[2025-06-19T03:10:13.959Z] Running test renaissance-movie-lens_0 ... [2025-06-19T03:10:13.959Z] =============================================== [2025-06-19T03:10:13.959Z] renaissance-movie-lens_0 Start Time: Thu Jun 19 03:10:13 2025 Epoch Time (ms): 1750302613156 [2025-06-19T03:10:13.959Z] variation: NoOptions [2025-06-19T03:10:13.959Z] JVM_OPTIONS: [2025-06-19T03:10:13.959Z] { \ [2025-06-19T03:10:13.959Z] echo ""; echo "TEST SETUP:"; \ [2025-06-19T03:10:13.959Z] echo "Nothing to be done for setup."; \ [2025-06-19T03:10:13.959Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17503018595800/renaissance-movie-lens_0"; \ [2025-06-19T03:10:13.959Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17503018595800/renaissance-movie-lens_0"; \ [2025-06-19T03:10:13.959Z] echo ""; echo "TESTING:"; \ [2025-06-19T03:10:13.959Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17503018595800/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \ [2025-06-19T03:10:13.959Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17503018595800/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2025-06-19T03:10:13.959Z] echo ""; echo "TEST TEARDOWN:"; \ [2025-06-19T03:10:13.959Z] echo "Nothing to be done for teardown."; \ [2025-06-19T03:10:13.959Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64le_linux_testList_1/aqa-tests/TKG/../TKG/output_17503018595800/TestTargetResult"; [2025-06-19T03:10:13.959Z] [2025-06-19T03:10:13.959Z] TEST SETUP: [2025-06-19T03:10:13.959Z] Nothing to be done for setup. [2025-06-19T03:10:13.959Z] [2025-06-19T03:10:13.959Z] TESTING: [2025-06-19T03:10:19.301Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2025-06-19T03:10:25.965Z] 03:10:24.758 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. [2025-06-19T03:10:27.930Z] Got 100004 ratings from 671 users on 9066 movies. [2025-06-19T03:10:27.930Z] Training: 60056, validation: 20285, test: 19854 [2025-06-19T03:10:27.930Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2025-06-19T03:10:27.930Z] GC before operation: completed in 133.870 ms, heap usage 166.873 MB -> 75.812 MB. [2025-06-19T03:10:34.616Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:10:38.731Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:10:41.745Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:10:44.738Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:10:46.673Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:10:48.608Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:10:50.546Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:10:51.488Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:10:52.430Z] 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. [2025-06-19T03:10:52.430Z] The best model improves the baseline by 14.52%. [2025-06-19T03:10:52.430Z] Top recommended movies for user id 72: [2025-06-19T03:10:52.430Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:10:52.430Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:10:52.430Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:10:52.430Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:10:52.430Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:10:52.430Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (24177.345 ms) ====== [2025-06-19T03:10:52.430Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2025-06-19T03:10:52.430Z] GC before operation: completed in 126.614 ms, heap usage 551.826 MB -> 90.709 MB. [2025-06-19T03:10:55.419Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:10:58.389Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:11:00.325Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:11:03.324Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:11:04.266Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:11:06.205Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:11:08.140Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:11:10.077Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:11:10.077Z] 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. [2025-06-19T03:11:10.077Z] The best model improves the baseline by 14.52%. [2025-06-19T03:11:10.077Z] Top recommended movies for user id 72: [2025-06-19T03:11:10.077Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:11:10.077Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:11:10.077Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:11:10.077Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:11:10.077Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:11:10.077Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17556.584 ms) ====== [2025-06-19T03:11:10.077Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2025-06-19T03:11:10.077Z] GC before operation: completed in 120.346 ms, heap usage 376.865 MB -> 91.162 MB. [2025-06-19T03:11:13.064Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:11:16.067Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:11:18.002Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:11:21.014Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:11:21.957Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:11:23.895Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:11:24.838Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:11:26.771Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:11:26.771Z] 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. [2025-06-19T03:11:26.771Z] The best model improves the baseline by 14.52%. [2025-06-19T03:11:26.771Z] Top recommended movies for user id 72: [2025-06-19T03:11:26.771Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:11:26.771Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:11:26.771Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:11:26.771Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:11:26.771Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:11:26.771Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (16939.174 ms) ====== [2025-06-19T03:11:26.771Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2025-06-19T03:11:27.714Z] GC before operation: completed in 135.002 ms, heap usage 194.229 MB -> 90.742 MB. [2025-06-19T03:11:30.697Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:11:33.687Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:11:35.624Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:11:38.613Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:11:39.556Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:11:41.493Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:11:43.428Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:11:44.370Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:11:44.370Z] 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. [2025-06-19T03:11:44.370Z] The best model improves the baseline by 14.52%. [2025-06-19T03:11:44.370Z] Top recommended movies for user id 72: [2025-06-19T03:11:44.370Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:11:44.370Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:11:44.370Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:11:44.370Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:11:44.370Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:11:44.370Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17456.345 ms) ====== [2025-06-19T03:11:44.370Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2025-06-19T03:11:45.311Z] GC