renaissance-movie-lens_0
[2025-09-25T06:34:00.287Z] Running test renaissance-movie-lens_0 ...
[2025-09-25T06:34:00.287Z] ===============================================
[2025-09-25T06:34:00.287Z] renaissance-movie-lens_0 Start Time: Thu Sep 25 06:33:59 2025 Epoch Time (ms): 1758782039817
[2025-09-25T06:34:00.287Z] variation: NoOptions
[2025-09-25T06:34:00.287Z] JVM_OPTIONS:
[2025-09-25T06:34:00.287Z] { \
[2025-09-25T06:34:00.287Z] echo ""; echo "TEST SETUP:"; \
[2025-09-25T06:34:00.287Z] echo "Nothing to be done for setup."; \
[2025-09-25T06:34:00.287Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17587813262706/renaissance-movie-lens_0"; \
[2025-09-25T06:34:00.287Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17587813262706/renaissance-movie-lens_0"; \
[2025-09-25T06:34:00.287Z] echo ""; echo "TESTING:"; \
[2025-09-25T06:34:00.287Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/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_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17587813262706/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-25T06:34:00.287Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17587813262706/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-25T06:34:00.287Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-25T06:34:00.287Z] echo "Nothing to be done for teardown."; \
[2025-09-25T06:34:00.287Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_x86-64_alpine-linux_testList_1/aqa-tests/TKG/../TKG/output_17587813262706/TestTargetResult";
[2025-09-25T06:34:00.287Z]
[2025-09-25T06:34:00.287Z] TEST SETUP:
[2025-09-25T06:34:00.287Z] Nothing to be done for setup.
[2025-09-25T06:34:00.287Z]
[2025-09-25T06:34:00.287Z] TESTING:
[2025-09-25T06:34:05.579Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-09-25T06:34:17.774Z] 06:34:16.219 WARN [dispatcher-event-loop-0] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-25T06:34:19.424Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-25T06:34:19.425Z] Training: 60056, validation: 20285, test: 19854
[2025-09-25T06:34:19.425Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-25T06:34:20.150Z] GC before operation: completed in 134.758 ms, heap usage 291.826 MB -> 75.900 MB.
[2025-09-25T06:34:26.678Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:34:30.280Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:34:33.511Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:34:36.741Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:34:39.069Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:34:40.563Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:34:42.056Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:34:44.415Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:34:44.415Z] 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.
[2025-09-25T06:34:44.415Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:34:44.415Z] Top recommended movies for user id 72:
[2025-09-25T06:34:44.415Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:34:44.415Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:34:44.415Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:34:44.415Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:34:44.415Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:34:44.415Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24959.595 ms) ======
[2025-09-25T06:34:44.415Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-25T06:34:44.415Z] GC before operation: completed in 119.174 ms, heap usage 126.807 MB -> 91.197 MB.
[2025-09-25T06:34:47.651Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:34:50.888Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:34:54.106Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:34:56.465Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:34:58.803Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:35:01.128Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:35:03.193Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:35:04.681Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:35:05.403Z] 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.
[2025-09-25T06:35:05.403Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:35:05.403Z] Top recommended movies for user id 72:
[2025-09-25T06:35:05.403Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:35:05.403Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:35:05.403Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:35:05.403Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:35:05.403Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:35:05.403Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (20611.709 ms) ======
[2025-09-25T06:35:05.403Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-25T06:35:05.403Z] GC before operation: completed in 105.617 ms, heap usage 370.372 MB -> 89.033 MB.
[2025-09-25T06:35:07.724Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:35:18.127Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:35:20.443Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:35:22.762Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:35:24.256Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:35:25.764Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:35:27.261Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:35:28.760Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:35:29.479Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-25T06:35:29.479Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:35:29.479Z] Top recommended movies for user id 72:
[2025-09-25T06:35:29.479Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:35:29.479Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:35:29.479Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:35:29.479Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:35:29.479Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:35:29.479Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (24016.192 ms) ======
[2025-09-25T06:35:29.479Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-25T06:35:29.479Z] GC before operation: completed in 120.028 ms, heap usage 408.228 MB -> 89.668 MB.
