renaissance-movie-lens_0
[2025-11-20T11:38:19.220Z] Running test renaissance-movie-lens_0 ...
[2025-11-20T11:38:19.220Z] ===============================================
[2025-11-20T11:38:19.220Z] renaissance-movie-lens_0 Start Time: Thu Nov 20 11:38:18 2025 Epoch Time (ms): 1763638698469
[2025-11-20T11:38:19.220Z] variation: NoOptions
[2025-11-20T11:38:19.220Z] JVM_OPTIONS:
[2025-11-20T11:38:19.220Z] { \
[2025-11-20T11:38:19.220Z] echo ""; echo "TEST SETUP:"; \
[2025-11-20T11:38:19.220Z] echo "Nothing to be done for setup."; \
[2025-11-20T11:38:19.220Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17636377121423/renaissance-movie-lens_0"; \
[2025-11-20T11:38:19.220Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17636377121423/renaissance-movie-lens_0"; \
[2025-11-20T11:38:19.220Z] echo ""; echo "TESTING:"; \
[2025-11-20T11:38:19.220Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/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_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17636377121423/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-11-20T11:38:19.220Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17636377121423/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-11-20T11:38:19.220Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-11-20T11:38:19.220Z] echo "Nothing to be done for teardown."; \
[2025-11-20T11:38:19.220Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17636377121423/TestTargetResult";
[2025-11-20T11:38:19.220Z]
[2025-11-20T11:38:19.220Z] TEST SETUP:
[2025-11-20T11:38:19.220Z] Nothing to be done for setup.
[2025-11-20T11:38:19.220Z]
[2025-11-20T11:38:19.220Z] TESTING:
[2025-11-20T11:38:23.599Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-11-20T11:38:31.781Z] 11:38:30.331 WARN [dispatcher-event-loop-3] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-11-20T11:38:33.347Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-11-20T11:38:33.347Z] Training: 60056, validation: 20285, test: 19854
[2025-11-20T11:38:33.347Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-11-20T11:38:34.109Z] GC before operation: completed in 133.231 ms, heap usage 425.759 MB -> 75.781 MB.
[2025-11-20T11:38:42.313Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:38:48.108Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:38:51.472Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:38:54.835Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:38:57.265Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:38:58.829Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:39:01.261Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:39:02.841Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:39:02.841Z] 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.
[2025-11-20T11:39:02.841Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:39:03.596Z] Top recommended movies for user id 72:
[2025-11-20T11:39:03.596Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:39:03.596Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:39:03.596Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:39:03.596Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:39:03.596Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:39:03.596Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (29475.969 ms) ======
[2025-11-20T11:39:03.596Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-11-20T11:39:03.596Z] GC before operation: completed in 114.924 ms, heap usage 525.652 MB -> 86.789 MB.
[2025-11-20T11:39:06.969Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:39:10.343Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:39:13.724Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:39:16.146Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:39:17.710Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:39:19.277Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:39:20.844Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:39:22.410Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:39:23.163Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-20T11:39:23.163Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:39:23.163Z] Top recommended movies for user id 72:
[2025-11-20T11:39:23.163Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:39:23.163Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:39:23.163Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:39:23.163Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:39:23.163Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:39:23.163Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (19805.374 ms) ======
[2025-11-20T11:39:23.163Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-11-20T11:39:23.163Z] GC before operation: completed in 105.027 ms, heap usage 136.149 MB -> 92.218 MB.
[2025-11-20T11:39:25.592Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:39:29.481Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:39:31.048Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:39:33.481Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:39:35.038Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:39:36.604Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:39:38.175Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:39:39.740Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:39:40.497Z] 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.
[2025-11-20T11:39:40.497Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:39:40.497Z] Top recommended movies for user id 72:
[2025-11-20T11:39:40.497Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:39:40.497Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:39:40.497Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:39:40.497Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:39:40.497Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:39:40.497Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17138.886 ms) ======
[2025-11-20T11:39:40.497Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-11-20T11:39:40.497Z] GC before operation: completed in 101.795 ms, heap usage 233.245 MB -> 89.176 MB.
