[2025-08-29T09:26:38.985Z] Running test renaissance-movie-lens_0 ... [2025-08-29T09:26:38.985Z] =============================================== [2025-08-29T09:26:38.985Z] renaissance-movie-lens_0 Start Time: Fri Aug 29 09:26:38 2025 Epoch Time (ms): 1756459598138 [2025-08-29T09:26:38.985Z] variation: NoOptions [2025-08-29T09:26:38.985Z] JVM_OPTIONS: [2025-08-29T09:26:38.985Z] { \ [2025-08-29T09:26:38.985Z] echo ""; echo "TEST SETUP:"; \ [2025-08-29T09:26:38.985Z] echo "Nothing to be done for setup."; \ [2025-08-29T09:26:38.985Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17564581767989/renaissance-movie-lens_0"; \ [2025-08-29T09:26:38.985Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17564581767989/renaissance-movie-lens_0"; \ [2025-08-29T09:26:38.985Z] echo ""; echo "TESTING:"; \ [2025-08-29T09:26:38.985Z] "/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_17564581767989/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-08-29T09:26:38.985Z] 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_17564581767989/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-08-29T09:26:38.985Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-08-29T09:26:38.985Z] echo "Nothing to be done for teardown."; \ [2025-08-29T09:26:38.985Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17564581767989/TestTargetResult"; [2025-08-29T09:26:38.985Z] [2025-08-29T09:26:38.985Z] TEST SETUP: [2025-08-29T09:26:38.985Z] Nothing to be done for setup. [2025-08-29T09:26:38.985Z] [2025-08-29T09:26:38.985Z] TESTING: [2025-08-29T09:26:44.401Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-08-29T09:26:51.130Z] 09:26:49.714 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-08-29T09:26:52.091Z] Got 100004 ratings from 671 users on 9066 movies. [2025-08-29T09:26:52.091Z] Training: 60056, validation: 20285, test: 19854 [2025-08-29T09:26:52.091Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-08-29T09:26:53.047Z] GC before operation: completed in 125.342 ms, heap usage 383.940 MB -> 75.841 MB. [2025-08-29T09:26:57.947Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:27:00.977Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:27:04.007Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:27:07.054Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:27:09.017Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:27:09.972Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:27:11.935Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:27:13.901Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:27:13.901Z] 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. [2025-08-29T09:27:13.901Z] The best model improves the baseline by 14.52%. [2025-08-29T09:27:13.901Z] Top recommended movies for user id 72: [2025-08-29T09:27:13.901Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:27:13.901Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:27:13.901Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:27:13.901Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:27:13.901Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:27:13.901Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21648.336 ms) ====== [2025-08-29T09:27:13.901Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-08-29T09:27:14.857Z] GC before operation: completed in 153.858 ms, heap usage 718.387 MB -> 93.088 MB. [2025-08-29T09:27:16.823Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:27:19.854Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:27:22.892Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:27:25.033Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:27:26.998Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:27:27.959Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:27:29.964Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:27:31.928Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:27:31.928Z] 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. [2025-08-29T09:27:31.928Z] The best model improves the baseline by 14.52%. [2025-08-29T09:27:31.928Z] Top recommended movies for user id 72: [2025-08-29T09:27:31.928Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:27:31.928Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:27:31.928Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:27:31.928Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:27:31.928Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:27:31.928Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17715.642 ms) ====== [2025-08-29T09:27:31.928Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-08-29T09:27:31.928Z] GC before operation: completed in 132.752 ms, heap usage 365.567 MB -> 88.921 MB. [2025-08-29T09:27:34.957Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:27:37.991Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:27:39.966Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:27:43.005Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:27:43.962Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:27:45.923Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:27:47.888Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:27:48.847Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:27:49.806Z] 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. [2025-08-29T09:27:49.806Z] The best model improves the baseline by 14.52%. [2025-08-29T09:27:49.806Z] Top recommended movies for user id 72: [2025-08-29T09:27:49.806Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:27:49.806Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:27:49.806Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:27:49.806Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:27:49.806Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:27:49.806Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17295.229 ms) ====== [2025-08-29T09:27:49.806Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-08-29T09:27:49.806Z] GC before operation: completed in 153.991 ms, heap usage 360.839 MB -> 89.619 MB. [2025-08-29T09:27:52.515Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:27:54.477Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:27:57.507Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:27:59.648Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:28:01.613Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:28:02.571Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:28:04.552Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:28:05.507Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:28:06.463Z] 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. [2025-08-29T09:28:06.463Z] The best model improves the baseline by 14.52%. [2025-08-29T09:28:06.463Z] Top recommended movies for user id 72: [2025-08-29T09:28:06.463Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:28:06.463Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:28:06.463Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:28:06.463Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:28:06.463Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:28:06.463Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16633.116 ms) ====== [2025-08-29T09:28:06.463Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-08-29T09:28:06.463Z] GC