[2025-09-25T06:35:31.806Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:35:35.029Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:35:37.346Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:35:39.673Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:35:41.165Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:35:42.671Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:35:44.162Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:35:45.661Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:35:46.387Z] 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.
[2025-09-25T06:35:46.387Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:35:46.387Z] Top recommended movies for user id 72:
[2025-09-25T06:35:46.387Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:35:46.387Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:35:46.387Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:35:46.387Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:35:46.387Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:35:46.387Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16728.995 ms) ======
[2025-09-25T06:35:46.387Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-25T06:35:46.387Z] GC before operation: completed in 111.847 ms, heap usage 405.407 MB -> 89.883 MB.
[2025-09-25T06:35:49.761Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:35:53.450Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:35:55.772Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:35:58.088Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:35:59.577Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:36:01.069Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:36:02.648Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:36:04.146Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:36:04.146Z] 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.
[2025-09-25T06:36:04.146Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:36:04.862Z] Top recommended movies for user id 72:
[2025-09-25T06:36:04.862Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:36:04.862Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:36:04.862Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:36:04.862Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:36:04.862Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:36:04.862Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18251.143 ms) ======
[2025-09-25T06:36:04.862Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-25T06:36:04.862Z] GC before operation: completed in 104.023 ms, heap usage 364.747 MB -> 89.865 MB.
[2025-09-25T06:36:07.188Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:36:10.409Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:36:12.723Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:36:15.053Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:36:16.540Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:36:18.035Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:36:20.359Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:36:21.082Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:36:21.811Z] 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.
[2025-09-25T06:36:21.811Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:36:21.811Z] Top recommended movies for user id 72:
[2025-09-25T06:36:21.811Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:36:21.811Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:36:21.811Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:36:21.811Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:36:21.811Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:36:21.811Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (17036.441 ms) ======
[2025-09-25T06:36:21.811Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-25T06:36:21.811Z] GC before operation: completed in 114.300 ms, heap usage 493.292 MB -> 90.282 MB.
[2025-09-25T06:36:24.143Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:36:26.466Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:36:28.793Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:36:31.152Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:36:32.644Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:36:33.361Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:36:35.312Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:36:36.053Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:36:36.776Z] 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.
[2025-09-25T06:36:36.776Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:36:36.776Z] Top recommended movies for user id 72:
[2025-09-25T06:36:36.776Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:36:36.776Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:36:36.776Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:36:36.776Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:36:36.776Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:36:36.776Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14816.515 ms) ======
[2025-09-25T06:36:36.776Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-25T06:36:36.776Z] GC before operation: completed in 117.713 ms, heap usage 238.496 MB -> 89.874 MB.
[2025-09-25T06:36:39.106Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:36:41.427Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:36:43.750Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:36:46.071Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:36:47.559Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:36:49.054Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:36:50.543Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:36:52.036Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:36:52.036Z] 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.
[2025-09-25T06:36:52.036Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:36:52.036Z] Top recommended movies for user id 72:
[2025-09-25T06:36:52.036Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:36:52.036Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:36:52.036Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:36:52.036Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:36:52.036Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:36:52.036Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15441.801 ms) ======
[2025-09-25T06:36:52.036Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-25T06:36:52.036Z] GC before operation: completed in 102.536 ms, heap usage 459.021 MB -> 90.426 MB.
[2025-09-25T06:36:55.296Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:36:57.623Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:36:59.950Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:37:02.275Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:37:03.792Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:37:05.283Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:37:06.789Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:37:07.514Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:37:08.347Z] 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.
[2025-09-25T06:37:08.347Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:37:08.347Z] Top recommended movies for user id 72:
[2025-09-25T06:37:08.347Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:37:08.347Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:37:08.347Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:37:08.347Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:37:08.347Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:37:08.347Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15884.631 ms) ======
[2025-09-25T06:37:08.347Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-25T06:37:08.347Z] GC before operation: completed in 109.581 ms, heap usage 130.527 MB -> 89.863 MB.
