[2025-06-27T21:46:52.056Z] Running test renaissance-movie-lens_0 ... [2025-06-27T21:46:52.056Z] =============================================== [2025-06-27T21:46:52.056Z] renaissance-movie-lens_0 Start Time: Fri Jun 27 21:46:51 2025 Epoch Time (ms): 1751060811485 [2025-06-27T21:46:52.056Z] variation: NoOptions [2025-06-27T21:46:52.056Z] JVM_OPTIONS: [2025-06-27T21:46:52.056Z] { \ [2025-06-27T21:46:52.056Z] echo ""; echo "TEST SETUP:"; \ [2025-06-27T21:46:52.056Z] echo "Nothing to be done for setup."; \ [2025-06-27T21:46:52.056Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17510586499301/renaissance-movie-lens_0"; \ [2025-06-27T21:46:52.056Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17510586499301/renaissance-movie-lens_0"; \ [2025-06-27T21:46:52.056Z] echo ""; echo "TESTING:"; \ [2025-06-27T21:46:52.056Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17510586499301/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-27T21:46:52.057Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17510586499301/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-27T21:46:52.057Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-27T21:46:52.057Z] echo "Nothing to be done for teardown."; \ [2025-06-27T21:46:52.057Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_aarch64_alpine-linux/aqa-tests/TKG/../TKG/output_17510586499301/TestTargetResult"; [2025-06-27T21:46:52.057Z] [2025-06-27T21:46:52.057Z] TEST SETUP: [2025-06-27T21:46:52.057Z] Nothing to be done for setup. [2025-06-27T21:46:52.057Z] [2025-06-27T21:46:52.057Z] TESTING: [2025-06-27T21:46:57.769Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-06-27T21:47:06.891Z] 21:47:06.468 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB. [2025-06-27T21:47:12.759Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-27T21:47:14.427Z] Training: 60056, validation: 20285, test: 19854 [2025-06-27T21:47:14.427Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-27T21:47:14.427Z] GC before operation: completed in 204.767 ms, heap usage 146.961 MB -> 75.461 MB. [2025-06-27T21:47:26.727Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:47:34.192Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:47:40.017Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:47:44.658Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:47:47.256Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:47:49.878Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:47:52.425Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:47:55.025Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:47:55.826Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:47:55.826Z] The best model improves the baseline by 14.34%. [2025-06-27T21:47:55.826Z] Top recommended movies for user id 72: [2025-06-27T21:47:55.826Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:47:55.826Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:47:55.826Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:47:55.826Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:47:55.826Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:47:55.826Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (41674.591 ms) ====== [2025-06-27T21:47:55.826Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-27T21:47:56.659Z] GC before operation: completed in 263.911 ms, heap usage 391.799 MB -> 89.239 MB. [2025-06-27T21:48:01.344Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:48:04.866Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:48:08.491Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:48:12.527Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:48:14.161Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:48:15.794Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:48:17.420Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:48:19.978Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:48:19.978Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:48:19.978Z] The best model improves the baseline by 14.34%. [2025-06-27T21:48:19.978Z] Top recommended movies for user id 72: [2025-06-27T21:48:19.978Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:48:19.978Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:48:19.978Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:48:19.978Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:48:19.978Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:48:19.978Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23945.096 ms) ====== [2025-06-27T21:48:19.978Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-27T21:48:20.764Z] GC before operation: completed in 283.761 ms, heap usage 144.579 MB -> 87.481 MB. [2025-06-27T21:48:24.274Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:48:26.795Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:48:29.316Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:48:32.827Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:48:34.459Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:48:36.095Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:48:38.626Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:48:40.261Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:48:40.261Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:48:40.261Z] The best model improves the baseline by 14.34%. [2025-06-27T21:48:40.261Z] Top recommended movies for user id 72: [2025-06-27T21:48:40.261Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:48:40.261Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:48:40.261Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:48:40.261Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:48:40.261Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:48:40.261Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19984.344 ms) ====== [2025-06-27T21:48:40.261Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-27T21:48:41.059Z] GC before operation: completed in 250.202 ms, heap usage 404.902 MB -> 88.480 MB. [2025-06-27T21:48:43.616Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:48:47.102Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:48:49.657Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:48:52.194Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:48:54.347Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:48:56.035Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:48:57.655Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:48:59.295Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:48:59.295Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:48:59.295Z] The best model improves the baseline by 14.34%. [2025-06-27T21:48:59.295Z] Top recommended movies for user id 72: [2025-06-27T21:48:59.295Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:48:59.295Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:48:59.295Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:48:59.295Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:48:59.295Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:48:59.295Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (18679.081 