renaissance-movie-lens_0
[2025-12-27T17:53:55.931Z] Running test renaissance-movie-lens_0 ...
[2025-12-27T17:53:55.931Z] ===============================================
[2025-12-27T17:53:55.931Z] renaissance-movie-lens_0 Start Time: Sat Dec 27 17:53:55 2025 Epoch Time (ms): 1766858035197
[2025-12-27T17:53:55.931Z] variation: NoOptions
[2025-12-27T17:53:55.931Z] JVM_OPTIONS:
[2025-12-27T17:53:55.931Z] { \
[2025-12-27T17:53:55.931Z] echo ""; echo "TEST SETUP:"; \
[2025-12-27T17:53:55.931Z] echo "Nothing to be done for setup."; \
[2025-12-27T17:53:55.931Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17668568543754/renaissance-movie-lens_0"; \
[2025-12-27T17:53:55.931Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17668568543754/renaissance-movie-lens_0"; \
[2025-12-27T17:53:55.931Z] echo ""; echo "TESTING:"; \
[2025-12-27T17:53:55.931Z] "/home/jenkins/workspace/Test_openjdk25_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_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17668568543754/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-12-27T17:53:55.931Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17668568543754/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-12-27T17:53:55.931Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-12-27T17:53:55.931Z] echo "Nothing to be done for teardown."; \
[2025-12-27T17:53:55.931Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/../TKG/output_17668568543754/TestTargetResult";
[2025-12-27T17:53:55.931Z]
[2025-12-27T17:53:55.931Z] TEST SETUP:
[2025-12-27T17:53:55.931Z] Nothing to be done for setup.
[2025-12-27T17:53:55.931Z]
[2025-12-27T17:53:55.931Z] TESTING:
[2025-12-27T17:53:55.931Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-12-27T17:53:55.931Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_x86-64_alpine-linux/aqa-tests/TKG/output_17668568543754/renaissance-movie-lens_0/launcher-175355-6379566548577254756/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-12-27T17:53:55.931Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-12-27T17:53:55.931Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-12-27T17:54:00.751Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-12-27T17:54:07.547Z] 17:54:06.312 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.
[2025-12-27T17:54:10.877Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-12-27T17:54:10.877Z] Training: 60056, validation: 20285, test: 19854
[2025-12-27T17:54:10.877Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-12-27T17:54:10.877Z] GC before operation: completed in 134.090 ms, heap usage 432.571 MB -> 76.004 MB.
[2025-12-27T17:54:17.730Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:54:21.058Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:54:25.402Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:54:27.810Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:54:30.218Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:54:31.764Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:54:33.315Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:54:34.865Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:54:34.865Z] 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.
[2025-12-27T17:54:34.865Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:54:35.615Z] Top recommended movies for user id 72:
[2025-12-27T17:54:35.615Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:54:35.615Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:54:35.615Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:54:35.615Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:54:35.615Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:54:35.615Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24237.997 ms) ======
[2025-12-27T17:54:35.615Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-12-27T17:54:35.615Z] GC before operation: completed in 117.919 ms, heap usage 385.303 MB -> 86.621 MB.
[2025-12-27T17:54:38.024Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:54:41.347Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:54:44.226Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:54:46.632Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:54:48.175Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:54:49.713Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:54:51.254Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:54:52.795Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:54:52.795Z] 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.
[2025-12-27T17:54:52.795Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:54:52.795Z] Top recommended movies for user id 72:
[2025-12-27T17:54:52.795Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:54:52.795Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:54:52.795Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:54:52.795Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:54:52.795Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:54:52.795Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17640.527 ms) ======
[2025-12-27T17:54:52.795Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-12-27T17:54:52.795Z] GC before operation: completed in 119.441 ms, heap usage 375.152 MB -> 88.745 MB.
[2025-12-27T17:54:56.113Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:54:58.546Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:55:00.931Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:55:03.337Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:55:05.734Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:55:06.480Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:55:08.065Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:55:09.612Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:55:10.357Z] 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.
