renaissance-movie-lens_0
[2025-05-22T20:13:03.985Z] Running test renaissance-movie-lens_0 ...
[2025-05-22T20:13:03.985Z] ===============================================
[2025-05-22T20:13:03.985Z] renaissance-movie-lens_0 Start Time: Thu May 22 20:12:58 2025 Epoch Time (ms): 1747944778829
[2025-05-22T20:13:03.985Z] variation: NoOptions
[2025-05-22T20:13:03.985Z] JVM_OPTIONS:
[2025-05-22T20:13:03.985Z] { \
[2025-05-22T20:13:03.985Z] echo ""; echo "TEST SETUP:"; \
[2025-05-22T20:13:03.985Z] echo "Nothing to be done for setup."; \
[2025-05-22T20:13:03.985Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17479401791604/renaissance-movie-lens_0"; \
[2025-05-22T20:13:03.985Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17479401791604/renaissance-movie-lens_0"; \
[2025-05-22T20:13:03.985Z] echo ""; echo "TESTING:"; \
[2025-05-22T20:13:03.985Z] "/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_17479401791604/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-05-22T20:13:03.985Z] 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_17479401791604/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-05-22T20:13:03.985Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-05-22T20:13:03.985Z] echo "Nothing to be done for teardown."; \
[2025-05-22T20:13:03.985Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_riscv64_linux_testList_1/aqa-tests/TKG/../TKG/output_17479401791604/TestTargetResult";
[2025-05-22T20:13:03.985Z]
[2025-05-22T20:13:03.985Z] TEST SETUP:
[2025-05-22T20:13:03.985Z] Nothing to be done for setup.
[2025-05-22T20:13:03.985Z]
[2025-05-22T20:13:03.985Z] TESTING:
[2025-05-22T20:13:23.070Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2025-05-22T20:13:56.367Z] 20:13:55.289 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.
[2025-05-22T20:14:09.453Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-05-22T20:14:10.595Z] Training: 60056, validation: 20285, test: 19854
[2025-05-22T20:14:10.595Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-05-22T20:14:11.321Z] GC before operation: completed in 651.152 ms, heap usage 315.524 MB -> 77.047 MB.
[2025-05-22T20:14:44.668Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:15:03.803Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:15:19.663Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:15:32.785Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:15:41.870Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:15:47.864Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:15:55.110Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:16:00.993Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:16:02.129Z] 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.
[2025-05-22T20:16:02.456Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:16:03.596Z] Top recommended movies for user id 72:
[2025-05-22T20:16:03.596Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:16:03.596Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:16:03.596Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:16:03.596Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:16:03.596Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:16:03.596Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (112515.071 ms) ======
[2025-05-22T20:16:03.596Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-05-22T20:16:04.776Z] GC before operation: completed in 859.571 ms, heap usage 144.521 MB -> 94.626 MB.
[2025-05-22T20:16:17.866Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:16:28.656Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:16:39.470Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:16:48.368Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:16:54.259Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:17:01.506Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:17:06.244Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:17:12.146Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:17:13.286Z] 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.
[2025-05-22T20:17:13.286Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:17:13.987Z] Top recommended movies for user id 72:
[2025-05-22T20:17:13.987Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:17:13.987Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:17:13.987Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:17:13.987Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:17:13.987Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:17:13.987Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (69543.182 ms) ======
[2025-05-22T20:17:13.987Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-05-22T20:17:15.164Z] GC before operation: completed in 893.151 ms, heap usage 532.295 MB -> 91.512 MB.
[2025-05-22T20:17:26.090Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:17:34.954Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:17:45.777Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:17:54.657Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:18:00.570Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:18:06.527Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:18:12.493Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:18:18.377Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:18:18.703Z] 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.
[2025-05-22T20:18:19.030Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:18:19.730Z] Top recommended movies for user id 72:
[2025-05-22T20:18:19.730Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:18:19.730Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:18:19.730Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:18:19.730Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:18:19.730Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:18:19.730Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (64647.302 ms) ======
[2025-05-22T20:18:19.730Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-05-22T20:18:20.882Z] GC before operation: completed in 981.226 ms, heap usage 545.354 MB -> 94.223 MB.
