renaissance-movie-lens_0
[2024-09-06T01:43:42.301Z] Running test renaissance-movie-lens_0 ...
[2024-09-06T01:43:42.301Z] ===============================================
[2024-09-06T01:43:42.301Z] renaissance-movie-lens_0 Start Time: Thu Sep 5 18:43:41 2024 Epoch Time (ms): 1725587021667
[2024-09-06T01:43:42.301Z] variation: NoOptions
[2024-09-06T01:43:42.301Z] JVM_OPTIONS:
[2024-09-06T01:43:42.301Z] { \
[2024-09-06T01:43:42.301Z] echo ""; echo "TEST SETUP:"; \
[2024-09-06T01:43:42.301Z] echo "Nothing to be done for setup."; \
[2024-09-06T01:43:42.301Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17255853141760/renaissance-movie-lens_0"; \
[2024-09-06T01:43:42.301Z] cd "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17255853141760/renaissance-movie-lens_0"; \
[2024-09-06T01:43:42.301Z] echo ""; echo "TESTING:"; \
[2024-09-06T01:43:42.301Z] "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" -jar "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17255853141760/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-06T01:43:42.301Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17255853141760/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-06T01:43:42.301Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-06T01:43:42.301Z] echo "Nothing to be done for teardown."; \
[2024-09-06T01:43:42.301Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk8_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17255853141760/TestTargetResult";
[2024-09-06T01:43:42.301Z]
[2024-09-06T01:43:42.301Z] TEST SETUP:
[2024-09-06T01:43:42.301Z] Nothing to be done for setup.
[2024-09-06T01:43:42.301Z]
[2024-09-06T01:43:42.301Z] TESTING:
[2024-09-06T01:43:49.289Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-06T01:43:52.807Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-09-06T01:43:59.834Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-06T01:44:00.265Z] Training: 60056, validation: 20285, test: 19854
[2024-09-06T01:44:00.265Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-06T01:44:00.725Z] GC before operation: completed in 307.205 ms, heap usage 80.977 MB -> 25.882 MB.
[2024-09-06T01:44:16.078Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:44:25.176Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:44:34.000Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:44:41.250Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:44:46.965Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:44:52.099Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:44:56.853Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:45:00.691Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:45:00.691Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:45:01.174Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:45:01.174Z] Movies recommended for you:
[2024-09-06T01:45:01.174Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:45:01.174Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:45:01.174Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (60696.110 ms) ======
[2024-09-06T01:45:01.174Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-06T01:45:01.679Z] GC before operation: completed in 426.374 ms, heap usage 967.222 MB -> 47.862 MB.
[2024-09-06T01:45:10.349Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:45:17.586Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:45:25.846Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:45:35.761Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:45:38.708Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:45:44.168Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:45:49.630Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:45:55.232Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:45:55.232Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:45:55.232Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:45:55.232Z] Movies recommended for you:
[2024-09-06T01:45:55.232Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:45:55.232Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:45:55.232Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (53767.780 ms) ======
[2024-09-06T01:45:55.232Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-06T01:45:55.640Z] GC before operation: completed in 225.108 ms, heap usage 1.018 GB -> 49.171 MB.
[2024-09-06T01:46:05.850Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:46:14.094Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:46:22.412Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:46:30.690Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:46:34.425Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:46:39.953Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:46:45.375Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:46:50.974Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:46:50.974Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:46:50.974Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:46:51.427Z] Movies recommended for you:
[2024-09-06T01:46:51.427Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:46:51.427Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:46:51.427Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (55593.299 ms) ======
[2024-09-06T01:46:51.427Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-06T01:46:51.427Z] GC before operation: completed in 221.533 ms, heap usage 899.235 MB -> 47.372 MB.
[2024-09-06T01:46:59.672Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:47:09.573Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:47:16.677Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:47:25.343Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:47:30.011Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:47:34.692Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:47:41.455Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:47:45.451Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:47:46.346Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:47:46.346Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:47:46.346Z] Movies recommended for you:
[2024-09-06T01:47:46.346Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:47:46.346Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:47:46.346Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (54969.938 ms) ======
[2024-09-06T01:47:46.346Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-06T01:47:46.830Z] GC before operation: completed in 215.671 ms, heap usage 881.739 MB -> 47.361 MB.
[2024-09-06T01:47:54.869Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:48:05.031Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:48:11.868Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:48:20.295Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:48:25.024Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:48:29.477Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:48:34.360Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:48:39.846Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:48:39.846Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526.
[2024-09-06T01:48:40.278Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:48:40.278Z] Movies recommended for you:
[2024-09-06T01:48:40.278Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:48:40.278Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:48:40.278Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (53557.323 ms) ======
[2024-09-06T01:48:40.278Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-06T01:48:40.716Z] GC before operation: completed in 281.806 ms, heap usage 878.577 MB -> 48.089 MB.