[2025-11-20T11:39:43.911Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:39:46.340Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:39:48.776Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:39:51.213Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:39:52.777Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:39:54.347Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:39:55.916Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:39:56.675Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:39:57.459Z] 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.
[2025-11-20T11:39:57.459Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:39:57.459Z] Top recommended movies for user id 72:
[2025-11-20T11:39:57.459Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:39:57.459Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:39:57.459Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:39:57.459Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:39:57.459Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:39:57.459Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16857.002 ms) ======
[2025-11-20T11:39:57.459Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-11-20T11:39:57.459Z] GC before operation: completed in 108.016 ms, heap usage 557.581 MB -> 93.188 MB.
[2025-11-20T11:39:59.895Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:40:02.333Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:40:05.745Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:40:08.175Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:40:09.934Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:40:10.688Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:40:13.121Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:40:13.881Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:40:14.639Z] 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.
[2025-11-20T11:40:14.639Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:40:14.639Z] Top recommended movies for user id 72:
[2025-11-20T11:40:14.639Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:40:14.639Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:40:14.639Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:40:14.639Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:40:14.639Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:40:14.639Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17203.557 ms) ======
[2025-11-20T11:40:14.639Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-11-20T11:40:14.639Z] GC before operation: completed in 95.471 ms, heap usage 201.624 MB -> 91.675 MB.
[2025-11-20T11:40:18.008Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:40:20.445Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:40:23.819Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:40:25.380Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:40:26.941Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:40:28.511Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:40:30.077Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:40:31.638Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:40:31.638Z] 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.
[2025-11-20T11:40:31.638Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:40:31.638Z] Top recommended movies for user id 72:
[2025-11-20T11:40:31.638Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:40:31.638Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:40:31.638Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:40:31.638Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:40:31.638Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:40:31.638Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17139.532 ms) ======
[2025-11-20T11:40:31.638Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-11-20T11:40:32.394Z] GC before operation: completed in 110.072 ms, heap usage 218.889 MB -> 89.770 MB.
[2025-11-20T11:40:34.829Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:40:37.248Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:40:39.687Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:40:42.110Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:40:43.680Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:40:44.438Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:40:46.002Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:40:47.575Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:40:47.575Z] 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.
[2025-11-20T11:40:47.575Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:40:48.329Z] Top recommended movies for user id 72:
[2025-11-20T11:40:48.329Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:40:48.329Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:40:48.329Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:40:48.329Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:40:48.329Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:40:48.329Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15920.218 ms) ======
[2025-11-20T11:40:48.329Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-11-20T11:40:48.329Z] GC before operation: completed in 99.422 ms, heap usage 631.062 MB -> 93.533 MB.
[2025-11-20T11:40:50.907Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:40:52.471Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:40:54.907Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:40:57.379Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:40:58.944Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:41:00.512Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:41:02.076Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:41:03.641Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:41:03.641Z] 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.
[2025-11-20T11:41:03.641Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:41:03.641Z] Top recommended movies for user id 72:
[2025-11-20T11:41:03.641Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:41:03.641Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:41:03.641Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:41:03.641Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:41:03.641Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:41:03.642Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15629.050 ms) ======
[2025-11-20T11:41:03.642Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-11-20T11:41:03.642Z] GC before operation: completed in 102.136 ms, heap usage 373.786 MB -> 93.602 MB.
[2025-11-20T11:41:06.067Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:41:08.503Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:41:10.943Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:41:13.372Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:41:14.938Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:41:15.697Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:41:17.264Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:41:18.837Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:41:18.837Z] 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.
[2025-11-20T11:41:18.837Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:41:19.588Z] Top recommended movies for user id 72:
[2025-11-20T11:41:19.588Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:41:19.588Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:41:19.588Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:41:19.588Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:41:19.588Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:41:19.588Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15440.459 ms) ======
[2025-11-20T11:41:19.588Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-11-20T11:41:19.588Z] GC before operation: completed in 98.040 ms, heap usage 172.592 MB -> 89.732 MB.