[2025-05-22T20:18:31.686Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:18:40.556Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:18:49.430Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:18:58.298Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:19:04.185Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:19:10.060Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:19:15.967Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:19:20.698Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:19:21.401Z] 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.
[2025-05-22T20:19:21.401Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:19:22.102Z] Top recommended movies for user id 72:
[2025-05-22T20:19:22.102Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:19:22.102Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:19:22.102Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:19:22.102Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:19:22.102Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:19:22.102Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (61591.850 ms) ======
[2025-05-22T20:19:22.102Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-05-22T20:19:23.287Z] GC before operation: completed in 957.402 ms, heap usage 618.127 MB -> 94.588 MB.
[2025-05-22T20:19:34.099Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:19:41.336Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:19:52.145Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:20:01.017Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:20:05.745Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:20:11.824Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:20:17.734Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:20:22.461Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:20:23.598Z] 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.
[2025-05-22T20:20:23.925Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:20:24.627Z] Top recommended movies for user id 72:
[2025-05-22T20:20:24.627Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:20:24.627Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:20:24.627Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:20:24.627Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:20:24.627Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:20:24.627Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (61392.673 ms) ======
[2025-05-22T20:20:24.627Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-05-22T20:20:25.783Z] GC before operation: completed in 971.695 ms, heap usage 233.539 MB -> 90.740 MB.
[2025-05-22T20:20:36.586Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:20:43.827Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:20:52.751Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:21:01.610Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:21:06.348Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:21:11.089Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:21:16.976Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:21:22.858Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:21:22.858Z] 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.
[2025-05-22T20:21:23.184Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:21:23.891Z] Top recommended movies for user id 72:
[2025-05-22T20:21:23.891Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:21:23.891Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:21:23.891Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:21:23.891Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:21:23.891Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:21:23.891Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (58189.662 ms) ======
[2025-05-22T20:21:23.891Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-05-22T20:21:24.640Z] GC before operation: completed in 947.559 ms, heap usage 792.609 MB -> 95.238 MB.
[2025-05-22T20:21:33.628Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:21:42.492Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:21:51.355Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:21:58.617Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:22:03.351Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:22:09.404Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:22:15.286Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:22:20.027Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:22:20.354Z] 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.
[2025-05-22T20:22:20.354Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:22:21.057Z] Top recommended movies for user id 72:
[2025-05-22T20:22:21.057Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:22:21.057Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:22:21.057Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:22:21.057Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:22:21.057Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:22:21.057Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (56481.206 ms) ======
[2025-05-22T20:22:21.057Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-05-22T20:22:22.234Z] GC before operation: completed in 952.384 ms, heap usage 806.045 MB -> 95.107 MB.
[2025-05-22T20:22:31.105Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:22:39.979Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:22:48.903Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:22:56.155Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:23:02.050Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:23:06.783Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:23:12.663Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:23:17.390Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:23:18.092Z] 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.
[2025-05-22T20:23:18.092Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:23:18.794Z] Top recommended movies for user id 72:
[2025-05-22T20:23:18.794Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:23:18.794Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:23:18.794Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:23:18.794Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:23:18.794Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:23:18.794Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (56575.142 ms) ======
[2025-05-22T20:23:18.794Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-05-22T20:23:19.959Z] GC before operation: completed in 1012.467 ms, heap usage 759.550 MB -> 95.237 MB.
[2025-05-22T20:23:28.988Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:23:37.878Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:23:45.126Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:23:53.987Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:23:59.869Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:24:04.662Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:24:09.398Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:24:15.295Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:24:15.295Z] 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.
[2025-05-22T20:24:15.637Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:24:16.343Z] Top recommended movies for user id 72:
[2025-05-22T20:24:16.343Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:24:16.343Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:24:16.343Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:24:16.343Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:24:16.343Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:24:16.343Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (56661.292 ms) ======
[2025-05-22T20:24:16.343Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-05-22T20:24:17.505Z] GC before operation: completed in 1027.608 ms, heap usage 748.662 MB -> 96.323 MB.
