renaissance-movie-lens_0
[2024-08-08T00:57:56.855Z] Running test renaissance-movie-lens_0 ...
[2024-08-08T00:57:56.855Z] ===============================================
[2024-08-08T00:57:56.855Z] renaissance-movie-lens_0 Start Time: Thu Aug 8 00:57:56 2024 Epoch Time (ms): 1723078676011
[2024-08-08T00:57:56.855Z] variation: NoOptions
[2024-08-08T00:57:56.855Z] JVM_OPTIONS:
[2024-08-08T00:57:56.855Z] { \
[2024-08-08T00:57:56.855Z] echo ""; echo "TEST SETUP:"; \
[2024-08-08T00:57:56.855Z] echo "Nothing to be done for setup."; \
[2024-08-08T00:57:56.855Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17230777328015/renaissance-movie-lens_0"; \
[2024-08-08T00:57:56.855Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17230777328015/renaissance-movie-lens_0"; \
[2024-08-08T00:57:56.855Z] echo ""; echo "TESTING:"; \
[2024-08-08T00:57:56.855Z] "/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_17230777328015/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-08T00:57:56.855Z] 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_17230777328015/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-08T00:57:56.855Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-08T00:57:56.855Z] echo "Nothing to be done for teardown."; \
[2024-08-08T00:57:56.855Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_ppc64le_linux_testList_0/aqa-tests/TKG/../TKG/output_17230777328015/TestTargetResult";
[2024-08-08T00:57:56.855Z]
[2024-08-08T00:57:56.855Z] TEST SETUP:
[2024-08-08T00:57:56.855Z] Nothing to be done for setup.
[2024-08-08T00:57:56.855Z]
[2024-08-08T00:57:56.855Z] TESTING:
[2024-08-08T00:57:59.804Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-08T00:58:01.713Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-08T00:58:05.774Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-08T00:58:05.774Z] Training: 60056, validation: 20285, test: 19854
[2024-08-08T00:58:05.774Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-08T00:58:05.774Z] GC before operation: completed in 63.761 ms, heap usage 121.495 MB -> 36.462 MB.
[2024-08-08T00:58:12.332Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T00:58:15.281Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T00:58:18.233Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T00:58:21.182Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T00:58:23.100Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T00:58:25.014Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T00:58:25.951Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T00:58:27.867Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T00:58:27.867Z] 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.
[2024-08-08T00:58:27.867Z] The best model improves the baseline by 14.52%.
[2024-08-08T00:58:28.796Z] Movies recommended for you:
[2024-08-08T00:58:28.796Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T00:58:28.796Z] There is no way to check that no silent failure occurred.
[2024-08-08T00:58:28.796Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22673.085 ms) ======
[2024-08-08T00:58:28.796Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-08T00:58:28.796Z] GC before operation: completed in 100.441 ms, heap usage 80.818 MB -> 48.022 MB.
[2024-08-08T00:58:30.706Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T00:58:33.660Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T00:58:36.611Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T00:58:39.074Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T00:58:40.986Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T00:58:41.921Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T00:58:43.832Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T00:58:45.744Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T00:58:45.744Z] 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.
[2024-08-08T00:58:45.744Z] The best model improves the baseline by 14.52%.
[2024-08-08T00:58:45.744Z] Movies recommended for you:
[2024-08-08T00:58:45.744Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T00:58:45.744Z] There is no way to check that no silent failure occurred.
[2024-08-08T00:58:45.744Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17311.455 ms) ======
[2024-08-08T00:58:45.744Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-08T00:58:45.744Z] GC before operation: completed in 106.733 ms, heap usage 261.755 MB -> 49.196 MB.
[2024-08-08T00:58:48.693Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T00:58:50.626Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T00:58:53.730Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T00:58:55.637Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T00:58:57.555Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T00:58:58.486Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T00:59:00.412Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T00:59:01.343Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T00:59:02.273Z] 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.
