renaissance-movie-lens_0
[2024-08-22T07:40:23.819Z] Running test renaissance-movie-lens_0 ...
[2024-08-22T07:40:23.819Z] ===============================================
[2024-08-22T07:40:23.819Z] renaissance-movie-lens_0 Start Time: Thu Aug 22 07:40:22 2024 Epoch Time (ms): 1724312422734
[2024-08-22T07:40:23.819Z] variation: NoOptions
[2024-08-22T07:40:23.819Z] JVM_OPTIONS:
[2024-08-22T07:40:23.819Z] { \
[2024-08-22T07:40:23.819Z] echo ""; echo "TEST SETUP:"; \
[2024-08-22T07:40:23.819Z] echo "Nothing to be done for setup."; \
[2024-08-22T07:40:23.819Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17243115972199/renaissance-movie-lens_0"; \
[2024-08-22T07:40:23.819Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17243115972199/renaissance-movie-lens_0"; \
[2024-08-22T07:40:23.819Z] echo ""; echo "TESTING:"; \
[2024-08-22T07:40:23.819Z] "/home/jenkins/workspace/Test_openjdk17_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_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17243115972199/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-22T07:40:23.819Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17243115972199/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-22T07:40:23.819Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-22T07:40:23.819Z] echo "Nothing to be done for teardown."; \
[2024-08-22T07:40:23.819Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17243115972199/TestTargetResult";
[2024-08-22T07:40:23.819Z]
[2024-08-22T07:40:23.819Z] TEST SETUP:
[2024-08-22T07:40:23.819Z] Nothing to be done for setup.
[2024-08-22T07:40:23.819Z]
[2024-08-22T07:40:23.819Z] TESTING:
[2024-08-22T07:40:26.330Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-22T07:40:27.939Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-22T07:40:32.463Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-22T07:40:32.463Z] Training: 60056, validation: 20285, test: 19854
[2024-08-22T07:40:32.463Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-22T07:40:33.247Z] GC before operation: completed in 82.093 ms, heap usage 86.063 MB -> 37.034 MB.
[2024-08-22T07:40:41.666Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:40:46.213Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:40:51.296Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:40:55.823Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:40:57.445Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:40:59.955Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:41:01.571Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:41:03.191Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:41:03.974Z] 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.
[2024-08-22T07:41:03.974Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:41:03.974Z] Movies recommended for you:
[2024-08-22T07:41:03.974Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:41:03.974Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:41:03.974Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (31016.523 ms) ======
[2024-08-22T07:41:03.974Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-22T07:41:03.974Z] GC before operation: completed in 102.028 ms, heap usage 83.482 MB -> 53.014 MB.
[2024-08-22T07:41:07.439Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:41:09.940Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:41:13.428Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:41:16.898Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:41:18.528Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:41:20.986Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:41:22.538Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:41:24.949Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:41:24.949Z] 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.
[2024-08-22T07:41:24.949Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:41:25.700Z] Movies recommended for you:
[2024-08-22T07:41:25.700Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:41:25.700Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:41:25.700Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21348.959 ms) ======
[2024-08-22T07:41:25.700Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-22T07:41:25.700Z] GC before operation: completed in 79.760 ms, heap usage 209.168 MB -> 49.549 MB.
[2024-08-22T07:41:29.058Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:41:32.440Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:41:34.855Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:41:38.229Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:41:40.160Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:41:42.584Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:41:44.134Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:41:45.704Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:41:46.453Z] 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.
[2024-08-22T07:41:46.453Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:41:46.453Z] Movies recommended for you:
[2024-08-22T07:41:46.453Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:41:46.453Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:41:46.453Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (20833.200 ms) ======
[2024-08-22T07:41:46.453Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-22T07:41:46.453Z] GC before operation: completed in 93.266 ms, heap usage 231.230 MB -> 49.914 MB.
[2024-08-22T07:41:48.910Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:41:52.262Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:41:55.619Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:41:58.039Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:42:00.462Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:42:02.020Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:42:03.578Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:42:05.993Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:42:05.993Z] 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.
[2024-08-22T07:42:05.993Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:42:05.993Z] Movies recommended for you:
[2024-08-22T07:42:05.993Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:42:05.993Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:42:05.993Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19706.330 ms) ======
[2024-08-22T07:42:05.993Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-22T07:42:05.993Z] GC before operation: completed in 70.940 ms, heap usage 126.265 MB -> 50.159 MB.
[2024-08-22T07:42:09.331Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:42:12.692Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:42:15.103Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:42:18.454Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:42:20.013Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:42:22.426Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:42:24.844Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:42:26.401Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:42:26.401Z] 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.
