renaissance-movie-lens_0
[2025-05-30T01:26:49.883Z] Running test renaissance-movie-lens_0 ...
[2025-05-30T01:26:49.883Z] ===============================================
[2025-05-30T01:26:49.883Z] renaissance-movie-lens_0 Start Time: Thu May 29 18:26:48 2025 Epoch Time (ms): 1748568408765
[2025-05-30T01:26:49.883Z] variation: NoOptions
[2025-05-30T01:26:49.883Z] JVM_OPTIONS:
[2025-05-30T01:26:49.883Z] { \
[2025-05-30T01:26:49.883Z] echo ""; echo "TEST SETUP:"; \
[2025-05-30T01:26:49.883Z] echo "Nothing to be done for setup."; \
[2025-05-30T01:26:49.883Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17485661111589/renaissance-movie-lens_0"; \
[2025-05-30T01:26:49.883Z] cd "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17485661111589/renaissance-movie-lens_0"; \
[2025-05-30T01:26:49.883Z] echo ""; echo "TESTING:"; \
[2025-05-30T01:26:49.883Z] "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17485661111589/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-05-30T01:26:49.883Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17485661111589/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-05-30T01:26:49.883Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-05-30T01:26:49.883Z] echo "Nothing to be done for teardown."; \
[2025-05-30T01:26:49.883Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/../TKG/output_17485661111589/TestTargetResult";
[2025-05-30T01:26:49.883Z]
[2025-05-30T01:26:49.883Z] TEST SETUP:
[2025-05-30T01:26:49.883Z] Nothing to be done for setup.
[2025-05-30T01:26:49.883Z]
[2025-05-30T01:26:49.883Z] TESTING:
[2025-05-30T01:26:51.004Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-05-30T01:26:51.004Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/Users/admin/workspace/workspace/Test_openjdk25_hs_extended.perf_x86-64_mac/aqa-tests/TKG/output_17485661111589/renaissance-movie-lens_0/launcher-182649-6004282492104504564/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-05-30T01:26:51.004Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-05-30T01:26:51.004Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-05-30T01:27:01.206Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2025-05-30T01:27:12.979Z] 18:27:11.942 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB.
[2025-05-30T01:27:18.077Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-05-30T01:27:19.258Z] Training: 60056, validation: 20285, test: 19854
[2025-05-30T01:27:19.258Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-05-30T01:27:19.258Z] GC before operation: completed in 389.620 ms, heap usage 505.451 MB -> 75.564 MB.
[2025-05-30T01:27:37.587Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:27:46.881Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:27:57.654Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:28:05.145Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:28:10.071Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:28:14.916Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:28:18.756Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:28:24.133Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:28:24.617Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:28:25.128Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:28:25.128Z] Top recommended movies for user id 72:
[2025-05-30T01:28:25.128Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:28:25.128Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:28:25.128Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:28:25.128Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:28:25.128Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:28:25.128Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (65786.790 ms) ======
[2025-05-30T01:28:25.128Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-05-30T01:28:25.611Z] GC before operation: completed in 292.432 ms, heap usage 453.967 MB -> 88.255 MB.
[2025-05-30T01:28:33.148Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:28:45.775Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:28:52.876Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:29:01.602Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:29:06.441Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:29:11.306Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:29:17.330Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:29:22.114Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:29:22.625Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:29:22.625Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:29:23.173Z] Top recommended movies for user id 72:
[2025-05-30T01:29:23.173Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:29:23.173Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:29:23.173Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:29:23.173Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:29:23.173Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:29:23.173Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (57348.129 ms) ======
[2025-05-30T01:29:23.173Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-05-30T01:29:23.173Z] GC before operation: completed in 317.542 ms, heap usage 572.738 MB -> 91.738 MB.
