renaissance-movie-lens_0
[2025-02-25T21:51:42.067Z] Running test renaissance-movie-lens_0 ...
[2025-02-25T21:51:42.067Z] ===============================================
[2025-02-25T21:51:42.067Z] renaissance-movie-lens_0 Start Time: Tue Feb 25 21:51:41 2025 Epoch Time (ms): 1740520301945
[2025-02-25T21:51:42.067Z] variation: NoOptions
[2025-02-25T21:51:42.067Z] JVM_OPTIONS:
[2025-02-25T21:51:42.067Z] { \
[2025-02-25T21:51:42.067Z] echo ""; echo "TEST SETUP:"; \
[2025-02-25T21:51:42.067Z] echo "Nothing to be done for setup."; \
[2025-02-25T21:51:42.067Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17405193194599/renaissance-movie-lens_0"; \
[2025-02-25T21:51:42.067Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17405193194599/renaissance-movie-lens_0"; \
[2025-02-25T21:51:42.067Z] echo ""; echo "TESTING:"; \
[2025-02-25T21:51:42.067Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17405193194599/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-25T21:51:42.067Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17405193194599/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-25T21:51:42.067Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-25T21:51:42.067Z] echo "Nothing to be done for teardown."; \
[2025-02-25T21:51:42.067Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17405193194599/TestTargetResult";
[2025-02-25T21:51:42.067Z]
[2025-02-25T21:51:42.067Z] TEST SETUP:
[2025-02-25T21:51:42.067Z] Nothing to be done for setup.
[2025-02-25T21:51:42.067Z]
[2025-02-25T21:51:42.067Z] TESTING:
[2025-02-25T21:51:46.204Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-25T21:51:48.161Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-02-25T21:51:53.514Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-25T21:51:53.514Z] Training: 60056, validation: 20285, test: 19854
[2025-02-25T21:51:53.514Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-25T21:51:53.514Z] GC before operation: completed in 253.082 ms, heap usage 170.388 MB -> 26.145 MB.
[2025-02-25T21:52:00.239Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:52:03.252Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:52:06.258Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:52:09.277Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:52:11.229Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:52:12.196Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:52:14.149Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:52:16.115Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:52:16.115Z] 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.
[2025-02-25T21:52:16.115Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:52:16.115Z] Movies recommended for you:
[2025-02-25T21:52:16.115Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:52:16.115Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:52:16.115Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22586.076 ms) ======
[2025-02-25T21:52:16.115Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-25T21:52:17.064Z] GC before operation: completed in 319.170 ms, heap usage 223.722 MB -> 42.256 MB.
[2025-02-25T21:52:19.012Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:52:22.044Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:52:25.063Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:52:27.020Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:52:28.974Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:52:29.921Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:52:31.899Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:52:34.071Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:52:34.071Z] 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.
[2025-02-25T21:52:34.071Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:52:34.071Z] Movies recommended for you:
[2025-02-25T21:52:34.071Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:52:34.071Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:52:34.071Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16856.647 ms) ======
[2025-02-25T21:52:34.071Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-25T21:52:34.071Z] GC before operation: completed in 224.949 ms, heap usage 155.163 MB -> 43.226 MB.
[2025-02-25T21:52:36.017Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:52:39.044Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:52:40.996Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:52:42.944Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:52:44.892Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:52:45.892Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:52:47.840Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:52:48.789Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:52:48.789Z] 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.
[2025-02-25T21:52:48.789Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:52:49.744Z] Movies recommended for you:
[2025-02-25T21:52:49.744Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:52:49.744Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:52:49.744Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (15448.095 ms) ======
[2025-02-25T21:52:49.744Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-25T21:52:49.744Z] GC before operation: completed in 210.159 ms, heap usage 219.239 MB -> 43.239 MB.
[2025-02-25T21:52:51.706Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:52:53.659Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:52:56.693Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:52:58.649Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:53:00.624Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:53:01.580Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:53:02.531Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:53:06.057Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:53:06.058Z] 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.
[2025-02-25T21:53:06.058Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:53:06.058Z] Movies recommended for you:
[2025-02-25T21:53:06.058Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:53:06.058Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:53:06.058Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15214.754 ms) ======
[2025-02-25T21:53:06.058Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-25T21:53:06.058Z] GC before operation: completed in 181.005 ms, heap usage 216.871 MB -> 43.079 MB.
[2025-02-25T21:53:07.011Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:53:08.981Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:53:12.054Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:53:14.003Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:53:14.951Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:53:16.952Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:53:17.901Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:53:19.847Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:53:19.847Z] 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.
