renaissance-movie-lens_0
[2025-09-04T06:28:05.265Z] Running test renaissance-movie-lens_0 ...
[2025-09-04T06:28:05.265Z] ===============================================
[2025-09-04T06:28:05.265Z] renaissance-movie-lens_0 Start Time: Thu Sep 4 06:28:05 2025 Epoch Time (ms): 1756967285100
[2025-09-04T06:28:05.265Z] variation: NoOptions
[2025-09-04T06:28:05.265Z] JVM_OPTIONS:
[2025-09-04T06:28:05.265Z] { \
[2025-09-04T06:28:05.265Z] echo ""; echo "TEST SETUP:"; \
[2025-09-04T06:28:05.265Z] echo "Nothing to be done for setup."; \
[2025-09-04T06:28:05.265Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17569652695027/renaissance-movie-lens_0"; \
[2025-09-04T06:28:05.265Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17569652695027/renaissance-movie-lens_0"; \
[2025-09-04T06:28:05.265Z] echo ""; echo "TESTING:"; \
[2025-09-04T06:28:05.265Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17569652695027/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-04T06:28:05.265Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17569652695027/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-04T06:28:05.265Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-04T06:28:05.265Z] echo "Nothing to be done for teardown."; \
[2025-09-04T06:28:05.265Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17569652695027/TestTargetResult";
[2025-09-04T06:28:05.265Z]
[2025-09-04T06:28:05.265Z] TEST SETUP:
[2025-09-04T06:28:05.265Z] Nothing to be done for setup.
[2025-09-04T06:28:05.265Z]
[2025-09-04T06:28:05.265Z] TESTING:
[2025-09-04T06:28:13.512Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-09-04T06:28:25.215Z] 06:28:25.117 WARN [dispatcher-event-loop-1] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-04T06:28:29.834Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-04T06:28:30.604Z] Training: 60056, validation: 20285, test: 19854
[2025-09-04T06:28:30.604Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-04T06:28:31.385Z] GC before operation: completed in 252.567 ms, heap usage 405.884 MB -> 75.875 MB.
[2025-09-04T06:28:43.113Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:28:48.706Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:28:53.296Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:28:56.159Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:28:57.750Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:28:59.327Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:29:01.783Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:29:03.362Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:29:03.362Z] 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.
[2025-09-04T06:29:04.124Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:29:04.124Z] Top recommended movies for user id 72:
[2025-09-04T06:29:04.124Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:29:04.124Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:29:04.124Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:29:04.124Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:29:04.124Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:29:04.124Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (33021.710 ms) ======
[2025-09-04T06:29:04.124Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-04T06:29:04.124Z] GC before operation: completed in 138.824 ms, heap usage 115.865 MB -> 90.961 MB.
[2025-09-04T06:29:07.516Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:29:09.963Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:29:12.421Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:29:15.820Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:29:16.585Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:29:18.165Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:29:19.747Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:29:21.324Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:29:22.086Z] 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.
[2025-09-04T06:29:22.086Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:29:22.086Z] Top recommended movies for user id 72:
[2025-09-04T06:29:22.086Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:29:22.086Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:29:22.086Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:29:22.086Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:29:22.086Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:29:22.086Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17910.304 ms) ======
[2025-09-04T06:29:22.086Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-04T06:29:22.086Z] GC before operation: completed in 122.302 ms, heap usage 513.826 MB -> 88.853 MB.
[2025-09-04T06:29:24.530Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:29:27.053Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:29:30.445Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:29:32.898Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:29:33.662Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:29:35.368Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:29:36.942Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:29:38.526Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:29:39.801Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-04T06:29:39.801Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:29:39.801Z] Top recommended movies for user id 72:
[2025-09-04T06:29:39.801Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:29:39.801Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:29:39.801Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:29:39.801Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:29:39.801Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:29:39.801Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16870.195 ms) ======
[2025-09-04T06:29:39.801Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-04T06:29:39.801Z] GC before operation: completed in 103.099 ms, heap usage 503.377 MB -> 89.550 MB.
