Create and alter Azure Storage external tables

The commands in this article can be used to create or alter an Azure Storage external table in the database from which the command is executed. An Azure Storage external table references data located in Azure Blob Storage, Azure Data Lake Store Gen1, or Azure Data Lake Store Gen2.

Permissions

To .create requires at least Database User permissions, and to .alter requires at least Table Admin permissions.

To .create-or-alter an external table using managed identity authentication requires AllDatabasesAdmin permissions.

Syntax

(.create | .alter | .create-or-alter) external table TableName (Schema) kind = storage [partition by (Partitions) [pathformat = (PathFormat)]] dataformat = DataFormat (StorageConnectionString [, ...] ) [with (Property [, ...])]

Learn more about syntax conventions.

Parameters

Name	Type	Required	Description
TableName	string	✔️	An external table name that adheres to the entity names rules. An external table can't have the same name as a regular table in the same database.
Schema	string	✔️	The external data schema is a comma-separated list of one or more column names and data types, where each item follows the format: ColumnName : ColumnType. If the schema is unknown, use infer_storage_schema to infer the schema based on external file contents.
Partitions	string		A comma-separated list of columns by which the external table is partitioned. Partition column can exist in the data file itself, or as part of the file path. See partitions formatting to learn how this value should look.
PathFormat	string		An external data folder URI path format to use with partitions. See path format.
DataFormat	string	✔️	The data format, which can be any of the ingestion formats. We recommend using the Parquet format for external tables to improve query and export performance, unless you use JSON paths mapping. When using an external table for export scenario, you're limited to the following formats: CSV, TSV, JSON and Parquet.
StorageConnectionString	string	✔️	One or more comma-separated paths to Azure Blob Storage blob containers, Azure Data Lake Gen 2 file systems or Azure Data Lake Gen 1 containers, including credentials. The external table storage type is determined by the provided connection strings. See storage connection strings.
Property	string		A key-value property pair in the format PropertyName = PropertyValue. See optional properties.

Authentication and authorization

The authentication method to access an external table is based on the connection string provided during its creation, and the permissions required to access the table vary depending on the authentication method.

The following table lists the supported authentication methods for Azure Storage external tables and the permissions needed to read or write to the table.

Authentication method	Azure Blob Storage / Data Lake Storage Gen2	Data Lake Storage Gen1
Impersonation	Read permissions: Storage Blob Data Reader Write permissions: Storage Blob Data Contributor	Read permissions: Reader Write permissions: Contributor
Managed identity	Read permissions: Storage Blob Data Reader Write permissions: Storage Blob Data Contributor	Read permissions: Reader Write permissions: Contributor
Shared Access (SAS) token	Read permissions: List + Read Write permissions: Write	This authentication method isn't supported in Gen1.
Microsoft Entra access token	No additional permissions required.	No additional permissions required.
Storage account access key	No additional permissions required.	This authentication method isn't supported in Gen1.

Partitions formatting

The partitions list is any combination of partition columns, specified using one of the forms shown in the following table.

Partition Type	Syntax	Notes
Virtual column	PartitionName : (datetime | string)	Read more on virtual columns.
String column value	PartitionName : string = ColumnName
String column value hash	PartitionName : long = hash(ColumnName, Number)	The hash is modulo Number.
Truncated datetime column (value)	PartitionName : datetime = (startofyear | startofmonth | startofweek | startofday) ( ColumnName )	See documentation on startofyear, startofmonth, startofweek, or startofday functions.
Truncated Datetime Column Value (bin)	PartitionName : datetime = bin ( ColumnName , TimeSpan )	Read more about the bin function.

Path format

The PathFormat parameter allows you to specify the format for the external data folder URI path in addition to partitions. It consists of a sequence of partition elements and text separators. A partition element refers to a partition that is declared in the partition by clause, and the text separator is any text enclosed in quotes. Consecutive partition elements must be set apart using the text separator.

[ StringSeparator ] Partition [ StringSeparator ] [Partition [ StringSeparator ] ...]

To construct the original file path prefix, partition elements are rendered as strings and separated with corresponding text separators. You can use the datetime_pattern macro (datetime_pattern(DateTimeFormat, PartitionName)) to specify the format used for rendering a datetime partition value. The macro adheres to the .NET format specification, and allows format specifiers to be enclosed in curly brackets. For example, the following two formats are equivalent:

• 'year='yyyy'/month='MM
• year={yyyy}/month={MM}

By default, datetime values are rendered using the following formats:

Partition function	Default format
startofyear	yyyy
startofmonth	yyyy/MM
startofweek	yyyy/MM/dd
startofday	yyyy/MM/dd
bin(Column, 1d)	yyyy/MM/dd
bin(Column, 1h)	yyyy/MM/dd/HH
bin(Column, 1m)	yyyy/MM/dd/HH/mm

Virtual columns

When data is exported from Spark, partition columns (that are provided to the dataframe writer's partitionBy method) aren't written to data files. This process avoids data duplication because the data is already present in the folder names (for example, column1=<value>/column2=<value>/), and Spark can recognize it upon read.

