Na última parte da série de cursos do Dataflow, vamos abordar os componentes do modelo operacional do Dataflow. Veremos ferramentas e técnicas para solucionar problemas e otimizar o desempenho do pipeline. Depois analisaremos as práticas recomendadas de teste, implantação e confiabilidade para pipelines do Dataflow. Por fim, faremos uma revisão dos modelos, que facilitam o escalonamento dos pipelines do Dataflow para organizações com centenas de usuários. Essas lições garantem que a plataforma de dados seja estável e resiliente a circunstâncias imprevistas.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Serverless Data Processing Dataflow em Português Brasileiro
Serverless Data Processing with Dataflow: Operations em Português Brasileiro
Über diesen Kurs
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Über den Spezialisierung Serverless Data Processing Dataflow em Português Brasileiro
Está se tornando cada vez mais difícil manter uma pilha de tecnologia que possa acompanhar as crescentes demandas de um negócio orientado a dados. Todo praticante de Big Data está familiarizado com os três V’s do Big Data: volume, velocidade e variedade. E se houvesse uma tecnologia à prova de escala projetada para atender a essas demandas? Entre no Google Cloud Dataflow. O Google Cloud Dataflow simplifica o processamento de dados unificando o processamento em lote e fluxo e fornecendo uma experiência sem servidor que permite que os usuários se concentrem na análise, não na infraestrutura. Essa especialização destina-se a clientes e parceiros que desejam aprofundar sua compreensão do Dataflow para aprimorar seus aplicativos de processamento de dados. Esta especialização contém três cursos: Foundations, que explica como o Apache Beam e o Dataflow trabalham juntos para atender às suas necessidades de processamento de dados sem o risco de dependência do fornecedor Developing Pipelines, que aborda como você converte nossa lógica de negócios em aplicativos de processamento de dados que podem ser executados no Dataflow Operations, que analisa as lições mais importantes para operar um aplicativo de dados no Dataflow, incluindo monitoramento, solução de problemas, teste e confiabilidade.
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Last Updated: September 1, 2015
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