renaissance-movie-lens_0
[2025-06-11T21:11:43.419Z] Running test renaissance-movie-lens_0 ...
[2025-06-11T21:11:43.419Z] ===============================================
[2025-06-11T21:11:43.419Z] renaissance-movie-lens_0 Start Time: Wed Jun 11 17:11:43 2025 Epoch Time (ms): 1749676303153
[2025-06-11T21:11:43.419Z] variation: NoOptions
[2025-06-11T21:11:43.419Z] JVM_OPTIONS:
[2025-06-11T21:11:43.419Z] { \
[2025-06-11T21:11:43.419Z] echo ""; echo "TEST SETUP:"; \
[2025-06-11T21:11:43.419Z] echo "Nothing to be done for setup."; \
[2025-06-11T21:11:43.419Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17496757656972/renaissance-movie-lens_0"; \
[2025-06-11T21:11:43.419Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17496757656972/renaissance-movie-lens_0"; \
[2025-06-11T21:11:43.419Z] echo ""; echo "TESTING:"; \
[2025-06-11T21:11:43.419Z] "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_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_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17496757656972/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-06-11T21:11:43.419Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17496757656972/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-06-11T21:11:43.419Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-06-11T21:11:43.419Z] echo "Nothing to be done for teardown."; \
[2025-06-11T21:11:43.419Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17496757656972/TestTargetResult";
[2025-06-11T21:11:43.419Z]
[2025-06-11T21:11:43.419Z] TEST SETUP:
[2025-06-11T21:11:43.419Z] Nothing to be done for setup.
[2025-06-11T21:11:43.419Z]
[2025-06-11T21:11:43.419Z] TESTING:
[2025-06-11T21:11:47.412Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2025-06-11T21:11:50.501Z] 17:11:49.838 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1866 KiB). The maximum recommended task size is 1000 KiB.
[2025-06-11T21:11:51.297Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-06-11T21:11:51.682Z] Training: 60056, validation: 20285, test: 19854
[2025-06-11T21:11:51.682Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-06-11T21:11:51.682Z] GC before operation: completed in 55.835 ms, heap usage 100.600 MB -> 75.568 MB.
[2025-06-11T21:11:56.688Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:11:59.105Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:12:00.890Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:12:02.698Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:12:03.981Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:12:04.768Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:12:05.537Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:12:06.787Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:12:06.787Z] 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.
[2025-06-11T21:12:06.787Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:12:06.787Z] Top recommended movies for user id 72:
[2025-06-11T21:12:06.787Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:12:06.787Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:12:06.787Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:12:06.787Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:12:06.787Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:12:06.787Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (15172.815 ms) ======
[2025-06-11T21:12:06.787Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-06-11T21:12:07.138Z] GC before operation: completed in 50.854 ms, heap usage 472.216 MB -> 96.141 MB.
[2025-06-11T21:12:08.920Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:12:10.686Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:12:12.480Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:12:13.687Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:12:14.451Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:12:15.691Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:12:16.458Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:12:17.222Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:12:17.222Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T21:12:17.222Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:12:17.574Z] Top recommended movies for user id 72:
[2025-06-11T21:12:17.574Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:12:17.574Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:12:17.574Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:12:17.574Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:12:17.574Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:12:17.574Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (10420.613 ms) ======
[2025-06-11T21:12:17.574Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-06-11T21:12:17.574Z] GC before operation: completed in 44.737 ms, heap usage 167.484 MB -> 89.989 MB.
[2025-06-11T21:12:18.820Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:12:20.595Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:12:21.837Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:12:23.598Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:12:24.363Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:12:25.626Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:12:26.396Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:12:27.150Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:12:27.611Z] 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.
[2025-06-11T21:12:27.611Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:12:27.611Z] Top recommended movies for user id 72:
[2025-06-11T21:12:27.611Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:12:27.611Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:12:27.611Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:12:27.611Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:12:27.611Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:12:27.611Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (10044.987 ms) ======
[2025-06-11T21:12:27.611Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-06-11T21:12:27.611Z] GC before operation: completed in 88.048 ms, heap usage 123.675 MB -> 91.677 MB.
