renaissance-movie-lens_0
[2024-11-28T22:10:55.151Z] Running test renaissance-movie-lens_0 ...
[2024-11-28T22:10:55.151Z] ===============================================
[2024-11-28T22:10:55.151Z] renaissance-movie-lens_0 Start Time: Thu Nov 28 22:10:53 2024 Epoch Time (ms): 1732831853217
[2024-11-28T22:10:55.151Z] variation: NoOptions
[2024-11-28T22:10:55.151Z] JVM_OPTIONS:
[2024-11-28T22:10:55.151Z] { \
[2024-11-28T22:10:55.151Z] echo ""; echo "TEST SETUP:"; \
[2024-11-28T22:10:55.151Z] echo "Nothing to be done for setup."; \
[2024-11-28T22:10:55.151Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17328306537033/renaissance-movie-lens_0"; \
[2024-11-28T22:10:55.151Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17328306537033/renaissance-movie-lens_0"; \
[2024-11-28T22:10:55.151Z] echo ""; echo "TESTING:"; \
[2024-11-28T22:10:55.151Z] "/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_17328306537033/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-28T22:10:55.151Z] 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_17328306537033/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-28T22:10:55.151Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-28T22:10:55.151Z] echo "Nothing to be done for teardown."; \
[2024-11-28T22:10:55.151Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_aarch64_linux/aqa-tests/TKG/../TKG/output_17328306537033/TestTargetResult";
[2024-11-28T22:10:55.151Z]
[2024-11-28T22:10:55.151Z] TEST SETUP:
[2024-11-28T22:10:55.151Z] Nothing to be done for setup.
[2024-11-28T22:10:55.151Z]
[2024-11-28T22:10:55.151Z] TESTING:
[2024-11-28T22:10:57.710Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-28T22:11:00.318Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-28T22:11:05.596Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-28T22:11:06.010Z] Training: 60056, validation: 20285, test: 19854
[2024-11-28T22:11:06.010Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-28T22:11:06.010Z] GC before operation: completed in 232.647 ms, heap usage 142.419 MB -> 25.993 MB.
[2024-11-28T22:11:13.932Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:11:19.233Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:11:24.494Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:11:28.723Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:11:31.271Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:11:33.830Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:11:36.418Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:11:39.850Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:11:39.850Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-28T22:11:39.850Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:11:40.280Z] Movies recommended for you:
[2024-11-28T22:11:40.280Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:11:40.280Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:11:40.280Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (33972.847 ms) ======
[2024-11-28T22:11:40.280Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-28T22:11:40.688Z] GC before operation: completed in 397.574 ms, heap usage 465.634 MB -> 44.240 MB.
[2024-11-28T22:11:44.927Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:11:48.292Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:11:51.612Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:11:54.877Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:11:56.789Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:11:59.333Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:12:01.232Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:12:03.143Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:12:03.143Z] 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.
[2024-11-28T22:12:03.523Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:12:03.523Z] Movies recommended for you:
[2024-11-28T22:12:03.523Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:12:03.523Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:12:03.523Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (22987.301 ms) ======
[2024-11-28T22:12:03.523Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-28T22:12:03.902Z] GC before operation: completed in 277.848 ms, heap usage 161.092 MB -> 40.886 MB.
[2024-11-28T22:12:07.195Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:12:10.510Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:12:13.037Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:12:16.404Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:12:17.713Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:12:19.614Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:12:21.524Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:12:23.441Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:12:23.441Z] 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.
[2024-11-28T22:12:23.441Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:12:23.849Z] Movies recommended for you:
[2024-11-28T22:12:23.849Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:12:23.849Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:12:23.849Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (19910.921 ms) ======
[2024-11-28T22:12:23.849Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-28T22:12:23.849Z] GC before operation: completed in 243.719 ms, heap usage 475.399 MB -> 45.262 MB.
[2024-11-28T22:12:27.212Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:12:30.548Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:12:33.100Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:12:36.473Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:12:39.266Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:12:41.180Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:12:42.519Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:12:44.450Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:12:44.870Z] 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.
[2024-11-28T22:12:44.870Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:12:44.870Z] Movies recommended for you:
[2024-11-28T22:12:44.870Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:12:44.870Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:12:44.870Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21084.354 ms) ======
[2024-11-28T22:12:44.870Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-28T22:12:45.250Z] GC before operation: completed in 209.694 ms, heap usage 437.537 MB -> 45.590 MB.
[2024-11-28T22:12:47.801Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:12:51.102Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:12:54.438Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:12:57.804Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:12:59.127Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:13:01.001Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:13:02.935Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:13:05.519Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:13:05.519Z] 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.