[2025-11-20T11:41:22.021Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:41:24.461Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:41:26.899Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:41:28.465Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:41:30.035Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:41:31.603Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:41:33.184Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:41:34.438Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:41:34.438Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-11-20T11:41:34.438Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:41:34.438Z] Top recommended movies for user id 72:
[2025-11-20T11:41:34.438Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:41:34.438Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:41:34.438Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:41:34.438Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:41:34.438Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:41:34.438Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15303.747 ms) ======
[2025-11-20T11:41:34.438Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-11-20T11:41:34.438Z] GC before operation: completed in 102.010 ms, heap usage 192.858 MB -> 89.952 MB.
[2025-11-20T11:41:37.810Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:41:40.245Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:41:42.700Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:41:45.138Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:41:45.895Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:41:47.453Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:41:49.023Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:41:50.590Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:41:50.590Z] 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.
[2025-11-20T11:41:50.590Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:41:50.590Z] Top recommended movies for user id 72:
[2025-11-20T11:41:50.590Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:41:50.590Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:41:50.590Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:41:50.590Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:41:50.590Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:41:50.590Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16028.265 ms) ======
[2025-11-20T11:41:50.590Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-11-20T11:41:50.590Z] GC before operation: completed in 100.396 ms, heap usage 284.305 MB -> 89.865 MB.
[2025-11-20T11:41:53.033Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:41:55.674Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:41:58.115Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:42:00.534Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:42:01.289Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:42:02.849Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:42:04.424Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:42:06.002Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:42:06.002Z] 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.
[2025-11-20T11:42:06.002Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:42:06.002Z] Top recommended movies for user id 72:
[2025-11-20T11:42:06.002Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:42:06.002Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:42:06.002Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:42:06.002Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:42:06.002Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:42:06.002Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15153.182 ms) ======
[2025-11-20T11:42:06.002Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-11-20T11:42:06.002Z] GC before operation: completed in 107.808 ms, heap usage 443.420 MB -> 90.275 MB.
[2025-11-20T11:42:08.432Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:42:10.867Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:42:13.789Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:42:15.363Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:42:16.936Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:42:18.511Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:42:20.087Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:42:20.856Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:42:21.615Z] 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.
[2025-11-20T11:42:21.615Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:42:21.615Z] Top recommended movies for user id 72:
[2025-11-20T11:42:21.615Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:42:21.615Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:42:21.615Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:42:21.615Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:42:21.615Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:42:21.615Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15328.621 ms) ======
[2025-11-20T11:42:21.615Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-11-20T11:42:21.615Z] GC before operation: completed in 104.135 ms, heap usage 373.969 MB -> 90.296 MB.
[2025-11-20T11:42:24.046Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:42:26.490Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:42:28.926Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:42:31.361Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:42:32.921Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:42:33.678Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:42:35.239Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:42:36.806Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:42:36.806Z] 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.
[2025-11-20T11:42:36.806Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:42:36.806Z] Top recommended movies for user id 72:
[2025-11-20T11:42:36.806Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:42:36.806Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:42:36.806Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:42:36.806Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:42:36.806Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:42:36.806Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15459.029 ms) ======
[2025-11-20T11:42:36.806Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-11-20T11:42:36.806Z] GC before operation: completed in 102.264 ms, heap usage 284.888 MB -> 89.960 MB.
[2025-11-20T11:42:39.239Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:42:41.671Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:42:44.169Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:42:46.607Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:42:48.178Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:42:48.933Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:42:50.505Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:42:52.073Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:42:52.073Z] 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.
[2025-11-20T11:42:52.074Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:42:52.074Z] Top recommended movies for user id 72:
[2025-11-20T11:42:52.074Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:42:52.074Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:42:52.074Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:42:52.074Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:42:52.074Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:42:52.074Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15157.073 ms) ======
[2025-11-20T11:42:52.074Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-11-20T11:42:52.074Z] GC before operation: completed in 100.299 ms, heap usage 227.860 MB -> 90.127 MB.
