renaissance-movie-lens_0
[2025-02-25T22:31:34.711Z] Running test renaissance-movie-lens_0 ...
[2025-02-25T22:31:34.711Z] ===============================================
[2025-02-25T22:31:34.711Z] renaissance-movie-lens_0 Start Time: Tue Feb 25 22:31:34 2025 Epoch Time (ms): 1740522694108
[2025-02-25T22:31:34.711Z] variation: NoOptions
[2025-02-25T22:31:34.711Z] JVM_OPTIONS:
[2025-02-25T22:31:34.711Z] { \
[2025-02-25T22:31:34.711Z] echo ""; echo "TEST SETUP:"; \
[2025-02-25T22:31:34.711Z] echo "Nothing to be done for setup."; \
[2025-02-25T22:31:34.711Z] mkdir -p "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17405209215578/renaissance-movie-lens_0"; \
[2025-02-25T22:31:34.711Z] cd "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17405209215578/renaissance-movie-lens_0"; \
[2025-02-25T22:31:34.711Z] echo ""; echo "TESTING:"; \
[2025-02-25T22:31:34.711Z] "/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_17405209215578/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-25T22:31:34.711Z] 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_17405209215578/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-25T22:31:34.711Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-25T22:31:34.711Z] echo "Nothing to be done for teardown."; \
[2025-02-25T22:31:34.711Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17405209215578/TestTargetResult";
[2025-02-25T22:31:34.711Z]
[2025-02-25T22:31:34.711Z] TEST SETUP:
[2025-02-25T22:31:34.711Z] Nothing to be done for setup.
[2025-02-25T22:31:34.711Z]
[2025-02-25T22:31:34.711Z] TESTING:
[2025-02-25T22:31:40.744Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-25T22:31:44.163Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-02-25T22:31:49.106Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-25T22:31:49.106Z] Training: 60056, validation: 20285, test: 19854
[2025-02-25T22:31:49.106Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-25T22:31:49.106Z] GC before operation: completed in 198.269 ms, heap usage 141.794 MB -> 27.178 MB.
[2025-02-25T22:32:02.805Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:32:08.452Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:32:13.939Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:32:19.424Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:32:21.828Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:32:24.226Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:32:26.634Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:32:29.049Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:32:29.049Z] 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.
[2025-02-25T22:32:29.049Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:32:29.793Z] Movies recommended for you:
[2025-02-25T22:32:29.793Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:32:29.793Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:32:29.793Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (40368.076 ms) ======
[2025-02-25T22:32:29.793Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-25T22:32:29.793Z] GC before operation: completed in 379.117 ms, heap usage 456.428 MB -> 45.434 MB.
[2025-02-25T22:32:35.265Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:32:40.780Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:32:46.674Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:32:50.031Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:32:52.459Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:32:54.864Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:32:57.258Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:32:59.661Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:32:59.661Z] 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.
[2025-02-25T22:32:59.661Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:33:00.407Z] Movies recommended for you:
[2025-02-25T22:33:00.407Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:33:00.407Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:33:00.407Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (30211.519 ms) ======
[2025-02-25T22:33:00.407Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-25T22:33:00.407Z] GC before operation: completed in 309.281 ms, heap usage 298.267 MB -> 42.398 MB.
[2025-02-25T22:33:03.737Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:33:08.064Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:33:11.399Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:33:15.722Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:33:17.256Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:33:19.654Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:33:22.754Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:33:23.502Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:33:24.243Z] 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.
[2025-02-25T22:33:24.244Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:33:24.244Z] Movies recommended for you:
[2025-02-25T22:33:24.244Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:33:24.244Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:33:24.244Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23672.747 ms) ======
[2025-02-25T22:33:24.244Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-25T22:33:24.244Z] GC before operation: completed in 224.169 ms, heap usage 537.282 MB -> 46.510 MB.
[2025-02-25T22:33:27.591Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:33:30.917Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:33:34.225Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:33:37.543Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:33:39.593Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:33:41.982Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:33:44.384Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:33:46.790Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:33:46.790Z] 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.
[2025-02-25T22:33:47.533Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:33:47.533Z] Movies recommended for you:
[2025-02-25T22:33:47.533Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:33:47.533Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:33:47.533Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (22925.492 ms) ======
[2025-02-25T22:33:47.533Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-25T22:33:47.533Z] GC before operation: completed in 229.461 ms, heap usage 472.037 MB -> 46.861 MB.
[2025-02-25T22:33:51.901Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:33:57.525Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:33:58.269Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:34:01.577Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:34:03.998Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:34:06.384Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:34:08.772Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:34:11.163Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:34:11.163Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-25T22:34:11.163Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:34:11.163Z] Movies recommended for you:
[2025-02-25T22:34:11.164Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:34:11.164Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:34:11.164Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (24043.689 ms) ======
[2025-02-25T22:34:11.164Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-25T22:34:11.910Z] GC before operation: completed in 211.481 ms, heap usage 454.106 MB -> 47.079 MB.
