renaissance-movie-lens_0
[2024-11-28T23:42:25.587Z] Running test renaissance-movie-lens_0 ...
[2024-11-28T23:42:25.587Z] ===============================================
[2024-11-28T23:42:25.587Z] renaissance-movie-lens_0 Start Time: Thu Nov 28 17:42:25 2024 Epoch Time (ms): 1732837345167
[2024-11-28T23:42:25.587Z] variation: NoOptions
[2024-11-28T23:42:25.587Z] JVM_OPTIONS:
[2024-11-28T23:42:25.587Z] { \
[2024-11-28T23:42:25.587Z] echo ""; echo "TEST SETUP:"; \
[2024-11-28T23:42:25.587Z] echo "Nothing to be done for setup."; \
[2024-11-28T23:42:25.587Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17328364844732/renaissance-movie-lens_0"; \
[2024-11-28T23:42:25.587Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17328364844732/renaissance-movie-lens_0"; \
[2024-11-28T23:42:25.587Z] echo ""; echo "TESTING:"; \
[2024-11-28T23:42:25.587Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/jdkbinary/j2sdk-image/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_17328364844732/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-28T23:42:25.587Z] 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_17328364844732/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-28T23:42:25.587Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-28T23:42:25.587Z] echo "Nothing to be done for teardown."; \
[2024-11-28T23:42:25.587Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_linux/aqa-tests/TKG/../TKG/output_17328364844732/TestTargetResult";
[2024-11-28T23:42:25.587Z]
[2024-11-28T23:42:25.587Z] TEST SETUP:
[2024-11-28T23:42:25.587Z] Nothing to be done for setup.
[2024-11-28T23:42:25.587Z]
[2024-11-28T23:42:25.587Z] TESTING:
[2024-11-28T23:42:28.642Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-28T23:42:30.835Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-11-28T23:42:34.837Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-28T23:42:34.837Z] Training: 60056, validation: 20285, test: 19854
[2024-11-28T23:42:34.837Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-28T23:42:35.528Z] GC before operation: completed in 406.033 ms, heap usage 95.166 MB -> 28.797 MB.
[2024-11-28T23:42:41.929Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:42:45.013Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:42:49.049Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:42:51.259Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:42:53.515Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:42:54.938Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:42:56.351Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:42:58.553Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:42:58.553Z] 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.
[2024-11-28T23:42:58.553Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:42:58.553Z] Movies recommended for you:
[2024-11-28T23:42:58.553Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:42:58.553Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:42:58.553Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23608.116 ms) ======
[2024-11-28T23:42:58.553Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-28T23:42:59.230Z] GC before operation: completed in 344.392 ms, heap usage 354.240 MB -> 50.516 MB.
[2024-11-28T23:43:01.452Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:43:04.608Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:43:08.311Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:43:09.727Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:43:11.126Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:43:13.362Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:43:14.804Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:43:17.008Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:43:17.696Z] 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.
[2024-11-28T23:43:17.696Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:43:17.696Z] Movies recommended for you:
[2024-11-28T23:43:17.696Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:43:17.696Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:43:17.696Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18519.796 ms) ======
[2024-11-28T23:43:17.696Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-28T23:43:17.696Z] GC before operation: completed in 177.770 ms, heap usage 383.688 MB -> 47.908 MB.
[2024-11-28T23:43:20.771Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:43:23.830Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:43:26.999Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:43:29.218Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:43:30.638Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:43:32.059Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:43:33.485Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:43:34.912Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:43:35.590Z] 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.
[2024-11-28T23:43:35.590Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:43:35.590Z] Movies recommended for you:
[2024-11-28T23:43:35.590Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:43:35.590Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:43:35.590Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17831.935 ms) ======
[2024-11-28T23:43:35.590Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-28T23:43:35.590Z] GC before operation: completed in 223.021 ms, heap usage 220.532 MB -> 45.774 MB.
[2024-11-28T23:43:38.660Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:43:40.100Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:43:43.193Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:43:45.418Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:43:46.827Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:43:48.250Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:43:49.695Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:43:51.931Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:43:51.931Z] 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.
[2024-11-28T23:43:51.931Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:43:51.931Z] Movies recommended for you:
[2024-11-28T23:43:51.931Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:43:51.931Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:43:51.931Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16114.558 ms) ======
[2024-11-28T23:43:51.931Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-28T23:43:51.931Z] GC before operation: completed in 145.308 ms, heap usage 267.489 MB -> 52.154 MB.
[2024-11-28T23:43:54.149Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:43:56.362Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:43:59.435Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:44:01.691Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:44:03.108Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:44:04.532Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:44:05.948Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:44:06.651Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:44:07.347Z] 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.
[2024-11-28T23:44:07.348Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:44:07.348Z] Movies recommended for you:
[2024-11-28T23:44:07.348Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:44:07.348Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:44:07.348Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15196.373 ms) ======
[2024-11-28T23:44:07.348Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-28T23:44:07.348Z] GC before operation: completed in 170.141 ms, heap usage 294.073 MB -> 48.969 MB.
