No Possible Issues Found via Git Search
renaissance-movie-lens_0
[2026-02-19T06:04:11.394Z] Running test renaissance-movie-lens_0 ...
[2026-02-19T06:04:11.394Z] ===============================================
[2026-02-19T06:04:11.394Z] renaissance-movie-lens_0 Start Time: Thu Feb 19 06:04:11 2026 Epoch Time (ms): 1771481051132
[2026-02-19T06:04:11.394Z] variation: NoOptions
[2026-02-19T06:04:11.394Z] JVM_OPTIONS:
[2026-02-19T06:04:11.394Z] { \
[2026-02-19T06:04:11.394Z] echo ""; echo "TEST SETUP:"; \
[2026-02-19T06:04:11.394Z] echo "Nothing to be done for setup."; \
[2026-02-19T06:04:11.394Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17714782492698/renaissance-movie-lens_0"; \
[2026-02-19T06:04:11.394Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17714782492698/renaissance-movie-lens_0"; \
[2026-02-19T06:04:11.394Z] echo ""; echo "TESTING:"; \
[2026-02-19T06:04:11.394Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_2/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17714782492698/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2026-02-19T06:04:11.394Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17714782492698/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2026-02-19T06:04:11.394Z] echo ""; echo "TEST TEARDOWN:"; \
[2026-02-19T06:04:11.394Z] echo "Nothing to be done for teardown."; \
[2026-02-19T06:04:11.394Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_2/aqa-tests/TKG/../TKG/output_17714782492698/TestTargetResult";
[2026-02-19T06:04:11.394Z]
[2026-02-19T06:04:11.394Z] TEST SETUP:
[2026-02-19T06:04:11.394Z] Nothing to be done for setup.
[2026-02-19T06:04:11.394Z]
[2026-02-19T06:04:11.394Z] TESTING:
[2026-02-19T06:04:34.349Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2026-02-19T06:05:07.521Z] 06:05:06.580 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.
[2026-02-19T06:05:18.237Z] Got 100004 ratings from 671 users on 9066 movies.
[2026-02-19T06:05:21.268Z] Training: 60056, validation: 20285, test: 19854
[2026-02-19T06:05:21.268Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2026-02-19T06:05:21.268Z] GC before operation: completed in 510.903 ms, heap usage 371.928 MB -> 76.966 MB.
[2026-02-19T06:05:54.499Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:06:13.515Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:06:26.524Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:06:39.523Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:06:46.719Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:06:53.946Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:07:01.115Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:07:06.958Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:07:08.083Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-19T06:07:08.405Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:07:09.539Z] Top recommended movies for user id 72:
[2026-02-19T06:07:09.539Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:07:09.539Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:07:09.539Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:07:09.539Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:07:09.539Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:07:09.539Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (108126.489 ms) ======
[2026-02-19T06:07:09.539Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2026-02-19T06:07:10.251Z] GC before operation: completed in 846.688 ms, heap usage 571.322 MB -> 91.783 MB.
[2026-02-19T06:07:23.267Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:07:34.364Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:07:45.096Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:07:55.822Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:08:02.984Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:08:08.811Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:08:14.692Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:08:20.538Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:08:21.229Z] 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.
[2026-02-19T06:08:21.229Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:08:21.917Z] Top recommended movies for user id 72:
[2026-02-19T06:08:21.917Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:08:21.917Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:08:21.917Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:08:21.917Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:08:21.917Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:08:21.917Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (71622.219 ms) ======
[2026-02-19T06:08:21.918Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2026-02-19T06:08:23.055Z] GC before operation: completed in 911.307 ms, heap usage 771.623 MB -> 96.013 MB.
[2026-02-19T06:08:33.766Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:08:42.584Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:08:53.290Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:09:02.105Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:09:06.942Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:09:12.753Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:09:18.567Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:09:24.378Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:09:25.069Z] 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.
[2026-02-19T06:09:25.069Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:09:25.765Z] Top recommended movies for user id 72:
[2026-02-19T06:09:25.765Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:09:25.765Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:09:25.765Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:09:25.765Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:09:25.765Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:09:25.765Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (63103.749 ms) ======
[2026-02-19T06:09:25.765Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2026-02-19T06:09:26.915Z] GC before operation: completed in 934.446 ms, heap usage 499.677 MB -> 92.005 MB.
[2026-02-19T06:09:37.621Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:09:46.406Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:09:55.228Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:10:04.007Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:10:09.824Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:10:14.517Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:10:20.353Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:10:25.025Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:10:26.639Z] 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.
