Get data from file

In this article, you learn how to get data from a local file into either a new or existing table.

Prerequisites

Source

  1. On the lower ribbon of your KQL database, select Get Data.

    In the Get data window, the Source tab is selected.

  2. Select the data source from the available list. In this example, you're ingesting data from Local file.

    Screenshot of get data window with source tab selected.

Configure

  1. Select a target table. If you want to ingest data into a new table, select + New table and enter a table name.

    Note

    Table names can be up to 1024 characters including spaces, alphanumeric, hyphens, and underscores. Special characters aren't supported.

  2. Either drag files into the window, or select Browse for files.

    Note

    You can add up to 1,000 files. Each file can be a max of 1 GB uncompressed.

    Screenshot of configure tab with new table entered and one sample data file selected.

  3. Select Next

Inspect

The Inspect tab opens with a preview of the data.

To complete the ingestion process, select Finish.

Screenshot of the inspect tab.

Optionally:

Edit columns

Note

  • For tabular formats (CSV, TSV, PSV), you can't map a column twice. To map to an existing column, first delete the new column.
  • You can't change an existing column type. If you try to map to a column having a different format, you may end up with empty columns.

The changes you can make in a table depend on the following parameters:

  • Table type is new or existing
  • Mapping type is new or existing
Table type Mapping type Available adjustments
New table New mapping Rename column, change data type, change data source, mapping transformation, add column, delete column
Existing table New mapping Add column (on which you can then change data type, rename, and update)
Existing table Existing mapping none

Screenshot of columns open for editing.

Mapping transformations

Some data format mappings (Parquet, JSON, and Avro) support simple ingest-time transformations. To apply mapping transformations, create or update a column in the Edit columns window.

Mapping transformations can be performed on a column of type string or datetime, with the source having data type int or long. Supported mapping transformations are:

  • DateTimeFromUnixSeconds
  • DateTimeFromUnixMilliseconds
  • DateTimeFromUnixMicroseconds
  • DateTimeFromUnixNanoseconds

Advanced options based on data type

Tabular (CSV, TSV, PSV):

  • If you're ingesting tabular formats in an existing table, you can select Advanced > Keep table schema. Tabular data doesn't necessarily include the column names that are used to map source data to the existing columns. When this option is checked, mapping is done by-order, and the table schema remains the same. If this option is unchecked, new columns are created for incoming data, regardless of data structure.

  • To use the first row as column names, select Advanced > First row is column header.

    Screenshot of advanced CSV options.

JSON:

  • To determine column division of JSON data, select Advanced > Nested levels, from 1 to 100.

  • If you select Advanced > Skip JSON lines with errors, the data is ingested in JSON format. If you leave this check box unselected, the data is ingested in multijson format.

    Screenshot of advanced JSON options.

Summary

In the Data preparation window, all three steps are marked with green check marks when data ingestion finishes successfully. You can select a card to query, drop the ingested data, or see a dashboard of your ingestion summary.

Screenshot of summary page with successful ingestion completed.