renaissance-movie-lens_0
[2024-06-07T23:04:47.832Z] Running test renaissance-movie-lens_0 ...
[2024-06-07T23:04:47.832Z] ===============================================
[2024-06-07T23:04:47.832Z] renaissance-movie-lens_0 Start Time: Fri Jun 7 23:04:46 2024 Epoch Time (ms): 1717801486972
[2024-06-07T23:04:47.832Z] variation: NoOptions
[2024-06-07T23:04:47.832Z] JVM_OPTIONS:
[2024-06-07T23:04:47.832Z] { \
[2024-06-07T23:04:47.832Z] echo ""; echo "TEST SETUP:"; \
[2024-06-07T23:04:47.832Z] echo "Nothing to be done for setup."; \
[2024-06-07T23:04:47.832Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17178005333360/renaissance-movie-lens_0"; \
[2024-06-07T23:04:47.832Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17178005333360/renaissance-movie-lens_0"; \
[2024-06-07T23:04:47.832Z] echo ""; echo "TESTING:"; \
[2024-06-07T23:04:47.832Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17178005333360/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-06-07T23:04:47.832Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17178005333360/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-06-07T23:04:47.833Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-06-07T23:04:47.833Z] echo "Nothing to be done for teardown."; \
[2024-06-07T23:04:47.833Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17178005333360/TestTargetResult";
[2024-06-07T23:04:47.833Z]
[2024-06-07T23:04:47.833Z] TEST SETUP:
[2024-06-07T23:04:47.833Z] Nothing to be done for setup.
[2024-06-07T23:04:47.833Z]
[2024-06-07T23:04:47.833Z] TESTING:
[2024-06-07T23:04:50.800Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-06-07T23:04:52.717Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-06-07T23:04:56.758Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-06-07T23:04:56.758Z] Training: 60056, validation: 20285, test: 19854
[2024-06-07T23:04:56.758Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-06-07T23:04:56.758Z] GC before operation: completed in 100.513 ms, heap usage 146.801 MB -> 36.489 MB.
[2024-06-07T23:05:03.507Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:05:06.468Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:05:10.538Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:05:12.457Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:05:14.374Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:05:16.295Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:05:18.215Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:05:20.140Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:05:20.140Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:05:20.140Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:05:20.140Z] Movies recommended for you:
[2024-06-07T23:05:20.140Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:05:20.140Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:05:20.140Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (23641.415 ms) ======
[2024-06-07T23:05:20.140Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-06-07T23:05:20.140Z] GC before operation: completed in 101.403 ms, heap usage 323.499 MB -> 48.320 MB.
[2024-06-07T23:05:24.233Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:05:27.212Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:05:29.132Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:05:32.101Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:05:33.035Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:05:34.962Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:05:36.880Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:05:37.811Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:05:38.745Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:05:38.745Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:05:38.745Z] Movies recommended for you:
[2024-06-07T23:05:38.745Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:05:38.745Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:05:38.745Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (18083.713 ms) ======
[2024-06-07T23:05:38.745Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-06-07T23:05:38.745Z] GC before operation: completed in 108.300 ms, heap usage 187.911 MB -> 49.088 MB.
[2024-06-07T23:05:41.718Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:05:44.678Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:05:46.597Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:05:49.569Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:05:50.502Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:05:52.423Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:05:53.356Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:05:55.285Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:05:55.285Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:05:55.285Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:05:55.285Z] Movies recommended for you:
[2024-06-07T23:05:55.285Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:05:55.285Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:05:55.285Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16894.869 ms) ======
[2024-06-07T23:05:55.285Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-06-07T23:05:56.219Z] GC before operation: completed in 105.156 ms, heap usage 187.090 MB -> 49.343 MB.
[2024-06-07T23:05:59.407Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:06:00.353Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:06:03.315Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:06:05.230Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:06:07.153Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:06:09.067Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:06:10.000Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:06:11.941Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:06:11.941Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:06:11.941Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:06:11.941Z] Movies recommended for you:
[2024-06-07T23:06:11.941Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:06:11.941Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:06:11.941Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16362.651 ms) ======
[2024-06-07T23:06:11.941Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-06-07T23:06:11.941Z] GC before operation: completed in 91.727 ms, heap usage 122.775 MB -> 49.642 MB.
[2024-06-07T23:06:14.896Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:06:16.812Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:06:19.777Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:06:21.697Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:06:23.613Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:06:24.549Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:06:26.463Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:06:27.399Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:06:28.333Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:06:28.333Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:06:28.333Z] Movies recommended for you:
[2024-06-07T23:06:28.333Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:06:28.333Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:06:28.333Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15819.315 ms) ======
[2024-06-07T23:06:28.333Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-06-07T23:06:28.333Z] GC before operation: completed in 96.948 ms, heap usage 204.066 MB -> 49.876 MB.
