renaissance-movie-lens_0
[2024-10-29T22:34:43.352Z] Running test renaissance-movie-lens_0 ...
[2024-10-29T22:34:43.352Z] ===============================================
[2024-10-29T22:34:43.352Z] renaissance-movie-lens_0 Start Time: Tue Oct 29 17:34:42 2024 Epoch Time (ms): 1730241282487
[2024-10-29T22:34:43.352Z] variation: NoOptions
[2024-10-29T22:34:43.352Z] JVM_OPTIONS:
[2024-10-29T22:34:43.352Z] { \
[2024-10-29T22:34:43.352Z] echo ""; echo "TEST SETUP:"; \
[2024-10-29T22:34:43.352Z] echo "Nothing to be done for setup."; \
[2024-10-29T22:34:43.352Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17302404021562/renaissance-movie-lens_0"; \
[2024-10-29T22:34:43.352Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17302404021562/renaissance-movie-lens_0"; \
[2024-10-29T22:34:43.352Z] echo ""; echo "TESTING:"; \
[2024-10-29T22:34:43.352Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/jdk8u442-b01/bin/..//bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17302404021562/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-10-29T22:34:43.352Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17302404021562/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-10-29T22:34:43.352Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-10-29T22:34:43.352Z] echo "Nothing to be done for teardown."; \
[2024-10-29T22:34:43.352Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17302404021562/TestTargetResult";
[2024-10-29T22:34:43.352Z]
[2024-10-29T22:34:43.352Z] TEST SETUP:
[2024-10-29T22:34:43.352Z] Nothing to be done for setup.
[2024-10-29T22:34:43.352Z]
[2024-10-29T22:34:43.352Z] TESTING:
[2024-10-29T22:34:45.576Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-10-29T22:34:47.807Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-10-29T22:34:50.935Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-10-29T22:34:51.654Z] Training: 60056, validation: 20285, test: 19854
[2024-10-29T22:34:51.654Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-10-29T22:34:51.654Z] GC before operation: completed in 223.932 ms, heap usage 121.269 MB -> 28.879 MB.
[2024-10-29T22:34:58.609Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:35:00.853Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:35:04.031Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:35:07.238Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:35:09.459Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:35:10.895Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:35:12.325Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:35:14.576Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:35:14.576Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-10-29T22:35:14.576Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:35:14.576Z] Movies recommended for you:
[2024-10-29T22:35:14.576Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:35:14.576Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:35:14.576Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23244.693 ms) ======
[2024-10-29T22:35:14.576Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-10-29T22:35:15.263Z] GC before operation: completed in 355.293 ms, heap usage 216.779 MB -> 55.210 MB.
[2024-10-29T22:35:18.415Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:35:21.517Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:35:24.633Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:35:26.857Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:35:28.321Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:35:30.570Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:35:32.007Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:35:34.232Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:35:34.232Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-10-29T22:35:34.232Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:35:34.928Z] Movies recommended for you:
[2024-10-29T22:35:34.928Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:35:34.928Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:35:34.928Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (19363.335 ms) ======
[2024-10-29T22:35:34.928Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-10-29T22:35:34.928Z] GC before operation: completed in 159.427 ms, heap usage 332.283 MB -> 50.520 MB.
[2024-10-29T22:35:37.167Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:35:40.293Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:35:42.548Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:35:45.643Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:35:47.085Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:35:48.532Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:35:49.956Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:35:51.395Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:35:51.395Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-10-29T22:35:51.395Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:35:52.083Z] Movies recommended for you:
[2024-10-29T22:35:52.083Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:35:52.083Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:35:52.083Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17007.078 ms) ======
[2024-10-29T22:35:52.083Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-10-29T22:35:52.083Z] GC before operation: completed in 185.183 ms, heap usage 222.366 MB -> 49.014 MB.
[2024-10-29T22:35:54.314Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:35:56.547Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:35:58.806Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:36:01.046Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:36:02.497Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:36:03.933Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:36:06.187Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:36:07.635Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:36:07.635Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:36:07.635Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:36:08.337Z] Movies recommended for you:
[2024-10-29T22:36:08.337Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:36:08.337Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:36:08.337Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16055.744 ms) ======
[2024-10-29T22:36:08.337Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-10-29T22:36:08.337Z] GC before operation: completed in 143.576 ms, heap usage 705.419 MB -> 66.395 MB.