[2025-09-04T06:29:41.374Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:29:43.831Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:29:46.280Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:29:48.725Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:29:50.303Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:29:51.876Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:29:53.457Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:29:55.039Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:29:55.039Z] 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.
[2025-09-04T06:29:55.039Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:29:55.798Z] Top recommended movies for user id 72:
[2025-09-04T06:29:55.798Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:29:55.798Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:29:55.798Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:29:55.798Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:29:55.798Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:29:55.798Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16275.799 ms) ======
[2025-09-04T06:29:55.798Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-04T06:29:55.798Z] GC before operation: completed in 102.374 ms, heap usage 385.079 MB -> 89.604 MB.
[2025-09-04T06:29:58.250Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:30:00.704Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:30:03.185Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:30:05.634Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:30:07.206Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:30:08.830Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:30:10.398Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:30:11.977Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:30:11.978Z] 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.
[2025-09-04T06:30:11.978Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:30:12.737Z] Top recommended movies for user id 72:
[2025-09-04T06:30:12.737Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:30:12.737Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:30:12.737Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:30:12.737Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:30:12.737Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:30:12.737Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16862.203 ms) ======
[2025-09-04T06:30:12.737Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-04T06:30:12.737Z] GC before operation: completed in 104.076 ms, heap usage 494.822 MB -> 89.777 MB.
[2025-09-04T06:30:15.185Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:30:17.646Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:30:19.226Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:30:21.692Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:30:23.271Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:30:24.843Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:30:27.012Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:30:27.774Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:30:28.535Z] 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.
[2025-09-04T06:30:28.535Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:30:28.535Z] Top recommended movies for user id 72:
[2025-09-04T06:30:28.535Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:30:28.535Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:30:28.535Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:30:28.535Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:30:28.535Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:30:28.535Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15811.089 ms) ======
[2025-09-04T06:30:28.535Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-04T06:30:28.535Z] GC before operation: completed in 107.597 ms, heap usage 172.449 MB -> 89.655 MB.
[2025-09-04T06:30:30.981Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:30:33.427Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:30:35.882Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:30:37.457Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:30:39.028Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:30:40.598Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:30:42.178Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:30:42.938Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:30:43.697Z] 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.
[2025-09-04T06:30:43.697Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:30:43.697Z] Top recommended movies for user id 72:
[2025-09-04T06:30:43.697Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:30:43.697Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:30:43.697Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:30:43.697Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:30:43.697Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:30:43.697Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (15122.045 ms) ======
[2025-09-04T06:30:43.697Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-04T06:30:43.697Z] GC before operation: completed in 106.784 ms, heap usage 182.031 MB -> 89.657 MB.
[2025-09-04T06:30:46.146Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:30:48.585Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:30:51.032Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:30:52.601Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:30:54.173Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:30:55.754Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:30:57.327Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:30:58.086Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:30:58.848Z] 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.
[2025-09-04T06:30:58.848Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:30:58.848Z] Top recommended movies for user id 72:
[2025-09-04T06:30:58.848Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:30:58.849Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:30:58.849Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:30:58.849Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:30:58.849Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:30:58.849Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15074.066 ms) ======
[2025-09-04T06:30:58.849Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-04T06:30:58.849Z] GC before operation: completed in 101.470 ms, heap usage 629.549 MB -> 93.707 MB.
[2025-09-04T06:31:01.288Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:31:03.735Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:31:06.177Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:31:08.624Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:31:09.887Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:31:11.459Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:31:13.035Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:31:13.797Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:31:14.562Z] 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.
[2025-09-04T06:31:14.562Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:31:14.562Z] Top recommended movies for user id 72:
[2025-09-04T06:31:14.562Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:31:14.562Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:31:14.562Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:31:14.562Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:31:14.562Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:31:14.562Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15688.284 ms) ======
[2025-09-04T06:31:14.562Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-04T06:31:14.562Z] GC before operation: completed in 110.630 ms, heap usage 521.290 MB -> 90.213 MB.