[2025-06-11T21:12:29.375Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:12:31.171Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:12:32.397Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:12:34.166Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:12:34.945Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:12:36.185Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:12:36.950Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:12:38.185Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:12:38.185Z] 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.
[2025-06-11T21:12:38.185Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:12:38.542Z] Top recommended movies for user id 72:
[2025-06-11T21:12:38.542Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:12:38.542Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:12:38.542Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:12:38.542Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:12:38.542Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:12:38.542Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (10806.482 ms) ======
[2025-06-11T21:12:38.542Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-06-11T21:12:38.542Z] GC before operation: completed in 76.150 ms, heap usage 244.413 MB -> 89.152 MB.
[2025-06-11T21:12:40.335Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:12:41.558Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:12:45.589Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:12:45.589Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:12:45.589Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:12:46.853Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:12:47.632Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:12:48.462Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:12:48.462Z] 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.
[2025-06-11T21:12:48.819Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:12:48.819Z] Top recommended movies for user id 72:
[2025-06-11T21:12:48.819Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:12:48.819Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:12:48.819Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:12:48.819Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:12:48.819Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:12:48.819Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (10251.492 ms) ======
[2025-06-11T21:12:48.819Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-06-11T21:12:48.819Z] GC before operation: completed in 60.127 ms, heap usage 396.911 MB -> 89.203 MB.
[2025-06-11T21:12:50.573Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:12:51.801Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:12:53.557Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:12:54.799Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:12:56.039Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:12:56.795Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:12:57.590Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:12:58.360Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:12:58.721Z] 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.
[2025-06-11T21:12:58.721Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:12:58.721Z] Top recommended movies for user id 72:
[2025-06-11T21:12:58.721Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:12:58.721Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:12:58.721Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:12:58.721Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:12:58.721Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:12:58.721Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (9976.657 ms) ======
[2025-06-11T21:12:58.721Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-06-11T21:12:58.721Z] GC before operation: completed in 68.361 ms, heap usage 254.448 MB -> 89.375 MB.
[2025-06-11T21:13:00.509Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:13:01.760Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:13:03.037Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:13:04.874Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:13:05.239Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:13:06.026Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:13:06.788Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:13:08.018Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:13:08.018Z] 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.
[2025-06-11T21:13:08.018Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:13:08.018Z] Top recommended movies for user id 72:
[2025-06-11T21:13:08.018Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:13:08.018Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:13:08.018Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:13:08.018Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:13:08.018Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:13:08.018Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (9230.123 ms) ======
[2025-06-11T21:13:08.018Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-06-11T21:13:08.018Z] GC before operation: completed in 60.837 ms, heap usage 284.973 MB -> 90.706 MB.
[2025-06-11T21:13:09.281Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:13:10.619Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:13:11.842Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:13:13.059Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:13:13.833Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:13:14.599Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:13:15.369Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:13:16.137Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:13:16.137Z] 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.
[2025-06-11T21:13:16.489Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:13:16.489Z] Top recommended movies for user id 72:
[2025-06-11T21:13:16.489Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:13:16.489Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:13:16.489Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:13:16.489Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:13:16.489Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:13:16.489Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (8251.389 ms) ======
[2025-06-11T21:13:16.489Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-06-11T21:13:16.489Z] GC before operation: completed in 51.786 ms, heap usage 250.594 MB -> 89.697 MB.
[2025-06-11T21:13:17.727Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:13:18.952Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:13:20.714Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:13:21.469Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:13:22.239Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:13:23.003Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:13:23.762Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:13:24.524Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:13:24.524Z] 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.
[2025-06-11T21:13:24.524Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:13:24.524Z] Top recommended movies for user id 72:
[2025-06-11T21:13:24.524Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:13:24.524Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:13:24.524Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:13:24.524Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:13:24.524Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:13:24.524Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8222.861 ms) ======
[2025-06-11T21:13:24.524Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-06-11T21:13:24.880Z] GC before operation: completed in 50.745 ms, heap usage 366.052 MB -> 91.889 MB.
