[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117249-en":3,"doc-seo-117249-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117249,8796095462418,"Noah","https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780",6,"Technology","Flink-ML - machine learning in Apache Flink","Big Data growth has driven the rise of data processing frameworks such as Hadoop, Spark, Flink, Storm, Pig, and Zookeeper, with Apache Flink recognized for strong stream and batch processing. The paper presents Flink-ML, Flink’s open-source distributed machine learning library integrated into the Flink ecosystem to meet the expanding need for scalable ML. Flink-ML offers efficient implementations of multiple algorithms, supports multiple programming languages, and provides a high-level API that streamlines end-to-end ML pipeline development, model building, and deployment for large-scale Big Data projects.","Flink-ML: machine learning in Apache Flink  \nFlink-ML: aprendizado de máquina no Apache Flink  \nFlink-ML: aprendizaje automático en Apache Flink  \nDOI:10.38152/bjtv7n4-015  \nSubmitted: Oct 10th,, 2024  \nApproved: Nov 04, 2024  \nMessaoud Mezati  \nDoctor in Computer Science  \nInstitution: Kasdi Merbah University – Ouargla  \nAddress: Ouargla, Algeria  \n[E-mail: mezati.messaoud@univ-ouargla.dz](E-mail: mezati.messaoud@univ-ouargla.dz)  \nInes Aouria  \nDoctor in Automation and Industrial Computing  \nInstitution: Faculty of Media and Information Science, Kasdi Merbah University –Ouargla  \nAddress: Biskra, Algeria  \nE-mail: [aouria.ines@univ-ouargla.dz](aouria.ines@univ-ouargla.dz)  \nABSTRACT  \nThe emergence of Big Data has spurred the development of various frameworks designed for efficient data storage and processing. Key frameworks include Hadoop, Spark, Flink, Storm, Pig, and Zookeeper. Among these, Apache Flink stands out as a prominent opensource platform known for its powerful stream and batch processing capabilities. It functions as a versatile engine for large-scale processing, incorporating built-in modules for streaming, SQL, machine learning (ML), and visualization tasks.This paper introduces Flink-ML, Flink’s open-source distributed machine learning library, which has been added to the Flink ecosystem in response to the exponential growth of machine learning applications in recent years. Flink-ML addresses the increasing demand for scalable machine learning solutions by offering efficient implementations ofa variety of algorithms. As the community around Flink continues to grow, so too does the number of contributors and available algorithms within Flink-ML.Flink-ML is designed to support multiple programming languages and provides a high-level API that leverages Flink’s rich ecosystem. This integration simplifies the development of end-to-end machine learning pipelines, allowing developers to efficiently build and deploy models. Overall, Flink-ML enhances the capabilities of the Flink framework, making it an ideal choice for organizations looking to harness the power of machine learning within their Big Data projects.  \nKeywords: Apache Flink, Flink-ML, scalable machine learning, distributed algorithms.  \nRESUMO  \nO surgimento do Big Data estimulou o desenvolvimento de várias estruturas projetadas para armazenamento e processamento eficientes de dados. As principais estruturas incluem Hadoop, Spark, Flink, Storm, Pig e Zookeeper. Entre elas, o Apache Flink se destaca como uma plataforma de código aberto proeminente, conhecida por seus poderosos recursos de processamento de fluxo e lote. Este documento apresenta o Flink-ML, a biblioteca de aprendizado de máquina distribuída de código aberto do Flink, que foi adicionada ao ecossistema do Flink em resposta ao crescimento exponencial dos aplicativos de  \naprendizado de máquina nos últimos anos. O Flink-ML atende à crescente demanda por soluções de aprendizado de máquina dimensionáveis, oferecendo implementações eficientes de uma variedade de algoritmos. Como a comunidade em torno do Flink continua a crescer, o mesmo acontece com o número de colaboradores e algoritmos disponíveis no Flink-ML. O Flink-ML foi projetado para suportar várias linguagens de programação e fornece uma API de alto nível que aproveita o rico ecossistema do Flink. Essa integração simplifica odesenvolvimento de pipelines de aprendizado de máquina de ponta a ponta, permitindo que os desenvolvedores criem e implementem modelos com eficiência. De modo geral, o FlinkML aprimora os recursos da estrutura do Flink, tornando-o a opção ideal para organizaçõesque buscam aproveitar o poder do aprendizado de máquina em seus projetos de Big Data.  \nPalavras-chave: Apache Flink, Flink-ML, aprendizado de máquina escalável, algoritmos distribuídos.  \nRESUMEN  \nLa aparición de Big Data ha impulsado el desarrollo de varios marcos diseñados para el almacenamiento y procesamiento eficiente de datos. Entre los principales ma","cbCaim78ikLYS0Gx","https://ap.wps.com/l/cbCaim78ikLYS0Gx","pdf",498377,1,18,"English","en",105,"# Introduction\n## Flink and Flink-ML overview\n## Motivation from Big Data and scalable ML\n## Integration for ML pipeline development","[{\"question\":\"What is Flink-ML and why was it introduced?\",\"answer\":\"Flink-ML is Flink’s open-source distributed machine learning library introduced to address the increasing demand for scalable machine learning as ML applications grow rapidly.\"},{\"question\":\"What capabilities does Apache Flink provide for Flink-ML integration?\",\"answer\":\"Apache Flink provides powerful stream and batch processing, and Flink-ML leverages Flink’s ecosystem through built-in modules and a high-level API for developing end-to-end ML pipelines.\"},{\"question\":\"How does Flink-ML help in building and deploying machine learning models?\",\"answer\":\"FlinK-ML simplifies development of end-to-end ML pipelines by enabling efficient implementations of various algorithms and allowing developers to build and deploy models effectively at scale.\"}]","Flink-ML - machine learning in Apache Flink | PDF",1785674662,45,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"flink-ml-machine-learning-in-apache-flink","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/technology/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/flink-ml-machine-learning-in-apache-flink/117249/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is Flink-ML and why was it introduced?","Question",{"text":75,"@type":76},"Flink-ML is Flink’s open-source distributed machine learning library introduced to address the increasing demand for scalable machine learning as ML applications grow rapidly.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What capabilities does Apache Flink provide for Flink-ML integration?",{"text":80,"@type":76},"Apache Flink provides powerful stream and batch processing, and Flink-ML leverages Flink’s ecosystem through built-in modules and a high-level API for developing end-to-end ML pipelines.",{"name":82,"@type":73,"acceptedAnswer":83},"How does Flink-ML help in building and deploying machine learning models?",{"text":84,"@type":76},"FlinK-ML simplifies development of end-to-end ML pipelines by enabling efficient implementations of various algorithms and allowing developers to build and deploy models effectively at scale.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,113,118,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":111,"slug":112},50,"technology",{"id":114,"doc_module":4,"doc_module_name":46,"category_name":115,"show_sort_weight":116,"slug":117},7,"Healthcare",40,"healthcare",{"id":119,"doc_module":4,"doc_module_name":46,"category_name":120,"show_sort_weight":121,"slug":122},8,"Research & Report",30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]