[2025-09-25T06:37:10.667Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:37:13.459Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:37:15.790Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:37:18.112Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:37:19.599Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:37:21.090Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:37:22.586Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:37:23.315Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:37:24.048Z] 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.
[2025-09-25T06:37:24.048Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:37:24.048Z] Top recommended movies for user id 72:
[2025-09-25T06:37:24.048Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:37:24.048Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:37:24.048Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:37:24.048Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:37:24.048Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:37:24.048Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15584.458 ms) ======
[2025-09-25T06:37:24.048Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-25T06:37:24.048Z] GC before operation: completed in 128.398 ms, heap usage 352.741 MB -> 90.410 MB.
[2025-09-25T06:37:26.373Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:37:28.689Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:37:31.013Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:37:33.336Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:37:34.832Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:37:36.328Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:37:37.843Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:37:39.334Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:37:40.055Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-25T06:37:40.055Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:37:40.055Z] Top recommended movies for user id 72:
[2025-09-25T06:37:40.055Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:37:40.055Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:37:40.055Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:37:40.055Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:37:40.055Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:37:40.055Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16005.510 ms) ======
[2025-09-25T06:37:40.055Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-25T06:37:40.055Z] GC before operation: completed in 104.547 ms, heap usage 289.503 MB -> 90.104 MB.
[2025-09-25T06:37:42.377Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:37:44.702Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:37:47.038Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:37:49.366Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:37:50.864Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:37:52.358Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:37:53.540Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:37:55.029Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:37:55.029Z] 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.
[2025-09-25T06:37:55.748Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:37:55.748Z] Top recommended movies for user id 72:
[2025-09-25T06:37:55.748Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:37:55.748Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:37:55.748Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:37:55.748Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:37:55.748Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:37:55.748Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15330.805 ms) ======
[2025-09-25T06:37:55.748Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-25T06:37:55.748Z] GC before operation: completed in 112.774 ms, heap usage 132.802 MB -> 89.986 MB.
[2025-09-25T06:37:58.064Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:38:00.394Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:38:02.722Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:38:05.060Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:38:06.554Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:38:08.047Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:38:09.542Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:38:11.035Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:38:11.761Z] 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.
[2025-09-25T06:38:11.761Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:38:11.761Z] Top recommended movies for user id 72:
[2025-09-25T06:38:11.761Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:38:11.761Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:38:11.761Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:38:11.761Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:38:11.761Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:38:11.761Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16026.371 ms) ======
[2025-09-25T06:38:11.761Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-25T06:38:11.761Z] GC before operation: completed in 103.390 ms, heap usage 361.752 MB -> 90.529 MB.
[2025-09-25T06:38:14.084Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:38:16.423Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:38:19.656Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:38:21.988Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:38:22.709Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:38:24.203Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:38:25.705Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:38:27.216Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:38:27.216Z] 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.
[2025-09-25T06:38:27.937Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:38:27.937Z] Top recommended movies for user id 72:
[2025-09-25T06:38:27.937Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:38:27.937Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:38:27.937Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:38:27.937Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:38:27.937Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:38:27.937Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15944.386 ms) ======
[2025-09-25T06:38:27.937Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-25T06:38:27.937Z] GC before operation: completed in 104.459 ms, heap usage 454.144 MB -> 90.426 MB.
[2025-09-25T06:38:30.263Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:38:32.586Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:38:34.928Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:38:37.494Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:38:38.988Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:38:39.714Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:38:41.208Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:38:42.701Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:38:43.425Z] 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.
[2025-09-25T06:38:43.425Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:38:43.425Z] Top recommended movies for user id 72:
[2025-09-25T06:38:43.425Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:38:43.425Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:38:43.425Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:38:43.425Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:38:43.425Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:38:43.425Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (15492.134 ms) ======
[2025-09-25T06:38:43.425Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-25T06:38:43.425Z] GC before operation: completed in 109.180 ms, heap usage 282.452 MB -> 90.450 MB.