[2024-08-08T00:59:02.273Z] The best model improves the baseline by 14.52%.
[2024-08-08T00:59:02.273Z] Movies recommended for you:
[2024-08-08T00:59:02.273Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T00:59:02.273Z] There is no way to check that no silent failure occurred.
[2024-08-08T00:59:02.273Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16209.496 ms) ======
[2024-08-08T00:59:02.273Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-08T00:59:02.273Z] GC before operation: completed in 102.710 ms, heap usage 322.864 MB -> 49.508 MB.
[2024-08-08T00:59:05.225Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T00:59:07.205Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T00:59:10.152Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T00:59:12.061Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T00:59:13.970Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T00:59:14.900Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T00:59:16.811Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T00:59:17.740Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T00:59:18.671Z] 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.
[2024-08-08T00:59:18.671Z] The best model improves the baseline by 14.52%.
[2024-08-08T00:59:18.671Z] Movies recommended for you:
[2024-08-08T00:59:18.671Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T00:59:18.671Z] There is no way to check that no silent failure occurred.
[2024-08-08T00:59:18.671Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16135.534 ms) ======
[2024-08-08T00:59:18.671Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-08T00:59:18.671Z] GC before operation: completed in 94.141 ms, heap usage 317.002 MB -> 49.806 MB.
[2024-08-08T00:59:21.620Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T00:59:23.531Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T00:59:26.483Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T00:59:28.393Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T00:59:29.326Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T00:59:32.089Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T00:59:33.019Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T00:59:33.948Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T00:59:33.948Z] 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.
[2024-08-08T00:59:33.948Z] The best model improves the baseline by 14.52%.
[2024-08-08T00:59:34.880Z] Movies recommended for you:
[2024-08-08T00:59:34.880Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T00:59:34.880Z] There is no way to check that no silent failure occurred.
[2024-08-08T00:59:34.880Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15931.006 ms) ======
[2024-08-08T00:59:34.880Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-08T00:59:34.880Z] GC before operation: completed in 92.489 ms, heap usage 82.301 MB -> 49.765 MB.
[2024-08-08T00:59:36.790Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T00:59:39.741Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T00:59:41.652Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T00:59:43.564Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T00:59:44.495Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T00:59:46.434Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T00:59:47.364Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T00:59:49.275Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T00:59:49.275Z] 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.
[2024-08-08T00:59:49.275Z] The best model improves the baseline by 14.52%.
[2024-08-08T00:59:49.275Z] Movies recommended for you:
[2024-08-08T00:59:49.275Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T00:59:49.275Z] There is no way to check that no silent failure occurred.
[2024-08-08T00:59:49.275Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14898.154 ms) ======
[2024-08-08T00:59:49.275Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-08T00:59:49.275Z] GC before operation: completed in 100.206 ms, heap usage 242.974 MB -> 49.888 MB.
[2024-08-08T00:59:52.409Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T00:59:54.322Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T00:59:56.231Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T00:59:59.184Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:00:00.137Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:00:01.067Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:00:02.979Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:00:04.891Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:00:04.891Z] 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.
[2024-08-08T01:00:04.891Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:00:04.891Z] Movies recommended for you:
[2024-08-08T01:00:04.891Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:00:04.891Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:00:04.891Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15291.567 ms) ======
[2024-08-08T01:00:04.891Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-08T01:00:04.891Z] GC before operation: completed in 96.086 ms, heap usage 67.129 MB -> 49.868 MB.
[2024-08-08T01:00:07.855Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:00:09.765Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:00:11.675Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:00:14.628Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:00:15.559Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:00:16.498Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:00:18.412Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:00:19.345Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:00:20.280Z] 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.
[2024-08-08T01:00:20.280Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:00:20.280Z] Movies recommended for you:
[2024-08-08T01:00:20.280Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:00:20.280Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:00:20.280Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15221.213 ms) ======
[2024-08-08T01:00:20.280Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-08T01:00:20.280Z] GC before operation: completed in 92.518 ms, heap usage 327.168 MB -> 50.367 MB.
