renaissance-movie-lens_0
[2025-09-03T22:23:02.738Z] Running test renaissance-movie-lens_0 ...
[2025-09-03T22:23:02.738Z] ===============================================
[2025-09-03T22:23:02.738Z] renaissance-movie-lens_0 Start Time: Wed Sep 3 22:23:02 2025 Epoch Time (ms): 1756938182510
[2025-09-03T22:23:02.738Z] variation: NoOptions
[2025-09-03T22:23:02.738Z] JVM_OPTIONS:
[2025-09-03T22:23:02.738Z] { \
[2025-09-03T22:23:02.738Z] echo ""; echo "TEST SETUP:"; \
[2025-09-03T22:23:02.738Z] echo "Nothing to be done for setup."; \
[2025-09-03T22:23:02.738Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17569367597953/renaissance-movie-lens_0"; \
[2025-09-03T22:23:02.738Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17569367597953/renaissance-movie-lens_0"; \
[2025-09-03T22:23:02.738Z] echo ""; echo "TESTING:"; \
[2025-09-03T22:23:02.738Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/jdkbinary/j2sdk-image/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 "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17569367597953/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-03T22:23:02.738Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17569367597953/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-03T22:23:02.738Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-03T22:23:02.738Z] echo "Nothing to be done for teardown."; \
[2025-09-03T22:23:02.738Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_ppc64le_linux/aqa-tests/TKG/../TKG/output_17569367597953/TestTargetResult";
[2025-09-03T22:23:02.738Z]
[2025-09-03T22:23:02.738Z] TEST SETUP:
[2025-09-03T22:23:02.738Z] Nothing to be done for setup.
[2025-09-03T22:23:02.738Z]
[2025-09-03T22:23:02.738Z] TESTING:
[2025-09-03T22:23:07.894Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-09-03T22:23:15.985Z] 22:23:14.760 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-03T22:23:17.925Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-03T22:23:17.925Z] Training: 60056, validation: 20285, test: 19854
[2025-09-03T22:23:17.925Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-03T22:23:17.925Z] GC before operation: completed in 159.912 ms, heap usage 332.088 MB -> 75.970 MB.
[2025-09-03T22:23:24.714Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:23:27.708Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:23:30.702Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:23:33.697Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:23:35.635Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:23:36.580Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:23:38.518Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:23:40.457Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:23:40.457Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:23:40.457Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:23:40.457Z] Top recommended movies for user id 72:
[2025-09-03T22:23:40.457Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:23:40.457Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:23:40.457Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:23:40.457Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:23:40.457Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:23:40.457Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (22720.953 ms) ======
[2025-09-03T22:23:40.457Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-03T22:23:41.399Z] GC before operation: completed in 160.858 ms, heap usage 388.912 MB -> 96.603 MB.
[2025-09-03T22:23:43.339Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:23:46.337Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:23:49.330Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:23:51.268Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:23:53.206Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:23:55.144Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:23:56.088Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:23:58.025Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:23:58.025Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:23:58.025Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:23:58.972Z] Top recommended movies for user id 72:
[2025-09-03T22:23:58.972Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:23:58.972Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:23:58.972Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:23:58.972Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:23:58.972Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:23:58.972Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17608.614 ms) ======
[2025-09-03T22:23:58.972Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-03T22:23:58.972Z] GC before operation: completed in 147.660 ms, heap usage 392.971 MB -> 88.976 MB.
[2025-09-03T22:24:00.912Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:24:03.894Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:24:06.885Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:24:08.828Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:24:10.767Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:24:12.707Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:24:13.651Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:24:15.594Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:24:15.594Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:24:15.594Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:24:16.543Z] Top recommended movies for user id 72:
[2025-09-03T22:24:16.543Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:24:16.543Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:24:16.543Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:24:16.543Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:24:16.543Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:24:16.543Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17367.176 ms) ======
[2025-09-03T22:24:16.543Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-03T22:24:16.543Z] GC before operation: completed in 124.543 ms, heap usage 154.929 MB -> 89.336 MB.
[2025-09-03T22:24:18.480Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:24:21.644Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:24:23.747Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:24:25.684Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:24:27.621Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:24:28.567Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:24:30.515Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:24:31.463Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:24:32.406Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:24:32.407Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:24:32.407Z] Top recommended movies for user id 72:
[2025-09-03T22:24:32.407Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:24:32.407Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:24:32.407Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:24:32.407Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:24:32.407Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:24:32.407Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (15966.939 ms) ======
[2025-09-03T22:24:32.407Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-03T22:24:32.407Z] GC before operation: completed in 214.894 ms, heap usage 368.333 MB -> 89.908 MB.
[2025-09-03T22:24:35.401Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:24:37.339Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:24:39.285Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:24:42.278Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:24:43.222Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:24:45.166Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:24:47.109Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:24:48.051Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:24:48.051Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:24:48.051Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:24:49.007Z] Top recommended movies for user id 72:
[2025-09-03T22:24:49.007Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:24:49.007Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:24:49.007Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:24:49.007Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:24:49.007Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:24:49.007Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16172.553 ms) ======
[2025-09-03T22:24:49.007Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-03T22:24:49.007Z] GC before operation: completed in 156.765 ms, heap usage 294.191 MB -> 89.866 MB.
