enough to be integrated into PlantUML standard distribution. PlantUML relies on the Java Scripting API (specifically: new ScriptEngineManager().getEngineByName("JavaScript");) to load a JavaScript engine icons in various IT areas such as architecture, cloud services, logos etc. It including AWS, Azure, Kubernetes, C4, product Logos and many others. To explore these libraries: • Browse the Github folders of left to right direction Users(sources, "Events", "millions of users") APIGateway(votingAPI, "Voting API", "user votes") Cognito(userAuth, "User Authentication", "jwt to submit votes") Lambda(generateToken

enough to be integrated into PlantUML standard distribution. PlantUML relies on the Java Scripting API (specifically: new ScriptEngineManager().getEngineByName("JavaScript");) to load a JavaScript engine icons in various IT areas such as architecture, cloud services, logos etc. It including AWS, Azure, Kubernetes, C4, product Logos and many others. To explore these libraries: • Browse the Github folders of left to right direction Users(sources, "Events", "millions of users") APIGateway(votingAPI, "Voting API", "user votes") Cognito(userAuth, "User Authentication", "jwt to submit votes") Lambda(generateToken

enough to be integrated into PlantUML standard distribution. PlantUML relies on the Java Scripting API (specifically: new ScriptEngineManager().getEngineByName("JavaScript");) to load a JavaScript engine icons in various IT areas such as architecture, cloud services, logos etc. It including AWS, Azure, Kubernetes, C4, product Logos and many others. To explore these libraries: • Browse the Github folders of left to right direction Users(sources, "Events", "millions of users") APIGateway(votingAPI, "Voting API", "user votes") Cognito(userAuth, "User Authentication", "jwt to submit votes") Lambda(generateToken

enough to be integrated into PlantUML standard distribution. PlantUML relies on the Java Scripting API (specifically: new ScriptEngineManager().getEngineByName("JavaScript");) to load a JavaScript engine icons in various IT areas such as architecture, cloud services, logos etc. It including AWS, Azure, Kubernetes, C4, product Logos and many others. To explore these libraries: • Browse the Github folders of left to right direction Users(sources, "Events", "millions of users") APIGateway(votingAPI, "Voting API", "user votes") Cognito(userAuth, "User Authentication", "jwt to submit votes") Lambda(generateToken

enough to be integrated into PlantUML standard distribution. PlantUML relies on the Java Scripting API (specifically: new ScriptEngineManager().getEngineByName("JavaScript");) to load a JavaScript engine icons in various IT areas such as architecture, cloud services, logos etc. It including AWS, Azure, Kubernetes, C4, product Logos and many others. To explore these libraries: • Browse the Github folders of left to right direction Users(sources, "Events", "millions of users") APIGateway(votingAPI, "Voting API", "user votes") Cognito(userAuth, "User Authentication", "jwt to submit votes") Lambda(generateToken

icons in various IT areas such as architecture, cloud services, logos etc. It including AWS, Azure, Kubernetes, C4, product Logos and many others. To explore these libraries: • Browse the Github folders of #ffffff DOGU_SMEAGOL(smeagol, Smeagol) #ffffff DOGU_NEXUS(nexus,Nexus) #ffffff } TOOL_K8S(k8s, Kubernetes) #ffffff actor developer developer --> smeagol : "Edit Slides" smeagol -> scm : Push scm -> jenkins include !include !include kubernetes/cloud_in_kubernetes> !include !include !include

报表等大数据应用。我们常见的大数据架构 的逻辑组件关系如下图所示： 这些逻辑组件包括：  数据源：数据源包括关系型数据库、日志文件、实时消息等。  数据存储：面向海量数据存储的分布式文件存储服务，支持 结构化数据和非结构数据数据存 储，我们也常称之为数据湖。如 HDFS、对象存储服务等。  批处理：由于大数据场景必须处理大规模的数据集，批处理往往需要从数据存储中读取大量 数据进 行长 MLib/ML、Tensorflow 等。  分析型数据存储：对数据进行处理加工后，面向应用场景，将数据以结构化的方式进行存储， 以便分析工具或分析应用能够获取数据。如利用 MPP 数据仓库、Spark SQL 等支持 BI 工具 访问，利用 Hbase 实现低延迟的在线服务等  分析与报表：对数据进行分析和展现以获取洞察。如 BI 工具、jupyter 等。  数据作业编排：将多个数据处理动作 MaxCompute 产品组件 特性介绍 数据存储 MaxCompute 表 (基于盘古分布式存储) MaxCompute 支持大规模计算存储，适用于 TB 以上规 模的存储及计算需求，最大可达 EB 级别。同一个 MaxCompute 项目支持企业从创业团队发展到独角兽的 数据规模需求； 数据分布式存储，多副本冗余，数据存储对外仅开放表的 操作接口，不提供文件系统访问接口

，以实现统一存储系统的需求，即在单个存储系统中多副 本PageFile支持块设备、三副本AppendFile（待开发）支持在线对象存储、AppendECFile（待开发）支持 近线对象存储可以共存。 如上所示LogicalPool与pool为多对一的关系，一个物理pool可以存放各种类型的file。当然由于curve支持 多个pool，可以选择一个logicalPool独享一个pool。 模块进行均衡及配置变更的依据 • 通过chunkserver定期上报copyset的copyset的epoch， 检测chunkserver的copyset与mds差异，同 步两者的copyset信息 • 支持配置变更功能，在心跳回复报文中下发mds发起的配置变更命令，并在后续心跳中获取配置 变更进度。HEARTBEAT MDS端：mds 端的心跳主要由三个部分组成： • TopoUpdater: 根据

Interfaces de AIDL . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 34.1.2 Generated Service API . . . . . . . . . . . . . . . . . . . . . . . . . . 207 34.1.3 Implementación del servicio . . . Cliente de AIDL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 34.1.7 Cambio de API . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 34.1.8 Updating Client and Service trait, sin nombrar el tipo. Esto puede ser útil cuando no quieres exponer el tipo concreto en una API pública. 87 La inferencia es más complicada en la posición de retorno. Una función que devuelve impl

4646 Documentación de Postfix en formato texto y html sasl2-bin V:5, I:13 371 Implementación de la API Cyrus SASL (complemento a postfix para SMTP AUTH) cyrus-sasl2-doc I:0 2154 Documentación Cyrus SASL configuración manual. Compatible con programas daemon.) El paquete xdg-desktop-portal proporciona una API estandarizada para funciones comunes de escritorio. Verportal de escritorio xdg (flatpack) y portal las llamada a la biblioteca del sistema sobre la propiedad del archivo, como fakeroot Emulación de API de SO como Wine Virtualización a nivel del intérprete, además de la selección de la ejecución y anulaciones