[2025-07-02T13:57:56.706Z] Running test renaissance-movie-lens_0 ... [2025-07-02T13:57:56.706Z] =============================================== [2025-07-02T13:57:56.706Z] renaissance-movie-lens_0 Start Time: Wed Jul 2 13:57:55 2025 Epoch Time (ms): 1751464675155 [2025-07-02T13:57:56.706Z] variation: NoOptions [2025-07-02T13:57:56.706Z] JVM_OPTIONS: [2025-07-02T13:57:56.706Z] { \ [2025-07-02T13:57:56.706Z] echo ""; echo "TEST SETUP:"; \ [2025-07-02T13:57:56.706Z] echo "Nothing to be done for setup."; \ [2025-07-02T13:57:56.706Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17514634842621/renaissance-movie-lens_0"; \ [2025-07-02T13:57:56.706Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17514634842621/renaissance-movie-lens_0"; \ [2025-07-02T13:57:56.706Z] echo ""; echo "TESTING:"; \ [2025-07-02T13:57:56.706Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17514634842621/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-07-02T13:57:56.706Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17514634842621/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-07-02T13:57:56.706Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-07-02T13:57:56.706Z] echo "Nothing to be done for teardown."; \ [2025-07-02T13:57:56.706Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_aarch64_linux_testList_1/aqa-tests/TKG/../TKG/output_17514634842621/TestTargetResult"; [2025-07-02T13:57:56.706Z] [2025-07-02T13:57:56.706Z] TEST SETUP: [2025-07-02T13:57:56.706Z] Nothing to be done for setup. [2025-07-02T13:57:56.706Z] [2025-07-02T13:57:56.706Z] TESTING: [2025-07-02T13:58:03.065Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-07-02T13:58:12.645Z] 13:58:12.377 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB. [2025-07-02T13:58:16.140Z] Got 100004 ratings from 671 users on 9066 movies. [2025-07-02T13:58:17.024Z] Training: 60056, validation: 20285, test: 19854 [2025-07-02T13:58:17.024Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-07-02T13:58:17.429Z] GC before operation: completed in 119.084 ms, heap usage 159.862 MB -> 75.587 MB. [2025-07-02T13:58:29.280Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:58:34.708Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:58:39.989Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:58:43.376Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:58:45.950Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:58:48.507Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:58:50.431Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:58:53.004Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:58:53.004Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-07-02T13:58:53.004Z] The best model improves the baseline by 14.52%. [2025-07-02T13:58:53.400Z] Top recommended movies for user id 72: [2025-07-02T13:58:53.400Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T13:58:53.400Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T13:58:53.400Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T13:58:53.400Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T13:58:53.400Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T13:58:53.400Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (36259.345 ms) ====== [2025-07-02T13:58:53.400Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-07-02T13:58:53.800Z] GC before operation: completed in 131.334 ms, heap usage 404.390 MB -> 90.110 MB. [2025-07-02T13:58:58.015Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:59:01.380Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:59:04.685Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:59:08.948Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:59:10.863Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:59:12.810Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:59:15.365Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:59:17.315Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:59:17.315Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2025-07-02T13:59:17.315Z] The best model improves the baseline by 14.52%. [2025-07-02T13:59:17.778Z] Top recommended movies for user id 72: [2025-07-02T13:59:17.779Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T13:59:17.779Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T13:59:17.779Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T13:59:17.779Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T13:59:17.779Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T13:59:17.779Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (23971.969 ms) ====== [2025-07-02T13:59:17.779Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-07-02T13:59:17.779Z] GC before operation: completed in 131.730 ms, heap usage 328.254 MB -> 90.706 MB. [2025-07-02T13:59:21.519Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:59:25.815Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:59:30.072Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:59:32.699Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:59:35.264Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:59:37.201Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T13:59:39.104Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T13:59:41.052Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T13:59:41.443Z] 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. [2025-07-02T13:59:41.443Z] The best model improves the baseline by 14.52%. [2025-07-02T13:59:41.840Z] Top recommended movies for user id 72: [2025-07-02T13:59:41.840Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T13:59:41.840Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T13:59:41.840Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T13:59:41.840Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T13:59:41.840Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T13:59:41.840Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23920.305 ms) ====== [2025-07-02T13:59:41.840Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-07-02T13:59:41.840Z] GC before operation: completed in 127.857 ms, heap usage 307.846 MB -> 89.240 MB. [2025-07-02T13:59:46.051Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T13:59:48.663Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T13:59:51.986Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T13:59:55.326Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T13:59:57.904Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T13:59:59.304Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:00:01.856Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:00:03.275Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:00:03.675Z] 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. [2025-07-02T14:00:03.675Z] The best model improves the baseline by 14.52%. [2025-07-02T14:00:04.066Z] Top recommended movies for user id 72: [2025-07-02T14:00:04.066Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:00:04.066Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:00:04.066Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:00:04.066Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:00:04.066Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:00:04.066Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22275.208 