renaissance-movie-lens_0
[2025-09-04T06:32:27.729Z] Running test renaissance-movie-lens_0 ...
[2025-09-04T06:32:27.729Z] ===============================================
[2025-09-04T06:32:27.729Z] renaissance-movie-lens_0 Start Time: Thu Sep 4 06:32:24 2025 Epoch Time (ms): 1756967544706
[2025-09-04T06:32:27.729Z] variation: NoOptions
[2025-09-04T06:32:27.729Z] JVM_OPTIONS:
[2025-09-04T06:32:27.729Z] { \
[2025-09-04T06:32:27.729Z] echo ""; echo "TEST SETUP:"; \
[2025-09-04T06:32:27.729Z] echo "Nothing to be done for setup."; \
[2025-09-04T06:32:27.729Z] mkdir -p "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569628091184/renaissance-movie-lens_0"; \
[2025-09-04T06:32:27.729Z] cd "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569628091184/renaissance-movie-lens_0"; \
[2025-09-04T06:32:27.729Z] echo ""; echo "TESTING:"; \
[2025-09-04T06:32:27.729Z] "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_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_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569628091184/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-04T06:32:27.729Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569628091184/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-04T06:32:27.729Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-04T06:32:27.729Z] echo "Nothing to be done for teardown."; \
[2025-09-04T06:32:27.729Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk21_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17569628091184/TestTargetResult";
[2025-09-04T06:32:27.729Z]
[2025-09-04T06:32:27.729Z] TEST SETUP:
[2025-09-04T06:32:27.729Z] Nothing to be done for setup.
[2025-09-04T06:32:27.729Z]
[2025-09-04T06:32:27.729Z] TESTING:
[2025-09-04T06:32:50.744Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-09-04T06:33:24.054Z] 06:33:20.500 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-04T06:33:31.335Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-04T06:33:34.296Z] Training: 60056, validation: 20285, test: 19854
[2025-09-04T06:33:34.296Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-04T06:33:34.630Z] GC before operation: completed in 662.322 ms, heap usage 284.153 MB -> 76.225 MB.
[2025-09-04T06:34:07.974Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:34:21.088Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:34:34.407Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:34:47.513Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:34:56.387Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:35:03.637Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:35:10.881Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:35:16.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:35:18.481Z] 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.
[2025-09-04T06:35:18.481Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:35:19.622Z] Top recommended movies for user id 72:
[2025-09-04T06:35:19.622Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:35:19.622Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:35:19.622Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:35:19.622Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:35:19.622Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:35:19.622Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (104922.298 ms) ======
[2025-09-04T06:35:19.622Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-04T06:35:20.787Z] GC before operation: completed in 981.490 ms, heap usage 532.836 MB -> 91.774 MB.
[2025-09-04T06:35:33.875Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:35:44.728Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:35:55.838Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:36:04.692Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:36:11.937Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:36:17.824Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:36:23.738Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:36:29.643Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:36:30.347Z] 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.
[2025-09-04T06:36:30.347Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:36:31.049Z] Top recommended movies for user id 72:
[2025-09-04T06:36:31.049Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:36:31.049Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:36:31.049Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:36:31.049Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:36:31.049Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:36:31.049Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (70607.208 ms) ======
[2025-09-04T06:36:31.049Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-04T06:36:32.230Z] GC before operation: completed in 1156.868 ms, heap usage 560.660 MB -> 89.539 MB.
[2025-09-04T06:36:43.042Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:36:53.829Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:37:02.692Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:37:11.563Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:37:17.456Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:37:24.789Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:37:29.524Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:37:36.777Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:37:37.104Z] 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.
[2025-09-04T06:37:37.104Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:37:37.806Z] Top recommended movies for user id 72:
[2025-09-04T06:37:37.806Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:37:37.806Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:37:37.806Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:37:37.806Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:37:37.806Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:37:37.806Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (65614.066 ms) ======
[2025-09-04T06:37:37.806Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-04T06:37:38.971Z] GC before operation: completed in 839.410 ms, heap usage 377.634 MB -> 90.411 MB.