[2026-02-19T06:10:26.639Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:10:27.324Z] Top recommended movies for user id 72:
[2026-02-19T06:10:27.324Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:10:27.324Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:10:27.324Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:10:27.324Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:10:27.324Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:10:27.324Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (60502.523 ms) ======
[2026-02-19T06:10:27.324Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2026-02-19T06:10:28.545Z] GC before operation: completed in 966.793 ms, heap usage 295.673 MB -> 90.851 MB.
[2026-02-19T06:10:39.237Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:10:50.166Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:11:00.860Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:11:10.985Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:11:16.801Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:11:21.477Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:11:27.289Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:11:33.105Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:11:33.422Z] 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.
[2026-02-19T06:11:33.422Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:11:34.216Z] Top recommended movies for user id 72:
[2026-02-19T06:11:34.216Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:11:34.216Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:11:34.216Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:11:34.216Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:11:34.216Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:11:34.216Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (66070.409 ms) ======
[2026-02-19T06:11:34.216Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2026-02-19T06:11:35.382Z] GC before operation: completed in 953.117 ms, heap usage 202.624 MB -> 94.088 MB.
[2026-02-19T06:11:46.084Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:11:56.959Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:12:05.819Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:12:14.600Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:12:19.284Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:12:23.960Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:12:29.813Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:12:34.502Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:12:35.618Z] 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.
[2026-02-19T06:12:35.618Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:12:36.748Z] Top recommended movies for user id 72:
[2026-02-19T06:12:36.748Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:12:36.748Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:12:36.748Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:12:36.748Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:12:36.748Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:12:36.748Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (61267.872 ms) ======
[2026-02-19T06:12:36.748Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2026-02-19T06:12:37.460Z] GC before operation: completed in 925.362 ms, heap usage 174.024 MB -> 92.836 MB.
[2026-02-19T06:12:46.263Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:12:55.046Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:13:03.832Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:13:12.617Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:13:16.354Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:13:21.139Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:13:26.982Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:13:31.651Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:13:31.973Z] 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.
[2026-02-19T06:13:32.292Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:13:33.019Z] Top recommended movies for user id 72:
[2026-02-19T06:13:33.019Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:13:33.019Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:13:33.019Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:13:33.019Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:13:33.019Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:13:33.019Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55289.509 ms) ======
[2026-02-19T06:13:33.019Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2026-02-19T06:13:33.750Z] GC before operation: completed in 943.062 ms, heap usage 742.167 MB -> 94.923 MB.
[2026-02-19T06:13:44.459Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:13:51.621Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:14:00.543Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:14:07.733Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:14:12.402Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:14:17.072Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:14:22.906Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:14:26.624Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:14:27.745Z] 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.
[2026-02-19T06:14:27.745Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:14:28.432Z] Top recommended movies for user id 72:
[2026-02-19T06:14:28.432Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:14:28.432Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:14:28.432Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:14:28.432Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:14:28.432Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:14:28.432Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (54725.284 ms) ======
[2026-02-19T06:14:28.432Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2026-02-19T06:14:29.593Z] GC before operation: completed in 977.489 ms, heap usage 530.507 MB -> 91.637 MB.
[2026-02-19T06:14:38.416Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:14:47.262Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:14:54.430Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:15:01.665Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:15:06.339Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:15:12.155Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:15:16.871Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:15:21.653Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:15:21.973Z] 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.
[2026-02-19T06:15:21.973Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:15:23.112Z] Top recommended movies for user id 72:
[2026-02-19T06:15:23.112Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:15:23.112Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:15:23.112Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:15:23.112Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:15:23.112Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:15:23.112Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (53405.515 ms) ======
[2026-02-19T06:15:23.112Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2026-02-19T06:15:23.822Z] GC before operation: completed in 985.557 ms, heap usage 735.939 MB -> 95.083 MB.
[2026-02-19T06:15:32.625Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:15:40.056Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:15:48.835Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:15:56.008Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:16:00.684Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:16:05.428Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:16:11.277Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:16:17.085Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:16:17.406Z] 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.
[2026-02-19T06:16:17.406Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:16:18.093Z] Top recommended movies for user id 72:
[2026-02-19T06:16:18.093Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:16:18.093Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:16:18.093Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:16:18.093Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:16:18.093Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:16:18.093Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (54260.793 ms) ======
[2026-02-19T06:16:18.093Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2026-02-19T06:16:19.249Z] GC before operation: completed in 946.937 ms, heap usage 632.708 MB -> 95.115 MB.
[2026-02-19T06:16:29.950Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:16:40.721Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:16:49.520Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:16:56.747Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:17:02.558Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:17:07.354Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:17:12.030Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:17:16.697Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:17:17.422Z] 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.
