In this case, all records from the InsightsMetrics table are returned and then sent to the count operator.

To find out how large the table is, we'll pipe its content into an operator that counts rows.Ī query is a data source (usually a table name), optionally followed by one or more pairs of the pipe character and some tabular operator. The InsightsMetrics table contains performance data that's collected by insights such as Azure Monitor for VMs and Azure Monitor for containers. Because the data in the demo environment isn't static, the results of your queries might vary slightly from the results shown here. You can use your own environment, but you might not have some of the tables that are used here.

If you aren't familiar with Log Analytics, complete the Log Analytics tutorial.Īll queries in this tutorial use the Log Analytics demo environment. Use log data in Azure Monitor, and then evaluate log query results. Log Analytics is a tool you can use to write log queries. Run these queries by using Log Analytics in the Azure portal. These queries are similar to queries in the Azure Data Explorer tutorial, but use data from common tables in an Azure Log Analytics workspace. The best way to learn about the Azure Data Explorer Query Language is to look at some basic queries to get a 'feel' for the language. If the Telemetry database was in a cluster named Telemetr圜, to access it, use this query: Logs | join cluster('Telemetr圜luster').database('Telemetry').Metrics on Request MachineId |. The preceding two queries assume that both databases are in the cluster you're currently connected to. Use this query if your default database is Telemetry: union Requests, database('Diagnostics').Logs |. To access a table in a different database, use the following syntax: database('db').Tableįor example, if you have databases named Diagnostics and Telemetry and you want to correlate some of the data in the two tables, you might use the following query (assuming Diagnostics is your default database): Logs | join database('Telemetry').Metrics on Request MachineId |. In the following query, the Logs table must be in your default database: Logs | where. Combine data from several databases in a query In Kusto Explorer, to execute the entire query, don't add blank lines between parts of the query.Īny two statements must be separated by a semicolon. The results are unchanged: let LightningStorms = Use let to separate out the parts of the query expression in the preceding join example. The query removes zero count entries: StartTime | project StartTime, InjuriesDirect, InjuriesIndirect, Percentage | extend Percentage = ( 100 * InjuriesDirect / (InjuriesDirect + InjuriesIndirect) ) | where duration 0) and (InjuriesIndirect > 0) | where StartTime > datetime() and StartTime 0s Use multiple values in a summarize by clause to create a separate row for each combination of values: StormEvents

| summarize event_count=count() by bin(StartTime, 1d) Going back to numeric bins, let's display a time series: StormEvents Still, it's integrated into the language, and it's useful for envisioning your results. Strictly speaking, render is a feature of the client rather than part of the query language. | where StartTime > datetime() and StartTime datetime() and StartTime 1800Īlthough we removed mid in the project operation, we still need it if we want the chart to display the states in that order. Let's see only flood events in California in Feb-2007: StormEvents See the following example, which uses both the projectĪnd the take operators. Use project to pick out only the columns you want. StormEvents | countįor more information, see count operator. Syntax note: A query is a data source (usually a table name), optionally followed by one or more pairs of the pipe character and some tabular operator. So we'll pipe its content into an operator that counts the rows in the table. we want to find out how large the table is. Our example database has a table called StormEvents. The StormEvents table in the sample database provides some information about storms that happened in the United States. The queries that are demonstrated in this tutorial should run on that database. We recommend using a database with some sample data. The best way to learn about the Kusto Query Language is to look at some basic queries to get a 'feel' for the language.

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