ms) ====== [2025-07-02T14:00:04.066Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-07-02T14:00:04.066Z] GC before operation: completed in 132.683 ms, heap usage 345.956 MB -> 91.330 MB. [2025-07-02T14:00:08.430Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:00:11.789Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:00:15.162Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:00:18.481Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:00:20.404Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:00:22.373Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:00:24.278Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:00:26.240Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:00:26.630Z] 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. [2025-07-02T14:00:26.630Z] The best model improves the baseline by 14.52%. [2025-07-02T14:00:27.009Z] Top recommended movies for user id 72: [2025-07-02T14:00:27.009Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:00:27.009Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:00:27.009Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:00:27.009Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:00:27.009Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:00:27.009Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (22681.906 ms) ====== [2025-07-02T14:00:27.009Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-07-02T14:00:27.009Z] GC before operation: completed in 126.790 ms, heap usage 494.760 MB -> 91.993 MB. [2025-07-02T14:00:31.225Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:00:34.568Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:00:37.887Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:00:40.432Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:00:42.351Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:00:44.258Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:00:45.585Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:00:47.456Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:00:47.882Z] 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. [2025-07-02T14:00:47.882Z] The best model improves the baseline by 14.52%. [2025-07-02T14:00:48.282Z] Top recommended movies for user id 72: [2025-07-02T14:00:48.282Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:00:48.282Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:00:48.282Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:00:48.282Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:00:48.282Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:00:48.282Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (21103.258 ms) ====== [2025-07-02T14:00:48.282Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-07-02T14:00:48.282Z] GC before operation: completed in 131.927 ms, heap usage 769.712 MB -> 93.755 MB. [2025-07-02T14:00:51.634Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:00:54.184Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:00:57.678Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:01:00.303Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:01:02.215Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:01:03.569Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:01:05.470Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:01:07.361Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:01:07.740Z] 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. [2025-07-02T14:01:07.740Z] The best model improves the baseline by 14.52%. [2025-07-02T14:01:07.740Z] Top recommended movies for user id 72: [2025-07-02T14:01:07.740Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:01:07.740Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:01:07.740Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:01:07.740Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:01:07.740Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:01:07.740Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19561.284 ms) ====== [2025-07-02T14:01:07.740Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-07-02T14:01:07.740Z] GC before operation: completed in 134.611 ms, heap usage 140.283 MB -> 96.291 MB. [2025-07-02T14:01:11.033Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:01:13.593Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:01:16.919Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:01:19.476Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:01:20.821Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:01:22.712Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:01:24.602Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:01:26.519Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:01:26.519Z] 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. [2025-07-02T14:01:26.519Z] The best model improves the baseline by 14.52%. [2025-07-02T14:01:26.519Z] Top recommended movies for user id 72: [2025-07-02T14:01:26.519Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:01:26.519Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:01:26.519Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:01:26.519Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:01:26.948Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:01:26.948Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18787.489 ms) ====== [2025-07-02T14:01:26.948Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-07-02T14:01:26.948Z] GC before operation: completed in 127.641 ms, heap usage 184.272 MB -> 92.217 MB. [2025-07-02T14:01:30.248Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:01:32.844Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:01:35.589Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:01:38.165Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:01:40.040Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:01:41.950Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:01:43.282Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:01:45.190Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:01:45.190Z] 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. [2025-07-02T14:01:45.190Z] The best model improves the baseline by 14.52%. [2025-07-02T14:01:45.570Z] Top recommended movies for user id 72: [2025-07-02T14:01:45.570Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:01:45.570Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:01:45.570Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:01:45.570Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:01:45.570Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:01:45.570Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18729.682 ms) ====== [2025-07-02T14:01:45.570Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-07-02T14:01:45.570Z] GC before operation: completed in 122.487 ms, heap usage 235.188 MB -> 92.250 MB. [2025-07-02T14:01:48.919Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:01:51.462Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:01:54.044Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:01:56.661Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:01:58.659Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:02:00.570Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:02:01.916Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:02:03.800Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:02:04.189Z] 