[2025-02-25T22:34:15.232Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:34:19.540Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:34:22.845Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:34:26.157Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:34:29.070Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:34:30.605Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:34:33.222Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:34:34.767Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:34:34.767Z] 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.
[2025-02-25T22:34:34.767Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:34:34.767Z] Movies recommended for you:
[2025-02-25T22:34:34.767Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:34:34.767Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:34:34.767Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (23099.403 ms) ======
[2025-02-25T22:34:34.767Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-25T22:34:34.767Z] GC before operation: completed in 192.997 ms, heap usage 471.968 MB -> 46.970 MB.
[2025-02-25T22:34:39.091Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:34:42.439Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:34:45.749Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:34:50.082Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:34:52.677Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:34:55.076Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:34:56.618Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:34:59.003Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:34:59.003Z] 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.
[2025-02-25T22:34:59.003Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:34:59.003Z] Movies recommended for you:
[2025-02-25T22:34:59.003Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:34:59.003Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:34:59.003Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (23909.745 ms) ======
[2025-02-25T22:34:59.003Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-25T22:34:59.003Z] GC before operation: completed in 195.405 ms, heap usage 509.791 MB -> 47.178 MB.
[2025-02-25T22:35:02.313Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:35:05.626Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:35:11.123Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:35:17.795Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:35:18.542Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:35:21.414Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:35:22.156Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:35:24.591Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:35:24.591Z] 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.
[2025-02-25T22:35:24.591Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:35:24.591Z] Movies recommended for you:
[2025-02-25T22:35:24.591Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:35:24.591Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:35:24.591Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (25498.987 ms) ======
[2025-02-25T22:35:24.591Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-25T22:35:24.591Z] GC before operation: completed in 179.954 ms, heap usage 471.242 MB -> 47.460 MB.
[2025-02-25T22:35:27.910Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:35:31.227Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:35:34.536Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:35:37.840Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:35:39.370Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:35:41.885Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:35:43.420Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:35:45.808Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:35:45.808Z] 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.
[2025-02-25T22:35:45.808Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:35:45.808Z] Movies recommended for you:
[2025-02-25T22:35:45.808Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:35:45.808Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:35:45.808Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (20961.217 ms) ======
[2025-02-25T22:35:45.808Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-25T22:35:45.808Z] GC before operation: completed in 194.172 ms, heap usage 476.636 MB -> 47.232 MB.
[2025-02-25T22:35:50.140Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:35:53.480Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:35:58.248Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:36:01.574Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:36:03.118Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:36:05.567Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:36:08.446Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:36:11.779Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:36:11.779Z] 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.
[2025-02-25T22:36:11.779Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:36:11.779Z] Movies recommended for you:
[2025-02-25T22:36:11.779Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:36:11.779Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:36:11.779Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (25718.796 ms) ======
[2025-02-25T22:36:11.779Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-25T22:36:11.779Z] GC before operation: completed in 257.325 ms, heap usage 497.626 MB -> 47.411 MB.
[2025-02-25T22:36:16.114Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:36:18.503Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:36:21.818Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:36:25.125Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:36:27.506Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:36:29.053Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:36:31.446Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:36:33.834Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:36:33.834Z] 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.
[2025-02-25T22:36:33.834Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:36:33.834Z] Movies recommended for you:
[2025-02-25T22:36:33.834Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:36:33.834Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:36:33.834Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (21821.513 ms) ======
[2025-02-25T22:36:33.834Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-25T22:36:33.834Z] GC before operation: completed in 162.805 ms, heap usage 471.958 MB -> 47.037 MB.
[2025-02-25T22:36:37.167Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:36:40.476Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:36:44.818Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:36:48.128Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:36:49.664Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:36:52.046Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:36:53.581Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:36:55.995Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:36:55.995Z] 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.
[2025-02-25T22:36:55.995Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:36:55.995Z] Movies recommended for you:
[2025-02-25T22:36:55.995Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:36:55.995Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:36:55.995Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (22114.866 ms) ======
[2025-02-25T22:36:55.995Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-25T22:36:55.995Z] GC before operation: completed in 182.822 ms, heap usage 467.950 MB -> 47.277 MB.
[2025-02-25T22:36:59.842Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:37:03.162Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:37:07.623Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:37:10.955Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:37:12.486Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:37:14.878Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:37:17.262Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:37:18.798Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:37:18.798Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252187379536.
[2025-02-25T22:37:18.798Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:37:18.798Z] Movies recommended for you:
[2025-02-25T22:37:18.798Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:37:18.798Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:37:18.798Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (22865.200 ms) ======
[2025-02-25T22:37:18.798Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-25T22:37:19.539Z] GC before operation: completed in 165.074 ms, heap usage 458.476 MB -> 47.504 MB.
[2025-02-25T22:37:22.885Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:37:28.345Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:37:32.707Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:37:38.222Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:37:40.619Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:37:43.983Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:37:46.900Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:37:50.346Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:37:50.346Z] 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.