before operation: completed in 127.990 ms, heap usage 365.694 MB -> 89.888 MB. [2025-08-29T09:28:08.427Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:28:11.460Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:28:13.427Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:28:15.391Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:28:17.369Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:28:18.326Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:28:19.282Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:28:21.260Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:28:21.260Z] 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. [2025-08-29T09:28:21.261Z] The best model improves the baseline by 14.52%. [2025-08-29T09:28:21.261Z] Top recommended movies for user id 72: [2025-08-29T09:28:21.261Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:28:21.261Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:28:21.261Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:28:21.261Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:28:21.261Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:28:21.261Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15071.436 ms) ====== [2025-08-29T09:28:21.261Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-08-29T09:28:21.261Z] GC before operation: completed in 123.337 ms, heap usage 301.196 MB -> 89.762 MB. [2025-08-29T09:28:24.381Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:28:26.351Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:28:28.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:28:31.360Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:28:32.320Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:28:34.284Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:28:35.242Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:28:37.211Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:28:37.211Z] 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. [2025-08-29T09:28:37.211Z] The best model improves the baseline by 14.52%. [2025-08-29T09:28:37.211Z] Top recommended movies for user id 72: [2025-08-29T09:28:37.211Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:28:37.211Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:28:37.211Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:28:37.211Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:28:37.211Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:28:37.211Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15659.322 ms) ====== [2025-08-29T09:28:37.211Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-08-29T09:28:37.211Z] GC before operation: completed in 120.298 ms, heap usage 120.015 MB -> 89.841 MB. [2025-08-29T09:28:39.177Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:28:42.208Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:28:44.171Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:28:46.135Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:28:49.175Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:28:49.175Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:28:51.138Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:28:52.095Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:28:53.053Z] 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. [2025-08-29T09:28:53.053Z] The best model improves the baseline by 14.52%. [2025-08-29T09:28:53.053Z] Top recommended movies for user id 72: [2025-08-29T09:28:53.053Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:28:53.053Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:28:53.053Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:28:53.053Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:28:53.053Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:28:53.053Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15342.537 ms) ====== [2025-08-29T09:28:53.053Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-08-29T09:28:53.053Z] GC before operation: completed in 171.733 ms, heap usage 414.510 MB -> 90.215 MB. [2025-08-29T09:28:55.019Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:28:56.982Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:29:00.013Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:29:01.978Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:29:03.942Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:29:04.900Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:29:06.864Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:29:07.820Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:29:07.820Z] 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. [2025-08-29T09:29:07.820Z] The best model improves the baseline by 14.52%. [2025-08-29T09:29:08.775Z] Top recommended movies for user id 72: [2025-08-29T09:29:08.775Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:29:08.775Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:29:08.775Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:29:08.775Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:29:08.775Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:29:08.775Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15405.188 ms) ====== [2025-08-29T09:29:08.775Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-08-29T09:29:08.775Z] GC before operation: completed in 141.274 ms, heap usage 297.235 MB -> 90.204 MB. [2025-08-29T09:29:10.741Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:29:12.707Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:29:15.732Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:29:17.701Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:29:19.666Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:29:20.630Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:29:22.593Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:29:23.551Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:29:23.551Z] 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. [2025-08-29T09:29:24.563Z] The best model improves the baseline by 14.52%. [2025-08-29T09:29:24.563Z] Top recommended movies for user id 72: [2025-08-29T09:29:24.563Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:29:24.563Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:29:24.563Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:29:24.563Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:29:24.563Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:29:24.563Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15698.854 ms) ====== [2025-08-29T09:29:24.563Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-08-29T09:29:24.563Z] GC before operation: completed in 142.288 ms, heap usage 359.272 MB -> 90.257 MB. [2025-08-29T09:29:26.525Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:29:28.494Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:29:30.456Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:29:32.418Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:29:34.385Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:29:35.344Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:29:36.304Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:29:38.266Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:29:38.266Z] 