[2024-11-28T23:44:09.578Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:44:11.788Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:44:15.292Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:44:16.740Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:44:18.148Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:44:19.569Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:44:20.981Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:44:22.390Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:44:23.071Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-28T23:44:23.071Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:44:23.071Z] Movies recommended for you:
[2024-11-28T23:44:23.071Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:44:23.071Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:44:23.071Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15543.549 ms) ======
[2024-11-28T23:44:23.071Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-28T23:44:23.071Z] GC before operation: completed in 152.093 ms, heap usage 177.826 MB -> 50.018 MB.
[2024-11-28T23:44:25.289Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:44:27.505Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:44:30.585Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:44:31.995Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:44:33.419Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:44:34.831Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:44:36.266Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:44:37.684Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:44:38.363Z] 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.
[2024-11-28T23:44:38.363Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:44:38.363Z] Movies recommended for you:
[2024-11-28T23:44:38.363Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:44:38.363Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:44:38.363Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15015.241 ms) ======
[2024-11-28T23:44:38.363Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-28T23:44:38.363Z] GC before operation: completed in 174.492 ms, heap usage 329.207 MB -> 51.941 MB.
[2024-11-28T23:44:40.597Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:44:42.819Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:44:45.066Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:44:47.347Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:44:48.748Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:44:50.172Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:44:51.589Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:44:52.994Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:44:53.688Z] 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.
[2024-11-28T23:44:53.688Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:44:53.688Z] Movies recommended for you:
[2024-11-28T23:44:53.688Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:44:53.688Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:44:53.688Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15232.429 ms) ======
[2024-11-28T23:44:53.688Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-28T23:44:53.688Z] GC before operation: completed in 127.634 ms, heap usage 407.408 MB -> 48.424 MB.
[2024-11-28T23:44:55.899Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:44:58.100Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:45:00.313Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:45:02.532Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:45:03.954Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:45:05.371Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:45:06.795Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:45:08.205Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:45:08.205Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-28T23:45:08.205Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:45:08.205Z] Movies recommended for you:
[2024-11-28T23:45:08.205Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:45:08.205Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:45:08.205Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14751.172 ms) ======
[2024-11-28T23:45:08.205Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-28T23:45:08.882Z] GC before operation: completed in 182.281 ms, heap usage 415.894 MB -> 55.544 MB.
[2024-11-28T23:45:11.104Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:45:13.295Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:45:15.525Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:45:17.738Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:45:19.156Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:45:20.871Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:45:22.282Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:45:23.704Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:45:23.704Z] 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.
[2024-11-28T23:45:23.704Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:45:23.704Z] Movies recommended for you:
[2024-11-28T23:45:23.704Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:45:23.704Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:45:23.704Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15100.199 ms) ======
[2024-11-28T23:45:23.704Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-28T23:45:23.704Z] GC before operation: completed in 218.515 ms, heap usage 407.066 MB -> 47.108 MB.
[2024-11-28T23:45:25.925Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:45:29.014Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:45:31.239Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:45:32.647Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:45:34.864Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:45:35.547Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:45:37.749Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:45:38.443Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:45:39.137Z] 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.
[2024-11-28T23:45:39.137Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:45:39.137Z] Movies recommended for you:
[2024-11-28T23:45:39.137Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:45:39.137Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:45:39.137Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15120.549 ms) ======
[2024-11-28T23:45:39.137Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-28T23:45:39.137Z] GC before operation: completed in 132.206 ms, heap usage 141.466 MB -> 45.832 MB.
[2024-11-28T23:45:41.349Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:45:43.553Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:45:45.781Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:45:48.008Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:45:49.416Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:45:50.836Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:45:52.255Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:45:53.716Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:45:54.393Z] 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.
[2024-11-28T23:45:54.393Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:45:54.393Z] Movies recommended for you:
[2024-11-28T23:45:54.393Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:45:54.393Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:45:54.393Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14947.074 ms) ======
[2024-11-28T23:45:54.393Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-28T23:45:54.393Z] GC before operation: completed in 129.488 ms, heap usage 275.280 MB -> 55.548 MB.
[2024-11-28T23:45:56.595Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:45:58.806Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:46:01.015Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:46:03.228Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:46:04.643Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:46:06.046Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:46:08.259Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:46:08.965Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:46:09.668Z] 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.
[2024-11-28T23:46:09.668Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:46:09.668Z] Movies recommended for you:
[2024-11-28T23:46:09.668Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:46:09.668Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:46:09.668Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15295.674 ms) ======
[2024-11-28T23:46:09.668Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-28T23:46:09.668Z] GC before operation: completed in 154.786 ms, heap usage 206.535 MB -> 51.864 MB.
[2024-11-28T23:46:11.873Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:46:14.101Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:46:17.182Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:46:19.417Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:46:20.839Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:46:21.521Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:46:22.945Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:46:24.356Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:46:25.047Z] 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.