[2024-10-29T22:36:10.590Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:36:12.840Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:36:15.072Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:36:17.327Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:36:19.219Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:36:20.668Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:36:22.100Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:36:23.552Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:36:23.552Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:36:23.552Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:36:23.552Z] Movies recommended for you:
[2024-10-29T22:36:23.552Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:36:23.552Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:36:23.552Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15514.857 ms) ======
[2024-10-29T22:36:23.552Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-10-29T22:36:23.552Z] GC before operation: completed in 153.080 ms, heap usage 272.544 MB -> 53.421 MB.
[2024-10-29T22:36:25.820Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:36:28.945Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:36:31.189Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:36:33.414Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:36:34.847Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:36:36.273Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:36:37.709Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:36:39.145Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:36:39.145Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-10-29T22:36:39.833Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:36:39.833Z] Movies recommended for you:
[2024-10-29T22:36:39.833Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:36:39.833Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:36:39.833Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15826.535 ms) ======
[2024-10-29T22:36:39.833Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-10-29T22:36:39.833Z] GC before operation: completed in 162.804 ms, heap usage 231.479 MB -> 47.414 MB.
[2024-10-29T22:36:42.072Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:36:44.316Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:36:46.578Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:36:48.827Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:36:50.269Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:36:52.523Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:36:53.973Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:36:54.672Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:36:55.374Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:36:55.374Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:36:55.374Z] Movies recommended for you:
[2024-10-29T22:36:55.374Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:36:55.374Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:36:55.374Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15603.982 ms) ======
[2024-10-29T22:36:55.374Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-10-29T22:36:55.374Z] GC before operation: completed in 139.354 ms, heap usage 269.618 MB -> 47.936 MB.
[2024-10-29T22:36:57.622Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:37:00.726Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:37:02.972Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:37:05.209Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:37:06.657Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:37:08.102Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:37:09.545Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:37:10.974Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:37:10.974Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949712.
[2024-10-29T22:37:10.974Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:37:10.974Z] Movies recommended for you:
[2024-10-29T22:37:10.974Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:37:10.974Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:37:10.974Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15598.347 ms) ======
[2024-10-29T22:37:10.974Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-10-29T22:37:10.974Z] GC before operation: completed in 155.721 ms, heap usage 212.093 MB -> 57.229 MB.
[2024-10-29T22:37:14.086Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:37:16.340Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:37:18.587Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:37:20.816Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:37:22.256Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:37:23.683Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:37:25.115Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:37:26.982Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:37:26.982Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:37:26.982Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:37:26.982Z] Movies recommended for you:
[2024-10-29T22:37:26.982Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:37:26.982Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:37:26.982Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15563.202 ms) ======
[2024-10-29T22:37:26.982Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-10-29T22:37:26.982Z] GC before operation: completed in 188.651 ms, heap usage 693.757 MB -> 60.136 MB.
[2024-10-29T22:37:29.236Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:37:31.458Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:37:33.700Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:37:35.942Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:37:37.393Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:37:39.649Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:37:41.083Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:37:42.515Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:37:42.515Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:37:42.515Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:37:42.515Z] Movies recommended for you:
[2024-10-29T22:37:42.515Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:37:42.515Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:37:42.515Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15481.134 ms) ======
[2024-10-29T22:37:42.515Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-10-29T22:37:42.515Z] GC before operation: completed in 181.363 ms, heap usage 156.352 MB -> 52.734 MB.
[2024-10-29T22:37:44.773Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:37:47.005Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:37:50.131Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:37:52.363Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:37:53.807Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:37:55.243Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:37:56.670Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:37:58.117Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:37:58.117Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:37:58.117Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:37:58.117Z] Movies recommended for you:
[2024-10-29T22:37:58.117Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:37:58.117Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:37:58.117Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15479.409 ms) ======
[2024-10-29T22:37:58.117Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-10-29T22:37:58.117Z] GC before operation: completed in 153.313 ms, heap usage 657.283 MB -> 54.815 MB.
[2024-10-29T22:38:00.348Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:38:02.683Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:38:04.935Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:38:08.030Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:38:08.740Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:38:10.193Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:38:11.652Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:38:13.090Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:38:13.782Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:38:13.782Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:38:13.782Z] Movies recommended for you:
[2024-10-29T22:38:13.782Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:38:13.782Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:38:13.782Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15380.628 ms) ======
[2024-10-29T22:38:13.782Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-10-29T22:38:13.782Z] GC before operation: completed in 139.781 ms, heap usage 237.203 MB -> 57.464 MB.
[2024-10-29T22:38:16.022Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:38:19.135Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:38:21.377Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:38:23.646Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:38:25.090Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:38:26.522Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:38:27.947Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:38:30.170Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:38:30.170Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:38:30.170Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:38:30.170Z] Movies recommended for you:
[2024-10-29T22:38:30.170Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:38:30.170Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:38:30.170Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16233.950 ms) ======
[2024-10-29T22:38:30.170Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-10-29T22:38:30.170Z] GC before operation: completed in 169.930 ms, heap usage 701.740 MB -> 64.987 MB.
