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azure-stream-analytics

azure-stream-analytics

github.com/microsoftdocs数据与数据库796167 次安装3 天前更新
代码仓库

关于 azure-stream-analytics

面向 Agent 的 Azure Stream Analytics 参考技能，结合本地速查内容与远程文档获取，覆盖作业开发、故障排查、部署和安全。

主要功能

  1. 01作业错误与性能排查
  2. 02查询和作业设计指导
  3. 03扩展与架构规划
  4. 04安全配置参考
  5. 05集成和代码模式

适用场景

  1. 01定位输入、输出或查询错误
  2. 02优化作业性能与并行化
  3. 03规划作业扩展和部署

MCP 相关

可通过 mcp_microsoftdocs 的工具获取远程文档；若该工具不可用，技能说明可改用 fetch_webpage。

安装

复制下面的命令，在终端中运行。

$npx skills add https://github.com/microsoftdocs/agent-skills --skill azure-stream-analytics

安装后在 Claude Code 中输入/azure-stream-analytics确认已加载。

详细介绍

Azure Stream Analytics 技能

此技能提供有关 Azure Stream Analytics 的专家指导，涵盖故障排除、最佳实践、决策、架构与设计模式、限制与配额、安全性、配置、集成与编码模式，以及部署。它结合本地快速参考内容与远程文档获取功能。

如何使用此技能

Agent 重要提示：使用下方的类别索引查找相关章节。对于带有行范围的类别（例如 L35-L120），请使用 read_file 读取指定行。对于带有文件链接的类别（例如 [security.md](security.md)），请使用 read_file 读取链接的参考文件

Agent 重要提示：如果 metadata.generated_at 的时间早于 3 个月以上，建议用户从代码仓库拉取最新版本。如果无法使用 mcp_microsoftdocs 工具，建议用户安装该工具：安装指南

此技能需要网络访问权限才能获取文档内容：

  • 首选：使用 mcp_microsoftdocs:microsoft_docs_fetch，并将查询字符串设为 from=learn-agent-skill。返回 Markdown。
  • 备用：使用 fetch_webpage，并将查询字符串设为 from=learn-agent-skill&accept=text/markdown。返回 Markdown。