[2025-12-27T17:55:10.357Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:55:10.357Z] Top recommended movies for user id 72:
[2025-12-27T17:55:10.357Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:55:10.357Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:55:10.357Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:55:10.357Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:55:10.357Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:55:10.357Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17275.118 ms) ======
[2025-12-27T17:55:10.357Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-12-27T17:55:10.357Z] GC before operation: completed in 116.699 ms, heap usage 95.785 MB -> 89.453 MB.
[2025-12-27T17:55:14.699Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:55:30.507Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:55:33.167Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:55:35.582Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:55:37.130Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:55:38.676Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:55:40.217Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:55:41.761Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:55:41.761Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T17:55:41.761Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:55:41.761Z] Top recommended movies for user id 72:
[2025-12-27T17:55:41.761Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:55:41.761Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:55:41.761Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:55:41.761Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:55:41.761Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:55:41.761Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (31460.440 ms) ======
[2025-12-27T17:55:41.761Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-12-27T17:55:42.509Z] GC before operation: completed in 112.581 ms, heap usage 188.017 MB -> 89.601 MB.
[2025-12-27T17:55:44.914Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:55:47.311Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:55:49.726Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:55:52.131Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:55:54.533Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:55:55.279Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:55:57.680Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:55:58.428Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:55:59.176Z] 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.
[2025-12-27T17:55:59.177Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:55:59.177Z] Top recommended movies for user id 72:
[2025-12-27T17:55:59.177Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:55:59.177Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:55:59.177Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:55:59.177Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:55:59.177Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:55:59.177Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (17103.881 ms) ======
[2025-12-27T17:55:59.177Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-12-27T17:55:59.177Z] GC before operation: completed in 109.265 ms, heap usage 148.909 MB -> 89.364 MB.
[2025-12-27T17:56:01.581Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:56:03.991Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:56:06.400Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:56:08.921Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:56:10.464Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:56:12.496Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:56:13.242Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:56:14.789Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:56:14.789Z] 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.
[2025-12-27T17:56:14.789Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:56:14.789Z] Top recommended movies for user id 72:
[2025-12-27T17:56:14.789Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:56:14.790Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:56:14.790Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:56:14.790Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:56:14.790Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:56:14.790Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15681.484 ms) ======
[2025-12-27T17:56:14.790Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-12-27T17:56:14.790Z] GC before operation: completed in 122.173 ms, heap usage 367.073 MB -> 90.069 MB.
[2025-12-27T17:56:18.117Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:56:19.664Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:56:22.068Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:56:24.475Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:56:25.228Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:56:26.767Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:56:28.310Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:56:29.065Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:56:29.813Z] 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.
[2025-12-27T17:56:29.813Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:56:29.813Z] Top recommended movies for user id 72:
[2025-12-27T17:56:29.813Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:56:29.813Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:56:29.813Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:56:29.813Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:56:29.813Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:56:29.813Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14514.601 ms) ======
[2025-12-27T17:56:29.813Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-12-27T17:56:29.813Z] GC before operation: completed in 120.315 ms, heap usage 440.018 MB -> 90.162 MB.
[2025-12-27T17:56:32.229Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:56:33.780Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:56:36.185Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:56:38.593Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:56:39.351Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:56:40.893Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:56:42.439Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:56:43.193Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:56:43.943Z] 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.
[2025-12-27T17:56:43.943Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:56:43.943Z] Top recommended movies for user id 72:
[2025-12-27T17:56:43.943Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:56:43.943Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:56:43.943Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:56:43.943Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:56:43.943Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:56:43.943Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (13981.065 ms) ======
[2025-12-27T17:56:43.943Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-12-27T17:56:43.943Z] GC before operation: completed in 120.792 ms, heap usage 255.448 MB -> 89.999 MB.
[2025-12-27T17:56:46.347Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:56:47.898Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:56:50.305Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:56:52.710Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:56:53.459Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:56:55.005Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:56:55.759Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:56:57.814Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:56:57.814Z] 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.