[2025-09-04T06:37:49.759Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:37:58.726Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:38:09.511Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:38:18.417Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:38:24.316Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:38:30.219Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:38:36.098Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:38:42.097Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:38:43.242Z] 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.
[2025-09-04T06:38:43.242Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:38:43.967Z] Top recommended movies for user id 72:
[2025-09-04T06:38:43.967Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:38:43.967Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:38:43.967Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:38:43.967Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:38:43.967Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:38:43.967Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (65155.459 ms) ======
[2025-09-04T06:38:43.967Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-04T06:38:44.683Z] GC before operation: completed in 832.609 ms, heap usage 404.104 MB -> 90.344 MB.
[2025-09-04T06:38:55.486Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:39:04.342Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:39:15.139Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:39:24.084Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:39:29.966Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:39:35.834Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:39:41.714Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:39:47.591Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:39:48.729Z] 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.
[2025-09-04T06:39:48.729Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:39:49.430Z] Top recommended movies for user id 72:
[2025-09-04T06:39:49.430Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:39:49.430Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:39:49.430Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:39:49.430Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:39:49.430Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:39:49.430Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (64786.619 ms) ======
[2025-09-04T06:39:49.430Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-04T06:39:50.594Z] GC before operation: completed in 804.303 ms, heap usage 140.655 MB -> 89.995 MB.
[2025-09-04T06:40:01.556Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:40:08.801Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:40:19.584Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:40:26.818Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:40:32.745Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:40:38.711Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:40:44.625Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:40:50.506Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:40:50.833Z] 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.
[2025-09-04T06:40:51.160Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:40:51.860Z] Top recommended movies for user id 72:
[2025-09-04T06:40:51.860Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:40:51.860Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:40:51.860Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:40:51.860Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:40:51.860Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:40:51.860Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (61481.646 ms) ======
[2025-09-04T06:40:51.860Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-04T06:40:52.574Z] GC before operation: completed in 814.731 ms, heap usage 381.619 MB -> 90.698 MB.
[2025-09-04T06:41:03.361Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:41:12.226Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:41:21.181Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:41:30.068Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:41:34.811Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:41:40.700Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:41:46.592Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:41:52.508Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:41:52.838Z] 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.
[2025-09-04T06:41:52.838Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:41:53.542Z] Top recommended movies for user id 72:
[2025-09-04T06:41:53.542Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:41:53.542Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:41:53.542Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:41:53.542Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:41:53.542Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:41:53.542Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (60973.038 ms) ======
[2025-09-04T06:41:53.542Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-04T06:41:54.272Z] GC before operation: completed in 810.346 ms, heap usage 344.285 MB -> 90.466 MB.
[2025-09-04T06:42:03.326Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:42:14.115Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:42:22.980Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:42:30.239Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:42:36.132Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:42:42.029Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:42:47.907Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:42:53.788Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:42:54.115Z] 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.
[2025-09-04T06:42:54.440Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:42:54.771Z] Top recommended movies for user id 72:
[2025-09-04T06:42:54.771Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:42:54.771Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:42:54.771Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:42:54.771Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:42:54.771Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:42:54.771Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (60507.109 ms) ======
[2025-09-04T06:42:54.771Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-04T06:42:55.942Z] GC before operation: completed in 845.973 ms, heap usage 398.813 MB -> 90.809 MB.
[2025-09-04T06:43:06.742Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:43:13.971Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:43:22.939Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:43:31.814Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:43:36.536Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:43:42.411Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:43:47.160Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:43:51.894Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:43:53.034Z] 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.
[2025-09-04T06:43:53.034Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:43:53.836Z] Top recommended movies for user id 72:
[2025-09-04T06:43:53.836Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:43:53.836Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:43:53.836Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:43:53.836Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:43:53.836Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:43:53.836Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (58161.171 ms) ======
[2025-09-04T06:43:53.836Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-04T06:43:54.991Z] GC before operation: completed in 884.554 ms, heap usage 561.909 MB -> 94.202 MB.
