renaissance-movie-lens_0
[2025-09-05T17:49:55.237Z] Running test renaissance-movie-lens_0 ...
[2025-09-05T17:49:55.237Z] ===============================================
[2025-09-05T17:49:55.237Z] renaissance-movie-lens_0 Start Time: Fri Sep 5 17:49:54 2025 Epoch Time (ms): 1757094594364
[2025-09-05T17:49:55.237Z] variation: NoOptions
[2025-09-05T17:49:55.237Z] JVM_OPTIONS:
[2025-09-05T17:49:55.237Z] { \
[2025-09-05T17:49:55.237Z] echo ""; echo "TEST SETUP:"; \
[2025-09-05T17:49:55.237Z] echo "Nothing to be done for setup."; \
[2025-09-05T17:49:55.237Z] mkdir -p "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17570933885958/renaissance-movie-lens_0"; \
[2025-09-05T17:49:55.237Z] cd "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17570933885958/renaissance-movie-lens_0"; \
[2025-09-05T17:49:55.237Z] echo ""; echo "TESTING:"; \
[2025-09-05T17:49:55.237Z] "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17570933885958/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-09-05T17:49:55.238Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17570933885958/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-09-05T17:49:55.238Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-09-05T17:49:55.238Z] echo "Nothing to be done for teardown."; \
[2025-09-05T17:49:55.238Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17570933885958/TestTargetResult";
[2025-09-05T17:49:55.238Z]
[2025-09-05T17:49:55.238Z] TEST SETUP:
[2025-09-05T17:49:55.238Z] Nothing to be done for setup.
[2025-09-05T17:49:55.238Z]
[2025-09-05T17:49:55.238Z] TESTING:
[2025-09-05T17:49:55.238Z] WARNING: A terminally deprecated method in sun.misc.Unsafe has been called
[2025-09-05T17:49:55.238Z] WARNING: sun.misc.Unsafe::objectFieldOffset has been called by scala.runtime.LazyVals$ (file:/home/jenkins/workspace/Test_openjdk25_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/output_17570933885958/renaissance-movie-lens_0/launcher-174954-10421806321448305626/renaissance-harness_3/lib/scala3-library_3-3.3.4.jar)
[2025-09-05T17:49:55.238Z] WARNING: Please consider reporting this to the maintainers of class scala.runtime.LazyVals$
[2025-09-05T17:49:55.238Z] WARNING: sun.misc.Unsafe::objectFieldOffset will be removed in a future release
[2025-09-05T17:50:00.634Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-09-05T17:50:06.077Z] 17:50:05.903 WARN [dispatcher-event-loop-2] org.apache.spark.scheduler.TaskSetManager - Stage 8 contains a task of very large size (1401 KiB). The maximum recommended task size is 1000 KiB.
[2025-09-05T17:50:08.041Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-09-05T17:50:08.998Z] Training: 60056, validation: 20285, test: 19854
[2025-09-05T17:50:08.998Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-09-05T17:50:08.998Z] GC before operation: completed in 135.809 ms, heap usage 300.143 MB -> 75.822 MB.
[2025-09-05T17:50:13.888Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:50:16.930Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:50:19.967Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:50:22.997Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:50:24.962Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:50:25.919Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:50:27.882Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:50:29.847Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:50:29.847Z] 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.
[2025-09-05T17:50:29.847Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:50:29.847Z] Top recommended movies for user id 72:
[2025-09-05T17:50:29.847Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:50:29.847Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:50:29.847Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:50:29.847Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:50:29.847Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:50:29.847Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (21212.887 ms) ======
[2025-09-05T17:50:29.847Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-09-05T17:50:29.847Z] GC before operation: completed in 146.866 ms, heap usage 137.566 MB -> 98.582 MB.
[2025-09-05T17:50:32.876Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:50:34.839Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:50:37.883Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:50:39.871Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:50:41.835Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:50:43.798Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:50:44.753Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:50:46.717Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:50:46.717Z] 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.