类别索引

类别行说明
故障排除L37-L58使用日志和作业图（逻辑/物理）诊断并修复 Stream Analytics 作业错误（配置、数据、内部/外部）、性能问题以及输入/输出/查询问题。
最佳实践L59-L73Stream Analytics 作业设计、查询模式、性能优化、扩展、可靠性、时间处理、地理空间逻辑、ML/Cosmos/SQL 输出及警报方面的最佳实践。
决策L74-L82有关选择 Stream Analytics 工具和服务、从 Visual Studio/.NET UDF 迁移，以及配置自动缩放和实时处理选项的指导。
架构与设计模式L83-L88设计具有复原能力、支持异地冗余的 Stream Analytics 拓扑，并使用流单元、输入/输出分区和性能优化模式扩展作业。
限制与配额L89-L96Stream Analytics 的限制、大小调整和性能：Event Hubs 输出大小上限、流单元/群集扩展，以及 IoT Edge 专属限制和支持。
安全性L97-L117保护 Stream Analytics 作业：为输入/输出（Event Hubs、SQL、Synapse、Cosmos、Blob、Service Bus、Power BI）配置托管标识、VNet/专用终结点、数据保护及 Azure Policy 合规性。
配置L118-L149配置 Stream Analytics 作业：输入、输出（Cosmos DB、SQL、Event Hubs、Kafka、Power BI、Delta Lake 等）、自动缩放、排序、错误处理、监视和兼容性。
集成与编码模式L150-L166将 Stream Analytics 与 Kafka、SQL、Azure ML、UDF（C#/JS）、异常检测和架构注册表集成的模式与代码，以及 HFT 和 .NET 作业管理等高级场景
部署L167-L180使用 ARM/Bicep、GitHub Actions、Azure DevOps、REST 以及边缘/Stack Hub 工具，自动执行 Stream Analytics 作业和群集的部署、迁移及生命周期管理（启动/停止/删除）
故障排除
主题URL
解决 Stream Analytics 配置错误代码https://learn.microsoft.com/en-us/azure/stream-analytics/configuration-error-codes
解决 Stream Analytics 数据错误代码https://learn.microsoft.com/en-us/azure/stream-analytics/data-error-codes
解决 Azure Stream Analytics 作业中的数据错误https://learn.microsoft.com/en-us/azure/stream-analytics/data-errors
使用 Visual Studio 作业关系图在本地调试 Stream Analytics 查询https://learn.microsoft.com/en-us/azure/stream-analytics/debug-locally-using-job-diagram
使用 VS Code 作业关系图在本地调试 Stream Analytics 查询https://learn.microsoft.com/en-us/azure/stream-analytics/debug-locally-using-job-diagram-vs-code
调试 Azure Stream Analytics 中的用户定义函数https://learn.microsoft.com/en-us/azure/stream-analytics/debug-user-defined-functions
解决 Stream Analytics 外部可用性错误代码https://learn.microsoft.com/en-us/azure/stream-analytics/external-availability-error-codes
解决 Stream Analytics 外部错误代码https://learn.microsoft.com/en-us/azure/stream-analytics/external-error-codes
解决 Stream Analytics 内部错误代码https://learn.microsoft.com/en-us/azure/stream-analytics/internal-error-codes
使用作业关系图指标排查 Stream Analytics 问题https://learn.microsoft.com/en-us/azure/stream-analytics/job-diagram-with-metrics
诊断 Azure Stream Analytics 作业性能https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-job-analysis-with-metric-dimensions
使用资源日志排查 Stream Analytics 作业问题https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-job-diagnostic-logs
使用逻辑作业关系图调试 Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-job-logical-diagram-with-metrics
使用物理作业关系图指标调试 Stream Analyticshttps://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-job-physical-diagram-with-metrics
监视和排查 Azure Stream Analytics 作业问题https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-monitoring
诊断并修复 Azure Stream Analytics 输入问题https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-troubleshoot-input
排查 Azure Stream Analytics 输出连接问题https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-troubleshoot-output
排查 Azure Stream Analytics 查询问题https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-troubleshoot-query
最佳实践
主题URL
在本地开发和调试 Azure Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/develop-locally
使用 Stream Analytics 构建地理围栏和地理空间聚合https://learn.microsoft.com/en-us/azure/stream-analytics/geospatial-scenarios
为 Stream Analytics 实现输入验证模式，增强复原能力https://learn.microsoft.com/en-us/azure/stream-analytics/input-validation
使用作业模拟优化 Stream Analytics 查询性能https://learn.microsoft.com/en-us/azure/stream-analytics/optimize-query-using-job-diagram-simulator
使用重新分区优化不可并行化的 Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/repartition
提高 Azure Stream Analytics 作业的可靠性并进行升级https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-job-reliability
使用查询并行化优化 Azure Stream Analyticshttps://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-parallelization
优化 Azure SQL Database 输出的 Stream Analytics 性能https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-sql-output-perf
在 Azure Stream Analytics 中应用常见查询模式https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-stream-analytics-query-patterns
在 Stream Analytics 中实现可配置的阈值告警https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-threshold-based-rules
设计 Azure Stream Analytics 中的时间处理和延迟处理https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-time-handling
决策
主题URL
选择 Azure Stream Analytics 门户或 VS Code 工具https://learn.microsoft.com/en-us/azure/stream-analytics/feature-comparison
将 Stream Analytics 项目从 Visual Studio 迁移到 VS Codehttps://learn.microsoft.com/en-us/azure/stream-analytics/migrate-to-vscode
选择并配置适用于 Stream Analytics SU 的自动缩放https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-autoscale