[2024-11-28T23:46:25.047Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:46:25.047Z] Movies recommended for you:
[2024-11-28T23:46:25.047Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:46:25.047Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:46:25.047Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15215.610 ms) ======
[2024-11-28T23:46:25.047Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-28T23:46:25.047Z] GC before operation: completed in 136.422 ms, heap usage 310.865 MB -> 56.111 MB.
[2024-11-28T23:46:27.302Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:46:29.520Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:46:32.635Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:46:34.061Z] RMSE (validation) = 1.0045407704488025 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:46:36.265Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:46:36.948Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:46:38.369Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:46:39.937Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:46:39.937Z] 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.
[2024-11-28T23:46:39.937Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:46:40.623Z] Movies recommended for you:
[2024-11-28T23:46:40.623Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:46:40.623Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:46:40.623Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15211.812 ms) ======
[2024-11-28T23:46:40.623Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-28T23:46:40.623Z] GC before operation: completed in 154.221 ms, heap usage 171.866 MB -> 51.688 MB.
[2024-11-28T23:46:42.838Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:46:45.053Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:46:47.344Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:46:49.543Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:46:50.960Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:46:52.373Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:46:53.786Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:46:55.191Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:46:55.191Z] 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.
[2024-11-28T23:46:55.874Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:46:55.874Z] Movies recommended for you:
[2024-11-28T23:46:55.874Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:46:55.874Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:46:55.874Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15154.968 ms) ======
[2024-11-28T23:46:55.874Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-28T23:46:55.874Z] GC before operation: completed in 158.624 ms, heap usage 160.323 MB -> 63.290 MB.
[2024-11-28T23:46:58.085Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:47:01.161Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:47:03.376Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:47:05.624Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:47:06.307Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:47:07.710Z] RMSE (validation) = 1.1174953757118413 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:47:09.137Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:47:10.570Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:47:11.248Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522617949711.
[2024-11-28T23:47:11.248Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:47:11.248Z] Movies recommended for you:
[2024-11-28T23:47:11.248Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:47:11.248Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:47:11.248Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15318.533 ms) ======
[2024-11-28T23:47:11.248Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-28T23:47:11.248Z] GC before operation: completed in 211.363 ms, heap usage 631.564 MB -> 72.458 MB.
[2024-11-28T23:47:13.462Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:47:16.539Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:47:17.954Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:47:20.161Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:47:21.589Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:47:23.015Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:47:25.225Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:47:26.637Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:47:26.637Z] 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.
[2024-11-28T23:47:26.637Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:47:26.637Z] Movies recommended for you:
[2024-11-28T23:47:26.637Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:47:26.637Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:47:26.637Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (15401.065 ms) ======
[2024-11-28T23:47:26.637Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-28T23:47:26.637Z] GC before operation: completed in 150.225 ms, heap usage 275.324 MB -> 53.808 MB.
[2024-11-28T23:47:28.845Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:47:31.076Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:47:34.131Z] RMSE (validation) = 1.3105189694032011 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:47:35.554Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:47:37.745Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:47:38.431Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:47:39.887Z] RMSE (validation) = 0.9275717388537591 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:47:41.320Z] RMSE (validation) = 0.9001440970559652 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:47:42.001Z] 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.
[2024-11-28T23:47:42.001Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:47:42.001Z] Movies recommended for you:
[2024-11-28T23:47:42.001Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:47:42.001Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:47:42.001Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14931.699 ms) ======
[2024-11-28T23:47:42.001Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-28T23:47:42.001Z] GC before operation: completed in 148.657 ms, heap usage 580.598 MB -> 74.884 MB.
[2024-11-28T23:47:44.207Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T23:47:46.457Z] RMSE (validation) = 2.1340923219297814 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T23:47:48.660Z] RMSE (validation) = 1.310518969403201 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T23:47:50.865Z] RMSE (validation) = 1.0045407704488027 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T23:47:52.325Z] RMSE (validation) = 1.221833058605191 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T23:47:53.731Z] RMSE (validation) = 1.117495375711841 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T23:47:55.158Z] RMSE (validation) = 0.9275717388537592 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T23:47:56.606Z] RMSE (validation) = 0.9001440970559653 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T23:47:56.606Z] 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.
[2024-11-28T23:47:56.606Z] The best model improves the baseline by 14.43%.
[2024-11-28T23:47:56.606Z] Movies recommended for you:
[2024-11-28T23:47:56.606Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T23:47:56.606Z] There is no way to check that no silent failure occurred.
[2024-11-28T23:47:56.606Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14809.476 ms) ======
[2024-11-28T23:47:58.010Z] -----------------------------------
[2024-11-28T23:47:58.010Z] renaissance-movie-lens_0_PASSED
[2024-11-28T23:47:58.010Z] -----------------------------------
[2024-11-28T23:47:58.010Z]
[2024-11-28T23:47:58.010Z] TEST TEARDOWN:
[2024-11-28T23:47:58.010Z] Nothing to be done for teardown.
[2024-11-28T23:47:58.010Z] renaissance-movie-lens_0 Finish Time: Thu Nov 28 17:47:57 2024 Epoch Time (ms): 1732837677545