[2025-02-25T21:53:19.847Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:53:19.847Z] Movies recommended for you:
[2025-02-25T21:53:19.847Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:53:19.847Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:53:19.847Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (14884.733 ms) ======
[2025-02-25T21:53:19.847Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-25T21:53:19.847Z] GC before operation: completed in 186.272 ms, heap usage 112.181 MB -> 41.651 MB.
[2025-02-25T21:53:21.868Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:53:23.816Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:53:26.876Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:53:28.830Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:53:29.791Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:53:30.743Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:53:32.702Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:53:33.655Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:53:33.655Z] 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.
[2025-02-25T21:53:33.655Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:53:33.655Z] Movies recommended for you:
[2025-02-25T21:53:33.655Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:53:33.655Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:53:33.655Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14126.199 ms) ======
[2025-02-25T21:53:33.655Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-25T21:53:35.503Z] GC before operation: completed in 150.109 ms, heap usage 124.862 MB -> 41.616 MB.
[2025-02-25T21:53:36.595Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:53:38.543Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:53:40.495Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:53:42.445Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:53:44.397Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:53:45.441Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:53:46.394Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:53:48.340Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:53:48.340Z] 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.
[2025-02-25T21:53:48.340Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:53:48.340Z] Movies recommended for you:
[2025-02-25T21:53:48.340Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:53:48.340Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:53:48.340Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14064.000 ms) ======
[2025-02-25T21:53:48.340Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-25T21:53:48.340Z] GC before operation: completed in 176.395 ms, heap usage 136.683 MB -> 41.858 MB.
[2025-02-25T21:53:50.289Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:53:52.355Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:53:55.366Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:53:57.324Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:53:58.285Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:54:00.241Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:54:01.194Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:54:03.142Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:54:03.142Z] 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.
[2025-02-25T21:54:03.142Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:54:03.142Z] Movies recommended for you:
[2025-02-25T21:54:03.142Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:54:03.142Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:54:03.142Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14797.154 ms) ======
[2025-02-25T21:54:03.142Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-25T21:54:03.142Z] GC before operation: completed in 200.983 ms, heap usage 121.133 MB -> 57.537 MB.
[2025-02-25T21:54:06.151Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:54:08.102Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:54:10.061Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:54:12.015Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:54:13.966Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:54:14.915Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:54:16.863Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:54:17.813Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:54:17.813Z] 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.
[2025-02-25T21:54:17.813Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:54:17.813Z] Movies recommended for you:
[2025-02-25T21:54:17.813Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:54:17.813Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:54:17.813Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14711.601 ms) ======
[2025-02-25T21:54:17.813Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-25T21:54:18.766Z] GC before operation: completed in 226.138 ms, heap usage 272.923 MB -> 59.813 MB.
[2025-02-25T21:54:20.715Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:54:22.664Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:54:24.611Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:54:27.671Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:54:28.624Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:54:29.572Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:54:31.521Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:54:32.471Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:54:33.420Z] 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.
[2025-02-25T21:54:33.420Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:54:33.420Z] Movies recommended for you:
[2025-02-25T21:54:33.420Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:54:33.420Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:54:33.420Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14715.742 ms) ======
[2025-02-25T21:54:33.420Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-25T21:54:33.420Z] GC before operation: completed in 214.831 ms, heap usage 222.987 MB -> 49.512 MB.
[2025-02-25T21:54:35.408Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:54:37.358Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:54:40.371Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:54:42.327Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:54:43.277Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:54:44.234Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:54:46.196Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:54:47.153Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:54:47.153Z] 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.
[2025-02-25T21:54:47.153Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:54:48.151Z] Movies recommended for you:
[2025-02-25T21:54:48.151Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:54:48.151Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:54:48.151Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14335.196 ms) ======
[2025-02-25T21:54:48.151Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-25T21:54:48.151Z] GC before operation: completed in 199.018 ms, heap usage 197.009 MB -> 70.137 MB.
[2025-02-25T21:54:50.104Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:54:52.084Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:54:54.140Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:54:56.091Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:54:58.055Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:54:59.007Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:55:00.990Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:55:01.943Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:55:02.900Z] 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.
[2025-02-25T21:55:02.900Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:55:02.900Z] Movies recommended for you:
[2025-02-25T21:55:02.900Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:55:02.900Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:55:02.900Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14666.111 ms) ======
[2025-02-25T21:55:02.900Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-25T21:55:02.900Z] GC before operation: completed in 180.730 ms, heap usage 215.264 MB -> 49.354 MB.
[2025-02-25T21:55:04.848Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:55:06.802Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:55:09.821Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:55:11.774Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:55:12.732Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:55:13.712Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:55:15.664Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:55:16.614Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:55:17.564Z] 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.
[2025-02-25T21:55:17.564Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:55:17.564Z] Movies recommended for you:
[2025-02-25T21:55:17.564Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:55:17.564Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:55:17.564Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14591.278 ms) ======
[2025-02-25T21:55:17.564Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-25T21:55:17.564Z] GC before operation: completed in 206.698 ms, heap usage 214.326 MB -> 70.890 MB.