[2024-09-06T01:48:50.818Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:48:56.621Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:49:08.941Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:49:17.425Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:49:21.071Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:49:26.563Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:49:31.104Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:49:36.702Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:49:37.625Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:49:37.625Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:49:37.625Z] Movies recommended for you:
[2024-09-06T01:49:37.625Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:49:37.625Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:49:37.625Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (57043.604 ms) ======
[2024-09-06T01:49:37.625Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-06T01:49:38.061Z] GC before operation: completed in 246.852 ms, heap usage 859.363 MB -> 47.510 MB.
[2024-09-06T01:49:46.520Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:49:54.731Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:50:02.975Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:50:11.272Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:50:16.938Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:50:21.521Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:50:26.096Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:50:30.604Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:50:31.081Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:50:31.081Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:50:31.081Z] Movies recommended for you:
[2024-09-06T01:50:31.081Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:50:31.081Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:50:31.081Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (53262.225 ms) ======
[2024-09-06T01:50:31.081Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-06T01:50:31.503Z] GC before operation: completed in 245.465 ms, heap usage 846.819 MB -> 47.649 MB.
[2024-09-06T01:50:39.833Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:50:48.283Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:50:56.730Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:51:05.415Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:51:09.072Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:51:14.572Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:51:18.863Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:51:23.605Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:51:24.019Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:51:24.019Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:51:24.497Z] Movies recommended for you:
[2024-09-06T01:51:24.497Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:51:24.497Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:51:24.497Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (52969.471 ms) ======
[2024-09-06T01:51:24.497Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-06T01:51:24.497Z] GC before operation: completed in 332.613 ms, heap usage 857.203 MB -> 47.993 MB.
[2024-09-06T01:51:32.951Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:51:40.001Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:51:48.240Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:51:56.394Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:51:59.841Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:52:04.513Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:52:08.511Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:52:14.122Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:52:14.122Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:52:14.122Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:52:14.529Z] Movies recommended for you:
[2024-09-06T01:52:14.529Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:52:14.529Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:52:14.529Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (49746.541 ms) ======
[2024-09-06T01:52:14.529Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-06T01:52:14.947Z] GC before operation: completed in 272.891 ms, heap usage 849.707 MB -> 47.746 MB.
[2024-09-06T01:52:23.100Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:52:30.197Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:52:38.342Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:52:45.264Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:52:49.841Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:52:54.434Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:52:59.987Z] RMSE (validation) = 0.9259652471505186 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:53:04.511Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:53:04.511Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526.
[2024-09-06T01:53:04.511Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:53:05.053Z] Movies recommended for you:
[2024-09-06T01:53:05.053Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:53:05.053Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:53:05.053Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (50221.594 ms) ======
[2024-09-06T01:53:05.053Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-06T01:53:05.053Z] GC before operation: completed in 235.336 ms, heap usage 859.433 MB -> 47.936 MB.
[2024-09-06T01:53:12.156Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:53:22.536Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:53:28.117Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:53:36.735Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:53:40.347Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:53:45.943Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:53:51.544Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:53:56.074Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:53:56.642Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:53:56.642Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:53:56.642Z] Movies recommended for you:
[2024-09-06T01:53:56.642Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:53:56.642Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:53:56.642Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (51436.821 ms) ======
[2024-09-06T01:53:56.642Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-06T01:53:57.113Z] GC before operation: completed in 364.931 ms, heap usage 849.655 MB -> 47.543 MB.
[2024-09-06T01:54:04.019Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:54:12.378Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:54:21.000Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:54:29.745Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:54:31.831Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:54:37.415Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:54:41.947Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:54:45.640Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:54:45.640Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:54:46.075Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:54:46.530Z] Movies recommended for you:
[2024-09-06T01:54:46.530Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:54:46.530Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:54:46.530Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (49397.830 ms) ======
[2024-09-06T01:54:46.530Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-06T01:54:46.530Z] GC before operation: completed in 232.506 ms, heap usage 859.080 MB -> 47.826 MB.
[2024-09-06T01:54:54.687Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:55:00.291Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:55:08.802Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:55:15.781Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:55:20.214Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:55:24.711Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:55:30.362Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:55:34.768Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:55:35.211Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:55:35.654Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:55:36.095Z] Movies recommended for you:
[2024-09-06T01:55:36.095Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:55:36.095Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:55:36.095Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (49097.999 ms) ======
[2024-09-06T01:55:36.095Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-06T01:55:36.095Z] GC before operation: completed in 243.750 ms, heap usage 856.870 MB -> 48.026 MB.
[2024-09-06T01:55:43.189Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:55:51.641Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:55:59.990Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:56:07.142Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:56:11.642Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:56:17.296Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:56:21.820Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:56:25.384Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:56:26.259Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:56:26.259Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:56:26.706Z] Movies recommended for you:
[2024-09-06T01:56:26.706Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:56:26.706Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:56:26.706Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (50760.883 ms) ======
[2024-09-06T01:56:26.706Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-06T01:56:26.706Z] GC before operation: completed in 234.524 ms, heap usage 857.669 MB -> 47.717 MB.
