renaissance-movie-lens_0
[2024-10-02T21:44:01.971Z] Running test renaissance-movie-lens_0 ...
[2024-10-02T21:44:01.971Z] ===============================================
[2024-10-02T21:44:01.971Z] renaissance-movie-lens_0 Start Time: Wed Oct 2 21:44:01 2024 Epoch Time (ms): 1727905441041
[2024-10-02T21:44:01.971Z] variation: NoOptions
[2024-10-02T21:44:01.971Z] JVM_OPTIONS:
[2024-10-02T21:44:01.971Z] { \
[2024-10-02T21:44:01.971Z] echo ""; echo "TEST SETUP:"; \
[2024-10-02T21:44:01.971Z] echo "Nothing to be done for setup."; \
[2024-10-02T21:44:01.971Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17279026359048/renaissance-movie-lens_0"; \
[2024-10-02T21:44:01.971Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17279026359048/renaissance-movie-lens_0"; \
[2024-10-02T21:44:01.971Z] echo ""; echo "TESTING:"; \
[2024-10-02T21:44:01.971Z] "/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_17279026359048/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-10-02T21:44:01.972Z] 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_17279026359048/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-10-02T21:44:01.972Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-10-02T21:44:01.972Z] echo "Nothing to be done for teardown."; \
[2024-10-02T21:44:01.972Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17279026359048/TestTargetResult";
[2024-10-02T21:44:01.972Z]
[2024-10-02T21:44:01.972Z] TEST SETUP:
[2024-10-02T21:44:01.972Z] Nothing to be done for setup.
[2024-10-02T21:44:01.972Z]
[2024-10-02T21:44:01.972Z] TESTING:
[2024-10-02T21:44:09.300Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-10-02T21:44:16.645Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-10-02T21:44:33.653Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-10-02T21:44:33.653Z] Training: 60056, validation: 20285, test: 19854
[2024-10-02T21:44:33.653Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-10-02T21:44:33.653Z] GC before operation: completed in 233.168 ms, heap usage 95.311 MB -> 37.182 MB.
[2024-10-02T21:45:04.945Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:45:24.726Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:45:41.707Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:45:58.643Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:46:09.115Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:46:18.514Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:46:25.838Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:46:33.132Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:46:33.994Z] 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.
[2024-10-02T21:46:34.813Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:46:34.814Z] Movies recommended for you:
[2024-10-02T21:46:34.814Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:46:34.814Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:46:34.814Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (121547.877 ms) ======
[2024-10-02T21:46:34.814Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-10-02T21:46:35.658Z] GC before operation: completed in 386.781 ms, heap usage 236.737 MB -> 52.475 MB.
[2024-10-02T21:46:48.019Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:47:00.468Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:47:12.873Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:47:22.448Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:47:29.701Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:47:35.617Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:47:41.617Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:47:47.554Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:47:49.241Z] 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.
[2024-10-02T21:47:49.241Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:47:49.241Z] Movies recommended for you:
[2024-10-02T21:47:49.241Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:47:49.241Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:47:49.241Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (74040.599 ms) ======
[2024-10-02T21:47:49.241Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-10-02T21:47:50.075Z] GC before operation: completed in 334.873 ms, heap usage 84.298 MB -> 51.077 MB.
[2024-10-02T21:48:00.482Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:48:11.019Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:48:20.372Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:48:30.840Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:48:35.590Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:48:41.591Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:48:48.907Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:48:54.929Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:48:55.848Z] 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.
[2024-10-02T21:48:55.848Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:48:56.683Z] Movies recommended for you:
[2024-10-02T21:48:56.683Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:48:56.683Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:48:56.683Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (66514.736 ms) ======
[2024-10-02T21:48:56.683Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-10-02T21:48:56.683Z] GC before operation: completed in 319.128 ms, heap usage 134.828 MB -> 49.912 MB.