[2024-08-08T01:00:22.193Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:00:25.648Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:00:27.562Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:00:29.476Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:00:30.407Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:00:32.322Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:00:33.252Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:00:35.163Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:00:35.163Z] 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.
[2024-08-08T01:00:35.163Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:00:35.163Z] Movies recommended for you:
[2024-08-08T01:00:35.163Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:00:35.163Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:00:35.163Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15142.353 ms) ======
[2024-08-08T01:00:35.163Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-08T01:00:35.163Z] GC before operation: completed in 91.752 ms, heap usage 77.623 MB -> 49.975 MB.
[2024-08-08T01:00:38.115Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:00:40.045Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:00:41.970Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:00:43.881Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:00:45.790Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:00:46.721Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:00:48.630Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:00:49.560Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:00:50.489Z] 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.
[2024-08-08T01:00:50.489Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:00:50.489Z] Movies recommended for you:
[2024-08-08T01:00:50.489Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:00:50.489Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:00:50.489Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14746.333 ms) ======
[2024-08-08T01:00:50.489Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-08T01:00:50.489Z] GC before operation: completed in 89.666 ms, heap usage 99.323 MB -> 50.094 MB.
[2024-08-08T01:00:52.526Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:00:54.440Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:00:56.355Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:00:59.306Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:01:00.241Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:01:01.174Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:01:03.083Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:01:04.013Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:01:04.948Z] 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.
[2024-08-08T01:01:04.948Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:01:04.948Z] Movies recommended for you:
[2024-08-08T01:01:04.948Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:01:04.948Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:01:04.948Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14313.727 ms) ======
[2024-08-08T01:01:04.948Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-08T01:01:04.948Z] GC before operation: completed in 89.871 ms, heap usage 191.824 MB -> 49.963 MB.
[2024-08-08T01:01:06.859Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:01:08.767Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:01:11.719Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:01:13.635Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:01:14.567Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:01:15.496Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:01:17.418Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:01:19.376Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:01:19.376Z] 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.
[2024-08-08T01:01:19.376Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:01:19.376Z] Movies recommended for you:
[2024-08-08T01:01:19.376Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:01:19.376Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:01:19.376Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14221.717 ms) ======
[2024-08-08T01:01:19.376Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-08T01:01:19.376Z] GC before operation: completed in 86.731 ms, heap usage 70.891 MB -> 49.949 MB.
[2024-08-08T01:01:21.288Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:01:23.199Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:01:26.149Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:01:28.075Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:01:29.030Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:01:30.939Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:01:31.868Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:01:32.889Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:01:33.818Z] 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.
[2024-08-08T01:01:33.818Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:01:33.818Z] Movies recommended for you:
[2024-08-08T01:01:33.818Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:01:33.818Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:01:33.818Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14629.752 ms) ======
[2024-08-08T01:01:33.818Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-08T01:01:33.818Z] GC before operation: completed in 91.999 ms, heap usage 194.835 MB -> 50.281 MB.
[2024-08-08T01:01:35.728Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:01:38.682Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:01:40.594Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:01:42.600Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:01:43.529Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:01:45.440Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:01:46.370Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:01:47.300Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:01:48.229Z] 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.
[2024-08-08T01:01:48.229Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:01:48.229Z] Movies recommended for you:
[2024-08-08T01:01:48.229Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:01:48.229Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:01:48.229Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14391.492 ms) ======
[2024-08-08T01:01:48.229Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-08T01:01:48.229Z] GC before operation: completed in 85.442 ms, heap usage 185.744 MB -> 49.985 MB.
[2024-08-08T01:01:50.137Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:01:53.090Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:01:55.040Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:01:56.948Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:01:57.879Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:01:59.795Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:02:00.725Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:02:02.634Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:02:02.634Z] 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.