[2025-09-05T17:50:46.717Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:50:46.717Z] Top recommended movies for user id 72:
[2025-09-05T17:50:46.717Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:50:46.717Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:50:46.717Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:50:46.717Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:50:46.717Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:50:46.717Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (16580.645 ms) ======
[2025-09-05T17:50:46.717Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-09-05T17:50:46.717Z] GC before operation: completed in 175.299 ms, heap usage 633.424 MB -> 92.495 MB.
[2025-09-05T17:50:49.748Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:50:51.712Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:50:54.744Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:50:56.713Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:50:58.679Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:50:59.639Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:51:01.608Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:51:02.569Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:51:03.534Z] 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.
[2025-09-05T17:51:03.534Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:51:03.534Z] Top recommended movies for user id 72:
[2025-09-05T17:51:03.534Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:51:03.534Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:51:03.534Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:51:03.534Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:51:03.534Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:51:03.534Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16556.876 ms) ======
[2025-09-05T17:51:03.534Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-09-05T17:51:03.534Z] GC before operation: completed in 121.459 ms, heap usage 376.807 MB -> 89.797 MB.
[2025-09-05T17:51:06.569Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:51:08.538Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:51:12.274Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:51:13.230Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:51:15.204Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:51:16.162Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:51:18.125Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:51:19.082Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:51:20.046Z] 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.
[2025-09-05T17:51:20.046Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:51:20.046Z] Top recommended movies for user id 72:
[2025-09-05T17:51:20.046Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:51:20.046Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:51:20.046Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:51:20.046Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:51:20.046Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:51:20.046Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (16214.622 ms) ======
[2025-09-05T17:51:20.046Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-09-05T17:51:20.046Z] GC before operation: completed in 107.213 ms, heap usage 323.771 MB -> 89.895 MB.
[2025-09-05T17:51:22.012Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:51:25.041Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:51:27.008Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:51:30.040Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:51:31.001Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:51:32.968Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:51:34.932Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:51:35.889Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:51:35.889Z] 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.
[2025-09-05T17:51:35.889Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:51:35.889Z] Top recommended movies for user id 72:
[2025-09-05T17:51:35.889Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:51:35.889Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:51:35.889Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:51:35.889Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:51:35.889Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:51:35.889Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16341.738 ms) ======
[2025-09-05T17:51:35.889Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-09-05T17:51:36.846Z] GC before operation: completed in 117.144 ms, heap usage 525.563 MB -> 90.113 MB.
[2025-09-05T17:51:38.812Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:51:40.777Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:51:43.809Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:51:45.774Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:51:47.737Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:51:48.694Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:51:50.660Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:51:51.617Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:51:51.617Z] 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.
[2025-09-05T17:51:51.617Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:51:51.617Z] Top recommended movies for user id 72:
[2025-09-05T17:51:51.617Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:51:51.617Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:51:51.617Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:51:51.617Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:51:51.617Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:51:51.617Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (15534.575 ms) ======
[2025-09-05T17:51:51.617Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-09-05T17:51:52.577Z] GC before operation: completed in 135.945 ms, heap usage 499.242 MB -> 90.420 MB.
[2025-09-05T17:51:54.541Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:51:56.510Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:51:58.473Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:52:01.504Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:52:02.460Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:52:03.416Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:52:05.504Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:52:06.459Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:52:06.460Z] 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.
[2025-09-05T17:52:06.460Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:52:06.460Z] Top recommended movies for user id 72:
[2025-09-05T17:52:06.460Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:52:06.460Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:52:06.460Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:52:06.460Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:52:06.460Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:52:06.460Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14662.092 ms) ======
[2025-09-05T17:52:06.460Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-09-05T17:52:06.460Z] GC before operation: completed in 116.850 ms, heap usage 449.834 MB -> 90.287 MB.
[2025-09-05T17:52:10.208Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:52:11.165Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:52:13.136Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:52:15.103Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:52:17.073Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:52:18.033Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:52:19.999Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:52:20.957Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:52:21.919Z] 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.
[2025-09-05T17:52:21.919Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:52:21.919Z] Top recommended movies for user id 72:
[2025-09-05T17:52:21.919Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:52:21.919Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:52:21.919Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:52:21.919Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:52:21.919Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:52:21.919Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (14790.119 ms) ======
[2025-09-05T17:52:21.919Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-09-05T17:52:21.919Z] GC before operation: completed in 122.541 ms, heap usage 449.353 MB -> 90.634 MB.