[2025-09-04T06:31:17.008Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:31:19.454Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:31:21.903Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:31:24.363Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:31:25.129Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:31:26.778Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:31:28.352Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:31:29.116Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:31:29.877Z] 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.
[2025-09-04T06:31:29.877Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:31:29.877Z] Top recommended movies for user id 72:
[2025-09-04T06:31:29.877Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:31:29.877Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:31:29.877Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:31:29.877Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:31:29.877Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:31:29.877Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (15088.875 ms) ======
[2025-09-04T06:31:29.877Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-04T06:31:29.877Z] GC before operation: completed in 101.158 ms, heap usage 500.418 MB -> 90.445 MB.
[2025-09-04T06:31:32.328Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:31:34.782Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:31:37.225Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:31:38.797Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:31:40.375Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:31:41.948Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:31:43.526Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:31:44.293Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:31:45.052Z] 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.
[2025-09-04T06:31:45.052Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:31:45.052Z] Top recommended movies for user id 72:
[2025-09-04T06:31:45.052Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:31:45.052Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:31:45.052Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:31:45.052Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:31:45.052Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:31:45.052Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15057.522 ms) ======
[2025-09-04T06:31:45.052Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-04T06:31:45.052Z] GC before operation: completed in 98.213 ms, heap usage 258.643 MB -> 89.786 MB.
[2025-09-04T06:31:47.498Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:31:49.073Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:31:51.528Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:31:54.512Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:31:55.275Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:31:56.848Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:31:58.434Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:31:59.199Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:31:59.963Z] 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.
[2025-09-04T06:31:59.963Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:31:59.963Z] Top recommended movies for user id 72:
[2025-09-04T06:31:59.963Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:31:59.963Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:31:59.963Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:31:59.963Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:31:59.963Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:31:59.963Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14870.867 ms) ======
[2025-09-04T06:31:59.963Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-04T06:31:59.963Z] GC before operation: completed in 106.223 ms, heap usage 417.056 MB -> 90.253 MB.
[2025-09-04T06:32:02.414Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:32:04.855Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:32:07.310Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:32:08.879Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:32:10.456Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:32:12.036Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:32:12.802Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:32:14.375Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:32:14.375Z] 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.
[2025-09-04T06:32:15.134Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:32:15.134Z] Top recommended movies for user id 72:
[2025-09-04T06:32:15.134Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:32:15.134Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:32:15.134Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:32:15.134Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:32:15.134Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:32:15.134Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14906.494 ms) ======
[2025-09-04T06:32:15.134Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-04T06:32:15.134Z] GC before operation: completed in 102.542 ms, heap usage 443.298 MB -> 90.347 MB.
[2025-09-04T06:32:17.591Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:32:19.162Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:32:21.618Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:32:24.072Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:32:25.647Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:32:26.408Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:32:27.984Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:32:29.560Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:32:30.319Z] 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.
[2025-09-04T06:32:30.319Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:32:30.319Z] Top recommended movies for user id 72:
[2025-09-04T06:32:30.319Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:32:30.319Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:32:30.319Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:32:30.319Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:32:30.319Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:32:30.319Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15108.382 ms) ======
[2025-09-04T06:32:30.319Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-04T06:32:30.319Z] GC before operation: completed in 108.962 ms, heap usage 314.040 MB -> 90.069 MB.
[2025-09-04T06:32:32.760Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:32:34.340Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:32:36.793Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:32:38.881Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:32:40.461Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:32:42.036Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:32:43.613Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:32:44.377Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:32:45.140Z] 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.
[2025-09-04T06:32:45.140Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:32:45.140Z] Top recommended movies for user id 72:
[2025-09-04T06:32:45.140Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:32:45.140Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:32:45.140Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:32:45.140Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:32:45.140Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:32:45.140Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14760.942 ms) ======
[2025-09-04T06:32:45.140Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-04T06:32:45.140Z] GC before operation: completed in 108.464 ms, heap usage 167.194 MB -> 90.099 MB.