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. [2025-08-29T09:29:38.266Z] The best model improves the baseline by 14.52%. [2025-08-29T09:29:38.266Z] Top recommended movies for user id 72: [2025-08-29T09:29:38.266Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:29:38.266Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:29:38.266Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:29:38.266Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:29:38.267Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:29:38.267Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13945.559 ms) ====== [2025-08-29T09:29:38.267Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-08-29T09:29:38.267Z] GC before operation: completed in 132.974 ms, heap usage 264.348 MB -> 90.298 MB. [2025-08-29T09:29:40.288Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:29:43.319Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:29:45.325Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:29:47.284Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:29:48.240Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:29:49.206Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:29:51.170Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:29:52.126Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:29:53.081Z] 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. [2025-08-29T09:29:53.081Z] The best model improves the baseline by 14.52%. [2025-08-29T09:29:53.081Z] Top recommended movies for user id 72: [2025-08-29T09:29:53.081Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:29:53.081Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:29:53.081Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:29:53.081Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:29:53.081Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:29:53.081Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14359.656 ms) ====== [2025-08-29T09:29:53.081Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-08-29T09:29:53.081Z] GC before operation: completed in 164.506 ms, heap usage 238.596 MB -> 89.942 MB. [2025-08-29T09:29:55.051Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:29:57.012Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:29:58.976Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:30:02.016Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:30:03.037Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:30:03.993Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:30:05.961Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:30:06.917Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:30:06.917Z] 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. [2025-08-29T09:30:07.873Z] The best model improves the baseline by 14.52%. [2025-08-29T09:30:07.873Z] Top recommended movies for user id 72: [2025-08-29T09:30:07.873Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:30:07.873Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:30:07.873Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:30:07.873Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:30:07.873Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:30:07.873Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14619.556 ms) ====== [2025-08-29T09:30:07.873Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-08-29T09:30:07.873Z] GC before operation: completed in 153.304 ms, heap usage 293.168 MB -> 90.269 MB. [2025-08-29T09:30:09.833Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:30:12.864Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:30:14.824Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:30:17.919Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:30:18.874Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:30:20.836Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:30:21.791Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:30:23.752Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:30:23.752Z] 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. [2025-08-29T09:30:23.752Z] The best model improves the baseline by 14.52%. [2025-08-29T09:30:24.709Z] Top recommended movies for user id 72: [2025-08-29T09:30:24.709Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:30:24.709Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:30:24.709Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:30:24.709Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:30:24.709Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:30:24.709Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16561.477 ms) ====== [2025-08-29T09:30:24.709Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-08-29T09:30:24.709Z] GC before operation: completed in 146.373 ms, heap usage 119.963 MB -> 90.244 MB. [2025-08-29T09:30:26.677Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:30:28.639Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:30:31.666Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:30:34.695Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:30:35.651Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:30:38.499Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:30:38.499Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:30:40.462Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:30:40.462Z] 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. [2025-08-29T09:30:40.462Z] The best model improves the baseline by 14.52%. [2025-08-29T09:30:40.462Z] Top recommended movies for user id 72: [2025-08-29T09:30:40.462Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:30:40.462Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:30:40.462Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:30:40.462Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:30:40.462Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:30:40.462Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16299.591 ms) ====== [2025-08-29T09:30:40.462Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-08-29T09:30:40.462Z] GC before operation: completed in 136.777 ms, heap usage 352.740 MB -> 90.375 MB. [2025-08-29T09:30:43.496Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:30:45.463Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:30:47.427Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:30:49.392Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:30:51.354Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:30:52.312Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:30:54.277Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:30:55.234Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:30:55.234Z] 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. [2025-08-29T09:30:55.234Z] The best model improves the baseline by 14.52%. [2025-08-29T09:30:56.191Z] Top recommended movies for user id 72: [2025-08-29T09:30:56.191Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:30:56.191Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:30:56.191Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:30:56.191Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:30:56.191Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:30:56.191Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14831.333 ms) ====== [2025-08-29T09:30:56.191Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-08-29T09:30:56.191Z] GC before operation: completed in 133.610 ms, heap usage 203.002 MB -> 90.254 MB. [2025-08-29T09:30:58.154Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:31:00.119Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:31:03.