renaissance-movie-lens_0
[2025-05-08T19:05:18.375Z] Running test renaissance-movie-lens_0 ...
[2025-05-08T19:05:18.375Z] ===============================================
[2025-05-08T19:05:18.375Z] renaissance-movie-lens_0 Start Time: Thu May 8 19:05:17 2025 Epoch Time (ms): 1746731117092
[2025-05-08T19:05:18.375Z] variation: NoOptions
[2025-05-08T19:05:18.375Z] JVM_OPTIONS:
[2025-05-08T19:05:18.375Z] { \
[2025-05-08T19:05:18.375Z] echo ""; echo "TEST SETUP:"; \
[2025-05-08T19:05:18.375Z] echo "Nothing to be done for setup."; \
[2025-05-08T19:05:18.375Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17467263696498/renaissance-movie-lens_0"; \
[2025-05-08T19:05:18.375Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17467263696498/renaissance-movie-lens_0"; \
[2025-05-08T19:05:18.375Z] echo ""; echo "TESTING:"; \
[2025-05-08T19:05:18.375Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17467263696498/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-05-08T19:05:18.375Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17467263696498/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-05-08T19:05:18.375Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-05-08T19:05:18.375Z] echo "Nothing to be done for teardown."; \
[2025-05-08T19:05:18.375Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17467263696498/TestTargetResult";
[2025-05-08T19:05:18.375Z]
[2025-05-08T19:05:18.375Z] TEST SETUP:
[2025-05-08T19:05:18.375Z] Nothing to be done for setup.
[2025-05-08T19:05:18.375Z]
[2025-05-08T19:05:18.375Z] TESTING:
[2025-05-08T19:05:41.403Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-05-08T19:06:14.701Z] 19:06:13.782 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.
[2025-05-08T19:06:28.725Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-05-08T19:06:29.434Z] Training: 60056, validation: 20285, test: 19854
[2025-05-08T19:06:29.434Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-05-08T19:06:30.152Z] GC before operation: completed in 530.542 ms, heap usage 158.298 MB -> 76.985 MB.
[2025-05-08T19:07:03.468Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:07:16.565Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:07:29.661Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:07:42.759Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:07:50.182Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:07:57.424Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:08:04.666Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:08:10.554Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:08:11.698Z] 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.
[2025-05-08T19:08:12.024Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:08:13.166Z] Top recommended movies for user id 72:
[2025-05-08T19:08:13.166Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:08:13.166Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:08:13.166Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:08:13.166Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:08:13.166Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:08:13.510Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (103345.402 ms) ======
[2025-05-08T19:08:13.510Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-05-08T19:08:14.244Z] GC before operation: completed in 904.454 ms, heap usage 187.412 MB -> 89.599 MB.
[2025-05-08T19:08:27.371Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:08:38.232Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:08:47.100Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:08:57.887Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:09:03.762Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:09:09.647Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:09:16.881Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:09:22.773Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:09:23.183Z] 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.
[2025-05-08T19:09:23.577Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:09:24.277Z] Top recommended movies for user id 72:
[2025-05-08T19:09:24.277Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:09:24.277Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:09:24.277Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:09:24.277Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:09:24.277Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:09:24.277Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (69996.066 ms) ======
[2025-05-08T19:09:24.277Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-05-08T19:09:25.414Z] GC before operation: completed in 903.933 ms, heap usage 236.091 MB -> 89.967 MB.
[2025-05-08T19:09:36.202Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:09:45.073Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:09:55.868Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:10:04.739Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:10:10.621Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:10:18.008Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:10:22.742Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:10:28.630Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:10:29.768Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-05-08T19:10:30.095Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:10:30.795Z] Top recommended movies for user id 72:
[2025-05-08T19:10:30.795Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:10:30.795Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:10:30.795Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:10:30.795Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:10:30.795Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:10:30.795Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (65741.852 ms) ======
[2025-05-08T19:10:30.795Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-05-08T19:10:31.970Z] GC before operation: completed in 929.233 ms, heap usage 1.228 GB -> 96.084 MB.
