renaissance-movie-lens_0
[2024-08-23T22:30:09.608Z] Running test renaissance-movie-lens_0 ...
[2024-08-23T22:30:09.608Z] ===============================================
[2024-08-23T22:30:09.608Z] renaissance-movie-lens_0 Start Time: Fri Aug 23 22:30:08 2024 Epoch Time (ms): 1724452208696
[2024-08-23T22:30:09.608Z] variation: NoOptions
[2024-08-23T22:30:09.608Z] JVM_OPTIONS:
[2024-08-23T22:30:09.608Z] { \
[2024-08-23T22:30:09.608Z] echo ""; echo "TEST SETUP:"; \
[2024-08-23T22:30:09.608Z] echo "Nothing to be done for setup."; \
[2024-08-23T22:30:09.608Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17244483233953/renaissance-movie-lens_0"; \
[2024-08-23T22:30:09.608Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17244483233953/renaissance-movie-lens_0"; \
[2024-08-23T22:30:09.608Z] echo ""; echo "TESTING:"; \
[2024-08-23T22:30:09.608Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/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_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17244483233953/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-23T22:30:09.608Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17244483233953/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-23T22:30:09.608Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-23T22:30:09.608Z] echo "Nothing to be done for teardown."; \
[2024-08-23T22:30:09.608Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17244483233953/TestTargetResult";
[2024-08-23T22:30:09.608Z]
[2024-08-23T22:30:09.608Z] TEST SETUP:
[2024-08-23T22:30:09.608Z] Nothing to be done for setup.
[2024-08-23T22:30:09.608Z]
[2024-08-23T22:30:09.608Z] TESTING:
[2024-08-23T22:30:19.252Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-23T22:30:27.542Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-23T22:30:43.824Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-23T22:30:45.412Z] Training: 60056, validation: 20285, test: 19854
[2024-08-23T22:30:45.412Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-23T22:30:45.412Z] GC before operation: completed in 340.331 ms, heap usage 42.419 MB -> 36.473 MB.
[2024-08-23T22:31:20.478Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:31:42.478Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:32:01.202Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:32:17.711Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:32:25.886Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:32:35.781Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:32:43.941Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:32:50.698Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:32:52.258Z] 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.
[2024-08-23T22:32:52.258Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:32:53.017Z] Movies recommended for you:
[2024-08-23T22:32:53.017Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:32:53.017Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:32:53.017Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (127593.763 ms) ======
[2024-08-23T22:32:53.017Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-23T22:32:53.798Z] GC before operation: completed in 475.629 ms, heap usage 205.955 MB -> 49.021 MB.
[2024-08-23T22:33:07.411Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:33:21.042Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:33:35.228Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:33:48.802Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:33:57.010Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:34:05.324Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:34:13.891Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:34:20.943Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:34:20.943Z] 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.
[2024-08-23T22:34:21.747Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:34:21.747Z] Movies recommended for you:
[2024-08-23T22:34:21.747Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:34:21.748Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:34:21.748Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (88411.214 ms) ======
[2024-08-23T22:34:21.748Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-23T22:34:22.541Z] GC before operation: completed in 328.603 ms, heap usage 151.655 MB -> 48.969 MB.
[2024-08-23T22:34:35.077Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:34:51.673Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:35:03.648Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:35:15.598Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:35:22.647Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:35:28.400Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:35:35.476Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:35:42.796Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:35:43.655Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-23T22:35:43.655Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:35:44.440Z] Movies recommended for you:
[2024-08-23T22:35:44.440Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:35:44.440Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:35:44.440Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (82089.480 ms) ======
[2024-08-23T22:35:44.440Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-23T22:35:44.440Z] GC before operation: completed in 420.271 ms, heap usage 166.455 MB -> 49.311 MB.
[2024-08-23T22:35:56.945Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:36:08.933Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:36:20.887Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:36:29.432Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:36:36.637Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:36:43.688Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:36:50.788Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:36:56.568Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:36:57.361Z] 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.
[2024-08-23T22:36:57.361Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:36:58.164Z] Movies recommended for you:
[2024-08-23T22:36:58.164Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:36:58.164Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:36:58.164Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (73291.493 ms) ======
[2024-08-23T22:36:58.164Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-23T22:36:58.164Z] GC before operation: completed in 474.225 ms, heap usage 208.241 MB -> 49.638 MB.
[2024-08-23T22:37:10.713Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:37:21.027Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:37:32.993Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:37:43.158Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:37:50.295Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:37:57.412Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:38:05.941Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:38:11.704Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:38:11.704Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-23T22:38:12.501Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:38:12.501Z] Movies recommended for you:
[2024-08-23T22:38:12.501Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:38:12.501Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:38:12.501Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (74053.785 ms) ======
[2024-08-23T22:38:12.501Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-23T22:38:13.305Z] GC before operation: completed in 355.805 ms, heap usage 115.438 MB -> 49.737 MB.