[2024-08-22T07:42:27.148Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:42:27.148Z] Movies recommended for you:
[2024-08-22T07:42:27.148Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:42:27.148Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:42:27.148Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (20761.893 ms) ======
[2024-08-22T07:42:27.148Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-22T07:42:27.148Z] GC before operation: completed in 73.753 ms, heap usage 180.454 MB -> 50.416 MB.
[2024-08-22T07:42:30.148Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:42:32.556Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:42:34.961Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:42:37.373Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:42:39.773Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:42:41.354Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:42:43.770Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:42:45.321Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:42:45.321Z] 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.
[2024-08-22T07:42:45.321Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:42:46.078Z] Movies recommended for you:
[2024-08-22T07:42:46.078Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:42:46.078Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:42:46.078Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (18825.624 ms) ======
[2024-08-22T07:42:46.078Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-22T07:42:46.078Z] GC before operation: completed in 105.967 ms, heap usage 323.193 MB -> 50.485 MB.
[2024-08-22T07:42:48.483Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:42:51.820Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:42:54.223Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:42:56.640Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:42:58.185Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:42:59.728Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:43:01.272Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:43:02.828Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:43:02.828Z] 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.
[2024-08-22T07:43:02.828Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:43:02.828Z] Movies recommended for you:
[2024-08-22T07:43:02.828Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:43:02.828Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:43:02.828Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (17110.334 ms) ======
[2024-08-22T07:43:02.828Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-22T07:43:02.828Z] GC before operation: completed in 79.222 ms, heap usage 73.400 MB -> 50.384 MB.
[2024-08-22T07:43:05.235Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:43:07.637Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:43:10.972Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:43:13.370Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:43:14.916Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:43:16.468Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:43:18.513Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:43:19.264Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:43:19.265Z] 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.
[2024-08-22T07:43:19.265Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:43:19.265Z] Movies recommended for you:
[2024-08-22T07:43:19.265Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:43:19.265Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:43:19.265Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16437.863 ms) ======
[2024-08-22T07:43:19.265Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-22T07:43:19.265Z] GC before operation: completed in 77.892 ms, heap usage 77.181 MB -> 52.825 MB.
[2024-08-22T07:43:22.605Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:43:25.017Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:43:28.359Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:43:30.758Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:43:32.302Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:43:33.851Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:43:35.396Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:43:36.149Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:43:36.895Z] 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.
[2024-08-22T07:43:36.895Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:43:36.895Z] Movies recommended for you:
[2024-08-22T07:43:36.895Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:43:36.895Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:43:36.895Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17176.059 ms) ======
[2024-08-22T07:43:36.895Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-22T07:43:36.895Z] GC before operation: completed in 77.372 ms, heap usage 422.397 MB -> 54.079 MB.
[2024-08-22T07:43:39.304Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:43:41.718Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:43:45.061Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:43:47.491Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:43:49.035Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:43:50.595Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:43:53.011Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:43:54.579Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:43:54.579Z] 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.
[2024-08-22T07:43:54.579Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:43:55.323Z] Movies recommended for you:
[2024-08-22T07:43:55.323Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:43:55.324Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:43:55.324Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (18135.087 ms) ======
[2024-08-22T07:43:55.324Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-22T07:43:55.324Z] GC before operation: completed in 102.973 ms, heap usage 201.453 MB -> 50.818 MB.
[2024-08-22T07:43:57.742Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:44:01.464Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:44:03.987Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:44:06.396Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:44:07.943Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:44:09.489Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:44:11.043Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:44:12.604Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:44:13.351Z] 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.
[2024-08-22T07:44:13.351Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:44:13.351Z] Movies recommended for you:
[2024-08-22T07:44:13.351Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:44:13.351Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:44:13.351Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (18016.336 ms) ======
[2024-08-22T07:44:13.351Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-22T07:44:13.351Z] GC before operation: completed in 77.325 ms, heap usage 262.808 MB -> 50.617 MB.
[2024-08-22T07:44:15.756Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:44:18.159Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:44:20.569Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:44:22.983Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:44:24.545Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:44:26.091Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:44:27.639Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:44:29.187Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:44:29.187Z] 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.
[2024-08-22T07:44:29.187Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:44:29.187Z] Movies recommended for you:
[2024-08-22T07:44:29.187Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:44:29.187Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:44:29.187Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16252.574 ms) ======
[2024-08-22T07:44:29.187Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-22T07:44:29.187Z] GC before operation: completed in 73.949 ms, heap usage 181.694 MB -> 50.774 MB.
[2024-08-22T07:44:31.593Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:44:34.932Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:44:37.341Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:44:39.748Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:44:41.294Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:44:42.845Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:44:44.391Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:44:45.944Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:44:45.944Z] 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.
[2024-08-22T07:44:45.944Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:44:45.944Z] Movies recommended for you:
[2024-08-22T07:44:45.944Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:44:45.944Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:44:45.944Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16632.741 ms) ======
[2024-08-22T07:44:45.944Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-22T07:44:45.944Z] GC before operation: completed in 74.430 ms, heap usage 158.961 MB -> 50.930 MB.
