What Is Kusto?

Kusto is a big data analytics platform created by Microsoft, designed as a powerful data exploration tool that enables users to discover patterns, identify anomalies and outliers, and create statistical models within large datasets. It is a query language used to query telemetry, metrics, and logs, making it optimal for working with these types of data. Kusto supports a wide range of operations including text search, parsing, time-series analysis, analytics, aggregation, geospatial and vector similarity searches, which contribute to its robust capabilities in data examination.

Internally referred to as Azure Data Explorer, Kusto employs KQL, Kusto Query Language, known for being a simple, expressive, and easy-to-read and understand language. This enhances the authoring experiences, allowing Kusto to cater to both technical and non-technical users. Its simplicity does not compromise its expressiveness and power, thus making it a versatile tool for a variety of data-related tasks. Kusto can be accessed using the Azure Data Explorer web UI, providing a user-friendly interface for performing complex data queries.

With its extensive usage in Microsoft services, Kusto is an integral part of Log Analytics, Sentinel, and Microsoft Defender ATP, where it plays a critical role in monitoring and security. The platform's name may be inspired by Jacques Cousteau, paying homage to its capability to explore vast 'oceans of data,' as suggested by the splash screen of Kusto Explorer. This imagery underlines the depth and breadth of insights Kusto can provide to its users.

Exporting Kusto Data to a CSV File

Using .export Command

The .export command in Kusto allows for writing the first result set of a query to an external cloud storage. To perform this operation, a storage connection string must be specified to define the destination of the exported data. The command executes asynchronously and by default, the operation is distributed. When exporting data in CSV format, the command creates a file with a .csv extension.

Specifying the Storage Connection

The external cloud storage to which the data will be exported is defined by a storage connection string. This connection string is critical as it dictates the storage location and must be set correctly to ensure successful data exportation.

Understanding Export Formats and Compression

While exporting data, it is possible to choose from various formats such as csv, tsv, json, or parquet. Each format corresponds to a specific file extension. Additionally, the .export command supports compression with gzip or snappy, potentially reducing file size and improving transfer speed.

Handling Failures

Errors such as authentication and authorization failures or storage failures due to too many concurrent writes can occur during the export process. It is important to be aware of these potential issues and plan to handle them accordingly.

Considerations for Export Performance

For optimal performance, it is recommended that the exported data reside in the same region as the cluster to expedite the operation. Local writes are generally faster than remote writes. To manage a high load on storage, distributing the load across multiple storage accounts or reducing concurrency may be effective strategies.

Streamline Your Data Workflow with Sourcetable

Using Sourcetable to import your Kusto data into a spreadsheet presents a seamless integration that outperforms the traditional method of exporting to CSV and then importing to a spreadsheet program. Sourcetable synchronizes with your live data from various apps or databases, including Kusto, ensuring that you always have the most up-to-date information at your fingertips. This direct connection eliminates the need for manual data exports, saving time and reducing the risk of errors associated with handling multiple file formats.

Sourcetable's automatic data pulling capabilities allow you to aggregate information from multiple sources into one place. This feature is especially beneficial for those who require a comprehensive overview of their data for in-depth analysis and business intelligence purposes. Moreover, the platform's intuitive spreadsheet interface will feel familiar to users, easing the transition and minimizing the learning curve. Embrace the power of automation and enhance your data management efficiency with Sourcetable.

Common Use Cases

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  Continuous data archiving
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  Data sharing with other cloud services
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  Data transfer to storage in different regions
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  Asynchronous data export tasks

Frequently Asked Questions

How can I export data from Kusto to a CSV file?

You can export data from Kusto to a CSV file using the .export command, which exports the first result set of a query to an external cloud storage in various formats including CSV.

Can I export data to a CSV file in a different region from my Kusto cluster?

Yes, the .export command can write to cloud storage that is in a different region from the cluster asynchronously.

Is it possible to compress the CSV file when exporting from Kusto?

Yes, the .export command can compress output files when exporting data to CSV.

How can I check the data export capacity of my Kusto cluster?

You can use the .show capacity command to display the total, consumed, and remaining data export capacity of your cluster.

Does exporting data from Kusto to CSV support parallel writing?

By default, the .export command writes to storage in parallel using multiple threads, and it performs this task from all nodes in parallel.