[2025-09-03T22:24:50.947Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:24:53.935Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:24:55.873Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:24:58.548Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:25:00.498Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:25:01.441Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:25:03.378Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:25:05.316Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:25:05.316Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:25:05.316Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:25:05.316Z] Top recommended movies for user id 72:
[2025-09-03T22:25:05.316Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:25:05.316Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:25:05.316Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:25:05.316Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:25:05.316Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:25:05.316Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16546.147 ms) ======
[2025-09-03T22:25:05.316Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-03T22:25:05.316Z] GC before operation: completed in 134.278 ms, heap usage 370.607 MB -> 90.206 MB.
[2025-09-03T22:25:07.253Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:25:10.265Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:25:12.203Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:25:14.144Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:25:16.083Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:25:17.030Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:25:18.970Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:25:20.911Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:25:20.911Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:25:20.911Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:25:20.911Z] Top recommended movies for user id 72:
[2025-09-03T22:25:20.911Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:25:20.911Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:25:20.911Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:25:20.911Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:25:20.911Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:25:20.911Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15635.966 ms) ======
[2025-09-03T22:25:20.911Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-03T22:25:20.911Z] GC before operation: completed in 146.065 ms, heap usage 373.943 MB -> 90.175 MB.
[2025-09-03T22:25:23.940Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:25:25.880Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:25:28.877Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:25:30.817Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:25:32.789Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:25:33.735Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:25:35.670Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:25:37.614Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:25:37.614Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:25:37.614Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:25:37.614Z] Top recommended movies for user id 72:
[2025-09-03T22:25:37.614Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:25:37.614Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:25:37.614Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:25:37.614Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:25:37.614Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:25:37.614Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (16298.718 ms) ======
[2025-09-03T22:25:37.614Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-03T22:25:37.614Z] GC before operation: completed in 131.075 ms, heap usage 424.208 MB -> 90.407 MB.
[2025-09-03T22:25:39.554Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:25:42.545Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:25:44.485Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:25:47.481Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:25:48.426Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:25:51.238Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:25:52.385Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:25:53.329Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:25:53.329Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:25:53.329Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:25:53.329Z] Top recommended movies for user id 72:
[2025-09-03T22:25:53.329Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:25:53.329Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:25:53.329Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:25:53.329Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:25:53.329Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:25:53.329Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15841.287 ms) ======
[2025-09-03T22:25:53.329Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-03T22:25:53.329Z] GC before operation: completed in 132.440 ms, heap usage 401.622 MB -> 90.283 MB.
[2025-09-03T22:25:56.324Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:25:58.271Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:26:01.264Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:26:03.204Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:26:04.147Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:26:06.088Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:26:08.033Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:26:08.981Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:26:08.981Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:26:08.981Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:26:09.927Z] Top recommended movies for user id 72:
[2025-09-03T22:26:09.927Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:26:09.927Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:26:09.927Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:26:09.927Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:26:09.927Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:26:09.927Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15902.860 ms) ======
[2025-09-03T22:26:09.927Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-03T22:26:09.927Z] GC before operation: completed in 166.821 ms, heap usage 371.079 MB -> 90.504 MB.
[2025-09-03T22:26:11.866Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:26:13.805Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:26:16.801Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:26:18.741Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:26:20.679Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:26:21.624Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:26:23.745Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:26:24.688Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:26:24.688Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:26:24.688Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:26:25.631Z] Top recommended movies for user id 72:
[2025-09-03T22:26:25.631Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:26:25.631Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:26:25.631Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:26:25.631Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:26:25.631Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:26:25.631Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15510.066 ms) ======
[2025-09-03T22:26:25.631Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-03T22:26:25.631Z] GC before operation: completed in 165.024 ms, heap usage 372.908 MB -> 90.220 MB.
[2025-09-03T22:26:27.577Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:26:30.570Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:26:32.521Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:26:35.516Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:26:36.461Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:26:38.399Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:26:39.349Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:26:41.290Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:26:41.290Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:26:41.290Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:26:41.290Z] Top recommended movies for user id 72:
[2025-09-03T22:26:41.290Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:26:41.290Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:26:41.290Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:26:41.290Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:26:41.290Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:26:41.290Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16209.336 ms) ======
[2025-09-03T22:26:41.290Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-03T22:26:42.235Z] GC before operation: completed in 140.496 ms, heap usage 180.446 MB -> 90.154 MB.
[2025-09-03T22:26:44.191Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:26:46.099Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:26:49.089Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:26:51.030Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:26:51.974Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:26:53.913Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:26:54.856Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:26:56.801Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:26:56.801Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:26:56.801Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:26:56.801Z] Top recommended movies for user id 72:
[2025-09-03T22:26:56.801Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:26:56.801Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:26:56.801Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:26:56.801Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:26:56.801Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:26:56.801Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15317.392 ms) ======
[2025-09-03T22:26:56.801Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-03T22:26:56.801Z] GC before operation: completed in 128.875 ms, heap usage 145.140 MB -> 90.208 MB.