[2024-10-02T21:49:07.134Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:49:19.397Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:49:28.755Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:49:37.455Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:49:43.417Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:49:48.199Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:49:54.178Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:50:00.152Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:50:01.032Z] 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.
[2024-10-02T21:50:01.032Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:50:01.032Z] Movies recommended for you:
[2024-10-02T21:50:01.032Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:50:01.032Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:50:01.032Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (64607.504 ms) ======
[2024-10-02T21:50:01.032Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-10-02T21:50:01.880Z] GC before operation: completed in 319.590 ms, heap usage 252.267 MB -> 50.284 MB.
[2024-10-02T21:50:10.666Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:50:21.734Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:50:32.041Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:50:40.517Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:50:47.555Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:50:54.621Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:50:59.342Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:51:05.067Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:51:05.852Z] 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.
[2024-10-02T21:51:05.852Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:51:05.852Z] Movies recommended for you:
[2024-10-02T21:51:05.852Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:51:05.852Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:51:05.852Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (64286.706 ms) ======
[2024-10-02T21:51:05.852Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-10-02T21:51:06.649Z] GC before operation: completed in 337.714 ms, heap usage 132.711 MB -> 50.345 MB.
[2024-10-02T21:51:15.135Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:51:24.090Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:51:34.218Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:51:44.257Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:51:48.837Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:51:55.980Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:52:01.811Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:52:07.628Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:52:08.429Z] 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.
[2024-10-02T21:52:08.429Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:52:08.429Z] Movies recommended for you:
[2024-10-02T21:52:08.429Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:52:08.429Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:52:08.429Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (62417.637 ms) ======
[2024-10-02T21:52:08.429Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-10-02T21:52:09.227Z] GC before operation: completed in 293.379 ms, heap usage 241.674 MB -> 50.345 MB.
[2024-10-02T21:52:19.637Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:52:29.786Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:52:38.419Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:52:48.611Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:52:54.421Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:53:00.258Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:53:06.046Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:53:11.835Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:53:11.835Z] 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.
[2024-10-02T21:53:12.635Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:53:12.635Z] Movies recommended for you:
[2024-10-02T21:53:12.636Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:53:12.636Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:53:12.636Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (63438.457 ms) ======
[2024-10-02T21:53:12.636Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-10-02T21:53:12.636Z] GC before operation: completed in 304.773 ms, heap usage 342.289 MB -> 50.714 MB.
[2024-10-02T21:53:23.083Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:53:33.263Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:53:43.233Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:53:51.522Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:53:57.160Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:54:02.816Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:54:08.512Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:54:14.349Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:54:15.998Z] 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.
[2024-10-02T21:54:15.998Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:54:16.787Z] Movies recommended for you:
[2024-10-02T21:54:16.788Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:54:16.788Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:54:16.788Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (63763.243 ms) ======
[2024-10-02T21:54:16.788Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-10-02T21:54:16.788Z] GC before operation: completed in 415.463 ms, heap usage 133.064 MB -> 50.950 MB.
[2024-10-02T21:54:26.738Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:54:36.690Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:54:45.080Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:54:53.430Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:54:59.020Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:55:04.680Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:55:10.401Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:55:17.814Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:55:19.411Z] 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.
[2024-10-02T21:55:19.411Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:55:20.216Z] Movies recommended for you:
[2024-10-02T21:55:20.216Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:55:20.216Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:55:20.216Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (62860.424 ms) ======
[2024-10-02T21:55:20.216Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-10-02T21:55:20.216Z] GC before operation: completed in 446.891 ms, heap usage 183.288 MB -> 50.647 MB.
[2024-10-02T21:55:31.838Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:55:41.719Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:55:51.552Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:56:05.236Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:56:10.805Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:56:16.950Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:56:25.342Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:56:32.272Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:56:33.066Z] 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.
[2024-10-02T21:56:33.066Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:56:33.066Z] Movies recommended for you:
[2024-10-02T21:56:33.066Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:56:33.066Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:56:33.066Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (72944.246 ms) ======
[2024-10-02T21:56:33.066Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-10-02T21:56:33.864Z] GC before operation: completed in 449.341 ms, heap usage 132.967 MB -> 50.908 MB.