[2025-05-08T19:10:42.771Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:10:51.625Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:11:00.601Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:11:09.452Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:11:15.326Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:11:20.057Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:11:25.929Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:11:31.829Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:11:32.969Z] 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.
[2025-05-08T19:11:33.303Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:11:34.004Z] Top recommended movies for user id 72:
[2025-05-08T19:11:34.004Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:11:34.004Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:11:34.004Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:11:34.004Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:11:34.004Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:11:34.004Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (62198.323 ms) ======
[2025-05-08T19:11:34.004Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-05-08T19:11:35.175Z] GC before operation: completed in 936.842 ms, heap usage 199.128 MB -> 92.608 MB.
[2025-05-08T19:11:48.362Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:11:59.153Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:12:12.246Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:12:23.040Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:12:27.782Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:12:33.658Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:12:39.644Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:12:44.377Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:12:46.022Z] 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.
[2025-05-08T19:12:46.022Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:12:46.725Z] Top recommended movies for user id 72:
[2025-05-08T19:12:46.725Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:12:46.725Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:12:46.725Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:12:46.725Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:12:46.725Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:12:46.725Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (71771.803 ms) ======
[2025-05-08T19:12:46.725Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-05-08T19:12:47.902Z] GC before operation: completed in 939.411 ms, heap usage 536.270 MB -> 91.348 MB.
[2025-05-08T19:13:00.980Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:13:09.864Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:13:18.767Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:13:26.156Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:13:32.042Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:13:36.784Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:13:42.681Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:13:47.406Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:13:48.542Z] 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.
[2025-05-08T19:13:48.542Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:13:49.254Z] Top recommended movies for user id 72:
[2025-05-08T19:13:49.254Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:13:49.254Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:13:49.254Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:13:49.254Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:13:49.254Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:13:49.254Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (61424.465 ms) ======
[2025-05-08T19:13:49.254Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-05-08T19:13:49.986Z] GC before operation: completed in 951.270 ms, heap usage 525.742 MB -> 91.691 MB.
[2025-05-08T19:13:58.852Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:14:07.832Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:14:16.690Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:14:23.945Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:14:28.679Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:14:34.557Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:14:39.313Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:14:44.040Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:14:44.741Z] 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.
[2025-05-08T19:14:44.741Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:14:45.441Z] Top recommended movies for user id 72:
[2025-05-08T19:14:45.441Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:14:45.441Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:14:45.441Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:14:45.441Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:14:45.441Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:14:45.441Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (55335.300 ms) ======
[2025-05-08T19:14:45.441Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-05-08T19:14:46.612Z] GC before operation: completed in 993.128 ms, heap usage 814.653 MB -> 95.372 MB.
[2025-05-08T19:14:55.513Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:15:04.382Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:15:13.232Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:15:20.478Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:15:25.200Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:15:29.923Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:15:35.841Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:15:40.616Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:15:41.755Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-05-08T19:15:41.755Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:15:42.463Z] Top recommended movies for user id 72:
[2025-05-08T19:15:42.463Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:15:42.463Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:15:42.463Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:15:42.463Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:15:42.463Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:15:42.463Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (56189.107 ms) ======
[2025-05-08T19:15:42.463Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-05-08T19:15:43.628Z] GC before operation: completed in 965.063 ms, heap usage 224.424 MB -> 91.388 MB.
[2025-05-08T19:15:52.489Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:16:01.338Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:16:10.184Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:16:17.414Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:16:22.283Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:16:27.001Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:16:31.747Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:16:36.471Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:16:37.186Z] 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.
[2025-05-08T19:16:37.511Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:16:38.224Z] Top recommended movies for user id 72:
[2025-05-08T19:16:38.224Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:16:38.224Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:16:38.224Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:16:38.224Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:16:38.224Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:16:38.224Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (54528.712 ms) ======
[2025-05-08T19:16:38.224Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-05-08T19:16:38.952Z] GC before operation: completed in 987.789 ms, heap usage 1.127 GB -> 96.515 MB.