在 Stream Analytics 中从 .NET UDF 迁移到 JavaScripthttps://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-edge-csharp-udf-methods
选择 Azure 实时和流处理服务https://learn.microsoft.com/en-us/azure/stream-analytics/streaming-technologies
架构与设计模式
主题URL
设计具有异地冗余的 Azure Stream Analytics 作业架构https://learn.microsoft.com/en-us/azure/stream-analytics/geo-redundancy
使用 SU 和分区扩展 Azure Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-scale-jobs
限制与配额
主题URL
将 Event Hubs 用作 Stream Analytics 输出并了解大小限制https://learn.microsoft.com/en-us/azure/stream-analytics/event-hubs-output
按流式处理单元调整 Azure Stream Analytics 群集大小https://learn.microsoft.com/en-us/azure/stream-analytics/scale-cluster
了解 Azure Stream Analytics 在 IoT Edge 上的限制和支持https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-edge
了解并调整 Azure Stream Analytics 流式处理单元https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-streaming-unit-consumption
安全性
主题URL
为 Azure Data Explorer 输出配置托管标识https://learn.microsoft.com/en-us/azure/stream-analytics/azure-data-explorer-managed-identity
为 Stream Analytics Blob 输出配置托管标识身份验证https://learn.microsoft.com/en-us/azure/stream-analytics/blob-output-managed-identity
安全地将 Stream Analytics 作业连接到 Azure VNethttps://learn.microsoft.com/en-us/azure/stream-analytics/connect-job-to-vnet
在 Stream Analytics 中为 Cosmos DB 输出使用托管标识https://learn.microsoft.com/en-us/azure/stream-analytics/cosmos-db-managed-identity
为 Azure Stream Analytics 配置数据保护https://learn.microsoft.com/en-us/azure/stream-analytics/data-protection
使用托管标识从 Stream Analytics 访问 Event Hubshttps://learn.microsoft.com/en-us/azure/stream-analytics/event-hubs-managed-identity
将内置 Azure Policy 定义应用于 Stream Analyticshttps://learn.microsoft.com/en-us/azure/stream-analytics/policy-reference
为 Stream Analytics Power BI 输出设置托管标识身份验证https://learn.microsoft.com/en-us/azure/stream-analytics/powerbi-output-managed-identity
配置 Stream Analytics 群集托管专用终结点https://learn.microsoft.com/en-us/azure/stream-analytics/private-endpoints
在虚拟网络中保护 Azure Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/run-job-in-virtual-network
将 Azure Policy 合规性控制应用于 Stream Analyticshttps://learn.microsoft.com/en-us/azure/stream-analytics/security-controls-policy
使用托管标识将 Stream Analytics 输出发送到 Service Bushttps://learn.microsoft.com/en-us/azure/stream-analytics/service-bus-managed-identity
使用托管标识将 Stream Analytics 连接到 Azure SQL 和 Synapsehttps://learn.microsoft.com/en-us/azure/stream-analytics/sql-database-output-managed-identity
配置 Stream Analytics 的 Kafka 输入和安全性https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-kafka-input
轮换 Azure Stream Analytics 作业的输入和输出凭据https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-login-credentials-inputs-outputs
在 Azure Stream Analytics 中使用托管标识https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-managed-identities-overview
为 Stream Analytics 配置用户分配的托管标识https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-user-assigned-managed-identity-overview
配置
主题URL
将 Azure Cosmos DB 配置为 Stream Analytics 输出https://learn.microsoft.com/en-us/azure/stream-analytics/azure-cosmos-db-output
将 Azure Data Explorer 配置为 Stream Analytics 输出https://learn.microsoft.com/en-us/azure/stream-analytics/azure-database-explorer-output
将 Azure Stream Analytics 输出连接到 Azure Functionshttps://learn.microsoft.com/en-us/azure/stream-analytics/azure-functions-output
将 Azure Synapse Analytics 专用 SQL 池配置为 Stream Analytics 输出https://learn.microsoft.com/en-us/azure/stream-analytics/azure-synapse-analytics-output
为 Stream Analytics 配置 Blob Storage 和 Data Lake Gen2 输出https://learn.microsoft.com/en-us/azure/stream-analytics/blob-storage-azure-data-lake-gen2-output
通过 CI/CD 工具配置 Stream Analytics 自动缩放设置https://learn.microsoft.com/en-us/azure/stream-analytics/cicd-autoscale
在 Azure Stream Analytics 中配置事件排序策略https://learn.microsoft.com/en-us/azure/stream-analytics/event-ordering
VS Code 中 Stream Analytics 的 JobConfig.json 字段参考https://learn.microsoft.com/en-us/azure/stream-analytics/job-config-json
为 Azure Stream Analytics 配置 Kafka 输出https://learn.microsoft.com/en-us/azure/stream-analytics/kafka-output
使用 Azure Monitor 配置 Azure Stream Analytics 监视https://learn.microsoft.com/en-us/azure/stream-analytics/monitor-azure-stream-analytics
Azure Stream Analytics 监视指标和日志参考https://learn.microsoft.com/en-us/azure/stream-analytics/monitor-azure-stream-analytics-reference
将 Azure Database for PostgreSQL 配置为 Stream Analytics 输出https://learn.microsoft.com/en-us/azure/stream-analytics/postgresql-database-output
将 Power BI 配置为 Azure Stream Analytics 输出https://learn.microsoft.com/en-us/azure/stream-analytics/power-bi-output