[2024-08-23T22:38:23.997Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:38:35.955Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:38:46.136Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:38:56.260Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:39:03.301Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:39:10.391Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:39:16.161Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:39:23.245Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:39:23.245Z] 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.
[2024-08-23T22:39:23.245Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:39:24.037Z] Movies recommended for you:
[2024-08-23T22:39:24.037Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:39:24.037Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:39:24.037Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (71020.972 ms) ======
[2024-08-23T22:39:24.037Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-23T22:39:24.037Z] GC before operation: completed in 463.053 ms, heap usage 112.979 MB -> 52.624 MB.
[2024-08-23T22:39:34.809Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:39:46.827Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:39:56.998Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:40:07.177Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:40:15.744Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:40:21.620Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:40:27.539Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:40:33.532Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:40:34.357Z] 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.
[2024-08-23T22:40:34.357Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:40:35.208Z] Movies recommended for you:
[2024-08-23T22:40:35.208Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:40:35.208Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:40:35.208Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (70631.254 ms) ======
[2024-08-23T22:40:35.208Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-23T22:40:35.208Z] GC before operation: completed in 329.784 ms, heap usage 132.614 MB -> 49.854 MB.
[2024-08-23T22:40:46.260Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:40:56.695Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:41:07.156Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:41:17.494Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:41:22.211Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:41:28.199Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:41:34.236Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:41:41.516Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:41:41.516Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-23T22:41:41.516Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:41:42.340Z] Movies recommended for you:
[2024-08-23T22:41:42.340Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:41:42.340Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:41:42.340Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (66681.696 ms) ======
[2024-08-23T22:41:42.340Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-23T22:41:42.340Z] GC before operation: completed in 403.949 ms, heap usage 141.753 MB -> 50.112 MB.
[2024-08-23T22:41:51.619Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:42:01.974Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:42:10.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:42:21.434Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:42:26.257Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:42:31.124Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:42:37.316Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:42:42.223Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:42:43.087Z] 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.
[2024-08-23T22:42:43.087Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:42:43.939Z] Movies recommended for you:
[2024-08-23T22:42:43.939Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:42:43.939Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:42:43.939Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (61236.407 ms) ======
[2024-08-23T22:42:43.939Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-23T22:42:43.939Z] GC before operation: completed in 369.098 ms, heap usage 273.530 MB -> 50.082 MB.
[2024-08-23T22:42:54.506Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:43:04.017Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:43:12.915Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:43:20.335Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:43:25.182Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:43:30.040Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:43:34.899Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:43:39.819Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:43:40.667Z] 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.
[2024-08-23T22:43:40.667Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:43:40.667Z] Movies recommended for you:
[2024-08-23T22:43:40.667Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:43:40.667Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:43:40.667Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (56934.275 ms) ======
[2024-08-23T22:43:40.667Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-23T22:43:41.531Z] GC before operation: completed in 275.575 ms, heap usage 152.341 MB -> 50.073 MB.
[2024-08-23T22:43:52.119Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:43:59.542Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:44:08.823Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:44:17.765Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:44:21.487Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:44:27.651Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:44:32.551Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:44:37.527Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:44:38.371Z] 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.
[2024-08-23T22:44:38.371Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:44:38.371Z] Movies recommended for you:
[2024-08-23T22:44:38.371Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:44:38.371Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:44:38.371Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (57503.957 ms) ======
[2024-08-23T22:44:38.371Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-23T22:44:39.224Z] GC before operation: completed in 358.505 ms, heap usage 281.491 MB -> 49.918 MB.
[2024-08-23T22:44:48.203Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:44:57.210Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:45:07.936Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:45:15.379Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:45:20.842Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:45:25.699Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:45:30.551Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:45:35.611Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:45:36.461Z] 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.
[2024-08-23T22:45:36.461Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:45:37.306Z] Movies recommended for you:
[2024-08-23T22:45:37.306Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:45:37.306Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:45:37.306Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (57827.901 ms) ======
[2024-08-23T22:45:37.306Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-23T22:45:37.307Z] GC before operation: completed in 312.403 ms, heap usage 322.835 MB -> 50.163 MB.
[2024-08-23T22:45:46.411Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:45:55.351Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:46:04.250Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:46:14.863Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:46:19.725Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:46:25.839Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:46:33.567Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:46:37.330Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:46:38.194Z] 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.
[2024-08-23T22:46:38.194Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:46:39.047Z] Movies recommended for you:
[2024-08-23T22:46:39.047Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:46:39.047Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:46:39.047Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (61590.725 ms) ======
[2024-08-23T22:46:39.047Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-23T22:46:39.047Z] GC before operation: completed in 378.406 ms, heap usage 288.180 MB -> 50.264 MB.