[2025-05-08T19:16:47.815Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:16:56.666Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:17:03.988Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:17:12.834Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:17:16.587Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:17:22.472Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:17:27.192Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:17:31.918Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:17:32.620Z] 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.
[2025-05-08T19:17:32.620Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:17:33.775Z] Top recommended movies for user id 72:
[2025-05-08T19:17:33.775Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:17:33.775Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:17:33.775Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:17:33.775Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:17:33.775Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:17:33.775Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (54501.062 ms) ======
[2025-05-08T19:17:33.775Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-05-08T19:17:34.501Z] GC before operation: completed in 913.376 ms, heap usage 212.157 MB -> 91.313 MB.
[2025-05-08T19:17:43.536Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:17:52.388Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:17:59.619Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:18:06.851Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:18:11.584Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:18:17.554Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:18:22.269Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:18:26.989Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:18:27.788Z] 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.
[2025-05-08T19:18:27.788Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:18:28.492Z] Top recommended movies for user id 72:
[2025-05-08T19:18:28.492Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:18:28.492Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:18:28.492Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:18:28.492Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:18:28.493Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:18:28.493Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (53919.116 ms) ======
[2025-05-08T19:18:28.493Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-05-08T19:18:29.224Z] GC before operation: completed in 936.621 ms, heap usage 829.729 MB -> 95.310 MB.
[2025-05-08T19:18:38.089Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:18:46.938Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:18:54.169Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:19:01.397Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:19:06.135Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:19:12.093Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:19:16.814Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:19:21.537Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:19:22.673Z] 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.
[2025-05-08T19:19:22.674Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:19:23.380Z] Top recommended movies for user id 72:
[2025-05-08T19:19:23.380Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:19:23.380Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:19:23.380Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:19:23.380Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:19:23.380Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:19:23.380Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (53909.688 ms) ======
[2025-05-08T19:19:23.380Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-05-08T19:19:24.095Z] GC before operation: completed in 944.600 ms, heap usage 282.417 MB -> 91.527 MB.
[2025-05-08T19:19:32.946Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:19:41.808Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:19:49.041Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:19:57.964Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:20:01.718Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:20:07.616Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:20:12.371Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:20:18.256Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:20:18.256Z] 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.
[2025-05-08T19:20:18.583Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:20:19.295Z] Top recommended movies for user id 72:
[2025-05-08T19:20:19.295Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:20:19.295Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:20:19.295Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:20:19.295Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:20:19.295Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:20:19.295Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (54980.374 ms) ======
[2025-05-08T19:20:19.295Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-05-08T19:20:20.018Z] GC before operation: completed in 977.949 ms, heap usage 864.207 MB -> 95.822 MB.
[2025-05-08T19:20:28.904Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:20:37.913Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:20:46.773Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:20:54.016Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:20:58.750Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:21:03.504Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:21:09.379Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:21:14.211Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:21:14.541Z] 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.
[2025-05-08T19:21:14.866Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:21:15.574Z] Top recommended movies for user id 72:
[2025-05-08T19:21:15.574Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:21:15.574Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:21:15.574Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:21:15.574Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:21:15.574Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:21:15.574Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (55208.537 ms) ======
[2025-05-08T19:21:15.574Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-05-08T19:21:16.292Z] GC before operation: completed in 959.140 ms, heap usage 270.206 MB -> 91.448 MB.
[2025-05-08T19:21:25.170Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:21:34.056Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:21:41.294Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:21:48.533Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:21:53.265Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:21:58.056Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:22:03.933Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:22:08.659Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:22:08.992Z] 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.
[2025-05-08T19:22:08.992Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:22:09.693Z] Top recommended movies for user id 72:
[2025-05-08T19:22:09.693Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:22:09.693Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:22:09.693Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:22:09.693Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:22:09.693Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:22:09.693Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (53394.851 ms) ======
[2025-05-08T19:22:09.693Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-05-08T19:22:10.877Z] GC before operation: completed in 956.237 ms, heap usage 527.563 MB -> 92.057 MB.