[2025-09-03T22:26:59.798Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:27:01.737Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:27:04.729Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:27:06.669Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:27:07.611Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:27:09.547Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:27:10.491Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:27:12.430Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:27:12.430Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:27:12.430Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:27:12.430Z] Top recommended movies for user id 72:
[2025-09-03T22:27:12.430Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:27:12.430Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:27:12.430Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:27:12.430Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:27:12.430Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:27:12.430Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15451.226 ms) ======
[2025-09-03T22:27:12.430Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-03T22:27:12.430Z] GC before operation: completed in 132.002 ms, heap usage 129.795 MB -> 89.997 MB.
[2025-09-03T22:27:15.422Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:27:17.427Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:27:19.365Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:27:22.364Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:27:23.308Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:27:25.341Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:27:26.286Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:27:28.226Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:27:28.226Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:27:28.226Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:27:28.226Z] Top recommended movies for user id 72:
[2025-09-03T22:27:28.226Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:27:28.226Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:27:28.226Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:27:28.226Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:27:28.226Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:27:28.226Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15638.378 ms) ======
[2025-09-03T22:27:28.226Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-03T22:27:28.226Z] GC before operation: completed in 192.418 ms, heap usage 523.288 MB -> 90.781 MB.
[2025-09-03T22:27:31.221Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:27:33.172Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:27:36.170Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:27:38.115Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:27:39.841Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:27:40.788Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:27:42.727Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:27:43.670Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:27:44.615Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:27:44.615Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:27:44.615Z] Top recommended movies for user id 72:
[2025-09-03T22:27:44.615Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:27:44.615Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:27:44.615Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:27:44.615Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:27:44.615Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:27:44.615Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15808.200 ms) ======
[2025-09-03T22:27:44.615Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-03T22:27:44.615Z] GC before operation: completed in 185.603 ms, heap usage 156.361 MB -> 90.098 MB.
[2025-09-03T22:27:46.552Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:27:49.546Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:27:51.498Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:27:54.500Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:27:55.444Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:27:57.386Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:27:58.330Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:28:00.267Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:28:00.267Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:28:00.267Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:28:00.267Z] Top recommended movies for user id 72:
[2025-09-03T22:28:00.267Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:28:00.267Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:28:00.267Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:28:00.267Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:28:00.267Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:28:00.267Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15887.326 ms) ======
[2025-09-03T22:28:00.267Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-03T22:28:00.267Z] GC before operation: completed in 132.520 ms, heap usage 106.057 MB -> 90.224 MB.
[2025-09-03T22:28:03.264Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:28:05.203Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:28:07.148Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:28:09.086Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:28:11.026Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:28:11.970Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:28:12.914Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:28:14.882Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:28:14.882Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:28:14.882Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:28:14.882Z] Top recommended movies for user id 72:
[2025-09-03T22:28:14.882Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:28:14.882Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:28:14.882Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:28:14.882Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:28:14.882Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:28:14.882Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14401.621 ms) ======
[2025-09-03T22:28:14.882Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-03T22:28:14.882Z] GC before operation: completed in 133.688 ms, heap usage 207.769 MB -> 90.125 MB.
[2025-09-03T22:28:17.873Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:28:19.811Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:28:21.748Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:28:23.740Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:28:25.676Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:28:26.646Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:28:28.582Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:28:29.527Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:28:30.474Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:28:30.474Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:28:30.474Z] Top recommended movies for user id 72:
[2025-09-03T22:28:30.474Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:28:30.474Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:28:30.474Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:28:30.474Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:28:30.474Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:28:30.474Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15336.278 ms) ======
[2025-09-03T22:28:30.474Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-03T22:28:30.474Z] GC before operation: completed in 148.337 ms, heap usage 440.846 MB -> 90.616 MB.
[2025-09-03T22:28:33.172Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-03T22:28:35.109Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-03T22:28:38.104Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-03T22:28:40.052Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-03T22:28:41.003Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-03T22:28:43.022Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-03T22:28:43.969Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-03T22:28:44.913Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-03T22:28:45.855Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-03T22:28:45.855Z] The best model improves the baseline by 14.52%.
[2025-09-03T22:28:45.855Z] Top recommended movies for user id 72:
[2025-09-03T22:28:45.855Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-03T22:28:45.855Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-03T22:28:45.855Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-03T22:28:45.855Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-03T22:28:45.855Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-03T22:28:45.855Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15101.451 ms) ======
[2025-09-03T22:28:45.855Z] -----------------------------------
[2025-09-03T22:28:45.855Z] renaissance-movie-lens_0_PASSED
[2025-09-03T22:28:45.855Z] -----------------------------------
[2025-09-03T22:28:45.855Z]
[2025-09-03T22:28:45.855Z] TEST TEARDOWN:
[2025-09-03T22:28:45.855Z] Nothing to be done for teardown.
[2025-09-03T22:28:45.856Z] renaissance-movie-lens_0 Finish Time: Wed Sep 3 22:28:45 2025 Epoch Time (ms): 1756938525750