[2026-02-19T06:17:17.740Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:17:18.429Z] Top recommended movies for user id 72:
[2026-02-19T06:17:18.429Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:17:18.429Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:17:18.429Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:17:18.429Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:17:18.429Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:17:18.429Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (59311.594 ms) ======
[2026-02-19T06:17:18.429Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2026-02-19T06:17:19.569Z] GC before operation: completed in 970.856 ms, heap usage 266.419 MB -> 96.762 MB.
[2026-02-19T06:17:30.275Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:17:39.125Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:17:46.301Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:17:55.097Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:17:58.806Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:18:04.622Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:18:09.344Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:18:14.124Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:18:14.818Z] 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.
[2026-02-19T06:18:14.818Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:18:15.502Z] Top recommended movies for user id 72:
[2026-02-19T06:18:15.502Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:18:15.502Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:18:15.502Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:18:15.502Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:18:15.502Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:18:15.502Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (56123.026 ms) ======
[2026-02-19T06:18:15.502Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2026-02-19T06:18:16.646Z] GC before operation: completed in 950.622 ms, heap usage 292.716 MB -> 91.459 MB.
[2026-02-19T06:18:25.414Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:18:32.566Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:18:41.405Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:18:48.574Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:18:53.251Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:18:59.161Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:19:03.845Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:19:09.672Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:19:09.995Z] 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.
[2026-02-19T06:19:09.995Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:19:10.688Z] Top recommended movies for user id 72:
[2026-02-19T06:19:10.688Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:19:10.688Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:19:10.688Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:19:10.688Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:19:10.688Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:19:10.688Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (54246.442 ms) ======
[2026-02-19T06:19:10.688Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2026-02-19T06:19:11.840Z] GC before operation: completed in 947.188 ms, heap usage 686.104 MB -> 95.330 MB.
[2026-02-19T06:19:20.635Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:19:27.818Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:19:36.606Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:19:45.550Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:19:49.252Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:19:55.134Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:19:59.828Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:20:04.510Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:20:05.197Z] 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.
[2026-02-19T06:20:05.197Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:20:05.882Z] Top recommended movies for user id 72:
[2026-02-19T06:20:05.882Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:20:05.882Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:20:05.882Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:20:05.882Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:20:05.882Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:20:05.882Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (54337.710 ms) ======
[2026-02-19T06:20:05.882Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2026-02-19T06:20:07.039Z] GC before operation: completed in 935.524 ms, heap usage 490.412 MB -> 91.672 MB.
[2026-02-19T06:20:17.733Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:20:26.544Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:20:37.252Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:20:44.482Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:20:49.168Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:20:54.991Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:20:59.676Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:21:04.390Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:21:05.558Z] 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.
[2026-02-19T06:21:05.558Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:21:06.323Z] Top recommended movies for user id 72:
[2026-02-19T06:21:06.324Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:21:06.324Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:21:06.324Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:21:06.324Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:21:06.324Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:21:06.324Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (59421.304 ms) ======
[2026-02-19T06:21:06.324Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2026-02-19T06:21:07.474Z] GC before operation: completed in 966.404 ms, heap usage 298.587 MB -> 97.288 MB.
[2026-02-19T06:21:18.205Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:21:26.977Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:21:34.142Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:21:42.912Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:21:46.618Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:21:51.312Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:21:57.135Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:22:02.114Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:22:02.800Z] 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.
[2026-02-19T06:22:02.800Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:22:03.489Z] Top recommended movies for user id 72:
[2026-02-19T06:22:03.489Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:22:03.489Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:22:03.489Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:22:03.489Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:22:03.489Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:22:03.489Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (56205.652 ms) ======
[2026-02-19T06:22:03.489Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2026-02-19T06:22:04.652Z] GC before operation: completed in 975.928 ms, heap usage 310.156 MB -> 91.427 MB.
[2026-02-19T06:22:13.438Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:22:22.246Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:22:29.420Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:22:36.649Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:22:41.343Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:22:46.016Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:22:51.832Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:22:56.526Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:22:56.847Z] 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.
[2026-02-19T06:22:56.847Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:22:57.535Z] Top recommended movies for user id 72:
[2026-02-19T06:22:57.535Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:22:57.535Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:22:57.535Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:22:57.535Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:22:57.535Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:22:57.535Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (53155.248 ms) ======
[2026-02-19T06:22:57.535Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2026-02-19T06:22:58.695Z] GC before operation: completed in 966.621 ms, heap usage 934.501 MB -> 96.059 MB.
