renaissance-movie-lens_0
[2025-03-04T22:04:07.073Z] Running test renaissance-movie-lens_0 ...
[2025-03-04T22:04:07.073Z] ===============================================
[2025-03-04T22:04:07.073Z] renaissance-movie-lens_0 Start Time: Tue Mar 4 22:04:05 2025 Epoch Time (ms): 1741125845560
[2025-03-04T22:04:07.073Z] variation: NoOptions
[2025-03-04T22:04:07.073Z] JVM_OPTIONS:
[2025-03-04T22:04:07.073Z] { \
[2025-03-04T22:04:07.073Z] echo ""; echo "TEST SETUP:"; \
[2025-03-04T22:04:07.073Z] echo "Nothing to be done for setup."; \
[2025-03-04T22:04:07.073Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17411246048607/renaissance-movie-lens_0"; \
[2025-03-04T22:04:07.073Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17411246048607/renaissance-movie-lens_0"; \
[2025-03-04T22:04:07.073Z] echo ""; echo "TESTING:"; \
[2025-03-04T22:04:07.073Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17411246048607/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-03-04T22:04:07.073Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17411246048607/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-03-04T22:04:07.073Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-03-04T22:04:07.073Z] echo "Nothing to be done for teardown."; \
[2025-03-04T22:04:07.073Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17411246048607/TestTargetResult";
[2025-03-04T22:04:07.073Z]
[2025-03-04T22:04:07.073Z] TEST SETUP:
[2025-03-04T22:04:07.073Z] Nothing to be done for setup.
[2025-03-04T22:04:07.073Z]
[2025-03-04T22:04:07.073Z] TESTING:
[2025-03-04T22:04:09.520Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-03-04T22:04:12.728Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-03-04T22:04:17.838Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-03-04T22:04:18.247Z] Training: 60056, validation: 20285, test: 19854
[2025-03-04T22:04:18.247Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-03-04T22:04:18.632Z] GC before operation: completed in 227.939 ms, heap usage 147.576 MB -> 26.009 MB.
[2025-03-04T22:04:26.414Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:04:30.590Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:04:35.844Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:04:39.201Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:04:41.070Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:04:43.643Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:04:45.562Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:04:48.109Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:04:48.109Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:04:48.109Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:04:48.488Z] Movies recommended for you:
[2025-03-04T22:04:48.488Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:04:48.488Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:04:48.488Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (30049.142 ms) ======
[2025-03-04T22:04:48.488Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-03-04T22:04:48.861Z] GC before operation: completed in 346.792 ms, heap usage 599.609 MB -> 44.790 MB.
[2025-03-04T22:04:52.140Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:04:55.406Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:04:58.667Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:05:01.891Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:05:03.759Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:05:06.424Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:05:07.730Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:05:10.237Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:05:10.237Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:05:10.237Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:05:10.237Z] Movies recommended for you:
[2025-03-04T22:05:10.237Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:05:10.237Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:05:10.237Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21503.494 ms) ======
[2025-03-04T22:05:10.237Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-03-04T22:05:10.617Z] GC before operation: completed in 274.439 ms, heap usage 584.475 MB -> 45.293 MB.
[2025-03-04T22:05:13.877Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:05:17.157Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:05:20.384Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:05:22.865Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:05:24.705Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:05:26.528Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:05:28.390Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:05:30.258Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:05:30.258Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:05:30.258Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:05:30.625Z] Movies recommended for you:
[2025-03-04T22:05:30.625Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:05:30.625Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:05:30.625Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19918.704 ms) ======
[2025-03-04T22:05:30.625Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-03-04T22:05:30.625Z] GC before operation: completed in 231.822 ms, heap usage 404.634 MB -> 45.145 MB.
[2025-03-04T22:05:33.869Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:05:37.179Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:05:39.665Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:05:42.904Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:05:44.750Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:05:46.648Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:05:48.559Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:05:49.832Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:05:50.209Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:05:50.209Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:05:50.609Z] Movies recommended for you:
[2025-03-04T22:05:50.609Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:05:50.609Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:05:50.609Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19694.651 ms) ======
[2025-03-04T22:05:50.609Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-03-04T22:05:50.609Z] GC before operation: completed in 208.817 ms, heap usage 389.120 MB -> 45.563 MB.
[2025-03-04T22:05:53.875Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:05:56.376Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:05:59.635Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:06:02.959Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:06:04.849Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:06:06.870Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:06:08.787Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:06:10.700Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:06:11.092Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:06:11.092Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:06:11.092Z] Movies recommended for you:
[2025-03-04T22:06:11.092Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:06:11.092Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:06:11.092Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20553.777 ms) ======
[2025-03-04T22:06:11.092Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-03-04T22:06:11.467Z] GC before operation: completed in 194.248 ms, heap usage 325.638 MB -> 42.194 MB.