[2024-10-02T21:56:45.593Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:56:59.610Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:57:11.520Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:57:23.740Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:57:30.721Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:57:37.745Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:57:46.081Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:57:53.078Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:57:53.877Z] 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.
[2024-10-02T21:57:53.877Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:57:54.676Z] Movies recommended for you:
[2024-10-02T21:57:54.676Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:57:54.676Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:57:54.676Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (80848.027 ms) ======
[2024-10-02T21:57:54.676Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-10-02T21:57:54.676Z] GC before operation: completed in 443.961 ms, heap usage 133.635 MB -> 50.569 MB.
[2024-10-02T21:58:06.639Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:58:20.828Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:58:30.674Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:58:44.416Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:58:51.283Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:58:58.205Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:59:06.493Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:59:14.798Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:59:14.798Z] 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.
[2024-10-02T21:59:15.578Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:59:15.578Z] Movies recommended for you:
[2024-10-02T21:59:15.578Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:59:15.578Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:59:15.578Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (80610.463 ms) ======
[2024-10-02T21:59:15.578Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-10-02T21:59:16.380Z] GC before operation: completed in 404.547 ms, heap usage 187.640 MB -> 50.784 MB.
[2024-10-02T21:59:26.903Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:59:39.018Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:59:50.636Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T22:00:04.369Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T22:00:12.661Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T22:00:19.571Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T22:00:27.845Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T22:00:36.207Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T22:00:36.996Z] 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.
[2024-10-02T22:00:37.773Z] The best model improves the baseline by 14.52%.
[2024-10-02T22:00:37.773Z] Movies recommended for you:
[2024-10-02T22:00:37.773Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T22:00:37.773Z] There is no way to check that no silent failure occurred.
[2024-10-02T22:00:37.773Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (81977.508 ms) ======
[2024-10-02T22:00:37.773Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-10-02T22:00:38.538Z] GC before operation: completed in 418.504 ms, heap usage 185.497 MB -> 51.281 MB.
[2024-10-02T22:00:50.368Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T22:01:04.681Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T22:01:18.543Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T22:01:30.363Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T22:01:37.338Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T22:01:44.320Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T22:01:54.280Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T22:02:02.534Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T22:02:03.344Z] 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.
[2024-10-02T22:02:03.344Z] The best model improves the baseline by 14.52%.
[2024-10-02T22:02:04.109Z] Movies recommended for you:
[2024-10-02T22:02:04.109Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T22:02:04.109Z] There is no way to check that no silent failure occurred.
[2024-10-02T22:02:04.109Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (85509.705 ms) ======
[2024-10-02T22:02:04.109Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-10-02T22:02:04.109Z] GC before operation: completed in 512.917 ms, heap usage 236.512 MB -> 50.671 MB.
[2024-10-02T22:02:17.901Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T22:02:27.971Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T22:02:39.630Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T22:02:49.925Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T22:02:54.363Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T22:03:01.236Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T22:03:06.780Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T22:03:14.943Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T22:03:16.497Z] 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.
[2024-10-02T22:03:16.497Z] The best model improves the baseline by 14.52%.
[2024-10-02T22:03:16.497Z] Movies recommended for you:
[2024-10-02T22:03:16.497Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T22:03:16.497Z] There is no way to check that no silent failure occurred.
[2024-10-02T22:03:16.497Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (72310.336 ms) ======
[2024-10-02T22:03:16.497Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-10-02T22:03:17.264Z] GC before operation: completed in 470.960 ms, heap usage 190.701 MB -> 51.146 MB.
[2024-10-02T22:03:30.951Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T22:03:45.216Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T22:03:58.897Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T22:04:10.546Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T22:04:18.807Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T22:04:25.600Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T22:04:37.234Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T22:04:44.734Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T22:04:46.321Z] 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.
[2024-10-02T22:04:46.321Z] The best model improves the baseline by 14.52%.