[2026-02-19T06:23:07.495Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:23:14.867Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:23:23.642Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:23:30.809Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:23:35.482Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:23:40.156Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:23:44.817Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:23:49.641Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:23:50.362Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2026-02-19T06:23:50.680Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:23:51.364Z] Top recommended movies for user id 72:
[2026-02-19T06:23:51.365Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:23:51.365Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:23:51.365Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:23:51.365Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:23:51.365Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:23:51.365Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (52695.694 ms) ======
[2026-02-19T06:23:51.365Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2026-02-19T06:23:52.520Z] GC before operation: completed in 969.747 ms, heap usage 629.083 MB -> 95.002 MB.
[2026-02-19T06:24:01.408Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:24:08.573Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:24:16.841Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:24:24.003Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:24:28.703Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:24:33.389Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:24:39.184Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:24:43.836Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2026-02-19T06:24:44.155Z] 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.
[2026-02-19T06:24:44.155Z] The best model improves the baseline by 14.52%.
[2026-02-19T06:24:44.846Z] Top recommended movies for user id 72:
[2026-02-19T06:24:44.846Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2026-02-19T06:24:44.846Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2026-02-19T06:24:44.846Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2026-02-19T06:24:44.846Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2026-02-19T06:24:44.846Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2026-02-19T06:24:44.846Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (52500.589 ms) ======
[2026-02-19T06:24:44.846Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2026-02-19T06:24:45.982Z] GC before operation: completed in 953.005 ms, heap usage 533.016 MB -> 91.792 MB.
[2026-02-19T06:24:54.757Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2026-02-19T06:25:02.005Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2026-02-19T06:25:10.791Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2026-02-19T06:25:17.955Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2026-02-19T06:25:21.699Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2026-02-19T06:25:26.371Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2026-02-19T06:25:32.180Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2026-02-19T06:25:34.413Z] 06:25:34.316 ERROR [Executor task launch worker for task 2.0 in stage 30732.0 (TID 29915)] org.apache.spark.executor.Executor - Exception in task 2.0 in stage 30732.0 (TID 29915)
[2026-02-19T06:25:34.413Z] java.lang.ClassCastException: cannot assign instance of org.apache.spark.executor.ShuffleWriteMetrics to field org.apache.spark.executor.TaskMetrics.shuffleWriteMetrics of type org.apache.spark.executor.ShuffleWriteMetrics in instance of org.apache.spark.executor.TaskMetrics
[2026-02-19T06:25:34.413Z] at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2096) ~[?:?]
[2026-02-19T06:25:34.413Z] at java.io.ObjectStreamClass$FieldReflector.checkObjectFieldValueTypes(ObjectStreamClass.java:2060) ~[?:?]
[2026-02-19T06:25:34.413Z] at java.io.ObjectStreamClass.checkObjFieldValueTypes(ObjectStreamClass.java:1347) ~[?:?]
[2026-02-19T06:25:34.413Z] at java.io.ObjectInputStream$FieldValues.defaultCheckFieldValues(ObjectInputStream.java:2679) ~[?:?]
[2026-02-19T06:25:34.413Z] at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2486) ~[?:?]
[2026-02-19T06:25:34.413Z] at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2257) ~[?:?]
[2026-02-19T06:25:34.413Z] at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1733) ~[?:?]
[2026-02-19T06:25:34.413Z] at java.io.ObjectInputStream.readObject(ObjectInputStream.java:509) ~[?:?]
[2026-02-19T06:25:34.413Z] at java.io.ObjectInputStream.readObject(ObjectInputStream.java:467) ~[?:?]
[2026-02-19T06:25:34.413Z] at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:87) ~[spark-core_2.13-3.5.3.jar:3.5.3]
[2026-02-19T06:25:34.413Z] at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:123) ~[spark-core_2.13-3.5.3.jar:3.5.3]
[2026-02-19T06:25:34.413Z] at org.apache.spark.scheduler.Task.metrics$lzycompute(Task.scala:76) ~[spark-core_2.13-3.5.3.jar:3.5.3]
[2026-02-19T06:25:34.413Z] at org.apache.spark.scheduler.Task.metrics(Task.scala:75) ~[spark-core_2.13-3.5.3.jar:3.5.3]
[2026-02-19T06:25:34.413Z] at org.apache.spark.scheduler.Task.run(Task.scala:109) ~[spark-core_2.13-3.5.3.jar:3.5.3]
[2026-02-19T06:25:34.413Z] at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620) ~[spark-core_2.13-3.5.3.jar:3.5.3]
[2026-02-19T06:25:34.413Z] at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64) ~[spark-common-utils_2.13-3.5.3.jar:3.5.3]
[2026-02-19T06:25:34.413Z] at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61) ~[spark-common-utils_2.13-3.5.3.jar:3.5.3]
[2026-02-19T06:25:34.413Z] at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94) ~[spark-core_2.13-3.5.3.jar:3.5.3]
[2026-02-19T06:25:34.413Z] at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623) [spark-core_2.13-3.5.3.jar:3.5.3]
[2026-02-19T06:25:34.413Z] at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136) [?:?]