[2024-10-29T22:38:32.394Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:38:34.630Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:38:37.748Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:38:40.415Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:38:41.159Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:38:42.602Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:38:44.032Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:38:45.506Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:38:46.197Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:38:46.197Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:38:46.197Z] Movies recommended for you:
[2024-10-29T22:38:46.197Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:38:46.197Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:38:46.197Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15765.422 ms) ======
[2024-10-29T22:38:46.197Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-10-29T22:38:46.197Z] GC before operation: completed in 148.455 ms, heap usage 123.484 MB -> 55.587 MB.
[2024-10-29T22:38:48.440Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:38:50.682Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:38:52.926Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:38:55.175Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:38:56.631Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:38:58.091Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:38:59.530Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:39:00.984Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:39:01.677Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:39:01.677Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:39:01.677Z] Movies recommended for you:
[2024-10-29T22:39:01.677Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:39:01.677Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:39:01.677Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15477.203 ms) ======
[2024-10-29T22:39:01.677Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-10-29T22:39:01.677Z] GC before operation: completed in 193.016 ms, heap usage 125.139 MB -> 66.011 MB.
[2024-10-29T22:39:03.903Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:39:06.166Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:39:08.396Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:39:11.501Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:39:12.218Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:39:13.646Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:39:15.131Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:39:16.562Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:39:17.271Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:39:17.271Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:39:17.271Z] Movies recommended for you:
[2024-10-29T22:39:17.271Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:39:17.271Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:39:17.271Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15405.066 ms) ======
[2024-10-29T22:39:17.271Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-10-29T22:39:17.271Z] GC before operation: completed in 182.474 ms, heap usage 554.643 MB -> 76.316 MB.
[2024-10-29T22:39:19.505Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:39:21.741Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:39:24.856Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:39:27.096Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:39:27.811Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:39:29.257Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:39:31.512Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:39:32.940Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:39:32.940Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:39:32.940Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:39:32.940Z] Movies recommended for you:
[2024-10-29T22:39:32.940Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:39:32.940Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:39:32.940Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15560.461 ms) ======
[2024-10-29T22:39:32.940Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-10-29T22:39:32.940Z] GC before operation: completed in 222.353 ms, heap usage 695.595 MB -> 54.933 MB.
[2024-10-29T22:39:36.054Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:39:38.277Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:39:40.504Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:39:42.732Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:39:44.177Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:39:45.602Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:39:47.040Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:39:48.477Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:39:48.477Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:39:48.477Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:39:49.164Z] Movies recommended for you:
[2024-10-29T22:39:49.165Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:39:49.165Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:39:49.165Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15616.596 ms) ======
[2024-10-29T22:39:49.165Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-10-29T22:39:49.165Z] GC before operation: completed in 209.080 ms, heap usage 551.480 MB -> 76.166 MB.
[2024-10-29T22:39:51.053Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:39:53.301Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:39:55.540Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:39:58.667Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:39:59.365Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:40:00.821Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:40:02.267Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:40:04.509Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:40:04.509Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:40:04.509Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:40:04.509Z] Movies recommended for you:
[2024-10-29T22:40:04.509Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:40:04.509Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:40:04.509Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15420.904 ms) ======
[2024-10-29T22:40:04.509Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-10-29T22:40:04.509Z] GC before operation: completed in 146.629 ms, heap usage 681.485 MB -> 77.099 MB.
[2024-10-29T22:40:06.853Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-29T22:40:09.082Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-29T22:40:11.330Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-29T22:40:13.565Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-29T22:40:15.007Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-29T22:40:16.436Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-29T22:40:17.873Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-29T22:40:20.159Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-29T22:40:20.159Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-10-29T22:40:20.159Z] The best model improves the baseline by 14.43%.
[2024-10-29T22:40:20.159Z] Movies recommended for you:
[2024-10-29T22:40:20.159Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-29T22:40:20.159Z] There is no way to check that no silent failure occurred.
[2024-10-29T22:40:20.159Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15487.352 ms) ======
[2024-10-29T22:40:21.586Z] -----------------------------------
[2024-10-29T22:40:21.586Z] renaissance-movie-lens_0_PASSED
[2024-10-29T22:40:21.586Z] -----------------------------------
[2024-10-29T22:40:21.586Z]
[2024-10-29T22:40:21.586Z] TEST TEARDOWN:
[2024-10-29T22:40:21.586Z] Nothing to be done for teardown.
[2024-10-29T22:40:21.586Z] renaissance-movie-lens_0 Finish Time: Tue Oct 29 17:40:20 2024 Epoch Time (ms): 1730241620899