before operation: completed in 175.981 ms, heap usage 446.580 MB -> 93.712 MB. [2025-06-19T03:11:47.245Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:11:49.178Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:11:52.166Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:11:54.099Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:11:56.035Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:11:56.980Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:11:58.915Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:11:59.855Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:12:00.799Z] 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. [2025-06-19T03:12:00.799Z] The best model improves the baseline by 14.52%. [2025-06-19T03:12:00.799Z] Top recommended movies for user id 72: [2025-06-19T03:12:00.799Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:12:00.799Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:12:00.799Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:12:00.799Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:12:00.799Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:12:00.799Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (15721.270 ms) ====== [2025-06-19T03:12:00.799Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2025-06-19T03:12:00.799Z] GC before operation: completed in 124.250 ms, heap usage 533.704 MB -> 95.074 MB. [2025-06-19T03:12:02.733Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:12:05.794Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:12:07.732Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:12:09.666Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:12:11.600Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:12:12.554Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:12:13.495Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:12:15.335Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:12:15.335Z] 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. [2025-06-19T03:12:15.335Z] The best model improves the baseline by 14.52%. [2025-06-19T03:12:15.335Z] Top recommended movies for user id 72: [2025-06-19T03:12:15.335Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:12:15.335Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:12:15.335Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:12:15.335Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:12:15.335Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:12:15.335Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (14889.703 ms) ====== [2025-06-19T03:12:15.335Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2025-06-19T03:12:16.277Z] GC before operation: completed in 140.599 ms, heap usage 183.809 MB -> 91.250 MB. [2025-06-19T03:12:18.214Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:12:20.150Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:12:22.085Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:12:25.072Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:12:26.016Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:12:26.959Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:12:28.898Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:12:29.842Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:12:30.793Z] 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. [2025-06-19T03:12:30.793Z] The best model improves the baseline by 14.52%. [2025-06-19T03:12:30.793Z] Top recommended movies for user id 72: [2025-06-19T03:12:30.793Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:12:30.793Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:12:30.793Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:12:30.793Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:12:30.793Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:12:30.793Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (14697.213 ms) ====== [2025-06-19T03:12:30.793Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2025-06-19T03:12:30.793Z] GC before operation: completed in 181.083 ms, heap usage 801.496 MB -> 94.053 MB. [2025-06-19T03:12:33.787Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:12:35.732Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:12:38.719Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:12:40.655Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:12:41.772Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:12:42.714Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:12:44.655Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:12:45.603Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:12:45.604Z] 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. [2025-06-19T03:12:45.604Z] The best model improves the baseline by 14.52%. [2025-06-19T03:12:45.604Z] Top recommended movies for user id 72: [2025-06-19T03:12:45.604Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:12:45.604Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:12:45.604Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:12:45.604Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:12:45.604Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:12:45.604Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (15149.829 ms) ====== [2025-06-19T03:12:45.604Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2025-06-19T03:12:46.567Z] GC before operation: completed in 230.762 ms, heap usage 445.358 MB -> 94.119 MB. [2025-06-19T03:12:48.501Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:12:50.437Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:12:52.374Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:12:55.365Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:12:56.309Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:12:58.245Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:12:59.239Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:13:00.181Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:13:01.125Z] 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. [2025-06-19T03:13:01.125Z] The best model improves the baseline by 14.52%. [2025-06-19T03:13:01.125Z] Top recommended movies for user id 72: [2025-06-19T03:13:01.125Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:13:01.125Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:13:01.125Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:13:01.125Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:13:01.125Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:13:01.125Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (14957.928 ms) ====== [2025-06-19T03:13:01.125Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2025-06-19T03:13:01.125Z] GC before operation: completed in 162.659 ms, heap usage 695.319 MB -> 94.005 MB. [2025-06-19T03:13:03.059Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:13:06.163Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:13:08.104Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:13:10.040Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:13:10.982Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:13:12.916Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:13:13.864Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:13:15.811Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:13:15.811Z] 