[2024-08-08T01:02:02.634Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:02:02.634Z] Movies recommended for you:
[2024-08-08T01:02:02.634Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:02:02.634Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:02:02.634Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14337.779 ms) ======
[2024-08-08T01:02:02.634Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-08T01:02:02.634Z] GC before operation: completed in 87.361 ms, heap usage 170.733 MB -> 50.203 MB.
[2024-08-08T01:02:04.546Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:02:06.457Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:02:09.389Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:02:11.302Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:02:12.233Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:02:14.145Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:02:15.074Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:02:16.174Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:02:17.104Z] 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.
[2024-08-08T01:02:17.104Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:02:17.104Z] Movies recommended for you:
[2024-08-08T01:02:17.104Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:02:17.104Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:02:17.104Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14381.885 ms) ======
[2024-08-08T01:02:17.104Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-08T01:02:17.104Z] GC before operation: completed in 86.293 ms, heap usage 121.738 MB -> 50.233 MB.
[2024-08-08T01:02:20.056Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:02:21.965Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:02:23.902Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:02:25.829Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:02:27.739Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:02:28.696Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:02:29.627Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:02:31.541Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:02:31.541Z] 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.
[2024-08-08T01:02:31.541Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:02:31.541Z] Movies recommended for you:
[2024-08-08T01:02:31.541Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:02:31.541Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:02:31.541Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14554.071 ms) ======
[2024-08-08T01:02:31.541Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-08T01:02:31.541Z] GC before operation: completed in 89.080 ms, heap usage 170.392 MB -> 50.116 MB.
[2024-08-08T01:02:34.490Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:02:36.403Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:02:38.316Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:02:40.228Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:02:42.146Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:02:43.077Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:02:44.009Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:02:45.923Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:02:45.923Z] 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.
[2024-08-08T01:02:45.923Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:02:45.923Z] Movies recommended for you:
[2024-08-08T01:02:45.923Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:02:45.923Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:02:45.923Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14271.180 ms) ======
[2024-08-08T01:02:45.923Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-08T01:02:45.923Z] GC before operation: completed in 92.486 ms, heap usage 207.946 MB -> 50.218 MB.
[2024-08-08T01:02:48.875Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:02:50.794Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:02:52.863Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:02:54.777Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:02:56.689Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:02:57.619Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:02:58.551Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:03:00.461Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:03:00.461Z] 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.
[2024-08-08T01:03:00.461Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:03:00.461Z] Movies recommended for you:
[2024-08-08T01:03:00.461Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:03:00.461Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:03:00.461Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14390.759 ms) ======
[2024-08-08T01:03:00.461Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-08T01:03:00.461Z] GC before operation: completed in 85.895 ms, heap usage 152.733 MB -> 50.313 MB.
[2024-08-08T01:03:03.092Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-08T01:03:05.032Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-08T01:03:06.948Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-08T01:03:08.859Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-08T01:03:10.768Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-08T01:03:11.699Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-08T01:03:13.611Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-08T01:03:14.543Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-08T01:03:14.543Z] 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.
[2024-08-08T01:03:14.543Z] The best model improves the baseline by 14.52%.
[2024-08-08T01:03:15.477Z] Movies recommended for you:
[2024-08-08T01:03:15.477Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-08T01:03:15.477Z] There is no way to check that no silent failure occurred.
[2024-08-08T01:03:15.477Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14423.651 ms) ======
[2024-08-08T01:03:15.477Z] -----------------------------------
[2024-08-08T01:03:15.477Z] renaissance-movie-lens_0_PASSED
[2024-08-08T01:03:15.477Z] -----------------------------------
[2024-08-08T01:03:15.477Z]
[2024-08-08T01:03:15.477Z] TEST TEARDOWN:
[2024-08-08T01:03:15.477Z] Nothing to be done for teardown.
[2024-08-08T01:03:15.477Z] renaissance-movie-lens_0 Finish Time: Thu Aug 8 01:03:15 2024 Epoch Time (ms): 1723078995072