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. [2025-07-02T14:02:04.189Z] The best model improves the baseline by 14.52%. [2025-07-02T14:02:04.189Z] Top recommended movies for user id 72: [2025-07-02T14:02:04.189Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:02:04.189Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:02:04.189Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:02:04.189Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:02:04.189Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:02:04.189Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18522.904 ms) ====== [2025-07-02T14:02:04.189Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-07-02T14:02:04.189Z] GC before operation: completed in 127.688 ms, heap usage 679.413 MB -> 93.824 MB. [2025-07-02T14:02:07.531Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:02:10.108Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:02:13.407Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:02:15.979Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:02:17.883Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:02:19.889Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:02:21.807Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:02:23.230Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:02:23.702Z] 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. [2025-07-02T14:02:23.702Z] The best model improves the baseline by 14.52%. [2025-07-02T14:02:23.702Z] Top recommended movies for user id 72: [2025-07-02T14:02:23.702Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:02:23.702Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:02:23.702Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:02:23.702Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:02:23.702Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:02:23.702Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19443.500 ms) ====== [2025-07-02T14:02:23.702Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-07-02T14:02:24.231Z] GC before operation: completed in 131.178 ms, heap usage 210.855 MB -> 96.495 MB. [2025-07-02T14:02:26.781Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:02:30.088Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:02:32.654Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:02:35.185Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:02:37.110Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:02:38.430Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:02:40.312Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:02:42.260Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:02:42.260Z] 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. [2025-07-02T14:02:42.260Z] The best model improves the baseline by 14.52%. [2025-07-02T14:02:42.656Z] Top recommended movies for user id 72: [2025-07-02T14:02:42.656Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:02:42.656Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:02:42.656Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:02:42.656Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:02:42.656Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:02:42.656Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18549.750 ms) ====== [2025-07-02T14:02:42.656Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-07-02T14:02:42.656Z] GC before operation: completed in 130.392 ms, heap usage 238.236 MB -> 92.159 MB. [2025-07-02T14:02:45.214Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:02:48.578Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:02:51.245Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:02:53.784Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:02:55.700Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:02:57.602Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:02:59.492Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:03:00.820Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:03:01.230Z] 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. [2025-07-02T14:03:01.230Z] The best model improves the baseline by 14.52%. [2025-07-02T14:03:01.230Z] Top recommended movies for user id 72: [2025-07-02T14:03:01.230Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:03:01.230Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:03:01.230Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:03:01.230Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:03:01.230Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:03:01.230Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18765.050 ms) ====== [2025-07-02T14:03:01.230Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-07-02T14:03:01.610Z] GC before operation: completed in 132.684 ms, heap usage 718.583 MB -> 93.907 MB. [2025-07-02T14:03:04.929Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:03:07.495Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:03:10.828Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:03:13.376Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:03:14.781Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:03:16.698Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:03:18.584Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:03:20.519Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:03:20.519Z] 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. [2025-07-02T14:03:20.519Z] The best model improves the baseline by 14.52%. [2025-07-02T14:03:20.908Z] Top recommended movies for user id 72: [2025-07-02T14:03:20.908Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:03:20.908Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:03:20.908Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:03:20.908Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:03:20.908Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:03:20.908Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (19232.993 ms) ====== [2025-07-02T14:03:20.908Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-07-02T14:03:20.908Z] GC before operation: completed in 131.152 ms, heap usage 142.664 MB -> 96.077 MB. [2025-07-02T14:03:24.253Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:03:26.797Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:03:29.384Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:03:31.952Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:03:33.845Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:03:35.808Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:03:37.154Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:03:39.060Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:03:39.448Z] 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. [2025-07-02T14:03:39.448Z] The best model improves the baseline by 14.52%. [2025-07-02T14:03:39.448Z] Top recommended movies for user id 72: [2025-07-02T14:03:39.448Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:03:39.448Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:03:39.448Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:03:39.448Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:03:39.448Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:03:39.448Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18640.523 