[2025-05-30T01:29:32.047Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:29:40.661Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:29:49.659Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:29:58.170Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:30:04.373Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:30:09.123Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:30:13.879Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:30:18.663Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:30:19.085Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:30:19.085Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:30:19.579Z] Top recommended movies for user id 72:
[2025-05-30T01:30:19.579Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:30:19.579Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:30:19.579Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:30:19.579Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:30:19.579Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:30:19.579Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (56180.425 ms) ======
[2025-05-30T01:30:19.579Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-05-30T01:30:19.579Z] GC before operation: completed in 193.594 ms, heap usage 205.249 MB -> 88.560 MB.
[2025-05-30T01:30:28.657Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:30:35.703Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:30:44.374Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:30:53.046Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:30:56.773Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:31:01.597Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:31:07.627Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:31:12.511Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:31:12.511Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:31:12.511Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:31:13.059Z] Top recommended movies for user id 72:
[2025-05-30T01:31:13.059Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:31:13.059Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:31:13.059Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:31:13.059Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:31:13.059Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:31:13.059Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (53254.201 ms) ======
[2025-05-30T01:31:13.059Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-05-30T01:31:13.059Z] GC before operation: completed in 345.373 ms, heap usage 562.549 MB -> 92.727 MB.
[2025-05-30T01:31:21.672Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:31:30.477Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:31:39.083Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:31:46.176Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:31:49.975Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:31:54.783Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:31:59.551Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:32:05.448Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:32:05.448Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:32:05.955Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:32:05.955Z] Top recommended movies for user id 72:
[2025-05-30T01:32:05.955Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:32:05.955Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:32:05.955Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:32:05.955Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:32:05.955Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:32:05.955Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (52808.908 ms) ======
[2025-05-30T01:32:05.955Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-05-30T01:32:06.436Z] GC before operation: completed in 242.459 ms, heap usage 740.655 MB -> 93.198 MB.
[2025-05-30T01:32:17.132Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:32:26.013Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:32:31.973Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:32:39.214Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:32:44.001Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:32:48.725Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:32:53.505Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:32:57.443Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:32:58.438Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:32:58.438Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:32:58.438Z] Top recommended movies for user id 72:
[2025-05-30T01:32:58.439Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:32:58.439Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:32:58.439Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:32:58.439Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:32:58.439Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:32:58.439Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (52379.589 ms) ======
[2025-05-30T01:32:58.439Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-05-30T01:32:59.463Z] GC before operation: completed in 310.004 ms, heap usage 448.887 MB -> 89.592 MB.
[2025-05-30T01:33:09.803Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:33:16.898Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:33:27.566Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:33:33.561Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:33:39.593Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:33:43.486Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:33:48.274Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:33:54.047Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:33:54.047Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:33:54.047Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:33:54.491Z] Top recommended movies for user id 72:
[2025-05-30T01:33:54.491Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:33:54.491Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:33:54.491Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:33:54.491Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:33:54.491Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:33:54.491Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55462.434 ms) ======
[2025-05-30T01:33:54.491Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-05-30T01:33:54.966Z] GC before operation: completed in 281.638 ms, heap usage 861.267 MB -> 93.874 MB.
[2025-05-30T01:34:03.562Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:34:10.474Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:34:19.025Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:34:27.722Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:34:32.486Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:34:37.210Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:34:41.225Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:34:46.140Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:34:46.609Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:34:46.609Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:34:47.063Z] Top recommended movies for user id 72:
[2025-05-30T01:34:47.063Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:34:47.063Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:34:47.063Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:34:47.063Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:34:47.063Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:34:47.063Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (52214.649 ms) ======
[2025-05-30T01:34:47.063Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-05-30T01:34:47.063Z] GC before operation: completed in 238.035 ms, heap usage 490.165 MB -> 89.819 MB.
