renaissance-movie-lens_0
[2025-06-18T22:36:09.624Z] Running test renaissance-movie-lens_0 ...
[2025-06-18T22:36:09.624Z] ===============================================
[2025-06-18T22:36:09.624Z] renaissance-movie-lens_0 Start Time: Wed Jun 18 22:36:09 2025 Epoch Time (ms): 1750286169485
[2025-06-18T22:36:09.624Z] variation: NoOptions
[2025-06-18T22:36:09.624Z] JVM_OPTIONS:
[2025-06-18T22:36:09.624Z] { \
[2025-06-18T22:36:09.624Z] echo ""; echo "TEST SETUP:"; \
[2025-06-18T22:36:09.624Z] echo "Nothing to be done for setup."; \
[2025-06-18T22:36:09.624Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17502861682636/renaissance-movie-lens_0"; \
[2025-06-18T22:36:09.624Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17502861682636/renaissance-movie-lens_0"; \
[2025-06-18T22:36:09.624Z] echo ""; echo "TESTING:"; \
[2025-06-18T22:36:09.624Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/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_s390x_linux_rerun/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17502861682636/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-06-18T22:36:09.624Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17502861682636/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-06-18T22:36:09.624Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-06-18T22:36:09.624Z] echo "Nothing to be done for teardown."; \
[2025-06-18T22:36:09.624Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_s390x_linux_rerun/aqa-tests/TKG/../TKG/output_17502861682636/TestTargetResult";
[2025-06-18T22:36:09.624Z]
[2025-06-18T22:36:09.624Z] TEST SETUP:
[2025-06-18T22:36:09.624Z] Nothing to be done for setup.
[2025-06-18T22:36:09.624Z]
[2025-06-18T22:36:09.624Z] TESTING:
[2025-06-18T22:36:23.097Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2025-06-18T22:36:45.533Z] 22:36:44.246 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (2797 KiB). The maximum recommended task size is 1000 KiB.
[2025-06-18T22:36:49.960Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-06-18T22:36:53.426Z] Training: 60056, validation: 20285, test: 19854
[2025-06-18T22:36:53.426Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-06-18T22:36:53.426Z] GC before operation: completed in 534.712 ms, heap usage 181.704 MB -> 75.828 MB.
[2025-06-18T22:37:12.154Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:37:26.178Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:37:35.887Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:37:43.879Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:37:50.410Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:38:00.729Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:38:07.643Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:38:10.817Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:38:11.488Z] 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.
[2025-06-18T22:38:11.488Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:38:11.488Z] Top recommended movies for user id 72:
[2025-06-18T22:38:11.488Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:38:11.488Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:38:11.488Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:38:11.488Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:38:11.488Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:38:11.488Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (78032.617 ms) ======
[2025-06-18T22:38:11.488Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-06-18T22:38:12.234Z] GC before operation: completed in 359.007 ms, heap usage 321.587 MB -> 94.731 MB.
[2025-06-18T22:38:20.003Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:38:26.242Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:38:32.664Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:38:39.066Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:38:45.830Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:38:48.017Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:38:53.310Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:38:57.526Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:38:58.281Z] 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.
[2025-06-18T22:38:59.053Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:38:59.799Z] Top recommended movies for user id 72:
[2025-06-18T22:38:59.799Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:38:59.799Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:38:59.799Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:38:59.799Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:38:59.799Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:38:59.799Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (47597.904 ms) ======
[2025-06-18T22:38:59.799Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-06-18T22:38:59.799Z] GC before operation: completed in 295.790 ms, heap usage 223.294 MB -> 89.596 MB.
[2025-06-18T22:39:06.234Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:39:19.708Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:39:27.577Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:39:34.197Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:39:39.710Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:39:43.925Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:39:52.174Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:39:56.333Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:39:57.052Z] 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.
[2025-06-18T22:39:57.052Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:39:57.825Z] Top recommended movies for user id 72:
[2025-06-18T22:39:57.825Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:39:57.825Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:39:57.825Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:39:57.825Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:39:57.825Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:39:57.825Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (57367.435 ms) ======
[2025-06-18T22:39:57.825Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-06-18T22:39:57.825Z] GC before operation: completed in 484.442 ms, heap usage 250.065 MB -> 88.600 MB.