[2025-12-27T17:56:57.814Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:56:57.814Z] Top recommended movies for user id 72:
[2025-12-27T17:56:57.814Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:56:57.814Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:56:57.814Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:56:57.814Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:56:57.814Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:56:57.814Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (13971.829 ms) ======
[2025-12-27T17:56:57.814Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-12-27T17:56:57.814Z] GC before operation: completed in 125.981 ms, heap usage 362.429 MB -> 90.109 MB.
[2025-12-27T17:57:00.222Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:57:02.631Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:57:05.033Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:57:06.578Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:57:08.175Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:57:09.726Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:57:10.478Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:57:12.027Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:57:12.027Z] 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.
[2025-12-27T17:57:12.027Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:57:12.771Z] Top recommended movies for user id 72:
[2025-12-27T17:57:12.771Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:57:12.771Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:57:12.771Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:57:12.771Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:57:12.771Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:57:12.771Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14419.025 ms) ======
[2025-12-27T17:57:12.771Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-12-27T17:57:12.771Z] GC before operation: completed in 117.003 ms, heap usage 162.000 MB -> 90.100 MB.
[2025-12-27T17:57:15.169Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:57:16.716Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:57:19.117Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:57:21.528Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:57:23.072Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:57:23.823Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:57:25.365Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:57:26.908Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:57:26.908Z] 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.
[2025-12-27T17:57:26.908Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:57:26.908Z] Top recommended movies for user id 72:
[2025-12-27T17:57:26.908Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:57:26.908Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:57:26.908Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:57:26.908Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:57:26.908Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:57:26.908Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14421.721 ms) ======
[2025-12-27T17:57:26.908Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-12-27T17:57:26.908Z] GC before operation: completed in 118.799 ms, heap usage 439.747 MB -> 90.196 MB.
[2025-12-27T17:57:29.314Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:57:32.209Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:57:33.758Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:57:36.160Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:57:37.708Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:57:39.249Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:57:40.797Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:57:42.342Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:57:42.342Z] 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.
[2025-12-27T17:57:42.342Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:57:42.342Z] Top recommended movies for user id 72:
[2025-12-27T17:57:42.342Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:57:42.342Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:57:42.342Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:57:42.343Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:57:42.343Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:57:42.343Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15311.159 ms) ======
[2025-12-27T17:57:42.343Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-12-27T17:57:42.343Z] GC before operation: completed in 127.397 ms, heap usage 366.510 MB -> 90.401 MB.
[2025-12-27T17:57:44.748Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:57:47.162Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:57:49.569Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:57:51.972Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:57:53.518Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:57:55.078Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:57:55.820Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:57:57.365Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:57:58.116Z] 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.
[2025-12-27T17:57:58.116Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:57:58.116Z] Top recommended movies for user id 72:
[2025-12-27T17:57:58.116Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:57:58.116Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:57:58.116Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:57:58.116Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:57:58.116Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:57:58.116Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15439.059 ms) ======
[2025-12-27T17:57:58.116Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-12-27T17:57:58.116Z] GC before operation: completed in 107.364 ms, heap usage 147.899 MB -> 90.039 MB.
[2025-12-27T17:58:00.520Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:58:02.934Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:58:05.332Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:58:07.744Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:58:08.488Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:58:10.032Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:58:11.576Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:58:13.614Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:58:13.614Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-12-27T17:58:13.614Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:58:13.614Z] Top recommended movies for user id 72:
[2025-12-27T17:58:13.614Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:58:13.614Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:58:13.614Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:58:13.614Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:58:13.614Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:58:13.614Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (15154.064 ms) ======
[2025-12-27T17:58:13.614Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-12-27T17:58:13.614Z] GC before operation: completed in 115.080 ms, heap usage 469.161 MB -> 90.275 MB.
[2025-12-27T17:58:16.015Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:58:17.558Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:58:19.969Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:58:22.374Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:58:23.924Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:58:25.473Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:58:26.223Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:58:27.767Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:58:27.768Z] 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.
[2025-12-27T17:58:27.768Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:58:27.768Z] Top recommended movies for user id 72:
[2025-12-27T17:58:27.768Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:58:27.768Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:58:27.768Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:58:27.768Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:58:27.768Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:58:27.768Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14590.303 ms) ======
[2025-12-27T17:58:27.768Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-12-27T17:58:27.768Z] GC before operation: completed in 110.058 ms, heap usage 441.690 MB -> 90.656 MB.