[2025-05-22T20:24:28.330Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:24:39.127Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:24:48.046Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:24:56.911Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:25:01.653Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:25:06.382Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:25:11.106Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:25:16.994Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:25:16.994Z] 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.
[2025-05-22T20:25:16.994Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:25:17.693Z] Top recommended movies for user id 72:
[2025-05-22T20:25:17.693Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:25:17.693Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:25:17.693Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:25:17.693Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:25:17.693Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:25:17.694Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (60352.257 ms) ======
[2025-05-22T20:25:17.694Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-05-22T20:25:18.877Z] GC before operation: completed in 988.096 ms, heap usage 761.628 MB -> 95.308 MB.
[2025-05-22T20:25:27.866Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:25:36.750Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:25:45.611Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:25:52.856Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:25:57.581Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:26:02.316Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:26:07.064Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:26:12.943Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:26:13.274Z] 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.
[2025-05-22T20:26:13.274Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:26:13.978Z] Top recommended movies for user id 72:
[2025-05-22T20:26:13.978Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:26:13.978Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:26:13.978Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:26:13.978Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:26:13.978Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:26:13.978Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (55196.940 ms) ======
[2025-05-22T20:26:13.978Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-05-22T20:26:15.156Z] GC before operation: completed in 962.627 ms, heap usage 1.043 GB -> 96.164 MB.
[2025-05-22T20:26:24.022Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:26:32.897Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:26:40.143Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:26:47.516Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:26:53.390Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:26:59.275Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:27:05.153Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:27:11.036Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:27:11.036Z] 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.
[2025-05-22T20:27:11.036Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:27:11.738Z] Top recommended movies for user id 72:
[2025-05-22T20:27:11.738Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:27:11.738Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:27:11.738Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:27:11.738Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:27:11.738Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:27:11.738Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (56835.579 ms) ======
[2025-05-22T20:27:11.738Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-05-22T20:27:12.889Z] GC before operation: completed in 940.882 ms, heap usage 142.916 MB -> 94.485 MB.
[2025-05-22T20:27:23.788Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:27:34.599Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:27:45.390Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:27:56.213Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:28:02.111Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:28:07.999Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:28:13.961Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:28:18.711Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:28:19.416Z] 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.
[2025-05-22T20:28:19.742Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:28:20.458Z] Top recommended movies for user id 72:
[2025-05-22T20:28:20.458Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:28:20.458Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:28:20.458Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:28:20.458Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:28:20.458Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:28:20.458Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (67569.423 ms) ======
[2025-05-22T20:28:20.458Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-05-22T20:28:21.184Z] GC before operation: completed in 934.628 ms, heap usage 474.119 MB -> 92.949 MB.
[2025-05-22T20:28:31.992Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:28:42.809Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:28:53.700Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:29:00.944Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:29:05.683Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:29:10.418Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:29:15.148Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:29:21.046Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:29:21.046Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2025-05-22T20:29:21.371Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:29:21.695Z] Top recommended movies for user id 72:
[2025-05-22T20:29:22.022Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:29:22.022Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:29:22.022Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:29:22.022Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:29:22.022Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:29:22.022Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (60637.995 ms) ======
[2025-05-22T20:29:22.022Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-05-22T20:29:22.754Z] GC before operation: completed in 972.153 ms, heap usage 801.055 MB -> 97.227 MB.
[2025-05-22T20:29:33.645Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:29:42.504Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:29:51.366Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:29:58.619Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:30:03.347Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:30:08.077Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:30:14.003Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:30:18.731Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:30:19.057Z] 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.
[2025-05-22T20:30:19.385Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:30:20.530Z] Top recommended movies for user id 72:
[2025-05-22T20:30:20.531Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:30:20.531Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:30:20.531Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:30:20.531Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:30:20.531Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:30:20.531Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (57081.289 ms) ======
[2025-05-22T20:30:20.531Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-05-22T20:30:20.991Z] GC before operation: completed in 941.017 ms, heap usage 446.547 MB -> 91.832 MB.
[2025-05-22T20:30:29.859Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:30:38.721Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:30:45.980Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:30:55.046Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:30:58.799Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:31:04.684Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:31:09.405Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:31:14.139Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:31:15.284Z] 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.