[2024-11-28T22:13:05.519Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:13:05.519Z] Movies recommended for you:
[2024-11-28T22:13:05.519Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:13:05.519Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:13:05.519Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20440.496 ms) ======
[2024-11-28T22:13:05.519Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-28T22:13:05.902Z] GC before operation: completed in 213.198 ms, heap usage 433.088 MB -> 45.802 MB.
[2024-11-28T22:13:08.480Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:13:11.978Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:13:14.614Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:13:17.331Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:13:18.707Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:13:20.601Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:13:22.509Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:13:23.892Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:13:24.303Z] 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.
[2024-11-28T22:13:24.303Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:13:24.303Z] Movies recommended for you:
[2024-11-28T22:13:24.304Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:13:24.304Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:13:24.304Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18455.095 ms) ======
[2024-11-28T22:13:24.304Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-28T22:13:24.690Z] GC before operation: completed in 193.546 ms, heap usage 420.341 MB -> 45.697 MB.
[2024-11-28T22:13:27.220Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:13:30.511Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:13:33.095Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:13:35.643Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:13:37.591Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:13:39.099Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:13:41.038Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:13:42.400Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:13:42.817Z] 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.
[2024-11-28T22:13:42.817Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:13:42.817Z] Movies recommended for you:
[2024-11-28T22:13:42.817Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:13:42.817Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:13:42.817Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (18300.587 ms) ======
[2024-11-28T22:13:42.817Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-28T22:13:43.197Z] GC before operation: completed in 199.923 ms, heap usage 409.656 MB -> 45.865 MB.
[2024-11-28T22:13:45.742Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:13:48.301Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:13:51.618Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:13:54.164Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:13:56.062Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:13:57.404Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:13:59.351Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:14:00.734Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:14:01.141Z] 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.
[2024-11-28T22:14:01.141Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:14:01.141Z] Movies recommended for you:
[2024-11-28T22:14:01.141Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:14:01.141Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:14:01.141Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (18134.241 ms) ======
[2024-11-28T22:14:01.141Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-28T22:14:01.549Z] GC before operation: completed in 165.514 ms, heap usage 421.736 MB -> 46.232 MB.
[2024-11-28T22:14:04.104Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:14:06.644Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:14:10.132Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:14:12.805Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:14:14.116Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:14:16.017Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:14:17.340Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:14:19.262Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:14:19.262Z] 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.
[2024-11-28T22:14:19.652Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:14:19.652Z] Movies recommended for you:
[2024-11-28T22:14:19.652Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:14:19.652Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:14:19.652Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (18247.793 ms) ======
[2024-11-28T22:14:19.652Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-28T22:14:19.652Z] GC before operation: completed in 158.846 ms, heap usage 403.658 MB -> 45.990 MB.
[2024-11-28T22:14:22.233Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:14:25.545Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:14:28.101Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:14:30.655Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:14:32.540Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:14:34.461Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:14:35.819Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:14:37.883Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:14:37.883Z] 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.
[2024-11-28T22:14:37.883Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:14:38.275Z] Movies recommended for you:
[2024-11-28T22:14:38.275Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:14:38.275Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:14:38.275Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18334.114 ms) ======
[2024-11-28T22:14:38.275Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-28T22:14:38.275Z] GC before operation: completed in 220.243 ms, heap usage 449.484 MB -> 47.453 MB.
[2024-11-28T22:14:40.827Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:14:43.504Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:14:46.780Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:14:49.354Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:14:50.695Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:14:52.582Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:14:54.506Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:14:55.889Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:14:56.274Z] 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.
[2024-11-28T22:14:56.274Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:14:56.274Z] Movies recommended for you:
[2024-11-28T22:14:56.274Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:14:56.274Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:14:56.274Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18068.044 ms) ======
[2024-11-28T22:14:56.274Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-28T22:14:56.654Z] GC before operation: completed in 166.592 ms, heap usage 486.115 MB -> 45.894 MB.
[2024-11-28T22:14:59.239Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:15:01.799Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:15:05.137Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:15:07.832Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:15:09.216Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:15:10.554Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:15:12.452Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:15:14.352Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:15:14.352Z] 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.
[2024-11-28T22:15:14.352Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:15:14.760Z] Movies recommended for you:
[2024-11-28T22:15:14.760Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:15:14.760Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:15:14.760Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (18053.577 ms) ======
[2024-11-28T22:15:14.760Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-28T22:15:14.760Z] GC before operation: completed in 167.774 ms, heap usage 404.983 MB -> 46.003 MB.
[2024-11-28T22:15:17.292Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:15:20.600Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:15:23.188Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:15:26.512Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:15:27.859Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:15:29.790Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:15:31.148Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:15:33.104Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:15:33.105Z] 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.
[2024-11-28T22:15:33.105Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:15:33.491Z] Movies recommended for you:
[2024-11-28T22:15:33.491Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:15:33.491Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:15:33.491Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (18645.654 ms) ======
[2024-11-28T22:15:33.491Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-28T22:15:33.491Z] GC before operation: completed in 158.358 ms, heap usage 435.484 MB -> 46.213 MB.