[2024-06-07T23:06:30.257Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:06:33.221Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:06:35.140Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:06:37.059Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:06:38.979Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:06:39.911Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:06:41.828Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:06:42.768Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:06:43.701Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:06:43.701Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:06:43.701Z] Movies recommended for you:
[2024-06-07T23:06:43.701Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:06:43.701Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:06:43.701Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15402.817 ms) ======
[2024-06-07T23:06:43.701Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-06-07T23:06:43.701Z] GC before operation: completed in 103.608 ms, heap usage 183.592 MB -> 49.856 MB.
[2024-06-07T23:06:45.623Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:06:48.580Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:06:50.499Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:06:52.414Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:06:54.332Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:06:55.270Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:06:57.298Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:06:58.233Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:06:58.233Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:06:58.233Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:06:58.233Z] Movies recommended for you:
[2024-06-07T23:06:58.233Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:06:58.233Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:06:58.233Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14958.542 ms) ======
[2024-06-07T23:06:58.233Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-06-07T23:06:59.170Z] GC before operation: completed in 92.674 ms, heap usage 164.794 MB -> 49.944 MB.
[2024-06-07T23:07:01.089Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:07:03.913Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:07:04.845Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:07:07.804Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:07:08.743Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:07:09.676Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:07:11.593Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:07:12.528Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:07:12.528Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:07:12.528Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:07:13.461Z] Movies recommended for you:
[2024-06-07T23:07:13.461Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:07:13.461Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:07:13.461Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14367.638 ms) ======
[2024-06-07T23:07:13.461Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-06-07T23:07:13.461Z] GC before operation: completed in 90.342 ms, heap usage 114.054 MB -> 50.198 MB.
[2024-06-07T23:07:15.376Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:07:17.297Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:07:20.257Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:07:22.174Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:07:23.109Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:07:24.042Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:07:25.961Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:07:26.892Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:07:27.826Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:07:27.826Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:07:27.826Z] Movies recommended for you:
[2024-06-07T23:07:27.826Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:07:27.826Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:07:27.826Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14378.121 ms) ======
[2024-06-07T23:07:27.826Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-06-07T23:07:27.826Z] GC before operation: completed in 91.944 ms, heap usage 264.732 MB -> 50.134 MB.
[2024-06-07T23:07:29.745Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:07:31.660Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:07:34.627Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:07:36.555Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:07:37.494Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:07:39.413Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:07:40.347Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:07:41.282Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:07:42.215Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:07:42.215Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:07:42.215Z] Movies recommended for you:
[2024-06-07T23:07:42.215Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:07:42.215Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:07:42.215Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14451.891 ms) ======
[2024-06-07T23:07:42.215Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-06-07T23:07:42.215Z] GC before operation: completed in 95.737 ms, heap usage 194.034 MB -> 50.216 MB.
[2024-06-07T23:07:44.133Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:07:47.093Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:07:49.016Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:07:50.935Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:07:52.853Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:07:53.788Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:07:54.723Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:07:56.672Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:07:56.673Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:07:56.673Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:07:56.673Z] Movies recommended for you:
[2024-06-07T23:07:56.673Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:07:56.673Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:07:56.673Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14673.157 ms) ======
[2024-06-07T23:07:56.673Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-06-07T23:07:56.673Z] GC before operation: completed in 91.488 ms, heap usage 334.410 MB -> 50.034 MB.
[2024-06-07T23:07:59.635Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:08:02.311Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:08:04.226Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:08:06.141Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:08:07.074Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:08:08.993Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:08:09.926Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:08:11.844Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:08:11.844Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:08:11.844Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:08:11.844Z] Movies recommended for you:
[2024-06-07T23:08:11.844Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:08:11.844Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:08:11.844Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15001.953 ms) ======
[2024-06-07T23:08:11.844Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-06-07T23:08:11.844Z] GC before operation: completed in 91.828 ms, heap usage 74.542 MB -> 49.978 MB.
[2024-06-07T23:08:14.804Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:08:16.725Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:08:18.641Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:08:21.606Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:08:22.541Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:08:24.461Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:08:25.396Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:08:27.315Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:08:27.315Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:08:27.315Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:08:27.315Z] Movies recommended for you:
[2024-06-07T23:08:27.315Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:08:27.315Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:08:27.315Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15341.516 ms) ======
[2024-06-07T23:08:27.315Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-06-07T23:08:27.315Z] GC before operation: completed in 92.566 ms, heap usage 173.613 MB -> 50.252 MB.