[2025-02-25T22:37:50.346Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:37:50.346Z] Movies recommended for you:
[2025-02-25T22:37:50.346Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:37:50.346Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:37:50.346Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (31191.261 ms) ======
[2025-02-25T22:37:50.346Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-25T22:37:53.534Z] GC before operation: completed in 326.218 ms, heap usage 497.144 MB -> 48.966 MB.
[2025-02-25T22:37:55.931Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:38:01.397Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:38:08.115Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:38:12.506Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:38:15.840Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:38:18.259Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:38:21.615Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:38:24.966Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:38:24.966Z] 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.
[2025-02-25T22:38:24.966Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:38:24.966Z] Movies recommended for you:
[2025-02-25T22:38:24.966Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:38:24.966Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:38:24.966Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (34334.710 ms) ======
[2025-02-25T22:38:24.966Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-25T22:38:24.966Z] GC before operation: completed in 192.692 ms, heap usage 468.232 MB -> 47.363 MB.
[2025-02-25T22:38:30.461Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:38:33.784Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:38:38.786Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:38:42.334Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:38:42.334Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:38:43.877Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:38:45.826Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:38:47.393Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:38:47.393Z] 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.
[2025-02-25T22:38:47.393Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:38:47.393Z] Movies recommended for you:
[2025-02-25T22:38:47.393Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:38:47.393Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:38:47.393Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (22160.185 ms) ======
[2025-02-25T22:38:47.393Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-25T22:38:47.393Z] GC before operation: completed in 151.779 ms, heap usage 495.052 MB -> 47.502 MB.
[2025-02-25T22:38:50.786Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:38:54.098Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:38:57.471Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:39:00.810Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:39:03.277Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:39:06.714Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:39:09.139Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:39:13.526Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:39:13.526Z] 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.
[2025-02-25T22:39:13.526Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:39:13.526Z] Movies recommended for you:
[2025-02-25T22:39:13.526Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:39:13.526Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:39:13.526Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (26205.551 ms) ======
[2025-02-25T22:39:13.526Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-25T22:39:14.274Z] GC before operation: completed in 332.200 ms, heap usage 502.343 MB -> 47.331 MB.
[2025-02-25T22:39:19.913Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:39:24.328Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:39:29.783Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:39:35.267Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:39:37.668Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:39:41.294Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:39:44.628Z] RMSE (validation) = 0.9227419497655964 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:39:47.963Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:39:47.963Z] 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.
[2025-02-25T22:39:47.963Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:39:47.963Z] Movies recommended for you:
[2025-02-25T22:39:47.963Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:39:47.963Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:39:47.963Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (33955.389 ms) ======
[2025-02-25T22:39:47.963Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-25T22:39:47.963Z] GC before operation: completed in 191.699 ms, heap usage 442.781 MB -> 47.280 MB.
[2025-02-25T22:39:53.442Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:39:58.939Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:40:04.546Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:40:12.706Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:40:16.174Z] RMSE (validation) = 1.2070175276098325 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:40:20.612Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:40:23.966Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:40:26.396Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:40:27.629Z] 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.
[2025-02-25T22:40:27.629Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:40:27.629Z] Movies recommended for you:
[2025-02-25T22:40:27.629Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:40:27.629Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:40:27.629Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (38641.515 ms) ======
[2025-02-25T22:40:27.629Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-25T22:40:27.629Z] GC before operation: completed in 211.577 ms, heap usage 442.077 MB -> 47.502 MB.
[2025-02-25T22:40:30.972Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-25T22:40:34.291Z] RMSE (validation) = 2.1340923220285766 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-25T22:40:39.843Z] RMSE (validation) = 1.3105186462138083 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-25T22:40:45.409Z] RMSE (validation) = 0.9919630851507418 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-25T22:40:49.881Z] RMSE (validation) = 1.2070175276098327 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-25T22:40:52.338Z] RMSE (validation) = 1.1146801722401463 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-25T22:40:56.801Z] RMSE (validation) = 0.9227419497655963 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-25T22:41:01.316Z] RMSE (validation) = 0.8980643995666189 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-25T22:41:02.093Z] 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.
[2025-02-25T22:41:02.093Z] The best model improves the baseline by 14.52%.
[2025-02-25T22:41:02.093Z] Movies recommended for you:
[2025-02-25T22:41:02.093Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-25T22:41:02.093Z] There is no way to check that no silent failure occurred.
[2025-02-25T22:41:02.093Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (34949.122 ms) ======
[2025-02-25T22:41:03.703Z] -----------------------------------
[2025-02-25T22:41:03.703Z] renaissance-movie-lens_0_PASSED
[2025-02-25T22:41:03.703Z] -----------------------------------
[2025-02-25T22:41:03.703Z]
[2025-02-25T22:41:03.703Z] TEST TEARDOWN:
[2025-02-25T22:41:03.703Z] Nothing to be done for teardown.
[2025-02-25T22:41:03.703Z] renaissance-movie-lens_0 Finish Time: Tue Feb 25 22:41:03 2025 Epoch Time (ms): 1740523263000