[2025-11-20T11:42:55.006Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:42:57.467Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:42:59.891Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:43:02.332Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:43:03.090Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:43:04.656Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:43:06.217Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:43:07.777Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:43:07.777Z] 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.
[2025-11-20T11:43:07.777Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:43:07.777Z] Top recommended movies for user id 72:
[2025-11-20T11:43:07.777Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:43:07.777Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:43:07.777Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:43:07.777Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:43:07.777Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:43:07.777Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15537.148 ms) ======
[2025-11-20T11:43:07.777Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-11-20T11:43:07.777Z] GC before operation: completed in 99.116 ms, heap usage 366.080 MB -> 90.233 MB.
[2025-11-20T11:43:10.211Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:43:12.642Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:43:15.081Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:43:17.519Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:43:18.289Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:43:19.871Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:43:21.433Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:43:22.998Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:43:22.998Z] 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.
[2025-11-20T11:43:22.998Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:43:22.998Z] Top recommended movies for user id 72:
[2025-11-20T11:43:22.998Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:43:22.998Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:43:22.998Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:43:22.998Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:43:22.998Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:43:22.998Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15129.791 ms) ======
[2025-11-20T11:43:22.998Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-11-20T11:43:22.998Z] GC before operation: completed in 104.660 ms, heap usage 198.288 MB -> 90.037 MB.
[2025-11-20T11:43:25.425Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:43:28.823Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:43:31.265Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:43:33.687Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:43:35.256Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:43:36.024Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:43:37.589Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:43:38.849Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:43:39.608Z] 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.
[2025-11-20T11:43:39.608Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:43:39.608Z] Top recommended movies for user id 72:
[2025-11-20T11:43:39.608Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:43:39.608Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:43:39.608Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:43:39.608Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:43:39.608Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:43:39.608Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16164.238 ms) ======
[2025-11-20T11:43:39.608Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-11-20T11:43:39.608Z] GC before operation: completed in 102.986 ms, heap usage 130.003 MB -> 95.561 MB.
[2025-11-20T11:43:42.045Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:43:44.483Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:43:46.921Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:43:48.484Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:43:50.052Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:43:51.611Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:43:53.172Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:43:54.747Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:43:54.747Z] 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.
[2025-11-20T11:43:54.747Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:43:54.747Z] Top recommended movies for user id 72:
[2025-11-20T11:43:54.747Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:43:54.747Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:43:54.747Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:43:54.747Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:43:54.747Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:43:54.747Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15394.766 ms) ======
[2025-11-20T11:43:54.747Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-11-20T11:43:54.747Z] GC before operation: completed in 101.250 ms, heap usage 453.422 MB -> 92.631 MB.
[2025-11-20T11:43:57.169Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-11-20T11:43:59.605Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-11-20T11:44:02.041Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-11-20T11:44:04.474Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-11-20T11:44:05.236Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-11-20T11:44:06.804Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-11-20T11:44:08.370Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-11-20T11:44:09.934Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-11-20T11:44:09.934Z] 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.
[2025-11-20T11:44:09.934Z] The best model improves the baseline by 14.52%.
[2025-11-20T11:44:09.934Z] Top recommended movies for user id 72:
[2025-11-20T11:44:09.934Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-11-20T11:44:09.934Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-11-20T11:44:09.934Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-11-20T11:44:09.934Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-11-20T11:44:09.934Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-11-20T11:44:09.934Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15007.341 ms) ======
[2025-11-20T11:44:10.689Z] -----------------------------------
[2025-11-20T11:44:10.689Z] renaissance-movie-lens_0_PASSED
[2025-11-20T11:44:10.689Z] -----------------------------------
[2025-11-20T11:44:10.689Z]
[2025-11-20T11:44:10.689Z] TEST TEARDOWN:
[2025-11-20T11:44:10.689Z] Nothing to be done for teardown.
[2025-11-20T11:44:10.689Z] renaissance-movie-lens_0 Finish Time: Thu Nov 20 11:44:10 2025 Epoch Time (ms): 1763639050051