[2024-08-23T22:46:49.659Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:46:58.600Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:47:07.539Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:47:18.162Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:47:23.017Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:47:27.907Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:47:32.939Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:47:38.479Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:47:39.325Z] 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.
[2024-08-23T22:47:39.325Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:47:39.325Z] Movies recommended for you:
[2024-08-23T22:47:39.325Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:47:39.325Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:47:39.325Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (60409.109 ms) ======
[2024-08-23T22:47:39.325Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-23T22:47:40.180Z] GC before operation: completed in 292.001 ms, heap usage 193.024 MB -> 49.971 MB.
[2024-08-23T22:47:49.126Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:47:58.066Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:48:05.526Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:48:16.114Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:48:20.954Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:48:27.063Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:48:31.930Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:48:35.703Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:48:36.559Z] 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.
[2024-08-23T22:48:36.559Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:48:36.559Z] Movies recommended for you:
[2024-08-23T22:48:36.559Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:48:36.559Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:48:36.559Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (56979.704 ms) ======
[2024-08-23T22:48:36.559Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-23T22:48:37.414Z] GC before operation: completed in 339.858 ms, heap usage 280.291 MB -> 50.190 MB.
[2024-08-23T22:48:48.030Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:48:57.311Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:49:06.279Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:49:13.685Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:49:18.538Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:49:24.626Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:49:30.715Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:49:35.590Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:49:35.590Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-23T22:49:35.590Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:49:36.465Z] Movies recommended for you:
[2024-08-23T22:49:36.465Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:49:36.465Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:49:36.465Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (58961.111 ms) ======
[2024-08-23T22:49:36.465Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-23T22:49:36.465Z] GC before operation: completed in 249.247 ms, heap usage 313.161 MB -> 50.327 MB.
[2024-08-23T22:49:43.895Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:49:52.811Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:49:59.206Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:50:04.426Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:50:08.210Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:50:13.128Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:50:16.880Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:50:21.733Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:50:22.585Z] 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.
[2024-08-23T22:50:22.585Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:50:22.585Z] Movies recommended for you:
[2024-08-23T22:50:22.585Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:50:22.585Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:50:22.585Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (46127.261 ms) ======
[2024-08-23T22:50:22.585Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-23T22:50:22.585Z] GC before operation: completed in 256.878 ms, heap usage 251.139 MB -> 51.925 MB.
[2024-08-23T22:50:30.036Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:50:37.299Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:50:43.364Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:50:50.597Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:50:54.254Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:50:58.976Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:51:03.681Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:51:07.591Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:51:08.419Z] 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.
[2024-08-23T22:51:08.419Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:51:08.419Z] Movies recommended for you:
[2024-08-23T22:51:08.419Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:51:08.419Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:51:08.419Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (45524.396 ms) ======
[2024-08-23T22:51:08.419Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-23T22:51:08.419Z] GC before operation: completed in 277.543 ms, heap usage 333.848 MB -> 50.240 MB.
[2024-08-23T22:51:14.325Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:51:21.531Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:51:26.229Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:51:32.136Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:51:35.911Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:51:40.610Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:51:43.224Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:51:47.927Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:51:47.927Z] 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.
[2024-08-23T22:51:47.927Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:51:48.779Z] Movies recommended for you:
[2024-08-23T22:51:48.779Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:51:48.779Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:51:48.779Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (39755.933 ms) ======
[2024-08-23T22:51:48.779Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-23T22:51:48.779Z] GC before operation: completed in 237.046 ms, heap usage 123.685 MB -> 50.214 MB.
[2024-08-23T22:51:56.030Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T22:52:03.238Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T22:52:09.434Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T22:52:16.878Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T22:52:19.506Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T22:52:24.197Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T22:52:27.838Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T22:52:31.466Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T22:52:32.295Z] 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.
[2024-08-23T22:52:32.295Z] The best model improves the baseline by 14.52%.
[2024-08-23T22:52:33.235Z] Movies recommended for you:
[2024-08-23T22:52:33.235Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T22:52:33.235Z] There is no way to check that no silent failure occurred.
[2024-08-23T22:52:33.235Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (44057.939 ms) ======
[2024-08-23T22:52:34.057Z] -----------------------------------
[2024-08-23T22:52:34.058Z] renaissance-movie-lens_0_PASSED
[2024-08-23T22:52:34.058Z] -----------------------------------
[2024-08-23T22:52:34.058Z]
[2024-08-23T22:52:34.058Z] TEST TEARDOWN:
[2024-08-23T22:52:34.058Z] Nothing to be done for teardown.
[2024-08-23T22:52:34.058Z] renaissance-movie-lens_0 Finish Time: Fri Aug 23 22:52:33 2024 Epoch Time (ms): 1724453553526