kql
适用于大规模时序与日志数据分析，包含实战与性能注意点。
提供 Kusto Query Language 的专业查询编写与优化建议。
帮你写、调试和优化 Kusto Query Language（KQL）查询，覆盖语法陷阱、join 模式、datetime 问题、性能和内存考量等常见错误。用在 Azure Data Explorer、Log Analytics 或 Fabric 的数据探索、告警和分析时，能避免低效查询带来的成本与重试。特别强调各种 gotchas 与高阶函数（geo、vector、graph）的实用写法，让查询既正确又高效。
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KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.
帮我安装这个 skill：https://raw.githubusercontent.com/microsoft/skills/main/.github/skills/kql/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/microsoft/skills/main/.github/skills/kql/SKILL.md"# KQL Mastery > **Try it yourself**: All `✅` examples in this skill can be run against the public help cluster: > `https://help.kusto.windows.net`, database `Samples` (contains `StormEvents`, `SimpleGraph_Nodes`/`Edges`, `nyc_taxi`, and more). ## 1. KQL Basics Kusto Query Language (KQL) is a pipe-forward query language for exploring data. It is the native query language for Azure Data Explorer (ADX), Microsoft Fabric Real-Time Intelligence (EventHouse), Azure Monitor Log Analytics, Microsoft Sentinel, and other Microsoft data services. ### Pipe-forward syntax KQL queries are a chain of operators separated by `|`. Data flows left to right: ```kql StormEvents //