ms) ====== [2025-06-27T21:48:59.295Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-27T21:48:59.295Z] GC before operation: completed in 220.808 ms, heap usage 545.639 MB -> 92.254 MB. [2025-06-27T21:49:02.798Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:49:05.323Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:49:07.867Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:49:10.387Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:49:12.907Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:49:13.735Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:49:16.257Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:49:17.893Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:49:17.893Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:49:17.893Z] The best model improves the baseline by 14.34%. [2025-06-27T21:49:17.893Z] Top recommended movies for user id 72: [2025-06-27T21:49:17.893Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:49:17.893Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:49:17.893Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:49:17.893Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:49:17.893Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:49:17.893Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18314.649 ms) ====== [2025-06-27T21:49:17.893Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-27T21:49:17.893Z] GC before operation: completed in 201.805 ms, heap usage 408.641 MB -> 88.746 MB. [2025-06-27T21:49:21.384Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:49:23.919Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:49:26.440Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:49:28.992Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:49:30.659Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:49:33.192Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:49:34.819Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:49:35.614Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:49:36.925Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:49:36.925Z] The best model improves the baseline by 14.34%. [2025-06-27T21:49:36.925Z] Top recommended movies for user id 72: [2025-06-27T21:49:36.925Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:49:36.925Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:49:36.925Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:49:36.925Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:49:36.925Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:49:36.925Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18210.716 ms) ====== [2025-06-27T21:49:36.925Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-27T21:49:36.925Z] GC before operation: completed in 236.126 ms, heap usage 242.411 MB -> 88.862 MB. [2025-06-27T21:49:39.460Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:49:43.082Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:49:45.618Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:49:49.106Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:49:50.727Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:49:52.346Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:49:54.863Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:49:56.493Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:49:57.290Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:49:57.290Z] The best model improves the baseline by 14.34%. [2025-06-27T21:49:57.290Z] Top recommended movies for user id 72: [2025-06-27T21:49:57.291Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:49:57.291Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:49:57.291Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:49:57.291Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:49:57.291Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:49:57.291Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20529.626 ms) ====== [2025-06-27T21:49:57.291Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-27T21:49:57.291Z] GC before operation: completed in 206.764 ms, heap usage 250.179 MB -> 88.877 MB. [2025-06-27T21:49:59.804Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:50:02.325Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:50:05.823Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:50:07.443Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:50:09.065Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:50:10.688Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:50:12.311Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:50:13.934Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:50:14.723Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:50:14.723Z] The best model improves the baseline by 14.34%. [2025-06-27T21:50:14.723Z] Top recommended movies for user id 72: [2025-06-27T21:50:14.723Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:50:14.723Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:50:14.723Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:50:14.723Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:50:14.723Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:50:14.723Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17387.878 ms) ====== [2025-06-27T21:50:14.723Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-27T21:50:14.723Z] GC before operation: completed in 212.922 ms, heap usage 230.034 MB -> 89.149 MB. [2025-06-27T21:50:17.806Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:50:20.347Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:50:22.870Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:50:26.355Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:50:27.141Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:50:28.762Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:50:30.382Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:50:32.004Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:50:32.004Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:50:32.004Z] The best model improves the baseline by 14.34%. [2025-06-27T21:50:32.789Z] Top recommended movies for user id 72: [2025-06-27T21:50:32.789Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:50:32.789Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:50:32.789Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:50:32.789Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:50:32.789Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:50:32.789Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17495.330 ms) ====== [2025-06-27T21:50:32.789Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-27T21:50:32.789Z] GC before operation: completed in 214.348 ms, heap usage 352.711 MB -> 89.158 MB. [2025-06-27T21:50:35.308Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:50:37.827Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:50:40.344Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:50:42.891Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:50:44.525Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:50:46.152Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:50:47.772Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:50:49.394Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:50:49.394Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:50:49.394Z] The