[2025-09-05T17:52:23.890Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:52:25.854Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:52:28.887Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:52:30.862Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:52:31.820Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:52:33.790Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:52:34.748Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:52:36.714Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:52:36.714Z] 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.
[2025-09-05T17:52:36.714Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:52:36.714Z] Top recommended movies for user id 72:
[2025-09-05T17:52:36.714Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:52:36.714Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:52:36.714Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:52:36.714Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:52:36.714Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:52:36.714Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (15130.201 ms) ======
[2025-09-05T17:52:36.714Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-09-05T17:52:36.714Z] GC before operation: completed in 131.341 ms, heap usage 241.875 MB -> 90.043 MB.
[2025-09-05T17:52:39.756Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:52:41.718Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:52:43.685Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:52:45.654Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:52:46.611Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:52:47.569Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:52:49.535Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:52:50.491Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:52:50.491Z] 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.
[2025-09-05T17:52:50.491Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:52:51.451Z] Top recommended movies for user id 72:
[2025-09-05T17:52:51.451Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:52:51.451Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:52:51.451Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:52:51.451Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:52:51.451Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:52:51.451Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (13879.380 ms) ======
[2025-09-05T17:52:51.451Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-09-05T17:52:51.451Z] GC before operation: completed in 107.894 ms, heap usage 227.115 MB -> 90.253 MB.
[2025-09-05T17:52:53.420Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:52:55.385Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:52:57.345Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:52:59.313Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:53:00.272Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:53:02.234Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:53:03.190Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:53:05.164Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:53:05.164Z] 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.
[2025-09-05T17:53:05.164Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:53:05.164Z] Top recommended movies for user id 72:
[2025-09-05T17:53:05.164Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:53:05.164Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:53:05.164Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:53:05.164Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:53:05.164Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:53:05.164Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (14240.557 ms) ======
[2025-09-05T17:53:05.164Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-09-05T17:53:05.164Z] GC before operation: completed in 116.105 ms, heap usage 520.269 MB -> 90.316 MB.
[2025-09-05T17:53:08.902Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:53:09.860Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:53:11.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:53:13.789Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:53:15.753Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:53:16.713Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:53:18.679Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:53:19.638Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:53:20.596Z] 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.
[2025-09-05T17:53:20.596Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:53:20.596Z] Top recommended movies for user id 72:
[2025-09-05T17:53:20.596Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:53:20.596Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:53:20.596Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:53:20.596Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:53:20.596Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:53:20.596Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (14942.155 ms) ======
[2025-09-05T17:53:20.596Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-09-05T17:53:20.596Z] GC before operation: completed in 118.186 ms, heap usage 98.014 MB -> 92.855 MB.
[2025-09-05T17:53:22.562Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:53:24.527Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:53:27.557Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:53:29.517Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:53:30.472Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:53:31.427Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:53:33.392Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:53:34.350Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:53:34.350Z] 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.
[2025-09-05T17:53:34.350Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:53:34.350Z] Top recommended movies for user id 72:
[2025-09-05T17:53:34.350Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:53:34.350Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:53:34.350Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:53:34.350Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:53:34.350Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:53:34.350Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (14116.134 ms) ======
[2025-09-05T17:53:34.350Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-09-05T17:53:34.350Z] GC before operation: completed in 107.894 ms, heap usage 371.612 MB -> 90.463 MB.
[2025-09-05T17:53:37.380Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:53:39.346Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:53:41.309Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:53:43.276Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:53:45.241Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:53:46.199Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:53:48.162Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:53:49.120Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:53:49.120Z] 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.
[2025-09-05T17:53:49.120Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:53:49.120Z] Top recommended movies for user id 72:
[2025-09-05T17:53:49.120Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:53:49.120Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:53:49.120Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:53:49.120Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:53:49.120Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:53:49.120Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14791.895 ms) ======
[2025-09-05T17:53:49.120Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-09-05T17:53:50.077Z] GC before operation: completed in 127.716 ms, heap usage 405.795 MB -> 90.335 MB.
[2025-09-05T17:53:52.042Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:53:54.017Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:53:55.992Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:53:59.024Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:53:59.982Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:54:00.939Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:54:02.904Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:54:03.862Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:54:04.860Z] 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.