[2024-09-06T01:56:35.148Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:56:41.917Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:56:50.246Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:56:57.135Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:57:00.715Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:57:04.413Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:57:08.922Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:57:14.632Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:57:15.060Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:57:15.060Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:57:15.060Z] Movies recommended for you:
[2024-09-06T01:57:15.060Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:57:15.060Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:57:15.060Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (48342.932 ms) ======
[2024-09-06T01:57:15.060Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-06T01:57:15.482Z] GC before operation: completed in 266.559 ms, heap usage 838.408 MB -> 47.833 MB.
[2024-09-06T01:57:23.795Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:57:30.954Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:57:39.333Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:57:45.018Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:57:49.539Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:57:53.966Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:57:59.760Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:58:03.326Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:58:03.796Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:58:03.796Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:58:04.248Z] Movies recommended for you:
[2024-09-06T01:58:04.248Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:58:04.248Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:58:04.248Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (48789.879 ms) ======
[2024-09-06T01:58:04.248Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-06T01:58:04.765Z] GC before operation: completed in 287.345 ms, heap usage 849.273 MB -> 47.987 MB.
[2024-09-06T01:58:13.090Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:58:21.359Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:58:29.541Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:58:36.405Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:58:40.040Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:58:44.573Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:58:49.010Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:58:53.668Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:58:54.086Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:58:54.086Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:58:54.086Z] Movies recommended for you:
[2024-09-06T01:58:54.086Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:58:54.086Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:58:54.086Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (49655.645 ms) ======
[2024-09-06T01:58:54.086Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-06T01:58:54.553Z] GC before operation: completed in 189.251 ms, heap usage 852.215 MB -> 47.845 MB.
[2024-09-06T01:59:02.776Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T01:59:11.072Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T01:59:18.075Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T01:59:26.637Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T01:59:30.181Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T01:59:34.646Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T01:59:39.133Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T01:59:43.567Z] RMSE (validation) = 0.8982232235186749 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T01:59:44.592Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328525.
[2024-09-06T01:59:44.592Z] The best model improves the baseline by 14.52%.
[2024-09-06T01:59:44.592Z] Movies recommended for you:
[2024-09-06T01:59:44.592Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T01:59:44.592Z] There is no way to check that no silent failure occurred.
[2024-09-06T01:59:44.592Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (50219.705 ms) ======
[2024-09-06T01:59:44.592Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-06T01:59:45.096Z] GC before operation: completed in 282.893 ms, heap usage 857.902 MB -> 47.902 MB.
[2024-09-06T01:59:53.242Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T02:00:01.607Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T02:00:08.715Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T02:00:17.090Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T02:00:20.689Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T02:00:25.277Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T02:00:29.756Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T02:00:34.224Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T02:00:34.647Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526.
[2024-09-06T02:00:34.647Z] The best model improves the baseline by 14.52%.
[2024-09-06T02:00:34.647Z] Movies recommended for you:
[2024-09-06T02:00:34.647Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T02:00:34.647Z] There is no way to check that no silent failure occurred.
[2024-09-06T02:00:34.647Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (49755.550 ms) ======
[2024-09-06T02:00:34.647Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-06T02:00:35.069Z] GC before operation: completed in 267.993 ms, heap usage 862.935 MB -> 48.149 MB.
[2024-09-06T02:00:42.158Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-06T02:00:50.524Z] RMSE (validation) = 2.134092320601772 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-06T02:00:58.946Z] RMSE (validation) = 1.3105190423866764 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-06T02:01:05.655Z] RMSE (validation) = 0.9920028102937645 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-06T02:01:09.348Z] RMSE (validation) = 1.212631717986921 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-06T02:01:13.724Z] RMSE (validation) = 1.1025694069785972 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-06T02:01:19.160Z] RMSE (validation) = 0.9259652471505185 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-06T02:01:23.650Z] RMSE (validation) = 0.8982232235186748 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-06T02:01:24.055Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003124328526.
[2024-09-06T02:01:24.055Z] The best model improves the baseline by 14.52%.
[2024-09-06T02:01:24.485Z] Movies recommended for you:
[2024-09-06T02:01:24.485Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-06T02:01:24.485Z] There is no way to check that no silent failure occurred.
[2024-09-06T02:01:24.485Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (49420.149 ms) ======
[2024-09-06T02:01:25.981Z] -----------------------------------
[2024-09-06T02:01:25.981Z] renaissance-movie-lens_0_PASSED
[2024-09-06T02:01:25.981Z] -----------------------------------
[2024-09-06T02:01:25.981Z]
[2024-09-06T02:01:25.981Z] TEST TEARDOWN:
[2024-09-06T02:01:25.981Z] Nothing to be done for teardown.
[2024-09-06T02:01:25.981Z] renaissance-movie-lens_0 Finish Time: Thu Sep 5 19:01:25 2024 Epoch Time (ms): 1725588085383