[2025-05-30T01:34:54.194Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:35:03.221Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:35:10.144Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:35:17.187Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:35:22.117Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:35:25.944Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:35:29.693Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:35:34.369Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:35:35.322Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:35:35.322Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:35:35.826Z] Top recommended movies for user id 72:
[2025-05-30T01:35:35.826Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:35:35.826Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:35:35.826Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:35:35.826Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:35:35.826Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:35:35.826Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (48572.852 ms) ======
[2025-05-30T01:35:35.826Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-05-30T01:35:35.826Z] GC before operation: completed in 273.525 ms, heap usage 281.345 MB -> 89.390 MB.
[2025-05-30T01:35:44.186Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:35:52.686Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:35:59.847Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:36:07.154Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:36:12.025Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:36:15.809Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:36:20.605Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:36:24.511Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:36:24.511Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:36:24.511Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:36:25.019Z] Top recommended movies for user id 72:
[2025-05-30T01:36:25.020Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:36:25.020Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:36:25.020Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:36:25.020Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:36:25.020Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:36:25.020Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (48987.510 ms) ======
[2025-05-30T01:36:25.020Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-05-30T01:36:25.491Z] GC before operation: completed in 218.190 ms, heap usage 424.106 MB -> 89.838 MB.
[2025-05-30T01:36:34.100Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:36:41.080Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:36:48.269Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:36:55.301Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:37:00.052Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:37:06.135Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:37:09.973Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:37:13.010Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:37:13.502Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:37:13.502Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:37:14.163Z] Top recommended movies for user id 72:
[2025-05-30T01:37:14.163Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:37:14.163Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:37:14.163Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:37:14.163Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:37:14.163Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:37:14.163Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (48762.408 ms) ======
[2025-05-30T01:37:14.163Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-05-30T01:37:14.163Z] GC before operation: completed in 181.368 ms, heap usage 563.452 MB -> 92.925 MB.
[2025-05-30T01:37:22.812Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:37:31.402Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:37:38.291Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:37:45.248Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:37:50.253Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:37:54.025Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:37:59.048Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:38:03.926Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:38:03.926Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:38:04.407Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:38:04.900Z] Top recommended movies for user id 72:
[2025-05-30T01:38:04.900Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:38:04.900Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:38:04.900Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:38:04.900Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:38:04.900Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:38:04.900Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (50574.924 ms) ======
[2025-05-30T01:38:04.900Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-05-30T01:38:04.900Z] GC before operation: completed in 221.345 ms, heap usage 840.731 MB -> 94.034 MB.
[2025-05-30T01:38:13.577Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:38:19.289Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:38:27.585Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:38:34.657Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:38:40.457Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:38:46.129Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:38:50.900Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:38:54.686Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:38:55.637Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:38:55.637Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:38:56.109Z] Top recommended movies for user id 72:
[2025-05-30T01:38:56.110Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:38:56.110Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:38:56.110Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:38:56.110Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:38:56.110Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:38:56.110Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (51118.002 ms) ======
[2025-05-30T01:38:56.110Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-05-30T01:38:56.649Z] GC before operation: completed in 295.601 ms, heap usage 866.358 MB -> 94.393 MB.
[2025-05-30T01:39:05.275Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:39:12.473Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:39:19.481Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:39:26.535Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:39:30.168Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:39:33.941Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:39:38.866Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:39:43.496Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:39:43.496Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:39:43.496Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:39:43.946Z] Top recommended movies for user id 72:
[2025-05-30T01:39:43.946Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:39:43.946Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:39:43.946Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:39:43.946Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:39:43.946Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:39:43.946Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (47714.888 ms) ======
[2025-05-30T01:39:43.946Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-05-30T01:39:44.378Z] GC before operation: completed in 200.989 ms, heap usage 695.656 MB -> 93.245 MB.
[2025-05-30T01:39:52.902Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:40:00.065Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:40:08.698Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:40:14.285Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:40:17.236Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:40:20.868Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:40:24.039Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:40:26.910Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:40:27.348Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:40:27.808Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:40:27.808Z] Top recommended movies for user id 72:
[2025-05-30T01:40:27.808Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:40:27.808Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:40:27.808Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:40:27.808Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:40:27.808Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:40:27.808Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (43733.651 ms) ======
[2025-05-30T01:40:27.808Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-05-30T01:40:28.261Z] GC before operation: completed in 195.902 ms, heap usage 272.601 MB -> 89.660 MB.