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:31:05.110Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:31:07.074Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:31:08.030Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:31:09.995Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:31:10.952Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:31:11.909Z] 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. [2025-08-29T09:31:11.909Z] The best model improves the baseline by 14.52%. [2025-08-29T09:31:11.909Z] Top recommended movies for user id 72: [2025-08-29T09:31:11.909Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:31:11.909Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:31:11.909Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:31:11.909Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:31:11.909Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:31:11.909Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15853.595 ms) ====== [2025-08-29T09:31:11.909Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-08-29T09:31:11.909Z] GC before operation: completed in 150.509 ms, heap usage 323.477 MB -> 90.358 MB. [2025-08-29T09:31:13.870Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:31:16.900Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:31:18.871Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:31:20.836Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:31:22.804Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:31:23.761Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:31:25.724Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:31:27.690Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:31:27.690Z] 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. [2025-08-29T09:31:27.690Z] The best model improves the baseline by 14.52%. [2025-08-29T09:31:27.690Z] Top recommended movies for user id 72: [2025-08-29T09:31:27.690Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:31:27.690Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:31:27.690Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:31:27.690Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:31:27.690Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:31:27.690Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15893.247 ms) ====== [2025-08-29T09:31:27.690Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-08-29T09:31:27.690Z] GC before operation: completed in 135.962 ms, heap usage 227.266 MB -> 90.309 MB. [2025-08-29T09:31:30.721Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:31:33.041Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:31:35.391Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:31:37.355Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:31:38.323Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:31:40.291Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:31:41.247Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:31:43.212Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:31:43.212Z] 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. [2025-08-29T09:31:43.212Z] The best model improves the baseline by 14.52%. [2025-08-29T09:31:43.213Z] Top recommended movies for user id 72: [2025-08-29T09:31:43.213Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:31:43.213Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:31:43.213Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:31:43.213Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:31:43.213Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:31:43.213Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15717.479 ms) ====== [2025-08-29T09:31:43.213Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-08-29T09:31:44.193Z] GC before operation: completed in 133.011 ms, heap usage 346.102 MB -> 90.286 MB. [2025-08-29T09:31:46.165Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:31:48.128Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:31:50.159Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:31:52.121Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:31:54.084Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:31:55.042Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:31:57.007Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:31:57.965Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:31:57.965Z] 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. [2025-08-29T09:31:57.965Z] The best model improves the baseline by 14.52%. [2025-08-29T09:31:58.921Z] Top recommended movies for user id 72: [2025-08-29T09:31:58.921Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:31:58.921Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:31:58.921Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:31:58.921Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:31:58.921Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:31:58.921Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14826.307 ms) ====== [2025-08-29T09:31:58.921Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-08-29T09:31:58.921Z] GC before operation: completed in 139.104 ms, heap usage 445.904 MB -> 90.602 MB. [2025-08-29T09:32:00.885Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-08-29T09:32:03.913Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-08-29T09:32:05.875Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-08-29T09:32:07.840Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-08-29T09:32:09.804Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-08-29T09:32:10.762Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-08-29T09:32:12.739Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-08-29T09:32:13.694Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-08-29T09:32:14.651Z] 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. [2025-08-29T09:32:14.651Z] The best model improves the baseline by 14.52%. [2025-08-29T09:32:14.651Z] Top recommended movies for user id 72: [2025-08-29T09:32:14.651Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-08-29T09:32:14.651Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-08-29T09:32:14.651Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-08-29T09:32:14.651Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-08-29T09:32:14.651Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-08-29T09:32:14.651Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15770.782 ms) ====== [2025-08-29T09:32:14.651Z] ----------------------------------- [2025-08-29T09:32:14.651Z] renaissance-movie-lens_0_PASSED [2025-08-29T09:32:14.651Z] ----------------------------------- [2025-08-29T09:32:14.651Z] [2025-08-29T09:32:14.651Z] TEST TEARDOWN: [2025-08-29T09:32:14.651Z] Nothing to be done for teardown. [2025-08-29T09:32:14.651Z] renaissance-movie-lens_0 Finish Time: Fri Aug 29 09:32:14 2025 Epoch Time (ms): 1756459934408