Test Results Summary Service

renaissance-movie-lens_0

[2025-06-28T05:03:36.723Z] Running test renaissance-movie-lens_0 ... [2025-06-28T05:03:36.723Z] =============================================== [2025-06-28T05:03:36.723Z] renaissance-movie-lens_0 Start Time: Sat Jun 28 05:03:36 2025 Epoch Time (ms): 1751087016424 [2025-06-28T05:03:36.723Z] variation: NoOptions [2025-06-28T05:03:36.723Z] JVM_OPTIONS: [2025-06-28T05:03:36.723Z] { \ [2025-06-28T05:03:36.723Z] echo ""; echo "TEST SETUP:"; \ [2025-06-28T05:03:36.723Z] echo "Nothing to be done for setup."; \ [2025-06-28T05:03:36.723Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17510850162280/renaissance-movie-lens_0"; \ [2025-06-28T05:03:36.723Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17510850162280/renaissance-movie-lens_0"; \ [2025-06-28T05:03:36.723Z] echo ""; echo "TESTING:"; \ [2025-06-28T05:03:36.723Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_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_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17510850162280/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-28T05:03:36.723Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17510850162280/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-28T05:03:36.723Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-28T05:03:36.723Z] echo "Nothing to be done for teardown."; \ [2025-06-28T05:03:36.723Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17510850162280/TestTargetResult"; [2025-06-28T05:03:36.723Z] [2025-06-28T05:03:36.723Z] TEST SETUP: [2025-06-28T05:03:36.723Z] Nothing to be done for setup. [2025-06-28T05:03:36.723Z] [2025-06-28T05:03:36.723Z] TESTING: [2025-06-28T05:03:42.693Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads. [2025-06-28T05:03:51.509Z] 05:03:50.323 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. [2025-06-28T05:03:54.435Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-28T05:03:55.130Z] Training: 60056, validation: 20285, test: 19854 [2025-06-28T05:03:55.130Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-28T05:03:55.454Z] GC before operation: completed in 231.211 ms, heap usage 475.594 MB -> 75.625 MB. [2025-06-28T05:04:04.277Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:04:10.199Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:04:16.138Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:04:19.899Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:04:22.837Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:04:25.876Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:04:28.821Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:04:32.224Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:04:32.224Z] 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. [2025-06-28T05:04:32.224Z] The best model improves the baseline by 14.34%. [2025-06-28T05:04:32.224Z] Top recommended movies for user id 72: [2025-06-28T05:04:32.224Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:04:32.224Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:04:32.224Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:04:32.224Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:04:32.224Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:04:32.224Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (36538.510 ms) ====== [2025-06-28T05:04:32.224Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-28T05:04:32.224Z] GC before operation: completed in 161.590 ms, heap usage 254.480 MB -> 85.890 MB. [2025-06-28T05:04:35.964Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:04:39.697Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:04:43.431Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:04:47.250Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:04:48.904Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:04:51.125Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:04:53.346Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:04:55.576Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:04:55.901Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-28T05:04:55.901Z] The best model improves the baseline by 14.34%. [2025-06-28T05:04:56.225Z] Top recommended movies for user id 72: [2025-06-28T05:04:56.225Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:04:56.225Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:04:56.225Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:04:56.225Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:04:56.225Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:04:56.225Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (24089.708 ms) ====== [2025-06-28T05:04:56.225Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-28T05:04:56.225Z] GC before operation: completed in 192.776 ms, heap usage 112.055 MB -> 87.576 MB. [2025-06-28T05:04:59.964Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:05:03.702Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:05:07.436Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:05:10.351Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:05:11.981Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:05:13.700Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:05:15.920Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:05:17.558Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:05:17.881Z] 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. [2025-06-28T05:05:17.881Z] The best model improves the baseline by 14.34%. [2025-06-28T05:05:18.203Z] Top recommended movies for user id 72: [2025-06-28T05:05:18.203Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:05:18.203Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:05:18.203Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:05:18.203Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:05:18.203Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:05:18.203Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (21813.652 ms) ====== [2025-06-28T05:05:18.203Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-28T05:05:18.203Z] GC before operation: completed in 192.308 ms, heap usage 404.711 MB -> 88.678 MB. [2025-06-28T05:05:22.063Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:05:24.972Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:05:27.893Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:05:30.809Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:05:33.036Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:05:34.666Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:05:36.303Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:05:38.569Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:05:38.569Z] 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. [2025-06-28T05:05:38.570Z] The best model improves the baseline by 14.34%. [2025-06-28T05:05:38.570Z] Top recommended movies for user id 72: [2025-06-28T05:05:38.570Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:05:38.570Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:05:38.570Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:05:38.570Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:05:38.570Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:05:38.570Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20362.304 