[2025-03-04T22:06:14.046Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:06:17.437Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:06:19.938Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:06:23.830Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:06:24.226Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:06:26.073Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:06:27.925Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:06:29.779Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:06:29.779Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:06:29.779Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:06:29.779Z] Movies recommended for you:
[2025-03-04T22:06:29.779Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:06:29.779Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:06:29.779Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18529.683 ms) ======
[2025-03-04T22:06:29.779Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-03-04T22:06:30.149Z] GC before operation: completed in 202.364 ms, heap usage 350.777 MB -> 42.114 MB.
[2025-03-04T22:06:32.638Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:06:36.063Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:06:38.601Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:06:41.146Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:06:43.015Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:06:44.336Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:06:46.250Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:06:48.162Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:06:48.162Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:06:48.162Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:06:48.553Z] Movies recommended for you:
[2025-03-04T22:06:48.553Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:06:48.553Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:06:48.553Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18203.988 ms) ======
[2025-03-04T22:06:48.553Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-03-04T22:06:48.553Z] GC before operation: completed in 169.183 ms, heap usage 369.049 MB -> 42.622 MB.
[2025-03-04T22:06:51.071Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:06:54.479Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:06:57.141Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:06:59.814Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:07:01.120Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:07:03.025Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:07:04.318Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:07:06.387Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:07:06.387Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:07:06.387Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:07:06.387Z] Movies recommended for you:
[2025-03-04T22:07:06.387Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:07:06.387Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:07:06.387Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17982.027 ms) ======
[2025-03-04T22:07:06.387Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-03-04T22:07:06.762Z] GC before operation: completed in 166.583 ms, heap usage 350.814 MB -> 42.691 MB.
[2025-03-04T22:07:09.250Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:07:12.566Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:07:15.104Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:07:17.640Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:07:19.533Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:07:20.854Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:07:22.719Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:07:24.619Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:07:24.619Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:07:24.619Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:07:25.009Z] Movies recommended for you:
[2025-03-04T22:07:25.009Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:07:25.009Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:07:25.009Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18144.831 ms) ======
[2025-03-04T22:07:25.009Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-03-04T22:07:25.009Z] GC before operation: completed in 191.747 ms, heap usage 369.877 MB -> 42.458 MB.
[2025-03-04T22:07:27.511Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:07:30.744Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:07:33.406Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:07:35.928Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:07:37.832Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:07:39.209Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:07:41.147Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:07:47.243Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:07:47.243Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:07:47.243Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:07:47.243Z] Movies recommended for you:
[2025-03-04T22:07:47.243Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:07:47.243Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:07:47.243Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18077.165 ms) ======
[2025-03-04T22:07:47.243Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-03-04T22:07:47.243Z] GC before operation: completed in 203.171 ms, heap usage 378.014 MB -> 46.104 MB.
[2025-03-04T22:07:47.243Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:07:50.409Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:07:52.786Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:07:55.270Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:07:55.679Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:07:57.576Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:07:59.453Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:08:00.898Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:08:01.292Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:08:01.292Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:08:01.292Z] Movies recommended for you:
[2025-03-04T22:08:01.292Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:08:01.292Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:08:01.292Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (17976.091 ms) ======
[2025-03-04T22:08:01.292Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-03-04T22:08:01.292Z] GC before operation: completed in 144.574 ms, heap usage 371.575 MB -> 42.479 MB.
[2025-03-04T22:08:03.840Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:08:07.192Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:08:09.839Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:08:12.381Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:08:13.689Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:08:15.584Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:08:17.514Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:08:18.878Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:08:19.256Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:08:19.256Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:08:19.256Z] Movies recommended for you:
[2025-03-04T22:08:19.256Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:08:19.256Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:08:19.256Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (17845.916 ms) ======
[2025-03-04T22:08:19.256Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-03-04T22:08:19.256Z] GC before operation: completed in 155.659 ms, heap usage 351.691 MB -> 42.533 MB.
[2025-03-04T22:08:22.547Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:08:25.057Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:08:27.641Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:08:30.969Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:08:32.297Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:08:34.234Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:08:35.572Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:08:37.479Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:08:37.479Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:08:37.857Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:08:37.857Z] Movies recommended for you:
[2025-03-04T22:08:37.857Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:08:37.857Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:08:37.857Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18390.935 ms) ======
[2025-03-04T22:08:37.857Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-03-04T22:08:37.857Z] GC before operation: completed in 153.264 ms, heap usage 363.402 MB -> 43.048 MB.