[2025-05-08T19:22:19.738Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:22:28.586Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:22:35.843Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:22:43.332Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:22:49.210Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:22:52.976Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:23:00.211Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:23:04.937Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:23:06.580Z] 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.
[2025-05-08T19:23:06.580Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:23:06.916Z] Top recommended movies for user id 72:
[2025-05-08T19:23:06.917Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:23:06.917Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:23:06.917Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:23:06.917Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:23:06.917Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:23:06.917Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (56391.494 ms) ======
[2025-05-08T19:23:06.917Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-05-08T19:23:08.090Z] GC before operation: completed in 957.899 ms, heap usage 483.423 MB -> 91.830 MB.
[2025-05-08T19:23:19.052Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:23:29.838Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:23:40.648Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:23:47.899Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:23:53.772Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:23:58.501Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:24:04.390Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:24:09.121Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:24:09.822Z] 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.
[2025-05-08T19:24:09.822Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:24:10.523Z] Top recommended movies for user id 72:
[2025-05-08T19:24:10.523Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:24:10.523Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:24:10.523Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:24:10.523Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:24:10.523Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:24:10.523Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (62480.668 ms) ======
[2025-05-08T19:24:10.523Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-05-08T19:24:11.699Z] GC before operation: completed in 984.544 ms, heap usage 551.467 MB -> 97.654 MB.
[2025-05-08T19:24:20.566Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:24:29.434Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:24:36.673Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:24:45.648Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:24:49.429Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:24:54.162Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:25:00.038Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:25:04.762Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:25:05.089Z] 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.
[2025-05-08T19:25:05.414Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:25:06.118Z] Top recommended movies for user id 72:
[2025-05-08T19:25:06.118Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:25:06.118Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:25:06.118Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:25:06.118Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:25:06.118Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:25:06.118Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (54459.003 ms) ======
[2025-05-08T19:25:06.118Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-05-08T19:25:06.833Z] GC before operation: completed in 980.983 ms, heap usage 444.088 MB -> 91.688 MB.
[2025-05-08T19:25:15.691Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:25:24.563Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:25:31.958Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:25:39.262Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:25:45.139Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:25:48.908Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:25:54.795Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:25:59.518Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:25:59.846Z] 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.
[2025-05-08T19:26:00.174Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:26:00.877Z] Top recommended movies for user id 72:
[2025-05-08T19:26:00.877Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:26:00.877Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:26:00.877Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:26:00.877Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:26:00.877Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:26:00.877Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (53948.988 ms) ======
[2025-05-08T19:26:00.877Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-05-08T19:26:02.098Z] GC before operation: completed in 977.725 ms, heap usage 179.156 MB -> 91.365 MB.
[2025-05-08T19:26:10.957Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-08T19:26:18.190Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-08T19:26:27.072Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-08T19:26:34.340Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-08T19:26:39.126Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-08T19:26:44.994Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-08T19:26:52.317Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-08T19:26:57.041Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-08T19:26:57.742Z] 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.
[2025-05-08T19:26:58.069Z] The best model improves the baseline by 14.52%.
[2025-05-08T19:26:58.771Z] Top recommended movies for user id 72:
[2025-05-08T19:26:58.771Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-08T19:26:58.771Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-08T19:26:58.771Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-08T19:26:58.771Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-08T19:26:58.771Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-08T19:26:58.771Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (56866.077 ms) ======
[2025-05-08T19:27:02.538Z] -----------------------------------
[2025-05-08T19:27:02.538Z] renaissance-movie-lens_0_PASSED
[2025-05-08T19:27:02.538Z] -----------------------------------
[2025-05-08T19:27:02.538Z]
[2025-05-08T19:27:02.538Z] TEST TEARDOWN:
[2025-05-08T19:27:02.538Z] Nothing to be done for teardown.
[2025-05-08T19:27:02.538Z] renaissance-movie-lens_0 Finish Time: Thu May 8 19:27:02 2025 Epoch Time (ms): 1746732422136