[2025-09-04T06:32:47.589Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:32:49.170Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:32:51.628Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:32:54.080Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:32:55.661Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:32:56.422Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:32:57.996Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:32:59.582Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:32:59.582Z] 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.
[2025-09-04T06:32:59.582Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:32:59.582Z] Top recommended movies for user id 72:
[2025-09-04T06:32:59.582Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:32:59.582Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:32:59.582Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:32:59.582Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:32:59.582Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:32:59.582Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14796.103 ms) ======
[2025-09-04T06:32:59.582Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-04T06:33:00.342Z] GC before operation: completed in 108.291 ms, heap usage 752.308 MB -> 93.923 MB.
[2025-09-04T06:33:01.921Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:33:04.381Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:33:06.842Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:33:09.288Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:33:10.867Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:33:11.629Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:33:13.207Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:33:14.781Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:33:14.781Z] 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.
[2025-09-04T06:33:14.781Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:33:14.781Z] Top recommended movies for user id 72:
[2025-09-04T06:33:14.781Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:33:14.781Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:33:14.781Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:33:14.781Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:33:14.781Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:33:14.781Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (14877.074 ms) ======
[2025-09-04T06:33:14.781Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-04T06:33:14.782Z] GC before operation: completed in 101.263 ms, heap usage 446.549 MB -> 90.311 MB.
[2025-09-04T06:33:17.232Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:33:19.680Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:33:22.133Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:33:23.709Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:33:25.791Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:33:26.559Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:33:28.137Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:33:29.717Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:33:29.717Z] 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.
[2025-09-04T06:33:29.717Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:33:29.717Z] Top recommended movies for user id 72:
[2025-09-04T06:33:29.717Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:33:29.717Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:33:29.717Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:33:29.717Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:33:29.717Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:33:29.717Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14779.118 ms) ======
[2025-09-04T06:33:29.717Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-04T06:33:29.717Z] GC before operation: completed in 104.711 ms, heap usage 432.405 MB -> 90.189 MB.
[2025-09-04T06:33:32.173Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:33:34.624Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:33:36.199Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:33:38.651Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:33:40.225Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:33:40.991Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:33:42.563Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:33:44.137Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:33:44.138Z] 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.
[2025-09-04T06:33:44.138Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:33:44.138Z] Top recommended movies for user id 72:
[2025-09-04T06:33:44.138Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:33:44.138Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:33:44.138Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:33:44.138Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:33:44.138Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:33:44.138Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14426.751 ms) ======
[2025-09-04T06:33:44.138Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-04T06:33:44.138Z] GC before operation: completed in 108.026 ms, heap usage 426.768 MB -> 90.217 MB.
[2025-09-04T06:33:46.587Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-04T06:33:49.029Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-04T06:33:50.563Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-04T06:33:52.950Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-04T06:33:54.479Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-04T06:33:56.022Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-04T06:33:58.450Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-04T06:33:59.986Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-04T06:33:59.986Z] 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.
[2025-09-04T06:33:59.986Z] The best model improves the baseline by 14.52%.
[2025-09-04T06:34:00.724Z] Top recommended movies for user id 72:
[2025-09-04T06:34:00.724Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-04T06:34:00.724Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-04T06:34:00.724Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-04T06:34:00.724Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-04T06:34:00.724Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-04T06:34:00.724Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16021.234 ms) ======
[2025-09-04T06:34:00.724Z] -----------------------------------
[2025-09-04T06:34:00.724Z] renaissance-movie-lens_0_PASSED
[2025-09-04T06:34:00.724Z] -----------------------------------
[2025-09-04T06:34:00.724Z]
[2025-09-04T06:34:00.724Z] TEST TEARDOWN:
[2025-09-04T06:34:00.724Z] Nothing to be done for teardown.
[2025-09-04T06:34:00.724Z] renaissance-movie-lens_0 Finish Time: Thu Sep 4 06:34:00 2025 Epoch Time (ms): 1756967640409