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. [2025-06-19T03:13:15.811Z] The best model improves the baseline by 14.52%. [2025-06-19T03:13:15.811Z] Top recommended movies for user id 72: [2025-06-19T03:13:15.811Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:13:15.811Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:13:15.811Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:13:15.811Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:13:15.811Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:13:15.811Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (14865.580 ms) ====== [2025-06-19T03:13:15.811Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2025-06-19T03:13:15.811Z] GC before operation: completed in 129.201 ms, heap usage 307.202 MB -> 96.200 MB. [2025-06-19T03:13:18.807Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:13:20.746Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:13:23.732Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:13:25.670Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:13:26.613Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:13:28.549Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:13:29.502Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:13:30.450Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:13:31.394Z] 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. [2025-06-19T03:13:31.394Z] The best model improves the baseline by 14.52%. [2025-06-19T03:13:31.394Z] Top recommended movies for user id 72: [2025-06-19T03:13:31.394Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:13:31.394Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:13:31.394Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:13:31.394Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:13:31.394Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:13:31.394Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (15083.258 ms) ====== [2025-06-19T03:13:31.394Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2025-06-19T03:13:31.394Z] GC before operation: completed in 185.187 ms, heap usage 249.061 MB -> 93.400 MB. [2025-06-19T03:13:33.329Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:13:36.334Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:13:38.327Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:13:40.263Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:13:41.205Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:13:43.141Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:13:45.077Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:13:46.021Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:13:46.021Z] 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. [2025-06-19T03:13:46.021Z] The best model improves the baseline by 14.52%. [2025-06-19T03:13:46.964Z] Top recommended movies for user id 72: [2025-06-19T03:13:46.964Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:13:46.964Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:13:46.964Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:13:46.964Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:13:46.964Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:13:46.964Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (15038.100 ms) ====== [2025-06-19T03:13:46.964Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2025-06-19T03:13:46.964Z] GC before operation: completed in 182.181 ms, heap usage 689.827 MB -> 94.127 MB. [2025-06-19T03:13:48.901Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:13:51.937Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:13:53.872Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:13:55.813Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:13:57.747Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:13:58.688Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:14:00.621Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:14:01.567Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:14:01.567Z] 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. [2025-06-19T03:14:01.567Z] The best model improves the baseline by 14.52%. [2025-06-19T03:14:02.511Z] Top recommended movies for user id 72: [2025-06-19T03:14:02.511Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:14:02.511Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:14:02.511Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:14:02.511Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:14:02.511Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:14:02.511Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (15440.662 ms) ====== [2025-06-19T03:14:02.511Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2025-06-19T03:14:02.511Z] GC before operation: completed in 230.893 ms, heap usage 533.040 MB -> 96.536 MB. [2025-06-19T03:14:04.444Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:14:06.500Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:14:09.486Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:14:11.422Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:14:12.369Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:14:14.313Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:14:15.257Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:14:16.198Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:14:17.141Z] 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. [2025-06-19T03:14:17.141Z] The best model improves the baseline by 14.52%. [2025-06-19T03:14:17.141Z] Top recommended movies for user id 72: [2025-06-19T03:14:17.141Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:14:17.141Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:14:17.141Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:14:17.141Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:14:17.141Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:14:17.141Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (14541.568 ms) ====== [2025-06-19T03:14:17.141Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2025-06-19T03:14:17.141Z] GC before operation: completed in 126.575 ms, heap usage 249.901 MB -> 92.622 MB. [2025-06-19T03:14:19.092Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:14:21.031Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:14:24.021Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:14:25.957Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:14:26.899Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:14:27.842Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:14:29.779Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:14:30.720Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:14:30.720Z] 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. [2025-06-19T03:14:30.720Z] The best model improves the baseline by 14.52%. [2025-06-19T03:14:31.662Z] Top recommended movies for user id 72: [2025-06-19T03:14:31.662Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:14:31.662Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:14:31.662Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:14:31.662Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:14:31.662Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:14:31.662Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (14242.087 