renaissance-movie-lens_0
[2024-11-29T19:28:38.625Z] Running test renaissance-movie-lens_0 ...
[2024-11-29T19:28:38.625Z] ===============================================
[2024-11-29T19:28:38.625Z] renaissance-movie-lens_0 Start Time: Fri Nov 29 19:28:38 2024 Epoch Time (ms): 1732908518440
[2024-11-29T19:28:38.625Z] variation: NoOptions
[2024-11-29T19:28:38.625Z] JVM_OPTIONS:
[2024-11-29T19:28:38.625Z] { \
[2024-11-29T19:28:38.625Z] echo ""; echo "TEST SETUP:"; \
[2024-11-29T19:28:38.625Z] echo "Nothing to be done for setup."; \
[2024-11-29T19:28:38.625Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_173290636086/renaissance-movie-lens_0"; \
[2024-11-29T19:28:38.625Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_173290636086/renaissance-movie-lens_0"; \
[2024-11-29T19:28:38.625Z] echo ""; echo "TESTING:"; \
[2024-11-29T19:28:38.625Z] "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" -jar "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_173290636086/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-29T19:28:38.625Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_173290636086/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-29T19:28:38.625Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-29T19:28:38.625Z] echo "Nothing to be done for teardown."; \
[2024-11-29T19:28:38.625Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_173290636086/TestTargetResult";
[2024-11-29T19:28:38.625Z]
[2024-11-29T19:28:38.625Z] TEST SETUP:
[2024-11-29T19:28:38.625Z] Nothing to be done for setup.
[2024-11-29T19:28:38.625Z]
[2024-11-29T19:28:38.625Z] TESTING:
[2024-11-29T19:28:45.485Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-29T19:28:57.144Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-11-29T19:29:13.935Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-29T19:29:13.935Z] Training: 60056, validation: 20285, test: 19854
[2024-11-29T19:29:13.935Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-29T19:29:13.935Z] GC before operation: completed in 790.823 ms, heap usage 166.601 MB -> 27.343 MB.
[2024-11-29T19:29:44.316Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:29:56.724Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:30:10.571Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:30:20.521Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:30:27.440Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:30:33.951Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:30:40.819Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:30:47.646Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:30:48.408Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:30:48.408Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:30:49.169Z] Movies recommended for you:
[2024-11-29T19:30:49.169Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:30:49.169Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:30:49.169Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (94570.109 ms) ======
[2024-11-29T19:30:49.169Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-29T19:30:49.925Z] GC before operation: completed in 1152.700 ms, heap usage 61.486 MB -> 44.544 MB.
[2024-11-29T19:30:59.853Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:31:14.158Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:31:25.805Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:31:35.671Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:31:41.304Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:31:48.213Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:31:56.522Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:32:03.616Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:32:04.414Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:32:05.196Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:32:05.196Z] Movies recommended for you:
[2024-11-29T19:32:05.196Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:32:05.196Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:32:05.196Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (75064.550 ms) ======
[2024-11-29T19:32:05.196Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-29T19:32:05.980Z] GC before operation: completed in 772.545 ms, heap usage 288.320 MB -> 42.264 MB.
[2024-11-29T19:32:21.533Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:32:35.124Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:32:46.857Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:32:53.645Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:32:58.067Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:33:03.608Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:33:09.671Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:33:15.233Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:33:15.991Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:33:15.991Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:33:16.742Z] Movies recommended for you:
[2024-11-29T19:33:16.742Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:33:16.742Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:33:16.742Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (70816.614 ms) ======
[2024-11-29T19:33:16.742Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-29T19:33:17.508Z] GC before operation: completed in 627.857 ms, heap usage 522.421 MB -> 46.667 MB.
[2024-11-29T19:33:29.037Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:33:38.784Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:33:48.518Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:33:56.805Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:34:04.169Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:34:10.953Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:34:16.492Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:34:22.012Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:34:23.579Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:34:23.579Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:34:23.579Z] Movies recommended for you:
[2024-11-29T19:34:23.579Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:34:23.579Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:34:23.579Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (66319.062 ms) ======
[2024-11-29T19:34:23.579Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-29T19:34:24.355Z] GC before operation: completed in 746.806 ms, heap usage 508.154 MB -> 46.844 MB.
[2024-11-29T19:34:35.925Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:34:47.495Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:34:59.038Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:35:10.960Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:35:20.735Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:35:28.951Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:35:35.736Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:35:44.001Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:35:44.001Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:35:44.001Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:35:44.001Z] Movies recommended for you:
[2024-11-29T19:35:44.001Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:35:44.001Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:35:44.001Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (79718.224 ms) ======
[2024-11-29T19:35:44.001Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-29T19:35:44.790Z] GC before operation: completed in 708.993 ms, heap usage 507.040 MB -> 47.056 MB.