[2024-06-07T23:08:30.280Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:08:32.200Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:08:34.120Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:08:37.085Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:08:38.021Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:08:39.947Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:08:40.880Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:08:42.811Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:08:42.811Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:08:42.811Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:08:42.811Z] Movies recommended for you:
[2024-06-07T23:08:42.811Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:08:42.811Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:08:42.811Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15283.058 ms) ======
[2024-06-07T23:08:42.811Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-06-07T23:08:42.811Z] GC before operation: completed in 113.864 ms, heap usage 164.074 MB -> 50.008 MB.
[2024-06-07T23:08:45.784Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:08:47.710Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:08:49.631Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:08:51.548Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:08:53.473Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:08:54.407Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:08:56.470Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:08:57.573Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:08:57.574Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:08:57.574Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:08:57.574Z] Movies recommended for you:
[2024-06-07T23:08:57.574Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:08:57.574Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:08:57.574Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14884.537 ms) ======
[2024-06-07T23:08:57.574Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-06-07T23:08:57.574Z] GC before operation: completed in 94.186 ms, heap usage 152.559 MB -> 50.141 MB.
[2024-06-07T23:09:00.550Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:09:02.471Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:09:05.413Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:09:06.507Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:09:08.427Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:09:09.364Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:09:11.281Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:09:12.215Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:09:13.149Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:09:13.149Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:09:13.149Z] Movies recommended for you:
[2024-06-07T23:09:13.149Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:09:13.149Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:09:13.149Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15060.664 ms) ======
[2024-06-07T23:09:13.149Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-06-07T23:09:13.149Z] GC before operation: completed in 97.734 ms, heap usage 278.597 MB -> 50.368 MB.
[2024-06-07T23:09:15.066Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:09:16.987Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:09:19.951Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:09:21.880Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:09:22.813Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:09:24.731Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:09:25.664Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:09:27.583Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:09:27.583Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:09:27.583Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:09:27.583Z] Movies recommended for you:
[2024-06-07T23:09:27.583Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:09:27.583Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:09:27.583Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14604.336 ms) ======
[2024-06-07T23:09:27.583Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-06-07T23:09:27.583Z] GC before operation: completed in 94.876 ms, heap usage 313.860 MB -> 50.226 MB.
[2024-06-07T23:09:30.546Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:09:32.471Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:09:34.389Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:09:36.307Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:09:38.224Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:09:39.156Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:09:41.075Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:09:42.016Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:09:42.016Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:09:42.016Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:09:42.016Z] Movies recommended for you:
[2024-06-07T23:09:42.016Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:09:42.016Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:09:42.016Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14715.853 ms) ======
[2024-06-07T23:09:42.016Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-06-07T23:09:42.951Z] GC before operation: completed in 103.081 ms, heap usage 180.819 MB -> 50.213 MB.
[2024-06-07T23:09:44.868Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:09:46.789Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:09:48.709Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:09:51.680Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:09:52.625Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:09:53.560Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:09:55.488Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:09:56.458Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:09:57.393Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:09:57.393Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:09:57.393Z] Movies recommended for you:
[2024-06-07T23:09:57.393Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:09:57.393Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:09:57.393Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14608.215 ms) ======
[2024-06-07T23:09:57.393Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-06-07T23:09:57.393Z] GC before operation: completed in 95.804 ms, heap usage 201.332 MB -> 50.346 MB.
[2024-06-07T23:09:59.311Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-06-07T23:10:02.275Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-06-07T23:10:04.195Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-06-07T23:10:07.015Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-06-07T23:10:07.949Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-06-07T23:10:08.883Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-06-07T23:10:10.802Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-06-07T23:10:11.739Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-06-07T23:10:11.739Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-06-07T23:10:11.739Z] The best model improves the baseline by 14.52%.
[2024-06-07T23:10:11.740Z] Movies recommended for you:
[2024-06-07T23:10:11.740Z] WARNING: This benchmark provides no result that can be validated.
[2024-06-07T23:10:11.740Z] There is no way to check that no silent failure occurred.
[2024-06-07T23:10:11.740Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14868.048 ms) ======
[2024-06-07T23:10:12.700Z] -----------------------------------
[2024-06-07T23:10:12.700Z] renaissance-movie-lens_0_PASSED
[2024-06-07T23:10:12.700Z] -----------------------------------
[2024-06-07T23:10:12.700Z]
[2024-06-07T23:10:12.700Z] TEST TEARDOWN:
[2024-06-07T23:10:12.700Z] Nothing to be done for teardown.
[2024-06-07T23:10:12.700Z] renaissance-movie-lens_0 Finish Time: Fri Jun 7 23:10:12 2024 Epoch Time (ms): 1717801812115