[2025-02-25T21:55:19.514Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:55:21.462Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:55:24.654Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:55:26.606Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:55:27.556Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:55:28.505Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:55:30.482Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:55:31.430Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:55:31.430Z] 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.
[2025-02-25T21:55:31.430Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:55:32.379Z] Movies recommended for you:
[2025-02-25T21:55:32.379Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:55:32.379Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:55:32.379Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14449.245 ms) ======
[2025-02-25T21:55:32.379Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-25T21:55:32.379Z] GC before operation: completed in 198.072 ms, heap usage 271.044 MB -> 70.681 MB.
[2025-02-25T21:55:35.554Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:55:36.502Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:55:38.472Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:55:40.418Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:55:42.372Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:55:43.330Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:55:45.281Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:55:46.231Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:55:46.231Z] 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.
[2025-02-25T21:55:46.231Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:55:46.231Z] Movies recommended for you:
[2025-02-25T21:55:46.231Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:55:46.231Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:55:46.231Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14409.938 ms) ======
[2025-02-25T21:55:46.231Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-25T21:55:47.182Z] GC before operation: completed in 230.804 ms, heap usage 293.682 MB -> 70.949 MB.
[2025-02-25T21:55:49.131Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:55:51.086Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:55:53.206Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:55:55.154Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:55:57.103Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:55:58.105Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:55:59.054Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:56:01.007Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:56:01.007Z] 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.
[2025-02-25T21:56:01.007Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:56:01.007Z] Movies recommended for you:
[2025-02-25T21:56:01.007Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:56:01.007Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:56:01.007Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14393.666 ms) ======
[2025-02-25T21:56:01.007Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-25T21:56:01.007Z] GC before operation: completed in 201.546 ms, heap usage 261.260 MB -> 71.079 MB.
[2025-02-25T21:56:04.018Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:56:05.972Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:56:07.948Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:56:09.895Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:56:11.854Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:56:12.806Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:56:13.756Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:56:15.743Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:56:15.743Z] 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.
[2025-02-25T21:56:15.743Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:56:15.743Z] Movies recommended for you:
[2025-02-25T21:56:15.743Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:56:15.743Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:56:15.743Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14634.753 ms) ======
[2025-02-25T21:56:15.743Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-25T21:56:17.320Z] GC before operation: completed in 170.099 ms, heap usage 225.719 MB -> 45.852 MB.
[2025-02-25T21:56:18.326Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:56:20.275Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:56:23.282Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:56:25.229Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:56:26.180Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:56:27.129Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:56:29.076Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:56:30.033Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:56:30.982Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-25T21:56:30.982Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:56:30.982Z] Movies recommended for you:
[2025-02-25T21:56:30.982Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:56:30.982Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:56:30.982Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14452.887 ms) ======
[2025-02-25T21:56:30.982Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-25T21:56:30.982Z] GC before operation: completed in 206.208 ms, heap usage 202.978 MB -> 70.679 MB.
[2025-02-25T21:56:32.931Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:56:34.878Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:56:37.961Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:56:39.920Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:56:40.871Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:56:41.820Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:56:43.767Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:56:44.717Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:56:45.670Z] 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.
[2025-02-25T21:56:45.670Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:56:45.670Z] Movies recommended for you:
[2025-02-25T21:56:45.670Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:56:45.670Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:56:45.670Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14456.156 ms) ======
[2025-02-25T21:56:45.670Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-25T21:56:45.670Z] GC before operation: completed in 214.523 ms, heap usage 291.660 MB -> 71.129 MB.
[2025-02-25T21:56:47.617Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T21:56:49.565Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T21:56:52.574Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T21:56:54.901Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T21:56:55.850Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T21:56:56.800Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T21:56:58.750Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T21:56:59.702Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T21:56:59.702Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-25T21:56:59.702Z] The best model improves the baseline by 14.52%.
[2025-02-25T21:56:59.702Z] Movies recommended for you:
[2025-02-25T21:56:59.702Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T21:56:59.702Z] There is no way to check that no silent failure occurred.
[2025-02-25T21:56:59.702Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14427.483 ms) ======
[2025-02-25T21:57:00.650Z] -----------------------------------
[2025-02-25T21:57:00.650Z] renaissance-movie-lens_0_PASSED
[2025-02-25T21:57:00.650Z] -----------------------------------
[2025-02-25T21:57:00.650Z]
[2025-02-25T21:57:00.650Z] TEST TEARDOWN:
[2025-02-25T21:57:00.650Z] Nothing to be done for teardown.
[2025-02-25T21:57:00.650Z] renaissance-movie-lens_0 Finish Time: Tue Feb 25 21:57:00 2025 Epoch Time (ms): 1740520620139