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所在平台: Udemy |
课程主页: https://www.udemy.com/course/azure-kusto-query-language-kql-for-log-analytics-and-fabric/
课程评论：没有评论
课程名称：Azure Kusto 查询语言 KQL 用于日志分析和 Fabric 课程概述：完成该课程后，学员将能够熟练使用 Azure Kusto 查询语言 (KQL) 进行日志分析，并实现与从 Databricks、Spark 和 Azure 日志中导入的 Azure 服务日志相关的指标的日志分析工作簿。KQL 是一款强大的工具，可以帮助用户探索数据、发现模式、识别异常和离群值、创建统计模型等。该语言简单而强大，适合查询结构化、半结构化和非结构化的数据，语法表达清晰，易于阅读和理解意图，并针对创作体验进行了优化。 KQL 适合查询遥测数据、指标和日志，并深度支持文本搜索和解析、时间序列操作符和函数、分析与聚合、地理空间查询、向量相似性搜索等多种语言构造，提供最佳的数据分析语言。该查询使用的模式实体按层次结构组织，类似 SQL 的数据库、表和列。KQL （Kusto 查询语言）是在易读易理解的语法、高性能扩展性以及从简单到复杂查询的平滑过渡等核心原则的指导下开发的。 有趣的是，KQL 是一种只读查询语言，处理数据并返回结果。它与 SQL 类似，由一系列语句构成，语句的执行流从前一个语句的表格数据输出传递到下一个语句。这些语句通过管道（|）字符连接。在 SQL 中，查询以列名开头，我们只能在遇到 "From" 语句时才得知表名，而在 KQL 中，查询以表名开头，后接管道字符，随后定义条件。我们将在课程中深入了解这种工作原理。
After completion of this you would be writing Azure Kusto Query Language KQL comfortably using the Azure Log analytics and implement the Log Analytics workbook with metrics related to the import azure service logs from Databricks, spark, Azure logs.Kusto Query Language (KQL) is a powerful tool to explore your data and discover patterns, identify anomalies and outliers, create statistical modeling, and more. KQL is a simple yet powerful language to query structured, semi-structured, and unstructured data. The language is expressive, easy to read and understand the query intent, and optimized for authoring experiences. Kusto Query Language is optimal for querying telemetry, metrics, and logs with deep support for text search and parsing, time-series operators and functions, analytics and aggregation, geospatial, vector similarity searches, and many other language constructs that provide the most optimal language for data analysis. The query uses schema entities that are organized in a hierarchy similar to SQLs: databases, tables, and columns.KQL (Kusto Query Language) was developed with certain key principals in mind, like - easy to read and understand syntax, provide high-performance through scaling, and the one that can transition smoothly from simple to complex query.Interestingly KQL is a read-only query language, which processes the data and returns results. It is very similar to SQL with a sequence of statements, where the statements are modeled as a flow of tabular data output from the previous statement to the next statement. These statements are concatenated with a pipe () character.In SQL, the queries start with the column names and we only get to know about the table name when we reach the "From" statement, whereas, in KQL, the query starts with the table name followed by the pipe character after which the conditions are defined. We will see how this works shortly.