将 Service Bus 队列配置为 Stream Analytics 输出https://learn.microsoft.com/en-us/azure/stream-analytics/service-bus-queues-output
将 Service Bus 主题配置为 Stream Analytics 输出https://learn.microsoft.com/en-us/azure/stream-analytics/service-bus-topics-output
将 Azure SQL Database 配置为 Stream Analytics 输出https://learn.microsoft.com/en-us/azure/stream-analytics/sql-database-output
将 Azure SQL Database 配置为 Stream Analytics 输出https://learn.microsoft.com/en-us/azure/stream-analytics/sql-db-table
为 Azure Stream Analytics 作业配置兼容性级别https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-compatibility-level
在 Stream Analytics 中配置自定义 Blob 输出分区https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-custom-path-patterns-blob-storage-output
为 Azure Stream Analytics 作业配置输入源https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-inputs
为 Stream Analytics 配置 Azure Cosmos DB 输出https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-documentdb-output
使用 PowerShell 监视和管理 Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-monitor-and-manage-jobs-use-powershell
以编程方式启用和配置 Stream Analytics 作业监视https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-monitor-jobs
在 Azure Stream Analytics 中配置输出错误处理策略https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-output-error-policy
在 Stream Analytics 中配置 Protobuf 输入反序列化https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-parsing-protobuf
为 Stream Analytics 作业设置 Azure Monitor 警报https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-set-up-alerts
为 Stream Analytics 设置 Azure Table 存储输出https://learn.microsoft.com/en-us/azure/stream-analytics/table-storage-output
将 Azure Stream Analytics 输出配置为 Delta Lakehttps://learn.microsoft.com/en-us/azure/stream-analytics/write-to-delta-lake
集成与编码模式
主题URL
将 Confluent Cloud Kafka 用作 Stream Analytics 输入https://learn.microsoft.com/en-us/azure/stream-analytics/confluent-kafka-input
将 Stream Analytics 输出发送到 Confluent Cloud Kafkahttps://learn.microsoft.com/en-us/azure/stream-analytics/confluent-kafka-output
将 Azure Machine Learning 模型集成为 Stream Analytics UDFhttps://learn.microsoft.com/en-us/azure/stream-analytics/machine-learning-udf
通过 Azure Functions 从 Stream Analytics 实现 SQL UPDATE/UPSERThttps://learn.microsoft.com/en-us/azure/stream-analytics/sql-database-upsert
将 Azure SQL Database 配置为参考输入https://learn.microsoft.com/en-us/azure/stream-analytics/sql-reference-data
使用 .NET Management SDK 管理 Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-dotnet-management-sdk
在 Visual Studio 中为 Stream Analytics 编写 C# 用户定义函数https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-edge-csharp-udf
使用 Stream Analytics 实现高频交易https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-high-frequency-trading
在 Stream Analytics 中创建 JavaScript 用户定义聚合函数https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-javascript-user-defined-aggregates
在 Azure Stream Analytics 中实现 JavaScript UDFhttps://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-javascript-user-defined-functions
在 Stream Analytics 中使用内置机器学习异常检测https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly-detection
在 Stream Analytics 中分析 JSON、Avro 和复杂数据https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-parsing-json
将 Azure Stream Analytics 与 Event Hubs Schema Registry 集成https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-schema-registry-integration
部署
主题URL
使用 Bicep 生成并部署 Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/cicd-deploy-with-bicep
使用 GitHub Actions 工作流部署 Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/cicd-github-actions
跨区域迁移 Azure Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/move-across-regions
跨区域移动 Azure Stream Analytics 群集https://learn.microsoft.com/en-us/azure/stream-analytics/move-cluster
将 Stream Analytics 边缘作业部署到 Azure Stack Hubhttps://learn.microsoft.com/en-us/azure/stream-analytics/on-azure-stack
将 Stream Analytics 作业导出为 ARM 模板https://learn.microsoft.com/en-us/azure/stream-analytics/resource-manager-export
为 Stream Analytics 设置 Azure DevOps CI/CDhttps://learn.microsoft.com/en-us/azure/stream-analytics/set-up-cicd-pipeline
通过门户、PowerShell 和 Visual Studio 启动 Azure Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/start-job
通过 REST 为 IoT Edge 上的 Stream Analytics 实现 CI/CDhttps://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-cicd-api
安全停止并删除 Azure Stream Analytics 作业https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-clean-up-your-job
将 Stream Analytics CI/CD NuGet 包与 MSBuild 配合使用https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-tools-for-visual-studio-cicd

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