[2024-10-02T22:04:47.070Z] Movies recommended for you:
[2024-10-02T22:04:47.070Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T22:04:47.070Z] There is no way to check that no silent failure occurred.
[2024-10-02T22:04:47.071Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (89533.843 ms) ======
[2024-10-02T22:04:47.071Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-10-02T22:04:47.071Z] GC before operation: completed in 407.665 ms, heap usage 160.248 MB -> 51.913 MB.
[2024-10-02T22:05:00.868Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T22:05:14.701Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T22:05:28.672Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T22:05:42.439Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T22:05:49.842Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T22:06:00.009Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T22:06:08.276Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T22:06:16.409Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T22:06:17.162Z] 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.
[2024-10-02T22:06:17.162Z] The best model improves the baseline by 14.52%.
[2024-10-02T22:06:17.934Z] Movies recommended for you:
[2024-10-02T22:06:17.934Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T22:06:17.934Z] There is no way to check that no silent failure occurred.
[2024-10-02T22:06:17.934Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (91111.677 ms) ======
[2024-10-02T22:06:17.934Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-10-02T22:06:18.691Z] GC before operation: completed in 587.520 ms, heap usage 133.839 MB -> 50.679 MB.
[2024-10-02T22:06:32.538Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T22:06:44.309Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T22:06:58.085Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T22:07:11.738Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T22:07:18.621Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T22:07:25.628Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T22:07:35.580Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T22:07:41.207Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T22:07:41.973Z] 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.
[2024-10-02T22:07:41.973Z] The best model improves the baseline by 14.52%.
[2024-10-02T22:07:42.726Z] Movies recommended for you:
[2024-10-02T22:07:42.726Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T22:07:42.726Z] There is no way to check that no silent failure occurred.
[2024-10-02T22:07:42.726Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (83683.859 ms) ======
[2024-10-02T22:07:42.726Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-10-02T22:07:42.726Z] GC before operation: completed in 286.975 ms, heap usage 165.712 MB -> 50.914 MB.
[2024-10-02T22:07:54.334Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T22:08:08.384Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T22:08:24.399Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T22:08:36.383Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T22:08:46.275Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T22:08:54.502Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T22:09:02.780Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T22:09:11.024Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T22:09:12.612Z] 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.
[2024-10-02T22:09:12.612Z] The best model improves the baseline by 14.52%.
[2024-10-02T22:09:13.387Z] Movies recommended for you:
[2024-10-02T22:09:13.387Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T22:09:13.387Z] There is no way to check that no silent failure occurred.
[2024-10-02T22:09:13.387Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (90549.789 ms) ======
[2024-10-02T22:09:13.387Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-10-02T22:09:14.160Z] GC before operation: completed in 595.151 ms, heap usage 159.768 MB -> 49.407 MB.
[2024-10-02T22:09:33.925Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T22:09:45.742Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T22:09:59.710Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T22:10:15.948Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T22:10:25.752Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T22:10:36.169Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T22:10:46.164Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T22:10:56.180Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T22:10:56.945Z] 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.
[2024-10-02T22:10:57.725Z] The best model improves the baseline by 14.52%.
[2024-10-02T22:10:57.725Z] Movies recommended for you:
[2024-10-02T22:10:57.725Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T22:10:57.725Z] There is no way to check that no silent failure occurred.
[2024-10-02T22:10:57.725Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (104061.765 ms) ======
[2024-10-02T22:11:01.178Z] -----------------------------------
[2024-10-02T22:11:01.178Z] renaissance-movie-lens_0_PASSED
[2024-10-02T22:11:01.178Z] -----------------------------------
[2024-10-02T22:11:01.178Z]
[2024-10-02T22:11:01.178Z] TEST TEARDOWN:
[2024-10-02T22:11:01.178Z] Nothing to be done for teardown.
[2024-10-02T22:11:01.178Z] renaissance-movie-lens_0 Finish Time: Wed Oct 2 22:11:00 2024 Epoch Time (ms): 1727907060788