[2025-12-27T17:58:30.171Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:58:32.568Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:58:34.984Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:58:36.533Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:58:38.076Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:58:38.825Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:58:40.362Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:58:41.906Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:58:41.907Z] 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.
[2025-12-27T17:58:41.907Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:58:41.907Z] Top recommended movies for user id 72:
[2025-12-27T17:58:41.907Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:58:41.907Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:58:41.907Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:58:41.907Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:58:41.907Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:58:41.907Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (13888.951 ms) ======
[2025-12-27T17:58:41.907Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-12-27T17:58:41.907Z] GC before operation: completed in 119.511 ms, heap usage 209.251 MB -> 90.121 MB.
[2025-12-27T17:58:44.306Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:58:46.703Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:58:49.108Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:58:51.514Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:58:53.063Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:58:53.810Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:58:55.359Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:58:57.405Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:58:57.405Z] 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.
[2025-12-27T17:58:57.405Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:58:57.405Z] Top recommended movies for user id 72:
[2025-12-27T17:58:57.405Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:58:57.405Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:58:57.405Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:58:57.405Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:58:57.406Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:58:57.406Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15098.775 ms) ======
[2025-12-27T17:58:57.406Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-12-27T17:58:57.406Z] GC before operation: completed in 115.089 ms, heap usage 398.841 MB -> 90.475 MB.
[2025-12-27T17:58:59.803Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:59:02.207Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:59:03.755Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:59:06.159Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:59:07.703Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:59:09.244Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:59:09.992Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:59:11.535Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:59:11.535Z] 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.
[2025-12-27T17:59:12.277Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:59:12.277Z] Top recommended movies for user id 72:
[2025-12-27T17:59:12.277Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:59:12.277Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:59:12.277Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:59:12.277Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:59:12.278Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:59:12.278Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14770.273 ms) ======
[2025-12-27T17:59:12.278Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-12-27T17:59:12.278Z] GC before operation: completed in 106.541 ms, heap usage 361.916 MB -> 90.313 MB.
[2025-12-27T17:59:14.679Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:59:16.346Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:59:18.749Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:59:21.150Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:59:22.697Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:59:24.239Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:59:24.988Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:59:26.533Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:59:27.276Z] 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.
[2025-12-27T17:59:27.276Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:59:27.276Z] Top recommended movies for user id 72:
[2025-12-27T17:59:27.276Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:59:27.276Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:59:27.276Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:59:27.276Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:59:27.276Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:59:27.276Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14981.554 ms) ======
[2025-12-27T17:59:27.276Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-12-27T17:59:27.276Z] GC before operation: completed in 105.544 ms, heap usage 373.571 MB -> 90.511 MB.
[2025-12-27T17:59:29.674Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-12-27T17:59:31.209Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-12-27T17:59:33.608Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-12-27T17:59:36.006Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-12-27T17:59:38.029Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-12-27T17:59:38.777Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-12-27T17:59:40.322Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-12-27T17:59:41.865Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-12-27T17:59:41.865Z] 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.
[2025-12-27T17:59:41.865Z] The best model improves the baseline by 14.52%.
[2025-12-27T17:59:41.865Z] Top recommended movies for user id 72:
[2025-12-27T17:59:41.865Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-12-27T17:59:41.865Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-12-27T17:59:41.865Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-12-27T17:59:41.865Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-12-27T17:59:41.865Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-12-27T17:59:41.865Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15025.082 ms) ======
[2025-12-27T17:59:42.611Z] -----------------------------------
[2025-12-27T17:59:42.611Z] renaissance-movie-lens_0_PASSED
[2025-12-27T17:59:42.611Z] -----------------------------------
[2025-12-27T17:59:42.611Z]
[2025-12-27T17:59:42.611Z] TEST TEARDOWN:
[2025-12-27T17:59:42.611Z] Nothing to be done for teardown.
[2025-12-27T17:59:42.611Z] renaissance-movie-lens_0 Finish Time: Sat Dec 27 17:59:42 2025 Epoch Time (ms): 1766858382209