[2025-09-04T06:44:03.849Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:44:12.716Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:44:23.509Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:44:32.365Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:44:37.268Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:44:41.996Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:44:47.876Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:44:53.758Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:44:54.086Z] 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.
[2025-09-04T06:44:54.412Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:44:55.130Z] Top recommended movies for user id 72:
[2025-09-04T06:44:55.130Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:44:55.130Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:44:55.130Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:44:55.130Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:44:55.130Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:44:55.130Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (60132.576 ms) ======
[2025-09-04T06:44:55.130Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-04T06:44:55.856Z] GC before operation: completed in 810.173 ms, heap usage 220.699 MB -> 90.649 MB.
[2025-09-04T06:45:04.714Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:45:13.588Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:45:22.571Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:45:31.448Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:45:36.197Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:45:42.069Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:45:47.950Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:45:53.992Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:45:54.323Z] 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.
[2025-09-04T06:45:54.323Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:45:55.022Z] Top recommended movies for user id 72:
[2025-09-04T06:45:55.022Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:45:55.022Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:45:55.022Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:45:55.022Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:45:55.022Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:45:55.022Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (59309.226 ms) ======
[2025-09-04T06:45:55.022Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-04T06:45:55.729Z] GC before operation: completed in 815.800 ms, heap usage 230.278 MB -> 90.418 MB.
[2025-09-04T06:46:04.594Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:46:13.477Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:46:22.340Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:46:31.215Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:46:36.098Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:46:41.984Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:46:47.876Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:46:52.615Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:46:54.284Z] 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.
[2025-09-04T06:46:54.284Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:46:55.008Z] Top recommended movies for user id 72:
[2025-09-04T06:46:55.008Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:46:55.008Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:46:55.008Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:46:55.008Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:46:55.008Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:46:55.008Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (59012.789 ms) ======
[2025-09-04T06:46:55.008Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-04T06:46:55.727Z] GC before operation: completed in 822.028 ms, heap usage 132.048 MB -> 90.636 MB.
[2025-09-04T06:47:04.606Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:47:13.568Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:47:22.433Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:47:31.349Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:47:37.236Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:47:43.121Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:47:49.011Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:47:53.942Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:47:55.083Z] 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.
[2025-09-04T06:47:55.409Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:47:56.115Z] Top recommended movies for user id 72:
[2025-09-04T06:47:56.115Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:47:56.115Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:47:56.115Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:47:56.115Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:47:56.115Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:47:56.115Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (60215.966 ms) ======
[2025-09-04T06:47:56.115Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-04T06:47:56.836Z] GC before operation: completed in 826.425 ms, heap usage 121.400 MB -> 90.697 MB.
[2025-09-04T06:48:05.709Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:48:16.510Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:48:25.379Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:48:34.296Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:48:39.048Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:48:44.934Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:48:49.689Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:48:55.571Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:48:56.274Z] 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.
[2025-09-04T06:48:56.274Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:48:56.976Z] Top recommended movies for user id 72:
[2025-09-04T06:48:56.977Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:48:56.977Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:48:56.977Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:48:56.977Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:48:56.977Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:48:56.977Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (60218.264 ms) ======
[2025-09-04T06:48:56.977Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-04T06:48:57.702Z] GC before operation: completed in 823.395 ms, heap usage 397.261 MB -> 90.819 MB.
[2025-09-04T06:49:06.586Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:49:15.579Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:49:26.383Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:49:33.629Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:49:38.393Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:49:44.283Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:49:49.274Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:49:54.009Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:49:54.716Z] 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.
[2025-09-04T06:49:55.047Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:49:55.385Z] Top recommended movies for user id 72:
[2025-09-04T06:49:55.385Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:49:55.385Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:49:55.385Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:49:55.385Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:49:55.385Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:49:55.385Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (57675.251 ms) ======
[2025-09-04T06:49:55.385Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-04T06:49:56.561Z] GC before operation: completed in 841.572 ms, heap usage 273.427 MB -> 91.015 MB.