ms) ====== [2025-06-28T05:05:38.570Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-28T05:05:38.932Z] GC before operation: completed in 209.820 ms, heap usage 180.873 MB -> 88.607 MB. [2025-06-28T05:05:42.665Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:05:45.578Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:05:48.490Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:05:51.406Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:05:53.034Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:05:54.664Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:05:56.882Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:05:58.516Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:05:58.516Z] 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. [2025-06-28T05:05:58.837Z] The best model improves the baseline by 14.34%. [2025-06-28T05:05:58.837Z] Top recommended movies for user id 72: [2025-06-28T05:05:58.837Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:05:58.837Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:05:58.837Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:05:58.837Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:05:58.837Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:05:58.837Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20072.261 ms) ====== [2025-06-28T05:05:58.837Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-28T05:05:59.160Z] GC before operation: completed in 185.905 ms, heap usage 146.199 MB -> 88.557 MB. [2025-06-28T05:06:02.936Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:06:05.868Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:06:08.777Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:06:10.995Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:06:13.221Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:06:14.851Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:06:16.482Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:06:18.697Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:06:18.697Z] 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. [2025-06-28T05:06:18.697Z] The best model improves the baseline by 14.34%. [2025-06-28T05:06:18.697Z] Top recommended movies for user id 72: [2025-06-28T05:06:18.697Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:06:18.697Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:06:18.697Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:06:18.697Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:06:18.697Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:06:18.697Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19689.134 ms) ====== [2025-06-28T05:06:18.697Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-28T05:06:19.023Z] GC before operation: completed in 200.605 ms, heap usage 359.066 MB -> 89.262 MB. [2025-06-28T05:06:21.940Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:06:24.895Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:06:28.631Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:06:30.979Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:06:33.204Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:06:34.837Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:06:36.476Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:06:38.105Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:06:38.427Z] 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. [2025-06-28T05:06:38.750Z] The best model improves the baseline by 14.34%. [2025-06-28T05:06:38.750Z] Top recommended movies for user id 72: [2025-06-28T05:06:38.750Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:06:38.750Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:06:38.750Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:06:38.750Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:06:38.750Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:06:38.750Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19741.748 ms) ====== [2025-06-28T05:06:38.750Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-28T05:06:39.072Z] GC before operation: completed in 185.083 ms, heap usage 170.165 MB -> 88.901 MB. [2025-06-28T05:06:41.993Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:06:44.909Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:06:47.819Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:06:50.042Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:06:51.671Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:06:53.413Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:06:55.647Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:06:57.300Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:06:57.300Z] 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. [2025-06-28T05:06:57.300Z] The best model improves the baseline by 14.34%. [2025-06-28T05:06:57.623Z] Top recommended movies for user id 72: [2025-06-28T05:06:57.623Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:06:57.623Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:06:57.623Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:06:57.623Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:06:57.623Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:06:57.623Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18677.665 ms) ====== [2025-06-28T05:06:57.623Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-28T05:06:57.949Z] GC before operation: completed in 177.164 ms, heap usage 119.487 MB -> 91.488 MB. [2025-06-28T05:07:00.854Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:07:03.774Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:07:06.691Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:07:09.609Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:07:11.239Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:07:12.907Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:07:15.129Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:07:16.257Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:07:16.584Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-28T05:07:16.584Z] The best model improves the baseline by 14.34%. [2025-06-28T05:07:16.907Z] Top recommended movies for user id 72: [2025-06-28T05:07:16.907Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:07:16.907Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:07:16.907Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:07:16.907Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:07:16.907Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:07:16.907Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19163.792 ms) ====== [2025-06-28T05:07:16.907Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-28T05:07:17.232Z] GC before operation: completed in 167.831 ms, heap usage 148.518 MB -> 89.064 MB. [2025-06-28T05:07:20.213Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:07:23.129Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:07:26.033Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:07:28.254Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:07:29.886Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:07:32.105Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:07:33.740Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:07:35.370Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:07:35.692Z] 