[2025-06-11T21:13:26.107Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:13:27.861Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:13:29.102Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:13:30.334Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:13:31.083Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:13:31.839Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:13:32.609Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:13:33.388Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:13:33.752Z] 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.
[2025-06-11T21:13:33.752Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:13:33.752Z] Top recommended movies for user id 72:
[2025-06-11T21:13:33.752Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:13:33.752Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:13:33.752Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:13:33.752Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:13:33.752Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:13:33.752Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (9028.310 ms) ======
[2025-06-11T21:13:33.752Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-06-11T21:13:33.752Z] GC before operation: completed in 51.434 ms, heap usage 410.624 MB -> 94.513 MB.
[2025-06-11T21:13:34.981Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:13:36.742Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:13:37.529Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:13:38.744Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:13:39.518Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:13:40.282Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:13:41.059Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:13:41.822Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:13:41.822Z] 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.
[2025-06-11T21:13:41.822Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:13:42.177Z] Top recommended movies for user id 72:
[2025-06-11T21:13:42.177Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:13:42.177Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:13:42.177Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:13:42.177Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:13:42.177Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:13:42.177Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (8214.424 ms) ======
[2025-06-11T21:13:42.177Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-06-11T21:13:42.177Z] GC before operation: completed in 49.995 ms, heap usage 123.301 MB -> 90.565 MB.
[2025-06-11T21:13:43.392Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:13:44.667Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:13:45.874Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:13:47.096Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:13:47.871Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:13:48.687Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:13:49.456Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:13:49.810Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:13:50.164Z] 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.
[2025-06-11T21:13:50.164Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:13:50.164Z] Top recommended movies for user id 72:
[2025-06-11T21:13:50.164Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:13:50.164Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:13:50.164Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:13:50.164Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:13:50.164Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:13:50.164Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (8098.154 ms) ======
[2025-06-11T21:13:50.164Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-06-11T21:13:50.164Z] GC before operation: completed in 45.639 ms, heap usage 196.313 MB -> 90.675 MB.
[2025-06-11T21:13:51.376Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:13:53.154Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:13:54.452Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:13:55.684Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:13:56.453Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:13:56.818Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:13:58.083Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:13:58.450Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:13:58.799Z] 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.
[2025-06-11T21:13:58.799Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:13:58.799Z] Top recommended movies for user id 72:
[2025-06-11T21:13:58.799Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:13:58.799Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:13:58.799Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:13:58.799Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:13:58.799Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:13:58.799Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (8591.756 ms) ======
[2025-06-11T21:13:58.799Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-06-11T21:13:58.799Z] GC before operation: completed in 47.103 ms, heap usage 167.158 MB -> 91.301 MB.
[2025-06-11T21:14:00.060Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:14:01.309Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:14:02.567Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:14:03.843Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:14:04.694Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:14:05.474Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:14:06.239Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:14:07.001Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:14:07.001Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T21:14:07.001Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:14:07.360Z] Top recommended movies for user id 72:
[2025-06-11T21:14:07.360Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:14:07.360Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:14:07.360Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:14:07.360Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:14:07.360Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:14:07.360Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (8362.547 ms) ======
[2025-06-11T21:14:07.360Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-06-11T21:14:07.360Z] GC before operation: completed in 51.768 ms, heap usage 169.703 MB -> 89.481 MB.
[2025-06-11T21:14:08.585Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:14:10.346Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:14:11.577Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:14:12.327Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:14:13.091Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:14:13.847Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:14:14.599Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:14:15.357Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:14:15.357Z] 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.
[2025-06-11T21:14:15.357Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:14:15.357Z] Top recommended movies for user id 72:
[2025-06-11T21:14:15.357Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:14:15.357Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:14:15.357Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:14:15.357Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:14:15.357Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:14:15.357Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8117.806 ms) ======
[2025-06-11T21:14:15.357Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-06-11T21:14:15.357Z] GC before operation: completed in 57.681 ms, heap usage 223.985 MB -> 89.734 MB.
[2025-06-11T21:14:16.590Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:14:18.348Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:14:19.581Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:14:20.798Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:14:21.564Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:14:22.339Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:14:23.108Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:14:23.876Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:14:24.226Z] 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.