[2025-05-30T01:40:35.290Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:40:42.552Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:40:49.536Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:40:56.499Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:41:00.347Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:41:04.166Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:41:10.111Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:41:15.748Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:41:15.748Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:41:15.748Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:41:16.235Z] Top recommended movies for user id 72:
[2025-05-30T01:41:16.235Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:41:16.235Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:41:16.235Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:41:16.235Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:41:16.235Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:41:16.235Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (47956.804 ms) ======
[2025-05-30T01:41:16.235Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-05-30T01:41:16.692Z] GC before operation: completed in 308.955 ms, heap usage 349.844 MB -> 89.635 MB.
[2025-05-30T01:41:25.384Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:41:32.529Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:41:38.374Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:41:46.680Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:41:50.409Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:41:54.069Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:41:59.084Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:42:05.013Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:42:05.479Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:42:05.479Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:42:05.927Z] Top recommended movies for user id 72:
[2025-05-30T01:42:05.927Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:42:05.927Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:42:05.927Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:42:05.927Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:42:05.927Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:42:05.927Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (49537.465 ms) ======
[2025-05-30T01:42:05.927Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-05-30T01:42:06.356Z] GC before operation: completed in 206.956 ms, heap usage 453.194 MB -> 89.909 MB.
[2025-05-30T01:42:15.140Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:42:21.224Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:42:29.763Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:42:38.373Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:42:42.376Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:42:47.225Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:42:51.899Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:42:55.636Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:42:56.674Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:42:56.674Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:42:56.674Z] Top recommended movies for user id 72:
[2025-05-30T01:42:56.674Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:42:56.674Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:42:56.674Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:42:56.674Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:42:56.674Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:42:56.674Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (50507.462 ms) ======
[2025-05-30T01:42:56.674Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-05-30T01:42:57.162Z] GC before operation: completed in 337.894 ms, heap usage 638.690 MB -> 93.313 MB.
[2025-05-30T01:43:05.669Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:43:16.265Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:43:24.911Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:43:29.858Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:43:35.490Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:43:41.391Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:43:45.202Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:43:49.990Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:43:50.435Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:43:50.435Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:43:50.924Z] Top recommended movies for user id 72:
[2025-05-30T01:43:50.924Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:43:50.924Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:43:50.924Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:43:50.924Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:43:50.924Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:43:50.924Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (53815.759 ms) ======
[2025-05-30T01:43:50.924Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-05-30T01:43:51.467Z] GC before operation: completed in 258.210 ms, heap usage 467.602 MB -> 89.988 MB.
[2025-05-30T01:43:59.633Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-30T01:44:07.062Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-30T01:44:16.010Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-30T01:44:23.140Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-30T01:44:27.727Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-30T01:44:32.834Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-30T01:44:37.558Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-30T01:44:43.249Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-30T01:44:43.249Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-05-30T01:44:43.249Z] The best model improves the baseline by 14.52%.
[2025-05-30T01:44:43.672Z] Top recommended movies for user id 72:
[2025-05-30T01:44:43.672Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-05-30T01:44:43.672Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-05-30T01:44:43.672Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-05-30T01:44:43.672Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-05-30T01:44:43.672Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-05-30T01:44:43.672Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (52517.839 ms) ======
[2025-05-30T01:44:45.320Z] -----------------------------------
[2025-05-30T01:44:45.320Z] renaissance-movie-lens_0_PASSED
[2025-05-30T01:44:45.320Z] -----------------------------------
[2025-05-30T01:44:45.320Z]
[2025-05-30T01:44:45.320Z] TEST TEARDOWN:
[2025-05-30T01:44:45.320Z] Nothing to be done for teardown.
[2025-05-30T01:44:45.781Z] renaissance-movie-lens_0 Finish Time: Thu May 29 18:44:44 2025 Epoch Time (ms): 1748569484556