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. [2025-06-28T05:07:35.692Z] The best model improves the baseline by 14.34%. [2025-06-28T05:07:35.692Z] Top recommended movies for user id 72: [2025-06-28T05:07:35.692Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:07:35.692Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:07:35.692Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:07:35.692Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:07:35.692Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:07:35.692Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18602.590 ms) ====== [2025-06-28T05:07:35.692Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-28T05:07:36.015Z] GC before operation: completed in 172.387 ms, heap usage 620.873 MB -> 93.137 MB. [2025-06-28T05:07:38.926Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:07:41.840Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:07:44.834Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:07:47.051Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:07:48.679Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:07:50.904Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:07:52.536Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:07:54.205Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:07:54.205Z] 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. [2025-06-28T05:07:54.205Z] The best model improves the baseline by 14.34%. [2025-06-28T05:07:54.533Z] Top recommended movies for user id 72: [2025-06-28T05:07:54.533Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:07:54.533Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:07:54.533Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:07:54.533Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:07:54.533Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:07:54.533Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18554.725 ms) ====== [2025-06-28T05:07:54.533Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-28T05:07:54.533Z] GC before operation: completed in 160.695 ms, heap usage 252.301 MB -> 89.075 MB. [2025-06-28T05:07:57.455Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:08:00.374Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:08:03.288Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:08:06.206Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:08:07.333Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:08:09.625Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:08:11.262Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:08:12.942Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:08:13.264Z] 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. [2025-06-28T05:08:13.264Z] The best model improves the baseline by 14.34%. [2025-06-28T05:08:13.264Z] Top recommended movies for user id 72: [2025-06-28T05:08:13.264Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:08:13.264Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:08:13.264Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:08:13.264Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:08:13.264Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:08:13.264Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18680.741 ms) ====== [2025-06-28T05:08:13.264Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-28T05:08:13.586Z] GC before operation: completed in 160.781 ms, heap usage 194.005 MB -> 89.114 MB. [2025-06-28T05:08:16.501Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:08:19.418Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:08:22.325Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:08:24.545Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:08:26.172Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:08:27.804Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:08:29.433Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:08:31.656Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:08:31.656Z] 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. [2025-06-28T05:08:31.656Z] The best model improves the baseline by 14.34%. [2025-06-28T05:08:32.009Z] Top recommended movies for user id 72: [2025-06-28T05:08:32.009Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:08:32.009Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:08:32.009Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:08:32.009Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:08:32.009Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:08:32.009Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18455.966 ms) ====== [2025-06-28T05:08:32.010Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-28T05:08:32.010Z] GC before operation: completed in 162.748 ms, heap usage 203.506 MB -> 89.208 MB. [2025-06-28T05:08:34.923Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:08:37.840Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:08:41.578Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:08:43.797Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:08:45.437Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:08:47.065Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:08:49.294Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:08:50.427Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:08:50.749Z] 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. [2025-06-28T05:08:50.749Z] The best model improves the baseline by 14.34%. [2025-06-28T05:08:51.072Z] Top recommended movies for user id 72: [2025-06-28T05:08:51.072Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:08:51.072Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:08:51.072Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:08:51.072Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:08:51.072Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:08:51.072Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18937.839 ms) ====== [2025-06-28T05:08:51.072Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-28T05:08:51.072Z] GC before operation: completed in 163.432 ms, heap usage 145.085 MB -> 89.017 MB. [2025-06-28T05:08:54.007Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:08:56.997Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:08:59.912Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:09:02.130Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:09:03.759Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:09:05.393Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:09:07.049Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:09:08.700Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:09:09.022Z] 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. [2025-06-28T05:09:09.022Z] The best model improves the baseline by 14.34%. [2025-06-28T05:09:09.022Z] Top recommended movies for user id 72: [2025-06-28T05:09:09.022Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:09:09.022Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:09:09.022Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:09:09.022Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:09:09.022Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:09:09.022Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (17930.885 