[2026-02-19T06:25:34.413Z] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635) [?:?]
[2026-02-19T06:25:34.413Z] at java.lang.Thread.run(Thread.java:840) [?:?]
[2026-02-19T06:25:34.413Z] Exception in thread "Executor task launch worker for task 2.0 in stage 30732.0 (TID 29915)" java.lang.ClassCastException: cannot assign instance of org.apache.spark.executor.ShuffleWriteMetrics to field org.apache.spark.executor.TaskMetrics.shuffleWriteMetrics of type org.apache.spark.executor.ShuffleWriteMetrics in instance of org.apache.spark.executor.TaskMetrics
[2026-02-19T06:25:34.414Z] at java.base/java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2096)
[2026-02-19T06:25:34.414Z] at java.base/java.io.ObjectStreamClass$FieldReflector.checkObjectFieldValueTypes(ObjectStreamClass.java:2060)
[2026-02-19T06:25:34.414Z] at java.base/java.io.ObjectStreamClass.checkObjFieldValueTypes(ObjectStreamClass.java:1347)
[2026-02-19T06:25:34.414Z] at java.base/java.io.ObjectInputStream$FieldValues.defaultCheckFieldValues(ObjectInputStream.java:2679)
[2026-02-19T06:25:34.414Z] at java.base/java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2486)
[2026-02-19T06:25:34.414Z] at java.base/java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2257)
[2026-02-19T06:25:34.414Z] at java.base/java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1733)
[2026-02-19T06:25:34.414Z] at java.base/java.io.ObjectInputStream.readObject(ObjectInputStream.java:509)
[2026-02-19T06:25:34.414Z] at java.base/java.io.ObjectInputStream.readObject(ObjectInputStream.java:467)
[2026-02-19T06:25:34.414Z] at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:87)
[2026-02-19T06:25:34.414Z] at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:123)
[2026-02-19T06:25:34.414Z] at org.apache.spark.scheduler.Task.metrics$lzycompute(Task.scala:76)
[2026-02-19T06:25:34.414Z] at org.apache.spark.scheduler.Task.metrics(Task.scala:75)
[2026-02-19T06:25:34.414Z] at org.apache.spark.executor.Executor$TaskRunner.$anonfun$collectAccumulatorsAndResetStatusOnFailure$1(Executor.scala:523)
[2026-02-19T06:25:34.414Z] at org.apache.spark.executor.Executor$TaskRunner.$anonfun$collectAccumulatorsAndResetStatusOnFailure$1$adapted(Executor.scala:522)
[2026-02-19T06:25:34.414Z] at scala.Option.foreach(Option.scala:437)
[2026-02-19T06:25:34.414Z] at org.apache.spark.executor.Executor$TaskRunner.collectAccumulatorsAndResetStatusOnFailure(Executor.scala:522)
[2026-02-19T06:25:34.414Z] at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:800)
[2026-02-19T06:25:34.414Z] at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136)
[2026-02-19T06:25:34.414Z] at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
[2026-02-19T06:25:34.414Z] at java.base/java.lang.Thread.run(Thread.java:840)
[2026-02-20T06:11:50.719Z] Cancelling nested steps due to timeout
[2026-02-20T06:11:50.748Z] Sending interrupt signal to process
[2026-02-20T06:11:53.278Z] ====== movie-lens (apache-spark) [default], iteration 19 failed (SparkException) ======
[2026-02-20T06:11:53.971Z] -----------------------------------
[2026-02-20T06:11:53.971Z] renaissance-movie-lens_0_FAILED
[2026-02-20T06:11:53.971Z] -----------------------------------
[2026-02-20T06:11:53.971Z]
[2026-02-20T06:11:53.971Z] TEST TEARDOWN:
[2026-02-20T06:11:53.971Z] Nothing to be done for teardown.
[2026-02-20T06:11:53.971Z] renaissance-movie-lens_0 Finish Time: Fri Feb 20 06:11:53 2026 Epoch Time (ms): 1771567913724