best model improves the baseline by 14.34%. [2025-06-27T21:50:50.180Z] Top recommended movies for user id 72: [2025-06-27T21:50:50.180Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:50:50.180Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:50:50.180Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:50:50.180Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:50:50.180Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:50:50.180Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (17217.542 ms) ====== [2025-06-27T21:50:50.180Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-27T21:50:50.180Z] GC before operation: completed in 183.429 ms, heap usage 248.356 MB -> 89.178 MB. [2025-06-27T21:50:52.831Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:50:55.349Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:50:58.397Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:51:00.019Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:51:01.640Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:51:03.268Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:51:04.890Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:51:06.511Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:51:06.511Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:51:06.511Z] The best model improves the baseline by 14.34%. [2025-06-27T21:51:07.297Z] Top recommended movies for user id 72: [2025-06-27T21:51:07.297Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:51:07.297Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:51:07.297Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:51:07.297Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:51:07.297Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:51:07.297Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16882.768 ms) ====== [2025-06-27T21:51:07.297Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-27T21:51:07.297Z] GC before operation: completed in 173.533 ms, heap usage 427.560 MB -> 89.178 MB. [2025-06-27T21:51:09.816Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:51:12.394Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:51:14.947Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:51:17.498Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:51:18.288Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:51:19.911Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:51:21.543Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:51:23.167Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:51:23.167Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:51:23.167Z] The best model improves the baseline by 14.34%. [2025-06-27T21:51:23.167Z] Top recommended movies for user id 72: [2025-06-27T21:51:23.167Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:51:23.167Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:51:23.167Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:51:23.167Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:51:23.167Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:51:23.167Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16376.338 ms) ====== [2025-06-27T21:51:23.167Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-27T21:51:23.961Z] GC before operation: completed in 187.596 ms, heap usage 211.024 MB -> 89.025 MB. [2025-06-27T21:51:26.484Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:51:29.024Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:51:31.541Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:51:34.065Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:51:35.698Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:51:37.332Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:51:39.000Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:51:40.315Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:51:40.315Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:51:40.315Z] The best model improves the baseline by 14.34%. [2025-06-27T21:51:40.315Z] Top recommended movies for user id 72: [2025-06-27T21:51:40.315Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:51:40.315Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:51:40.315Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:51:40.315Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:51:40.315Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:51:40.315Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16717.674 ms) ====== [2025-06-27T21:51:40.315Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-27T21:51:40.315Z] GC before operation: completed in 172.117 ms, heap usage 202.918 MB -> 89.094 MB. [2025-06-27T21:51:43.804Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:51:45.433Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:51:47.956Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:51:50.470Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:51:52.138Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:51:53.787Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:51:55.411Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:51:57.041Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:51:57.041Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:51:57.041Z] The best model improves the baseline by 14.34%. [2025-06-27T21:51:57.041Z] Top recommended movies for user id 72: [2025-06-27T21:51:57.041Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:51:57.041Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:51:57.041Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:51:57.041Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:51:57.041Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:51:57.041Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16635.643 ms) ====== [2025-06-27T21:51:57.041Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-27T21:51:57.041Z] GC before operation: completed in 171.053 ms, heap usage 498.276 MB -> 92.698 MB. [2025-06-27T21:52:00.560Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:52:02.188Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:52:05.685Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:52:08.208Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:52:08.998Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:52:10.620Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:52:12.241Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:52:13.863Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:52:13.863Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:52:13.863Z] The best model improves the baseline by 14.34%. [2025-06-27T21:52:13.863Z] Top recommended movies for user id 72: [2025-06-27T21:52:13.863Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:52:13.863Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:52:13.863Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:52:13.863Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:52:13.863Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:52:13.863Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16838.239 