[2025-03-04T22:08:40.490Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:08:43.873Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:08:46.450Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:08:48.959Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:08:50.844Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:08:52.172Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:08:54.036Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:08:55.974Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:08:55.974Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:08:55.974Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:08:55.975Z] Movies recommended for you:
[2025-03-04T22:08:55.975Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:08:55.975Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:08:55.975Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18162.288 ms) ======
[2025-03-04T22:08:55.975Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-03-04T22:08:56.355Z] GC before operation: completed in 199.421 ms, heap usage 381.333 MB -> 45.895 MB.
[2025-03-04T22:08:58.859Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:09:02.162Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:09:04.706Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:09:07.342Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:09:09.214Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:09:10.634Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:09:14.144Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:09:14.144Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:09:14.144Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:09:14.144Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:09:14.520Z] Movies recommended for you:
[2025-03-04T22:09:14.520Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:09:14.520Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:09:14.520Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18043.394 ms) ======
[2025-03-04T22:09:14.520Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-03-04T22:09:14.520Z] GC before operation: completed in 158.810 ms, heap usage 325.848 MB -> 42.536 MB.
[2025-03-04T22:09:17.048Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:09:20.391Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:09:22.908Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:09:25.464Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:09:26.790Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:09:28.670Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:09:30.583Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:09:31.959Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:09:32.339Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:09:32.339Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:09:32.339Z] Movies recommended for you:
[2025-03-04T22:09:32.339Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:09:32.339Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:09:32.339Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17889.146 ms) ======
[2025-03-04T22:09:32.339Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-03-04T22:09:32.723Z] GC before operation: completed in 155.065 ms, heap usage 351.275 MB -> 42.660 MB.
[2025-03-04T22:09:35.248Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:09:38.566Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:09:41.131Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:09:43.664Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:09:45.567Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:09:46.886Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:09:48.787Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:09:50.140Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:09:50.531Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:09:50.531Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:09:50.531Z] Movies recommended for you:
[2025-03-04T22:09:50.531Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:09:50.531Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:09:50.531Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18093.915 ms) ======
[2025-03-04T22:09:50.531Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-03-04T22:09:50.908Z] GC before operation: completed in 145.453 ms, heap usage 340.043 MB -> 42.500 MB.
[2025-03-04T22:09:53.457Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:09:56.904Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:09:58.861Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:10:02.206Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:10:05.190Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:10:05.190Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:10:06.555Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:10:08.453Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:10:08.453Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:10:08.453Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:10:08.834Z] Movies recommended for you:
[2025-03-04T22:10:08.834Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:10:08.834Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:10:08.834Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17932.029 ms) ======
[2025-03-04T22:10:08.834Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-03-04T22:10:08.834Z] GC before operation: completed in 150.986 ms, heap usage 375.540 MB -> 46.107 MB.
[2025-03-04T22:10:11.354Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:10:14.658Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:10:17.184Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:10:19.725Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:10:21.626Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:10:23.086Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:10:24.977Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:10:26.360Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:10:26.781Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:10:26.781Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:10:26.781Z] Movies recommended for you:
[2025-03-04T22:10:26.781Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:10:26.781Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:10:26.781Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17910.755 ms) ======
[2025-03-04T22:10:26.781Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-03-04T22:10:26.781Z] GC before operation: completed in 146.252 ms, heap usage 408.450 MB -> 47.622 MB.
[2025-03-04T22:10:30.106Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-03-04T22:10:32.673Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-03-04T22:10:35.365Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-03-04T22:10:37.949Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-03-04T22:10:41.454Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-03-04T22:10:41.454Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-03-04T22:10:44.008Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-03-04T22:10:46.493Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-03-04T22:10:46.493Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-03-04T22:10:46.493Z] The best model improves the baseline by 14.52%.
[2025-03-04T22:10:46.493Z] Movies recommended for you:
[2025-03-04T22:10:46.493Z] WARNING: This benchmark provides no result that can be validated.
[2025-03-04T22:10:46.493Z] There is no way to check that no silent failure occurred.
[2025-03-04T22:10:46.493Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (17949.627 ms) ======
[2025-03-04T22:10:46.493Z] -----------------------------------
[2025-03-04T22:10:46.493Z] renaissance-movie-lens_0_PASSED
[2025-03-04T22:10:46.493Z] -----------------------------------
[2025-03-04T22:10:46.493Z]
[2025-03-04T22:10:46.493Z] TEST TEARDOWN:
[2025-03-04T22:10:46.493Z] Nothing to be done for teardown.
[2025-03-04T22:10:46.493Z] renaissance-movie-lens_0 Finish Time: Tue Mar 4 22:10:45 2025 Epoch Time (ms): 1741126245446