External tables support reading this data in the form of virtual colums. Virtual columns can be of either type string or datetime, and are specified using the following syntax:

.create external table ExternalTable (EventName:string, Revenue:double)  
kind=storage  
partition by (CustomerName:string, Date:datetime)  
pathformat=("customer=" CustomerName "/date=" datetime_pattern("yyyyMMdd", Date))  
dataformat=parquet
( 
   h@'https://storageaccount.blob.core.chinacloudapi.cn/container1;secretKey'
)

To filter by virtual columns in a query, specify partition names in query predicate:

external_table("ExternalTable")
 | where Date between (datetime(2020-01-01) .. datetime(2020-02-01))
 | where CustomerName in ("John.Doe", "Ivan.Ivanov")

Optional properties

Property	Type	Description
folder	string	Table's folder
docString	string	String documenting the table
compressed	bool	If set, indicates whether the files are compressed as .gz files (used in export scenario only)
includeHeaders	string	For delimited text formats (CSV, TSV, ...), indicates whether files contain a header. Possible values are: All (all files contain a header), FirstFile (first file in a folder contains a header), None (no files contain a header).
namePrefix	string	If set, indicates the prefix of the files. On write operations, all files will be written with this prefix. On read operations, only files with this prefix are read.
fileExtension	string	If set, indicates file extensions of the files. On write, files names will end with this suffix. On read, only files with this file extension will be read.
encoding	string	Indicates how the text is encoded: UTF8NoBOM (default) or UTF8BOM.
sampleUris	bool	If set, the command result provides several examples of simulated external data files URI as they're expected by the external table definition. This option helps validate whether the Partitions and PathFormat parameters are defined properly.
filesPreview	bool	If set, one of the command result tables contains a preview of .show external table artifacts command. Like sampleUri, the option helps validate the Partitions and PathFormat parameters of external table definition.
validateNotEmpty	bool	If set, the connection strings are validated for having content in them. The command will fail if the specified URI location doesn't exist, or if there are insufficient permissions to access it.
dryRun	bool	If set, the external table definition isn't persisted. This option is useful for validating the external table definition, especially in conjunction with the filesPreview or sampleUris parameter.

File filtering logic

When querying an external table, performance is improved by filtering out irrelevant external storage files. The process of iterating files and deciding whether a file should be processed is as follows:

1. Build a URI pattern that represents a place where files are found. Initially, the URI pattern equals a connection string provided as part of the external table definition. If there are any partitions defined, they're rendered using PathFormat, then appended to the URI pattern.

2. For all files found under the URI pattern(s) created, check that:

   • Partition values match predicates used in a query.
   • Blob name starts with NamePrefix, if such a property is defined.
   • Blob name ends with FileExtension, if such a property is defined.

Once all the conditions are met, the file is fetched and processed.

Examples

Non-partitioned external table

In the following non-partitioned external table, the files are expected to be placed directly under the container(s) defined:

.create external table ExternalTable (x:long, s:string)  
kind=storage 
dataformat=csv 
( 
   h@'https://storageaccount.blob.core.chinacloudapi.cn/container1;secretKey' 
) 

Partitioned by date

In the following external table partitioned by date, the files are expected to be placed under directories of the default datetime format yyyy/MM/dd:

.create external table ExternalTable (Timestamp:datetime, x:long, s:string) 
kind=storage
partition by (Date:datetime = bin(Timestamp, 1d)) 
dataformat=csv 
( 
   h@'abfss://filesystem@storageaccount.dfs.core.chinacloudapi.cn/path;secretKey'
)

Partitioned by month

In the following external table partitioned by month, the directory format is year=yyyy/month=MM:

.create external table ExternalTable (Timestamp:datetime, x:long, s:string) 
kind=storage 
partition by (Month:datetime = startofmonth(Timestamp)) 
pathformat=(datetime_pattern("'year='yyyy'/month='MM", Month)) 
dataformat=csv 
( 
   h@'https://storageaccount.blob.core.chinacloudapi.cn/container1;secretKey' 
) 

Partitioned by name and date

In the following external table, the data is partitioned first by customer name and then by date, meaning that the expected directory structure is, for example, customer_name=Softworks/2019/02/01:

.create external table ExternalTable (Timestamp:datetime, CustomerName:string) 
kind=storage 
partition by (CustomerNamePart:string = CustomerName, Date:datetime = startofday(Timestamp)) 
pathformat=("customer_name=" CustomerNamePart "/" Date)
dataformat=csv 
(  
   h@'https://storageaccount.blob.core.chinacloudapi.cn/container1;secretKey' 
)

Partitioned by hash and date

The following external table is partitioned first by customer name hash (modulo ten), then by date. The expected directory structure is, for example, customer_id=5/dt=20190201, and data file names end with the .txt extension:

.create external table ExternalTable (Timestamp:datetime, CustomerName:string) 
kind=storage 
partition by (CustomerId:long = hash(CustomerName, 10), Date:datetime = startofday(Timestamp)) 
pathformat=("customer_id=" CustomerId "/dt=" datetime_pattern("yyyyMMdd", Date)) 
dataformat=csv 
( 
   h@'https://storageaccount.blob.core.chinacloudapi.cn/container1;secretKey'
)
with (fileExtension = ".txt")

Filter by partition columns in a query

To filter by partition columns in a query, specify original column name in query predicate:

external_table("ExternalTable")
 | where Timestamp between (datetime(2020-01-01) .. datetime(2020-02-01))
 | where CustomerName in ("John.Doe", "Ivan.Ivanov")

Sample Output

TableName	TableType	Folder	DocString	Properties	ConnectionStrings	Partitions	PathFormat
ExternalTable	Blob	ExternalTables	Docs	{"Format":"Csv","Compressed":false,"CompressionType":null,"FileExtension":null,"IncludeHeaders":"None","Encoding":null,"NamePrefix":null}	["https://storageaccount.blob.core.chinacloudapi.cn/container1;*******"]	[{"Mod":10,"Name":"CustomerId","ColumnName":"CustomerName","Ordinal":0},{"Function":"StartOfDay","Name":"Date","ColumnName":"Timestamp","Ordinal":1}]	"customer_id=" CustomerId "/dt=" datetime_pattern("yyyyMMdd",Date)

Related content

• Query external tables.
• Export data to an external table.
• Continuous data export to an external table.