ms) ====== [2025-06-19T03:14:31.662Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2025-06-19T03:14:31.662Z] GC before operation: completed in 145.923 ms, heap usage 287.165 MB -> 94.153 MB. [2025-06-19T03:14:33.604Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:14:35.546Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:14:37.482Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:14:39.423Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:14:41.358Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:14:42.302Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:14:44.238Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:14:45.182Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:14:45.182Z] 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. [2025-06-19T03:14:45.182Z] The best model improves the baseline by 14.52%. [2025-06-19T03:14:46.125Z] Top recommended movies for user id 72: [2025-06-19T03:14:46.125Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:14:46.125Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:14:46.125Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:14:46.125Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:14:46.125Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:14:46.125Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (14327.467 ms) ====== [2025-06-19T03:14:46.125Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2025-06-19T03:14:46.125Z] GC before operation: completed in 139.619 ms, heap usage 751.819 MB -> 94.241 MB. [2025-06-19T03:14:48.059Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:14:50.053Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:14:53.073Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:14:55.828Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:14:56.770Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:14:57.715Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:15:00.233Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:15:01.219Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:15:01.219Z] 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. [2025-06-19T03:15:01.219Z] The best model improves the baseline by 14.52%. [2025-06-19T03:15:01.219Z] Top recommended movies for user id 72: [2025-06-19T03:15:01.219Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:15:01.219Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:15:01.219Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:15:01.219Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:15:01.219Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:15:01.219Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (15063.058 ms) ====== [2025-06-19T03:15:01.219Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2025-06-19T03:15:01.219Z] GC before operation: completed in 145.331 ms, heap usage 210.722 MB -> 96.072 MB. [2025-06-19T03:15:03.157Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:15:06.149Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:15:08.095Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:15:10.029Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:15:10.979Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:15:12.917Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:15:13.860Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:15:15.796Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:15:15.796Z] 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. [2025-06-19T03:15:15.796Z] The best model improves the baseline by 14.52%. [2025-06-19T03:15:15.796Z] Top recommended movies for user id 72: [2025-06-19T03:15:15.796Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:15:15.796Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:15:15.796Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:15:15.796Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:15:15.796Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:15:15.796Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (14717.987 ms) ====== [2025-06-19T03:15:15.796Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2025-06-19T03:15:15.796Z] GC before operation: completed in 133.340 ms, heap usage 489.570 MB -> 96.661 MB. [2025-06-19T03:15:18.784Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:15:20.717Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:15:22.657Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:15:24.605Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:15:26.537Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:15:27.478Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:15:29.413Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:15:30.356Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:15:30.356Z] 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. [2025-06-19T03:15:30.356Z] The best model improves the baseline by 14.52%. [2025-06-19T03:15:31.302Z] Top recommended movies for user id 72: [2025-06-19T03:15:31.302Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:15:31.302Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:15:31.302Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:15:31.302Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:15:31.302Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:15:31.302Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (14958.733 ms) ====== [2025-06-19T03:15:31.302Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2025-06-19T03:15:31.302Z] GC before operation: completed in 139.817 ms, heap usage 459.536 MB -> 90.578 MB. [2025-06-19T03:15:33.238Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2025-06-19T03:15:36.226Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2025-06-19T03:15:39.211Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2025-06-19T03:15:41.145Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2025-06-19T03:15:42.087Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2025-06-19T03:15:43.208Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2025-06-19T03:15:45.141Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2025-06-19T03:15:46.082Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2025-06-19T03:15:46.082Z] 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. [2025-06-19T03:15:46.082Z] The best model improves the baseline by 14.52%. [2025-06-19T03:15:47.024Z] Top recommended movies for user id 72: [2025-06-19T03:15:47.024Z] 1: Land of Silence and Darkness (Land des Schweigens und der Dunkelheit) (1971) (rating: 4.659, id: 67504) [2025-06-19T03:15:47.024Z] 2: Goat, The (1921) (rating: 4.659, id: 83318) [2025-06-19T03:15:47.024Z] 3: Play House, The (1921) (rating: 4.659, id: 83359) [2025-06-19T03:15:47.024Z] 4: Cops (1922) (rating: 4.659, id: 83411) [2025-06-19T03:15:47.024Z] 5: Dear Frankie (2004) (rating: 4.267, id: 8530) [2025-06-19T03:15:47.024Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (15606.437 ms) ====== [2025-06-19T03:15:47.024Z] ----------------------------------- [2025-06-19T03:15:47.024Z] renaissance-movie-lens_0_PASSED [2025-06-19T03:15:47.024Z] ----------------------------------- [2025-06-19T03:15:47.024Z] [2025-06-19T03:15:47.024Z] TEST TEARDOWN: [2025-06-19T03:15:47.024Z] Nothing to be done for teardown. [2025-06-19T03:15:47.024Z] renaissance-movie-lens_0 Finish Time: Thu Jun 19 03:15:46 2025 Epoch Time (ms): 1750302946679