843Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-10-02T04:35:14.843Z] GC before operation: completed in 169.547 ms, heap usage 287.855 MB -> 90.569 MB. [2025-10-02T04:35:17.864Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:35:20.881Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:35:23.902Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:35:26.924Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:35:29.233Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:35:30.535Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:35:33.559Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:35:34.514Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:35:35.470Z] 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. [2025-10-02T04:35:35.470Z] The best model improves the baseline by 14.52%. [2025-10-02T04:35:35.470Z] Top recommended movies for user id 72: [2025-10-02T04:35:35.470Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:35:35.470Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:35:35.470Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:35:35.470Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:35:35.470Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:35:35.470Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20850.108 ms) ====== [2025-10-02T04:35:35.470Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-10-02T04:35:35.470Z] GC before operation: completed in 176.258 ms, heap usage 499.649 MB -> 90.598 MB. [2025-10-02T04:35:39.619Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:35:42.646Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:35:45.669Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:35:48.681Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:35:50.635Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:35:52.593Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:35:54.545Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:35:56.504Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:35:56.504Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-10-02T04:35:56.504Z] The best model improves the baseline by 14.52%. [2025-10-02T04:35:56.504Z] Top recommended movies for user id 72: [2025-10-02T04:35:56.504Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:35:56.504Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:35:56.504Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:35:56.504Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:35:56.504Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:35:56.504Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (21006.301 ms) ====== [2025-10-02T04:35:56.504Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-10-02T04:35:56.504Z] GC before operation: completed in 169.092 ms, heap usage 180.264 MB -> 90.290 MB. [2025-10-02T04:36:00.658Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:36:03.672Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:36:06.688Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:36:09.709Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:36:10.661Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:36:12.621Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:36:14.610Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:36:16.584Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:36:16.584Z] 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. [2025-10-02T04:36:16.584Z] The best model improves the baseline by 14.52%. [2025-10-02T04:36:17.538Z] Top recommended movies for user id 72: [2025-10-02T04:36:17.538Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:36:17.538Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:36:17.538Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:36:17.538Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:36:17.538Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:36:17.538Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (20495.112 ms) ====== [2025-10-02T04:36:17.538Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-10-02T04:36:17.538Z] GC before operation: completed in 172.475 ms, heap usage 755.433 MB -> 94.205 MB. [2025-10-02T04:36:20.567Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:36:24.727Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:36:27.743Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:36:31.182Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:36:33.152Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:36:35.109Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:36:37.069Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:36:39.028Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:36:39.028Z] 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. [2025-10-02T04:36:39.028Z] The best model improves the baseline by 14.52%. [2025-10-02T04:36:39.982Z] Top recommended movies for user id 72: [2025-10-02T04:36:39.982Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:36:39.982Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:36:39.982Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:36:39.982Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:36:39.982Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:36:39.982Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (22079.018 ms) ====== [2025-10-02T04:36:39.982Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-10-02T04:36:39.982Z] GC before operation: completed in 179.454 ms, heap usage 717.927 MB -> 96.539 MB. [2025-10-02T04:36:44.137Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-10-02T04:36:47.159Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-10-02T04:36:50.181Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-10-02T04:36:53.195Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-10-02T04:36:55.156Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-10-02T04:36:57.110Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-10-02T04:36:59.061Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-10-02T04:37:01.016Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-10-02T04:37:01.016Z] 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. [2025-10-02T04:37:01.016Z] The best model improves the baseline by 14.52%. [2025-10-02T04:37:01.964Z] Top recommended movies for user id 72: [2025-10-02T04:37:01.964Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-10-02T04:37:01.964Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-10-02T04:37:01.964Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-10-02T04:37:01.964Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-10-02T04:37:01.964Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-10-02T04:37:01.964Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (21950.686 ms) ====== [2025-10-02T04:37:02.911Z] ----------------------------------- [2025-10-02T04:37:02.911Z] renaissance-movie-lens_0_PASSED [2025-10-02T04:37:02.911Z] ----------------------------------- [2025-10-02T04:37:02.911Z] [2025-10-02T04:37:02.911Z] TEST TEARDOWN: [2025-10-02T04:37:02.911Z] Nothing to be done for teardown. [2025-10-02T04:37:02.911Z] renaissance-movie-lens_0 Finish Time: Thu Oct 2 04:37:02 2025 Epoch Time (ms): 1759379822519