[2025-09-04T06:50:05.429Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:50:14.305Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:50:23.170Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:50:30.450Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:50:35.197Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:50:39.938Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:50:45.832Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:50:50.572Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:50:51.719Z] 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.
[2025-09-04T06:50:51.719Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:50:52.433Z] Top recommended movies for user id 72:
[2025-09-04T06:50:52.433Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:50:52.433Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:50:52.433Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:50:52.433Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:50:52.433Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:50:52.433Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (55940.845 ms) ======
[2025-09-04T06:50:52.433Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-04T06:50:53.151Z] GC before operation: completed in 849.282 ms, heap usage 413.810 MB -> 90.846 MB.
[2025-09-04T06:51:02.096Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:51:10.975Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:51:19.847Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:51:28.722Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:51:33.463Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:51:39.350Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:51:44.266Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:51:50.179Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:51:50.891Z] 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.
[2025-09-04T06:51:50.891Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:51:51.613Z] Top recommended movies for user id 72:
[2025-09-04T06:51:51.613Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:51:51.613Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:51:51.613Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:51:51.613Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:51:51.613Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:51:51.613Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (58327.628 ms) ======
[2025-09-04T06:51:51.613Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-04T06:51:52.343Z] GC before operation: completed in 819.589 ms, heap usage 401.761 MB -> 90.929 MB.
[2025-09-04T06:52:01.214Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:52:10.093Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:52:18.958Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:52:27.846Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:52:32.574Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:52:38.464Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:52:44.345Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:52:49.096Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:52:50.755Z] 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.
[2025-09-04T06:52:50.755Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:52:51.087Z] Top recommended movies for user id 72:
[2025-09-04T06:52:51.087Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:52:51.087Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:52:51.087Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:52:51.087Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:52:51.087Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:52:51.087Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (58937.149 ms) ======
[2025-09-04T06:52:51.087Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-04T06:52:52.258Z] GC before operation: completed in 832.047 ms, heap usage 168.645 MB -> 90.596 MB.
[2025-09-04T06:53:01.249Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:53:10.118Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:53:17.385Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:53:24.644Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:53:30.538Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:53:35.276Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:53:40.073Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:53:45.954Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:53:45.954Z] 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.
[2025-09-04T06:53:45.954Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:53:46.680Z] Top recommended movies for user id 72:
[2025-09-04T06:53:46.680Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:53:46.680Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:53:46.680Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:53:46.680Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:53:46.680Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:53:46.680Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (54543.952 ms) ======
[2025-09-04T06:53:46.680Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-04T06:53:47.418Z] GC before operation: completed in 869.689 ms, heap usage 855.457 MB -> 95.031 MB.
[2025-09-04T06:53:56.301Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:54:05.170Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:54:12.411Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:54:19.780Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:54:24.518Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:54:30.405Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:54:35.136Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:54:39.867Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:54:40.194Z] 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.
[2025-09-04T06:54:40.194Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:54:40.896Z] Top recommended movies for user id 72:
[2025-09-04T06:54:40.896Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:54:40.896Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:54:40.896Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:54:40.896Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:54:40.896Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:54:40.896Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (53499.940 ms) ======
[2025-09-04T06:54:45.632Z] -----------------------------------
[2025-09-04T06:54:45.632Z] renaissance-movie-lens_0_PASSED
[2025-09-04T06:54:45.632Z] -----------------------------------
[2025-09-04T06:54:45.632Z]
[2025-09-04T06:54:45.632Z] TEST TEARDOWN:
[2025-09-04T06:54:45.632Z] Nothing to be done for teardown.
[2025-09-04T06:54:45.632Z] renaissance-movie-lens_0 Finish Time: Thu Sep 4 06:54:44 2025 Epoch Time (ms): 1756968884819