[2024-11-29T19:35:56.357Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:36:08.039Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:36:19.620Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:36:31.161Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:36:36.679Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:36:43.463Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:36:49.039Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:36:54.555Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:36:55.311Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:36:55.311Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:36:55.311Z] Movies recommended for you:
[2024-11-29T19:36:55.311Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:36:55.311Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:36:55.311Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (70765.364 ms) ======
[2024-11-29T19:36:55.311Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-29T19:36:56.076Z] GC before operation: completed in 527.833 ms, heap usage 472.272 MB -> 48.496 MB.
[2024-11-29T19:37:06.262Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:37:16.010Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:37:25.745Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:37:35.488Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:37:40.983Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:37:46.597Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:37:50.999Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:37:56.568Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:37:57.329Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:37:57.329Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:37:58.217Z] Movies recommended for you:
[2024-11-29T19:37:58.217Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:37:58.217Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:37:58.217Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (61767.273 ms) ======
[2024-11-29T19:37:58.217Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-29T19:37:58.217Z] GC before operation: completed in 441.516 ms, heap usage 474.216 MB -> 47.131 MB.
[2024-11-29T19:38:06.851Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:38:15.045Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:38:24.799Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:38:34.536Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:38:38.905Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:38:43.291Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:38:48.821Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:38:53.245Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:38:53.245Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:38:54.012Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:38:54.012Z] Movies recommended for you:
[2024-11-29T19:38:54.012Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:38:54.012Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:38:54.012Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (55550.933 ms) ======
[2024-11-29T19:38:54.012Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-29T19:38:54.767Z] GC before operation: completed in 543.514 ms, heap usage 438.026 MB -> 47.362 MB.
[2024-11-29T19:39:04.707Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:39:12.835Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:39:22.631Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:39:30.769Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:39:35.158Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:39:40.670Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:39:46.184Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:39:49.562Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:39:50.330Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:39:50.330Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:39:50.330Z] Movies recommended for you:
[2024-11-29T19:39:50.330Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:39:50.330Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:39:50.330Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (56183.086 ms) ======
[2024-11-29T19:39:50.330Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-29T19:39:51.087Z] GC before operation: completed in 344.399 ms, heap usage 455.717 MB -> 47.370 MB.
[2024-11-29T19:39:59.846Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:40:09.699Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:40:17.918Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:40:24.705Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:40:30.270Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:40:34.691Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:40:39.123Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:40:44.722Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:40:45.488Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:40:45.488Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:40:45.488Z] Movies recommended for you:
[2024-11-29T19:40:45.488Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:40:45.488Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:40:45.488Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (54599.448 ms) ======
[2024-11-29T19:40:45.488Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-29T19:40:46.248Z] GC before operation: completed in 577.619 ms, heap usage 469.019 MB -> 48.575 MB.
[2024-11-29T19:40:54.999Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:41:03.290Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:41:11.538Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:41:19.783Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:41:23.197Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:41:28.825Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:41:34.377Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:41:38.813Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:41:38.813Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:41:38.813Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:41:38.813Z] Movies recommended for you:
[2024-11-29T19:41:38.813Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:41:38.813Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:41:38.813Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (53047.957 ms) ======
[2024-11-29T19:41:38.813Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-29T19:41:39.576Z] GC before operation: completed in 341.955 ms, heap usage 98.440 MB -> 42.678 MB.
[2024-11-29T19:41:48.330Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:41:58.280Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:42:08.117Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:42:17.953Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:42:23.506Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:42:29.078Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:42:34.620Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:42:39.005Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:42:39.766Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:42:39.766Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:42:40.518Z] Movies recommended for you:
[2024-11-29T19:42:40.518Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:42:40.518Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:42:40.518Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (60758.715 ms) ======
[2024-11-29T19:42:40.518Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-29T19:42:40.518Z] GC before operation: completed in 481.488 ms, heap usage 479.914 MB -> 47.593 MB.
[2024-11-29T19:42:50.703Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:43:00.518Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:43:12.144Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:43:21.971Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:43:27.558Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:43:31.980Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:43:37.576Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:43:44.600Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:43:45.375Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:43:45.375Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:43:46.153Z] Movies recommended for you:
[2024-11-29T19:43:46.153Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:43:46.153Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:43:46.153Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (65014.892 ms) ======
[2024-11-29T19:43:46.153Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-29T19:43:46.153Z] GC before operation: completed in 430.222 ms, heap usage 440.191 MB -> 47.632 MB.