ms) ====== [2025-06-27T21:52:13.863Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-27T21:52:14.649Z] GC before operation: completed in 165.684 ms, heap usage 230.798 MB -> 89.270 MB. [2025-06-27T21:52:17.165Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:52:20.240Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:52:21.861Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:52:24.378Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:52:25.163Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:52:26.793Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:52:30.236Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:52:30.236Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:52:30.236Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:52:30.236Z] The best model improves the baseline by 14.34%. [2025-06-27T21:52:30.236Z] Top recommended movies for user id 72: [2025-06-27T21:52:30.236Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:52:30.236Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:52:30.236Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:52:30.236Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:52:30.236Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:52:30.236Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15936.695 ms) ====== [2025-06-27T21:52:30.236Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-27T21:52:30.236Z] GC before operation: completed in 156.314 ms, heap usage 359.191 MB -> 89.283 MB. [2025-06-27T21:52:32.758Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:52:35.277Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:52:37.792Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:52:40.311Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:52:41.950Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:52:43.580Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:52:45.226Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:52:46.862Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:52:46.862Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:52:46.862Z] The best model improves the baseline by 14.34%. [2025-06-27T21:52:47.662Z] Top recommended movies for user id 72: [2025-06-27T21:52:47.662Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:52:47.662Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:52:47.662Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:52:47.662Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:52:47.662Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:52:47.662Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16892.170 ms) ====== [2025-06-27T21:52:47.662Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-27T21:52:47.662Z] GC before operation: completed in 157.399 ms, heap usage 251.638 MB -> 89.202 MB. [2025-06-27T21:52:50.189Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:52:52.745Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:52:56.260Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:52:58.783Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:52:59.569Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:53:01.224Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:53:02.556Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:53:04.181Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:53:04.991Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:53:04.991Z] The best model improves the baseline by 14.34%. [2025-06-27T21:53:04.991Z] Top recommended movies for user id 72: [2025-06-27T21:53:04.991Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:53:04.991Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:53:04.991Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:53:04.991Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:53:04.991Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:53:04.991Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17544.748 ms) ====== [2025-06-27T21:53:04.991Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-27T21:53:04.991Z] GC before operation: completed in 172.833 ms, heap usage 358.411 MB -> 89.339 MB. [2025-06-27T21:53:08.495Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:53:11.983Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:53:15.494Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:53:18.025Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:53:22.196Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:53:22.196Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:53:23.819Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:53:25.438Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:53:25.438Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:53:25.438Z] The best model improves the baseline by 14.34%. [2025-06-27T21:53:25.438Z] Top recommended movies for user id 72: [2025-06-27T21:53:25.438Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:53:25.438Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:53:25.438Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:53:25.438Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:53:25.438Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:53:25.438Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (20516.389 ms) ====== [2025-06-27T21:53:25.438Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-27T21:53:26.223Z] GC before operation: completed in 174.411 ms, heap usage 216.783 MB -> 89.111 MB. [2025-06-27T21:53:28.741Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-27T21:53:31.260Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-27T21:53:33.781Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-27T21:53:35.404Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-27T21:53:37.024Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-27T21:53:38.650Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-27T21:53:40.326Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-27T21:53:43.374Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-27T21:53:43.374Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-27T21:53:43.374Z] The best model improves the baseline by 14.34%. [2025-06-27T21:53:43.374Z] Top recommended movies for user id 72: [2025-06-27T21:53:43.374Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-27T21:53:43.374Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-27T21:53:43.374Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-27T21:53:43.374Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-27T21:53:43.374Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-27T21:53:43.374Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16232.399 ms) ====== [2025-06-27T21:53:43.374Z] ----------------------------------- [2025-06-27T21:53:43.374Z] renaissance-movie-lens_0_PASSED [2025-06-27T21:53:43.374Z] ----------------------------------- [2025-06-27T21:53:43.374Z] [2025-06-27T21:53:43.374Z] TEST TEARDOWN: [2025-06-27T21:53:43.374Z] Nothing to be done for teardown. [2025-06-27T21:53:43.374Z] renaissance-movie-lens_0 Finish Time: Fri Jun 27 21:53:42 2025 Epoch Time (ms): 1751061222663