[2025-05-22T20:31:15.284Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:31:15.982Z] Top recommended movies for user id 72:
[2025-05-22T20:31:15.982Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:31:15.982Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:31:15.982Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:31:15.982Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:31:15.982Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:31:15.982Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (55137.020 ms) ======
[2025-05-22T20:31:15.982Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-05-22T20:31:17.155Z] GC before operation: completed in 962.593 ms, heap usage 262.737 MB -> 91.356 MB.
[2025-05-22T20:31:26.004Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:31:33.259Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:31:42.132Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:31:49.387Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:31:54.112Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:31:59.981Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:32:04.823Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:32:09.548Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:32:10.249Z] 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.
[2025-05-22T20:32:10.249Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:32:10.951Z] Top recommended movies for user id 72:
[2025-05-22T20:32:10.951Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:32:10.951Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:32:10.951Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:32:10.951Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:32:10.951Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:32:10.951Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (53971.459 ms) ======
[2025-05-22T20:32:10.951Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-05-22T20:32:12.107Z] GC before operation: completed in 970.622 ms, heap usage 265.934 MB -> 91.490 MB.
[2025-05-22T20:32:20.961Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:32:29.814Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:32:37.070Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:32:46.052Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:32:49.832Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:32:55.707Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:33:00.449Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:33:05.171Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:33:05.874Z] 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.
[2025-05-22T20:33:05.874Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:33:06.579Z] Top recommended movies for user id 72:
[2025-05-22T20:33:06.579Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:33:06.579Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:33:06.579Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:33:06.579Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:33:06.579Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:33:06.579Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (54695.711 ms) ======
[2025-05-22T20:33:06.579Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-05-22T20:33:07.729Z] GC before operation: completed in 977.874 ms, heap usage 368.039 MB -> 91.471 MB.
[2025-05-22T20:33:16.609Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:33:23.928Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:33:32.776Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:33:40.019Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:33:44.744Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:33:49.538Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:33:55.415Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:34:00.310Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:34:00.640Z] 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.
[2025-05-22T20:34:00.974Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:34:01.687Z] Top recommended movies for user id 72:
[2025-05-22T20:34:01.687Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:34:01.687Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:34:01.687Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:34:01.687Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:34:01.687Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:34:01.687Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (53957.253 ms) ======
[2025-05-22T20:34:01.687Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-05-22T20:34:02.415Z] GC before operation: completed in 963.752 ms, heap usage 260.695 MB -> 91.448 MB.
[2025-05-22T20:34:11.268Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-05-22T20:34:20.179Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-05-22T20:34:27.406Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-05-22T20:34:34.653Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-05-22T20:34:39.403Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-05-22T20:34:44.378Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-05-22T20:34:50.247Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-05-22T20:34:54.983Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-05-22T20:34:55.314Z] 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.
[2025-05-22T20:34:55.641Z] The best model improves the baseline by 14.52%.
[2025-05-22T20:34:56.343Z] Top recommended movies for user id 72:
[2025-05-22T20:34:56.343Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504)
[2025-05-22T20:34:56.343Z] 2: Goat, The (1921) (rating: 4.659, id: 83318)
[2025-05-22T20:34:56.343Z] 3: Play House, The (1921) (rating: 4.659, id: 83359)
[2025-05-22T20:34:56.343Z] 4: Cops (1922) (rating: 4.659, id: 83411)
[2025-05-22T20:34:56.343Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530)
[2025-05-22T20:34:56.343Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (53698.232 ms) ======
[2025-05-22T20:35:00.099Z] -----------------------------------
[2025-05-22T20:35:00.099Z] renaissance-movie-lens_0_PASSED
[2025-05-22T20:35:00.099Z] -----------------------------------
[2025-05-22T20:35:00.099Z]
[2025-05-22T20:35:00.099Z] TEST TEARDOWN:
[2025-05-22T20:35:00.099Z] Nothing to be done for teardown.
[2025-05-22T20:35:00.099Z] renaissance-movie-lens_0 Finish Time: Thu May 22 20:34:59 2025 Epoch Time (ms): 1747946099588