[2024-11-29T19:43:56.029Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:44:05.882Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:44:15.750Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:44:25.567Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:44:31.077Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:44:35.472Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:44:41.505Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:44:47.068Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:44:47.834Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:44:47.834Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:44:47.834Z] Movies recommended for you:
[2024-11-29T19:44:47.834Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:44:47.834Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:44:47.834Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (61606.995 ms) ======
[2024-11-29T19:44:47.834Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-29T19:44:47.834Z] GC before operation: completed in 355.422 ms, heap usage 493.384 MB -> 48.749 MB.
[2024-11-29T19:44:57.621Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:45:07.414Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:45:19.113Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:45:27.340Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:45:31.758Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:45:36.187Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:45:42.293Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:45:46.733Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:45:47.487Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:45:47.487Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:45:47.487Z] Movies recommended for you:
[2024-11-29T19:45:47.487Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:45:47.487Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:45:47.487Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (59272.893 ms) ======
[2024-11-29T19:45:47.487Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-29T19:45:47.488Z] GC before operation: completed in 349.184 ms, heap usage 481.300 MB -> 47.424 MB.
[2024-11-29T19:45:55.720Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:46:05.607Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:46:15.443Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:46:25.313Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:46:30.885Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:46:35.294Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:46:39.746Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:46:45.317Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:46:46.088Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:46:46.088Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:46:46.853Z] Movies recommended for you:
[2024-11-29T19:46:46.853Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:46:46.853Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:46:46.853Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (58807.747 ms) ======
[2024-11-29T19:46:46.853Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-29T19:46:47.638Z] GC before operation: completed in 748.757 ms, heap usage 481.426 MB -> 47.631 MB.
[2024-11-29T19:46:57.483Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:47:06.083Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:47:17.235Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:47:27.321Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:47:32.522Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:47:37.702Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:47:44.163Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:47:49.529Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:47:49.529Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:47:49.529Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:47:49.529Z] Movies recommended for you:
[2024-11-29T19:47:49.529Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:47:49.529Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:47:49.529Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (62485.165 ms) ======
[2024-11-29T19:47:49.529Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-29T19:47:50.403Z] GC before operation: completed in 457.736 ms, heap usage 468.601 MB -> 47.312 MB.
[2024-11-29T19:47:59.668Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:48:10.555Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:48:19.735Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:48:29.581Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:48:34.591Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:48:39.640Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:48:45.924Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:48:52.222Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:48:52.222Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:48:52.222Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:48:53.104Z] Movies recommended for you:
[2024-11-29T19:48:53.104Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:48:53.104Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:48:53.104Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (62350.274 ms) ======
[2024-11-29T19:48:53.104Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-29T19:48:53.104Z] GC before operation: completed in 530.140 ms, heap usage 458.800 MB -> 47.334 MB.
[2024-11-29T19:49:04.096Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:49:13.313Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:49:24.240Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:49:34.063Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:49:39.091Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:49:45.379Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:49:50.456Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:49:55.518Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:49:56.412Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:49:56.412Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:49:56.412Z] Movies recommended for you:
[2024-11-29T19:49:56.412Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:49:56.412Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:49:56.412Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (63355.502 ms) ======
[2024-11-29T19:49:56.412Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-29T19:49:57.292Z] GC before operation: completed in 629.763 ms, heap usage 442.043 MB -> 47.589 MB.
[2024-11-29T19:50:06.485Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-29T19:50:15.665Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-29T19:50:24.843Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-29T19:50:34.666Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-29T19:50:40.970Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-29T19:50:46.002Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-29T19:50:52.301Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-29T19:50:57.321Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-29T19:50:58.212Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2024-11-29T19:50:58.212Z] The best model improves the baseline by 14.52%.
[2024-11-29T19:50:58.212Z] Movies recommended for you:
[2024-11-29T19:50:58.212Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-29T19:50:58.212Z] There is no way to check that no silent failure occurred.
[2024-11-29T19:50:58.212Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (61078.728 ms) ======
[2024-11-29T19:51:00.019Z] -----------------------------------
[2024-11-29T19:51:00.019Z] renaissance-movie-lens_0_PASSED
[2024-11-29T19:51:00.019Z] -----------------------------------
[2024-11-29T19:51:00.019Z]
[2024-11-29T19:51:00.019Z] TEST TEARDOWN:
[2024-11-29T19:51:00.019Z] Nothing to be done for teardown.
[2024-11-29T19:51:00.019Z] renaissance-movie-lens_0 Finish Time: Fri Nov 29 19:50:59 2024 Epoch Time (ms): 1732909859524