[2025-09-25T06:38:45.746Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:38:48.160Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:38:50.494Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:38:52.821Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:38:54.314Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:38:55.806Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:38:57.305Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:38:58.807Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:38:58.807Z] 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.
[2025-09-25T06:38:59.525Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:38:59.525Z] Top recommended movies for user id 72:
[2025-09-25T06:38:59.525Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:38:59.525Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:38:59.525Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:38:59.525Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:38:59.525Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:38:59.525Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (15915.408 ms) ======
[2025-09-25T06:38:59.526Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-25T06:38:59.526Z] GC before operation: completed in 105.136 ms, heap usage 363.409 MB -> 90.370 MB.
[2025-09-25T06:39:01.859Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:39:04.177Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:39:06.502Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:39:08.819Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:39:10.312Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:39:11.802Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:39:12.992Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:39:14.491Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:39:15.209Z] 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.
[2025-09-25T06:39:15.209Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:39:15.209Z] Top recommended movies for user id 72:
[2025-09-25T06:39:15.209Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:39:15.209Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:39:15.209Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:39:15.209Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:39:15.209Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:39:15.209Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15624.254 ms) ======
[2025-09-25T06:39:15.209Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-25T06:39:15.209Z] GC before operation: completed in 104.403 ms, heap usage 466.155 MB -> 90.637 MB.
[2025-09-25T06:39:17.530Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:39:19.857Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:39:22.191Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:39:24.543Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:39:25.265Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:39:26.751Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:39:28.243Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:39:29.743Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:39:29.743Z] 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.
[2025-09-25T06:39:29.743Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:39:30.462Z] Top recommended movies for user id 72:
[2025-09-25T06:39:30.462Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:39:30.462Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:39:30.462Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:39:30.462Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:39:30.462Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:39:30.462Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14959.932 ms) ======
[2025-09-25T06:39:30.462Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-25T06:39:30.462Z] GC before operation: completed in 111.625 ms, heap usage 341.849 MB -> 90.293 MB.
[2025-09-25T06:39:32.795Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:39:35.127Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:39:37.451Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:39:39.784Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:39:41.278Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:39:42.771Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:39:44.272Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:39:45.762Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:39:45.762Z] 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.
[2025-09-25T06:39:45.762Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:39:45.762Z] Top recommended movies for user id 72:
[2025-09-25T06:39:45.762Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:39:45.762Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:39:45.762Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:39:45.762Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:39:45.762Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:39:45.762Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (15773.440 ms) ======
[2025-09-25T06:39:45.762Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-25T06:39:45.762Z] GC before operation: completed in 107.501 ms, heap usage 116.400 MB -> 90.063 MB.
[2025-09-25T06:39:49.076Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-25T06:39:50.582Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-25T06:39:53.380Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-25T06:39:54.880Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-25T06:39:56.373Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-25T06:39:57.868Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-25T06:39:59.412Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-25T06:40:00.132Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-25T06:40:00.849Z] 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.
[2025-09-25T06:40:00.849Z] The best model improves the baseline by 14.52%.
[2025-09-25T06:40:00.849Z] Top recommended movies for user id 72:
[2025-09-25T06:40:00.849Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-25T06:40:00.849Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-25T06:40:00.849Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-25T06:40:00.849Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-25T06:40:00.849Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-25T06:40:00.849Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14680.432 ms) ======
[2025-09-25T06:40:01.576Z] -----------------------------------
[2025-09-25T06:40:01.576Z] renaissance-movie-lens_0_PASSED
[2025-09-25T06:40:01.576Z] -----------------------------------
[2025-09-25T06:40:01.576Z]
[2025-09-25T06:40:01.576Z] TEST TEARDOWN:
[2025-09-25T06:40:01.576Z] Nothing to be done for teardown.
[2025-09-25T06:40:01.576Z] renaissance-movie-lens_0 Finish Time: Thu Sep 25 06:40:00 2025 Epoch Time (ms): 1758782400872