[2025-06-18T22:40:08.935Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:40:15.657Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:40:25.437Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:40:31.854Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:40:35.032Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:40:40.253Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:40:46.547Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:40:49.623Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:40:50.353Z] 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.
[2025-06-18T22:40:50.353Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:40:50.353Z] Top recommended movies for user id 72:
[2025-06-18T22:40:50.353Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:40:50.353Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:40:50.353Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:40:50.353Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:40:50.353Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:40:50.353Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (52360.017 ms) ======
[2025-06-18T22:40:50.353Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-06-18T22:40:50.353Z] GC before operation: completed in 316.393 ms, heap usage 151.007 MB -> 88.766 MB.
[2025-06-18T22:40:57.494Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:41:02.836Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:41:09.632Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:41:14.631Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:41:19.219Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:41:23.485Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:41:30.695Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:41:35.812Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:41:35.812Z] 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.
[2025-06-18T22:41:36.504Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:41:36.504Z] Top recommended movies for user id 72:
[2025-06-18T22:41:36.504Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:41:36.504Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:41:36.504Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:41:36.504Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:41:36.504Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:41:36.504Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (46004.891 ms) ======
[2025-06-18T22:41:36.504Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-06-18T22:41:36.504Z] GC before operation: completed in 208.166 ms, heap usage 391.777 MB -> 89.249 MB.
[2025-06-18T22:41:41.480Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:41:47.732Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:41:54.097Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:42:00.536Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:42:04.751Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:42:10.409Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:42:14.535Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:42:17.663Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:42:18.412Z] 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.
[2025-06-18T22:42:19.218Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:42:19.913Z] Top recommended movies for user id 72:
[2025-06-18T22:42:19.913Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:42:19.913Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:42:19.913Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:42:19.913Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:42:19.913Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:42:19.913Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (42946.214 ms) ======
[2025-06-18T22:42:19.913Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-06-18T22:42:20.567Z] GC before operation: completed in 616.598 ms, heap usage 227.058 MB -> 89.178 MB.
[2025-06-18T22:42:30.363Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:42:42.027Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:42:47.089Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:42:53.520Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:42:56.713Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:43:00.743Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:43:05.128Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:43:08.127Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:43:08.127Z] 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.
[2025-06-18T22:43:08.127Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:43:08.823Z] Top recommended movies for user id 72:
[2025-06-18T22:43:08.823Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:43:08.823Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:43:08.823Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:43:08.823Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:43:08.823Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:43:08.823Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (48235.719 ms) ======
[2025-06-18T22:43:08.823Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-06-18T22:43:08.823Z] GC before operation: completed in 230.364 ms, heap usage 206.229 MB -> 89.095 MB.
[2025-06-18T22:43:13.893Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:43:22.181Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:43:28.470Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:43:33.575Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:43:38.856Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:43:43.200Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:43:46.378Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:43:48.624Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:43:49.333Z] 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.
[2025-06-18T22:43:49.333Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:43:49.333Z] Top recommended movies for user id 72:
[2025-06-18T22:43:49.333Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:43:49.333Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:43:49.333Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:43:49.333Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:43:49.333Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:43:49.333Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (40702.896 ms) ======
[2025-06-18T22:43:49.333Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-06-18T22:43:50.114Z] GC before operation: completed in 260.475 ms, heap usage 224.649 MB -> 89.334 MB.
[2025-06-18T22:43:55.769Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:44:02.013Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:44:08.295Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:44:15.139Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:44:18.357Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:44:22.583Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:44:26.662Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:44:29.765Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:44:29.765Z] 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.
[2025-06-18T22:44:30.425Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:44:30.425Z] Top recommended movies for user id 72:
[2025-06-18T22:44:30.425Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:44:30.425Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:44:30.425Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:44:30.425Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:44:30.425Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:44:30.425Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (40756.510 ms) ======
[2025-06-18T22:44:30.425Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-06-18T22:44:31.088Z] GC before operation: completed in 258.575 ms, heap usage 219.087 MB -> 89.191 MB.