ms) ====== [2025-07-02T14:03:39.448Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-07-02T14:03:39.448Z] GC before operation: completed in 131.277 ms, heap usage 169.888 MB -> 94.881 MB. [2025-07-02T14:03:42.743Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:03:45.320Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:03:47.911Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:03:51.212Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:03:52.554Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:03:54.465Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:03:56.409Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:03:57.783Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:03:58.182Z] 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. [2025-07-02T14:03:58.182Z] The best model improves the baseline by 14.52%. [2025-07-02T14:03:58.182Z] Top recommended movies for user id 72: [2025-07-02T14:03:58.182Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:03:58.182Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:03:58.182Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:03:58.182Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:03:58.182Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:03:58.182Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18675.896 ms) ====== [2025-07-02T14:03:58.182Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-07-02T14:03:58.575Z] GC before operation: completed in 128.326 ms, heap usage 291.726 MB -> 92.310 MB. [2025-07-02T14:04:01.934Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:04:05.383Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:04:07.959Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:04:10.492Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:04:12.404Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:04:14.351Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:04:15.683Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:04:17.583Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:04:17.970Z] 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. [2025-07-02T14:04:17.970Z] The best model improves the baseline by 14.52%. [2025-07-02T14:04:18.348Z] Top recommended movies for user id 72: [2025-07-02T14:04:18.348Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:04:18.348Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:04:18.348Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:04:18.348Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:04:18.348Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:04:18.348Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19817.988 ms) ====== [2025-07-02T14:04:18.348Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-07-02T14:04:18.348Z] GC before operation: completed in 127.121 ms, heap usage 547.191 MB -> 93.828 MB. [2025-07-02T14:04:21.689Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:04:24.245Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:04:26.806Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:04:30.147Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:04:31.499Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:04:33.010Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:04:34.930Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:04:36.254Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:04:36.660Z] 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. [2025-07-02T14:04:36.660Z] The best model improves the baseline by 14.52%. [2025-07-02T14:04:37.070Z] Top recommended movies for user id 72: [2025-07-02T14:04:37.070Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:04:37.070Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:04:37.070Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:04:37.070Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:04:37.070Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:04:37.070Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18537.841 ms) ====== [2025-07-02T14:04:37.070Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-07-02T14:04:37.070Z] GC before operation: completed in 130.947 ms, heap usage 231.455 MB -> 92.117 MB. [2025-07-02T14:04:40.417Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:04:42.960Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:04:45.498Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:04:48.081Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:04:49.971Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:04:51.915Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:04:53.329Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:04:55.232Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:04:55.232Z] 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. [2025-07-02T14:04:55.612Z] The best model improves the baseline by 14.52%. [2025-07-02T14:04:55.612Z] Top recommended movies for user id 72: [2025-07-02T14:04:55.612Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:04:55.612Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:04:55.612Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:04:55.612Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:04:55.612Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:04:55.612Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18575.431 ms) ====== [2025-07-02T14:04:55.612Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-07-02T14:04:55.612Z] GC before operation: completed in 129.668 ms, heap usage 793.313 MB -> 94.141 MB. [2025-07-02T14:04:58.929Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-07-02T14:05:01.500Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-07-02T14:05:04.024Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-07-02T14:05:07.358Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-07-02T14:05:08.699Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-07-02T14:05:10.032Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-07-02T14:05:11.971Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-07-02T14:05:13.931Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-07-02T14:05:13.931Z] 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. [2025-07-02T14:05:13.931Z] The best model improves the baseline by 14.52%. [2025-07-02T14:05:13.931Z] Top recommended movies for user id 72: [2025-07-02T14:05:13.931Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-07-02T14:05:13.931Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-07-02T14:05:13.931Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-07-02T14:05:13.931Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-07-02T14:05:13.931Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-07-02T14:05:13.931Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18354.796 ms) ====== [2025-07-02T14:05:14.749Z] ----------------------------------- [2025-07-02T14:05:14.749Z] renaissance-movie-lens_0_PASSED [2025-07-02T14:05:14.749Z] ----------------------------------- [2025-07-02T14:05:14.749Z] [2025-07-02T14:05:14.749Z] TEST TEARDOWN: [2025-07-02T14:05:14.749Z] Nothing to be done for teardown. [2025-07-02T14:05:14.749Z] renaissance-movie-lens_0 Finish Time: Wed Jul 2 14:05:14 2025 Epoch Time (ms): 1751465114578