[2025-09-05T17:54:04.860Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:54:04.860Z] Top recommended movies for user id 72:
[2025-09-05T17:54:04.860Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:54:04.860Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:54:04.860Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:54:04.860Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:54:04.860Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:54:04.860Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14883.444 ms) ======
[2025-09-05T17:54:04.860Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-09-05T17:54:04.860Z] GC before operation: completed in 118.737 ms, heap usage 205.538 MB -> 90.294 MB.
[2025-09-05T17:54:07.098Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:54:09.062Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:54:11.024Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:54:12.989Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:54:14.953Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:54:15.908Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:54:16.865Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:54:18.828Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:54:18.828Z] 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.
[2025-09-05T17:54:18.828Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:54:18.828Z] Top recommended movies for user id 72:
[2025-09-05T17:54:18.828Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:54:18.828Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:54:18.828Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:54:18.828Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:54:18.828Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:54:18.828Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14313.539 ms) ======
[2025-09-05T17:54:18.828Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-09-05T17:54:18.828Z] GC before operation: completed in 111.783 ms, heap usage 197.094 MB -> 90.329 MB.
[2025-09-05T17:54:20.794Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:54:22.755Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:54:25.791Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:54:26.747Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:54:28.709Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:54:29.667Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:54:30.624Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:54:32.590Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:54:32.590Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-09-05T17:54:32.590Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:54:32.590Z] Top recommended movies for user id 72:
[2025-09-05T17:54:32.590Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:54:32.590Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:54:32.590Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:54:32.590Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:54:32.590Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:54:32.590Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (13571.556 ms) ======
[2025-09-05T17:54:32.590Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-09-05T17:54:32.590Z] GC before operation: completed in 108.275 ms, heap usage 531.753 MB -> 90.879 MB.
[2025-09-05T17:54:34.551Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:54:36.512Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:54:39.543Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:54:41.507Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:54:42.462Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:54:43.418Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:54:45.381Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:54:46.345Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:54:46.345Z] 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.
[2025-09-05T17:54:46.345Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:54:46.345Z] Top recommended movies for user id 72:
[2025-09-05T17:54:46.345Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:54:46.345Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:54:46.345Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:54:46.345Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:54:46.345Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:54:46.345Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (13891.027 ms) ======
[2025-09-05T17:54:46.345Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-09-05T17:54:46.345Z] GC before operation: completed in 111.886 ms, heap usage 217.608 MB -> 90.110 MB.
[2025-09-05T17:54:48.316Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:54:51.345Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:54:53.484Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:54:55.446Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:54:56.425Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:54:58.387Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:55:00.052Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:55:01.008Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:55:01.008Z] 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.
[2025-09-05T17:55:01.008Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:55:01.008Z] Top recommended movies for user id 72:
[2025-09-05T17:55:01.008Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:55:01.008Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:55:01.008Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:55:01.008Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:55:01.008Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:55:01.008Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14606.471 ms) ======
[2025-09-05T17:55:01.008Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-09-05T17:55:01.008Z] GC before operation: completed in 106.101 ms, heap usage 271.534 MB -> 90.424 MB.
[2025-09-05T17:55:04.038Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-09-05T17:55:06.043Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-09-05T17:55:08.017Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-09-05T17:55:09.982Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-09-05T17:55:11.947Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-09-05T17:55:12.906Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-09-05T17:55:14.871Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-09-05T17:55:15.827Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-09-05T17:55:15.827Z] 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.
[2025-09-05T17:55:15.827Z] The best model improves the baseline by 14.52%.
[2025-09-05T17:55:16.783Z] Top recommended movies for user id 72:
[2025-09-05T17:55:16.783Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-09-05T17:55:16.783Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-09-05T17:55:16.783Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-09-05T17:55:16.783Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-09-05T17:55:16.783Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-09-05T17:55:16.783Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (14872.771 ms) ======
[2025-09-05T17:55:16.783Z] -----------------------------------
[2025-09-05T17:55:16.783Z] renaissance-movie-lens_0_PASSED
[2025-09-05T17:55:16.783Z] -----------------------------------
[2025-09-05T17:55:16.783Z]
[2025-09-05T17:55:16.783Z] TEST TEARDOWN:
[2025-09-05T17:55:16.783Z] Nothing to be done for teardown.
[2025-09-05T17:55:16.783Z] renaissance-movie-lens_0 Finish Time: Fri Sep 5 17:55:16 2025 Epoch Time (ms): 1757094916359