[2025-06-18T22:44:37.991Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:44:43.145Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:44:49.426Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:44:54.665Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:45:01.818Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:45:07.277Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:45:14.375Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:45:18.562Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:45:19.248Z] 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.
[2025-06-18T22:45:19.248Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:45:20.183Z] Top recommended movies for user id 72:
[2025-06-18T22:45:20.183Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:45:20.183Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:45:20.183Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:45:20.183Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:45:20.183Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:45:20.183Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (49165.754 ms) ======
[2025-06-18T22:45:20.183Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-06-18T22:45:21.096Z] GC before operation: completed in 835.409 ms, heap usage 141.400 MB -> 89.312 MB.
[2025-06-18T22:45:28.905Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:45:35.203Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:45:44.734Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:45:52.538Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:45:56.552Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:45:59.713Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:46:03.798Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:46:08.063Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:46:08.889Z] 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.
[2025-06-18T22:46:08.889Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:46:09.776Z] Top recommended movies for user id 72:
[2025-06-18T22:46:09.776Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:46:09.776Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:46:09.776Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:46:09.776Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:46:09.776Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:46:09.776Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (49276.734 ms) ======
[2025-06-18T22:46:09.776Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-06-18T22:46:10.441Z] GC before operation: completed in 216.550 ms, heap usage 385.469 MB -> 89.459 MB.
[2025-06-18T22:46:17.309Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:46:23.962Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:46:30.397Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:46:35.606Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:46:39.619Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:46:42.568Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:46:44.834Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:46:50.294Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:46:50.294Z] 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.
[2025-06-18T22:46:50.294Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:46:51.234Z] Top recommended movies for user id 72:
[2025-06-18T22:46:51.234Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:46:51.234Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:46:51.234Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:46:51.234Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:46:51.234Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:46:51.234Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (41142.121 ms) ======
[2025-06-18T22:46:51.234Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-06-18T22:46:52.348Z] GC before operation: completed in 1244.374 ms, heap usage 177.607 MB -> 89.245 MB.
[2025-06-18T22:46:59.395Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:47:05.962Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:47:13.784Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:47:18.975Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:47:25.689Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:47:29.854Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:47:34.129Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:47:37.186Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:47:37.891Z] 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.
[2025-06-18T22:47:37.892Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:47:37.892Z] Top recommended movies for user id 72:
[2025-06-18T22:47:37.892Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:47:37.892Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:47:37.892Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:47:37.892Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:47:37.892Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:47:37.892Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (45477.792 ms) ======
[2025-06-18T22:47:37.892Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-06-18T22:47:38.559Z] GC before operation: completed in 422.443 ms, heap usage 204.841 MB -> 89.483 MB.
[2025-06-18T22:47:45.149Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:47:50.192Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:48:02.185Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:48:10.145Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:48:12.338Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:48:15.473Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:48:20.520Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:48:25.850Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:48:25.850Z] 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.
[2025-06-18T22:48:25.850Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:48:26.518Z] Top recommended movies for user id 72:
[2025-06-18T22:48:26.518Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:48:26.518Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:48:26.518Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:48:26.518Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:48:26.518Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:48:26.518Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (47605.292 ms) ======
[2025-06-18T22:48:26.518Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-06-18T22:48:26.518Z] GC before operation: completed in 335.526 ms, heap usage 204.788 MB -> 89.375 MB.
[2025-06-18T22:48:34.564Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:48:39.771Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:48:46.168Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:48:51.373Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:48:54.455Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:49:00.379Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:49:04.477Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:49:07.652Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:49:09.448Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2025-06-18T22:49:09.448Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:49:10.250Z] Top recommended movies for user id 72:
[2025-06-18T22:49:10.250Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:49:10.250Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:49:10.250Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:49:10.250Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:49:10.251Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:49:10.251Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (44017.517 ms) ======
[2025-06-18T22:49:10.251Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-06-18T22:49:10.914Z] GC before operation: completed in 562.245 ms, heap usage 204.176 MB -> 89.486 MB.
[2025-06-18T22:49:17.186Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:49:24.856Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:49:30.051Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:49:34.117Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:49:39.393Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:49:43.659Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:49:47.700Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:49:49.874Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:49:51.458Z] 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.