ms) ====== [2025-06-28T05:09:09.022Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-28T05:09:09.344Z] GC before operation: completed in 176.349 ms, heap usage 546.297 MB -> 93.086 MB. [2025-06-28T05:09:14.733Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:09:15.056Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:09:17.965Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:09:20.184Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:09:22.408Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:09:23.562Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:09:25.813Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:09:26.940Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:09:27.267Z] 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. [2025-06-28T05:09:27.267Z] The best model improves the baseline by 14.34%. [2025-06-28T05:09:27.587Z] Top recommended movies for user id 72: [2025-06-28T05:09:27.588Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:09:27.588Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:09:27.588Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:09:27.588Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:09:27.588Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:09:27.588Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18275.763 ms) ====== [2025-06-28T05:09:27.588Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-28T05:09:27.909Z] GC before operation: completed in 171.641 ms, heap usage 307.883 MB -> 89.397 MB. [2025-06-28T05:09:30.825Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:09:33.050Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:09:35.971Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:09:38.891Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:09:40.015Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:09:41.651Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:09:43.872Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:09:45.000Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:09:45.323Z] 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. [2025-06-28T05:09:45.323Z] The best model improves the baseline by 14.34%. [2025-06-28T05:09:45.648Z] Top recommended movies for user id 72: [2025-06-28T05:09:45.648Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:09:45.648Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:09:45.648Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:09:45.648Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:09:45.648Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:09:45.648Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17810.465 ms) ====== [2025-06-28T05:09:45.648Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-28T05:09:45.648Z] GC before operation: completed in 166.802 ms, heap usage 385.057 MB -> 89.589 MB. [2025-06-28T05:09:48.635Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:09:51.656Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:09:54.561Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:09:56.835Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:09:58.466Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:10:00.091Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:10:01.717Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:10:03.346Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:10:03.667Z] 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. [2025-06-28T05:10:03.667Z] The best model improves the baseline by 14.34%. [2025-06-28T05:10:03.667Z] Top recommended movies for user id 72: [2025-06-28T05:10:03.667Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:10:03.667Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:10:03.667Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:10:03.667Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:10:03.667Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:10:03.667Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18005.051 ms) ====== [2025-06-28T05:10:03.667Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-28T05:10:03.987Z] GC before operation: completed in 163.252 ms, heap usage 156.142 MB -> 89.064 MB. [2025-06-28T05:10:06.892Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:10:09.801Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:10:12.068Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:10:15.034Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:10:16.162Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:10:17.796Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:10:20.032Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:10:21.664Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:10:21.664Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-28T05:10:21.664Z] The best model improves the baseline by 14.34%. [2025-06-28T05:10:21.988Z] Top recommended movies for user id 72: [2025-06-28T05:10:21.988Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:10:21.988Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:10:21.988Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:10:21.988Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:10:21.988Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:10:21.988Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18026.406 ms) ====== [2025-06-28T05:10:21.988Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-28T05:10:21.988Z] GC before operation: completed in 164.691 ms, heap usage 167.831 MB -> 89.126 MB. [2025-06-28T05:10:25.023Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-28T05:10:27.960Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-28T05:10:30.873Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-28T05:10:33.090Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-28T05:10:34.782Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-28T05:10:35.908Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-28T05:10:38.130Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-28T05:10:39.261Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-28T05:10:39.584Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572. [2025-06-28T05:10:39.584Z] The best model improves the baseline by 14.34%. [2025-06-28T05:10:39.905Z] Top recommended movies for user id 72: [2025-06-28T05:10:39.905Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504) [2025-06-28T05:10:39.905Z] 2: Goat, The (1921) (rating: 4.687, id: 83318) [2025-06-28T05:10:39.905Z] 3: Play House, The (1921) (rating: 4.687, id: 83359) [2025-06-28T05:10:39.905Z] 4: Cops (1922) (rating: 4.687, id: 83411) [2025-06-28T05:10:39.905Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530) [2025-06-28T05:10:39.905Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17716.714 ms) ====== [2025-06-28T05:10:40.226Z] ----------------------------------- [2025-06-28T05:10:40.226Z] renaissance-movie-lens_0_PASSED [2025-06-28T05:10:40.226Z] ----------------------------------- [2025-06-28T05:10:40.226Z] [2025-06-28T05:10:40.226Z] TEST TEARDOWN: [2025-06-28T05:10:40.226Z] Nothing to be done for teardown. [2025-06-28T05:10:40.226Z] renaissance-movie-lens_0 Finish Time: Sat Jun 28 05:10:40 2025 Epoch Time (ms): 1751087440168