[2025-06-11T21:14:24.226Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:14:24.226Z] Top recommended movies for user id 72:
[2025-06-11T21:14:24.226Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:14:24.226Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:14:24.226Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:14:24.226Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:14:24.226Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:14:24.226Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (8824.503 ms) ======
[2025-06-11T21:14:24.226Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-06-11T21:14:24.226Z] GC before operation: completed in 71.327 ms, heap usage 238.151 MB -> 89.674 MB.
[2025-06-11T21:14:25.981Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:14:27.218Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:14:28.465Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:14:29.692Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:14:30.045Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:14:30.809Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:14:31.564Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:14:32.349Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:14:32.349Z] 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.
[2025-06-11T21:14:32.704Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:14:32.704Z] Top recommended movies for user id 72:
[2025-06-11T21:14:32.704Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:14:32.704Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:14:32.704Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:14:32.704Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:14:32.704Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:14:32.704Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (8271.332 ms) ======
[2025-06-11T21:14:32.704Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-06-11T21:14:32.704Z] GC before operation: completed in 61.849 ms, heap usage 263.222 MB -> 89.708 MB.
[2025-06-11T21:14:34.009Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:14:35.245Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:14:36.498Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:14:38.299Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:14:38.663Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:14:39.437Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:14:40.201Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:14:40.960Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:14:41.312Z] 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.
[2025-06-11T21:14:41.312Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:14:41.312Z] Top recommended movies for user id 72:
[2025-06-11T21:14:41.312Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:14:41.312Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:14:41.313Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:14:41.313Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:14:41.313Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:14:41.313Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8578.627 ms) ======
[2025-06-11T21:14:41.313Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-06-11T21:14:41.313Z] GC before operation: completed in 58.309 ms, heap usage 394.756 MB -> 89.762 MB.
[2025-06-11T21:14:43.069Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:14:44.291Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:14:46.056Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:14:47.291Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:14:48.053Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:14:49.272Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:14:50.031Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:14:50.801Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:14:51.162Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2025-06-11T21:14:51.162Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:14:51.162Z] Top recommended movies for user id 72:
[2025-06-11T21:14:51.162Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:14:51.162Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:14:51.162Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:14:51.162Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:14:51.162Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:14:51.162Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (9824.661 ms) ======
[2025-06-11T21:14:51.162Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-06-11T21:14:51.162Z] GC before operation: completed in 59.217 ms, heap usage 195.782 MB -> 90.766 MB.
[2025-06-11T21:14:52.935Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-06-11T21:14:54.172Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-06-11T21:14:55.945Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-06-11T21:14:57.176Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-06-11T21:14:58.395Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-06-11T21:14:59.163Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-06-11T21:15:00.402Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-06-11T21:15:01.180Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-06-11T21:15:01.180Z] 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.
[2025-06-11T21:15:01.180Z] The best model improves the baseline by 14.52%.
[2025-06-11T21:15:01.180Z] Top recommended movies for user id 72:
[2025-06-11T21:15:01.180Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.677, id: 67504)
[2025-06-11T21:15:01.180Z] 2: Goat, The (1921) (rating: 4.677, id: 83318)
[2025-06-11T21:15:01.180Z] 3: Play House, The (1921) (rating: 4.677, id: 83359)
[2025-06-11T21:15:01.180Z] 4: Cops (1922) (rating: 4.677, id: 83411)
[2025-06-11T21:15:01.180Z] 5: Dear Frankie (2004) (rating: 4.360, id: 8530)
[2025-06-11T21:15:01.180Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (10061.987 ms) ======
[2025-06-11T21:15:01.534Z] -----------------------------------
[2025-06-11T21:15:01.535Z] renaissance-movie-lens_0_PASSED
[2025-06-11T21:15:01.535Z] -----------------------------------
[2025-06-11T21:15:01.535Z]
[2025-06-11T21:15:01.535Z] TEST TEARDOWN:
[2025-06-11T21:15:01.535Z] Nothing to be done for teardown.
[2025-06-11T21:15:01.535Z] renaissance-movie-lens_0 Finish Time: Wed Jun 11 17:15:01 2025 Epoch Time (ms): 1749676501341