[2025-06-18T22:49:51.459Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:49:51.459Z] Top recommended movies for user id 72:
[2025-06-18T22:49:51.459Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:49:51.459Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:49:51.459Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:49:51.459Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:49:51.459Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:49:51.459Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (40619.047 ms) ======
[2025-06-18T22:49:51.459Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-06-18T22:49:52.589Z] GC before operation: completed in 986.323 ms, heap usage 163.760 MB -> 89.300 MB.
[2025-06-18T22:49:58.786Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:50:03.883Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:50:10.399Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:50:15.751Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:50:19.145Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:50:22.376Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:50:27.702Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:50:30.783Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:50:31.522Z] 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.
[2025-06-18T22:50:31.522Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:50:32.258Z] Top recommended movies for user id 72:
[2025-06-18T22:50:32.258Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:50:32.258Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:50:32.258Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:50:32.258Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:50:32.258Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:50:32.258Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (39203.386 ms) ======
[2025-06-18T22:50:32.258Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-06-18T22:50:32.258Z] GC before operation: completed in 220.238 ms, heap usage 146.129 MB -> 89.338 MB.
[2025-06-18T22:50:38.946Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:50:45.119Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:50:51.369Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:50:56.586Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:50:59.856Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:51:02.961Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:51:06.928Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:51:10.126Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:51:10.126Z] 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.
[2025-06-18T22:51:10.126Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:51:10.821Z] Top recommended movies for user id 72:
[2025-06-18T22:51:10.821Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:51:10.821Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:51:10.821Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:51:10.821Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:51:10.821Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:51:10.821Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (38589.532 ms) ======
[2025-06-18T22:51:10.821Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-06-18T22:51:10.821Z] GC before operation: completed in 360.132 ms, heap usage 205.217 MB -> 89.297 MB.
[2025-06-18T22:51:20.886Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:51:30.133Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:51:40.052Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:51:46.604Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:51:49.797Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:51:55.207Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:52:00.472Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:52:04.754Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:52:05.410Z] 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.
[2025-06-18T22:52:05.410Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:52:05.410Z] Top recommended movies for user id 72:
[2025-06-18T22:52:05.410Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:52:05.410Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:52:05.410Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:52:05.410Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:52:05.410Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:52:05.410Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (54589.363 ms) ======
[2025-06-18T22:52:05.410Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-06-18T22:52:06.093Z] GC before operation: completed in 595.688 ms, heap usage 204.441 MB -> 86.071 MB.
[2025-06-18T22:52:12.365Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-18T22:52:18.902Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-18T22:52:24.306Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-18T22:52:30.692Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-18T22:52:32.932Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-18T22:52:37.258Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-18T22:52:40.563Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-18T22:52:45.035Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-18T22:52:45.856Z] 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.
[2025-06-18T22:52:45.856Z] The best model improves the baseline by 14.34%.
[2025-06-18T22:52:47.434Z] Top recommended movies for user id 72:
[2025-06-18T22:52:47.434Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.687, id: 67504)
[2025-06-18T22:52:47.434Z] 2: Goat, The (1921) (rating: 4.687, id: 83318)
[2025-06-18T22:52:47.434Z] 3: Play House, The (1921) (rating: 4.687, id: 83359)
[2025-06-18T22:52:47.434Z] 4: Cops (1922) (rating: 4.687, id: 83411)
[2025-06-18T22:52:47.434Z] 5: Dear Frankie (2004) (rating: 4.297, id: 8530)
[2025-06-18T22:52:47.434Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (41283.050 ms) ======
[2025-06-18T22:52:48.756Z] -----------------------------------
[2025-06-18T22:52:48.756Z] renaissance-movie-lens_0_PASSED
[2025-06-18T22:52:48.756Z] -----------------------------------
[2025-06-18T22:52:48.756Z]
[2025-06-18T22:52:48.756Z] TEST TEARDOWN:
[2025-06-18T22:52:48.756Z] Nothing to be done for teardown.
[2025-06-18T22:52:48.756Z] renaissance-movie-lens_0 Finish Time: Wed Jun 18 22:52:48 2025 Epoch Time (ms): 1750287168149