[2024-08-22T07:44:48.356Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:44:51.725Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:44:54.125Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:44:56.541Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:44:58.095Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:44:59.645Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:45:01.195Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:45:02.747Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:45:03.496Z] 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.
[2024-08-22T07:45:03.497Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:45:03.497Z] Movies recommended for you:
[2024-08-22T07:45:03.497Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:45:03.497Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:45:03.497Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (17096.495 ms) ======
[2024-08-22T07:45:03.497Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-22T07:45:03.497Z] GC before operation: completed in 88.834 ms, heap usage 420.913 MB -> 54.001 MB.
[2024-08-22T07:45:05.902Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:45:08.306Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:45:10.716Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:45:14.044Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:45:14.794Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:45:16.337Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:45:18.746Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:45:19.494Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:45:20.245Z] 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.
[2024-08-22T07:45:20.245Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:45:20.245Z] Movies recommended for you:
[2024-08-22T07:45:20.245Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:45:20.245Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:45:20.245Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16595.427 ms) ======
[2024-08-22T07:45:20.245Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-22T07:45:20.245Z] GC before operation: completed in 99.113 ms, heap usage 250.727 MB -> 50.939 MB.
[2024-08-22T07:45:22.682Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:45:26.057Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:45:30.447Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:45:33.796Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:45:35.349Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:45:36.895Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:45:38.450Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:45:40.008Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:45:40.758Z] 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.
[2024-08-22T07:45:40.758Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:45:40.758Z] Movies recommended for you:
[2024-08-22T07:45:40.758Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:45:40.758Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:45:40.758Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (20551.569 ms) ======
[2024-08-22T07:45:40.758Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-22T07:45:40.758Z] GC before operation: completed in 69.107 ms, heap usage 433.906 MB -> 54.397 MB.
[2024-08-22T07:45:43.533Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:45:45.953Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:45:49.300Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:45:51.767Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:45:53.313Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:45:54.870Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:45:56.418Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:45:57.982Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:45:57.982Z] 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.
[2024-08-22T07:45:57.982Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:45:57.982Z] Movies recommended for you:
[2024-08-22T07:45:57.982Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:45:57.982Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:45:57.982Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (17520.032 ms) ======
[2024-08-22T07:45:57.982Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-22T07:45:57.982Z] GC before operation: completed in 58.603 ms, heap usage 195.821 MB -> 50.828 MB.
[2024-08-22T07:46:01.320Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:46:03.724Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:46:07.063Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:46:09.496Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:46:11.046Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:46:12.593Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:46:14.135Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:46:15.677Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:46:15.677Z] 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.
[2024-08-22T07:46:15.677Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:46:15.677Z] Movies recommended for you:
[2024-08-22T07:46:15.677Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:46:15.677Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:46:15.677Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (17594.165 ms) ======
[2024-08-22T07:46:15.677Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-22T07:46:15.677Z] GC before operation: completed in 65.582 ms, heap usage 262.112 MB -> 50.902 MB.
[2024-08-22T07:46:19.041Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:46:21.458Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:46:23.865Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:46:26.269Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:46:28.677Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:46:29.428Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:46:31.476Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:46:33.025Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:46:33.025Z] 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.
[2024-08-22T07:46:33.025Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:46:33.025Z] Movies recommended for you:
[2024-08-22T07:46:33.025Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:46:33.025Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:46:33.025Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (17358.045 ms) ======
[2024-08-22T07:46:33.025Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-22T07:46:33.771Z] GC before operation: completed in 81.664 ms, heap usage 230.417 MB -> 51.057 MB.
[2024-08-22T07:46:36.172Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-22T07:46:38.584Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-22T07:46:42.055Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-22T07:46:44.479Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-22T07:46:46.031Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-22T07:46:48.457Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-22T07:46:50.020Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-22T07:46:51.700Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-22T07:46:52.450Z] 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.
[2024-08-22T07:46:52.450Z] The best model improves the baseline by 14.52%.
[2024-08-22T07:46:52.450Z] Movies recommended for you:
[2024-08-22T07:46:52.450Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-22T07:46:52.450Z] There is no way to check that no silent failure occurred.
[2024-08-22T07:46:52.450Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18905.207 ms) ======
[2024-08-22T07:46:52.450Z] -----------------------------------
[2024-08-22T07:46:52.450Z] renaissance-movie-lens_0_PASSED
[2024-08-22T07:46:52.450Z] -----------------------------------
[2024-08-22T07:46:52.450Z]
[2024-08-22T07:46:52.450Z] TEST TEARDOWN:
[2024-08-22T07:46:52.450Z] Nothing to be done for teardown.
[2024-08-22T07:46:52.450Z] renaissance-movie-lens_0 Finish Time: Thu Aug 22 07:46:52 2024 Epoch Time (ms): 1724312812362