Differences between Cloudera Oryx and Apache Mahout<\/h2>\n<\/div>\n<\/div>\n

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• There are 3 broad things an operational ML system needs to do eventually\n
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  • Build models at scale, offline<\/li>\n
  • Update models in near real time<\/li>\n
  • Query models in real time<\/li>\n<\/ul>\n<\/li>\n
  • Most of the tools like Mahout or MLLib do building models at scale only.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
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    • Oryx tries to do all 3, and is not doing building model.<\/li>\n
    • Therefore it is really intended as a complement to any Hadoop-based model build system.<\/li>\n
    • As a result it is MapReduce based for model building and implemented algorithms instead of using Mahout to improve on perceived problems.<\/li>\n
    • The project which is open source, is more designed as 3 complete apps rather than a platform for extension.<\/li>\n
    • It only implements\n
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      • ALS for recommendation<\/li>\n
      • Kmeans for clustering<\/li>\n
      • Random decision forests for classification and regression<\/li>\n<\/ul>\n<\/li>\n
      • The major difference is fewer algorithms but complete apps including incremental update and serving. It is not the algorithms that are really the difference since Oryx is not a new library.<\/li>\n
      • The next version is built on Spark and Kafka then becomes more of generic lambda architecture for ML that happens to have entire apps too.<\/li>\n
      • It is kind of Summing bird for ML on Spark. It has no algorithms implementations at all, not now. Therefore it is even more different from Mahout or MLLib.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
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        <\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

        Answer : There are 3 broad things an operational ML system….<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"passster_activate_protection":false,"passster_protect_child_pages":"","passster_protection_type":"password","passster_password":"","passster_activate_overwrite_defaults":"","passster_headline":"","passster_instruction":"","passster_placeholder":"","passster_button":"","passster_id":"","passster_activate_misc_settings":"","passster_redirect_url":"","passster_hide":"no","passster_area_shortcode":"","gtb_hide_title":false,"gtb_wrap_title":false,"gtb_class_title":"","gtb_remove_headerfooter":false,"footnotes":""},"categories":[7524],"tags":[195,7530,7577,7531,7542,7582,7536,7581,7060,7575,7579,291,7576,7550,7578,7574],"class_list":["post-1079","post","type-post","status-publish","format-standard","hentry","category-mahout","tag-accenture-interview-questions-and-answers","tag-advanced-apache-mahout-interview-questions","tag-advanced-apache-mahout-interview-questions-for-experienced","tag-apache-mahout-interview-questions","tag-apache-mahout-interview-questions-and-answers","tag-apache-mahout-interview-questions-and-answers-for-experienced","tag-apache-mahout-interview-questions-and-answers-for-freshers","tag-apache-mahoutcloudera-mahout","tag-cloudera-architecture","tag-cloudera-oryx","tag-data-science-and-machine-learning-apache-mahout","tag-datamatics-global-services-ltd-interview-questions-and-answers","tag-latest-cloudera-version","tag-mahout-interview-question-and-answers","tag-mahout-interview-questions-and-answers-2018","tag-oryx-cloud-information-technology"],"yoast_head":"\n