[2024-11-28T22:15:36.085Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:15:39.497Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:15:42.091Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:15:44.658Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:15:46.573Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:15:47.918Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:15:49.838Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:15:51.735Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:15:51.735Z] 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.
[2024-11-28T22:15:51.735Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:15:51.735Z] Movies recommended for you:
[2024-11-28T22:15:51.735Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:15:51.735Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:15:51.735Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (18291.425 ms) ======
[2024-11-28T22:15:51.735Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-28T22:15:52.128Z] GC before operation: completed in 163.092 ms, heap usage 407.868 MB -> 45.869 MB.
[2024-11-28T22:15:54.720Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:15:57.314Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:16:00.635Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:16:03.208Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:16:04.567Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:16:06.514Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:16:07.931Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:16:09.880Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:16:09.880Z] 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.
[2024-11-28T22:16:09.880Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:16:10.295Z] Movies recommended for you:
[2024-11-28T22:16:10.295Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:16:10.295Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:16:10.295Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (18062.754 ms) ======
[2024-11-28T22:16:10.295Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-28T22:16:10.295Z] GC before operation: completed in 154.289 ms, heap usage 426.363 MB -> 46.148 MB.
[2024-11-28T22:16:12.838Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:16:15.414Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:16:18.728Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:16:21.290Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:16:22.630Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:16:24.516Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:16:26.498Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:16:27.856Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:16:28.240Z] 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.
[2024-11-28T22:16:28.240Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:16:28.631Z] Movies recommended for you:
[2024-11-28T22:16:28.631Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:16:28.631Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:16:28.631Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (18242.453 ms) ======
[2024-11-28T22:16:28.631Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-28T22:16:28.631Z] GC before operation: completed in 161.362 ms, heap usage 439.007 MB -> 46.235 MB.
[2024-11-28T22:16:31.168Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:16:34.595Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:16:37.250Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:16:39.857Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:16:41.190Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:16:43.181Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:16:44.508Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:16:46.516Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:16:46.516Z] 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.
[2024-11-28T22:16:46.516Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:16:46.516Z] Movies recommended for you:
[2024-11-28T22:16:46.516Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:16:46.516Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:16:46.516Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (18024.326 ms) ======
[2024-11-28T22:16:46.516Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-28T22:16:46.900Z] GC before operation: completed in 164.878 ms, heap usage 477.239 MB -> 48.392 MB.
[2024-11-28T22:16:49.450Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:16:52.799Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:16:55.370Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:16:57.923Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:16:59.842Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:17:01.190Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:17:02.764Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:17:04.694Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:17:04.695Z] 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.
[2024-11-28T22:17:05.074Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:17:05.074Z] Movies recommended for you:
[2024-11-28T22:17:05.074Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:17:05.074Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:17:05.074Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18184.950 ms) ======
[2024-11-28T22:17:05.074Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-28T22:17:05.074Z] GC before operation: completed in 152.532 ms, heap usage 499.738 MB -> 46.190 MB.
[2024-11-28T22:17:07.638Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:17:10.997Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:17:13.566Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:17:16.157Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:17:17.506Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:17:19.399Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:17:21.340Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:17:22.670Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:17:23.059Z] 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.
[2024-11-28T22:17:23.059Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:17:23.059Z] Movies recommended for you:
[2024-11-28T22:17:23.059Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:17:23.059Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:17:23.059Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18006.219 ms) ======
[2024-11-28T22:17:23.059Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-28T22:17:23.451Z] GC before operation: completed in 156.482 ms, heap usage 393.024 MB -> 46.290 MB.
[2024-11-28T22:17:26.038Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-28T22:17:28.601Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-28T22:17:31.988Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-28T22:17:34.596Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-28T22:17:35.950Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-28T22:17:37.944Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-28T22:17:39.299Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-28T22:17:41.236Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-28T22:17:41.236Z] 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.
[2024-11-28T22:17:41.236Z] The best model improves the baseline by 14.52%.
[2024-11-28T22:17:41.619Z] Movies recommended for you:
[2024-11-28T22:17:41.619Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-28T22:17:41.619Z] There is no way to check that no silent failure occurred.
[2024-11-28T22:17:41.619Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18205.025 ms) ======
[2024-11-28T22:17:42.447Z] -----------------------------------
[2024-11-28T22:17:42.447Z] renaissance-movie-lens_0_PASSED
[2024-11-28T22:17:42.447Z] -----------------------------------
[2024-11-28T22:17:42.447Z]
[2024-11-28T22:17:42.447Z] TEST TEARDOWN:
[2024-11-28T22:17:42.447Z] Nothing to be done for teardown.
[2024-11-28T22:17:42.447Z] renaissance-movie-lens_0 Finish Time: Thu Nov 28 22:17:42 2024 Epoch Time (ms): 1732832262054