CREATE EXTERNAL TABLE (Transact-SQL)

Creates an external table.

This article provides the syntax, arguments, remarks, permissions, and examples for whichever SQL product you choose.

For more information about the syntax conventions, see Transact-SQL syntax conventions.

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Overview: SQL Server

This command creates an external table for PolyBase to access data stored in a Hadoop cluster or Azure Blob Storage PolyBase external table that references data stored in a Hadoop cluster or Azure Blob Storage.

Applies to: SQL Server 2016 (or higher)

Use an external table with an external data source for PolyBase queries. External data sources are used to establish connectivity and support these primary use cases:

• Data virtualization and data load using PolyBase
• Bulk load operations using SQL Server or SQL Database using BULK INSERT or OPENROWSET

See also CREATE EXTERNAL DATA SOURCE and DROP EXTERNAL TABLE.

Syntax

-- Create a new external table
CREATE EXTERNAL TABLE { database_name.schema_name.table_name | schema_name.table_name | table_name }
    ( <column_definition> [ ,...n ] )
    WITH (
        LOCATION = 'folder_or_filepath',
        DATA_SOURCE = external_data_source_name,
        [ FILE_FORMAT = external_file_format_name ]
        [ , <reject_options> [ ,...n ] ]
    )
[;]

<reject_options> ::=
{
    | REJECT_TYPE = value | percentage
    | REJECT_VALUE = reject_value
    | REJECT_SAMPLE_VALUE = reject_sample_value,
    | REJECTED_ROW_LOCATION = '/REJECT_Directory'
}

<column_definition> ::=
column_name <data_type>
    [ COLLATE collation_name ]
    [ NULL | NOT NULL ]

Arguments

{ database_name.schema_name.table_name | schema_name.table_name | table_name }

The one to three-part name of the table to create. For an external table, SQL stores only the table metadata along with basic statistics about the file or folder that is referenced in Hadoop or Azure Blob Storage. No actual data is moved or stored in SQL Server.

Important

For best performance, if the external data source driver supports a three-part name, it is strongly recommended to provide the three-part name.

<column_definition> [ ,...n ]

CREATE EXTERNAL TABLE supports the ability to configure column name, data type, nullability, and collation. You can't use the DEFAULT CONSTRAINT on external tables.

The column definitions, including the data types and number of columns, must match the data in the external files. If there's a mismatch, the file rows will be rejected when querying the actual data.

LOCATION = 'folder_or_filepath'

Specifies the folder or the file path and file name for the actual data in Hadoop or Azure Blob Storage. Additionally, S3-compatible object storage is supported starting in SQL Server 2022 (16.x)). The location starts from the root folder. The root folder is the data location specified in the external data source.

In SQL Server, the CREATE EXTERNAL TABLE statement creates the path and folder if it doesn't already exist. You can then use INSERT INTO to export data from a local SQL Server table to the external data source. For more information, see PolyBase Queries.

If you specify LOCATION to be a folder, a PolyBase query that selects from the external table will retrieve files from the folder and all of its subfolders. Just like Hadoop, PolyBase doesn't return hidden folders. It also doesn't return files for which the file name begins with an underline (_) or a period (.).

In the following image example, if LOCATION='/webdata/', a PolyBase query will return rows from mydata.txt and mydata2.txt. It won't return mydata3.txt because it's a file in a hidden subfolder. And it won't return _hidden.txt because it's a hidden file.

To change the default and only read from the root folder, set the attribute <polybase.recursive.traversal> to 'false' in the core-site.xml configuration file. This file is located under <SqlBinRoot>\PolyBase\Hadoop\Conf under the bin root of SQL Server. For example, C:\Program Files\Microsoft SQL Server\MSSQL13.XD14\MSSQL\Binn.

DATA_SOURCE = external_data_source_name

Specifies the name of the external data source that contains the location of the external data. This location is a Hadoop File System (HDFS), an Azure Blob Storage container, or Azure Data Lake Store. To create an external data source, use CREATE EXTERNAL DATA SOURCE.

FILE_FORMAT = external_file_format_name

Specifies the name of the external file format object that stores the file type and compression method for the external data. To create an external file format, use CREATE EXTERNAL FILE FORMAT.

External file formats can be reused by multiple similar external files.

Reject Options

This option can be used only with external data sources where TYPE = HADOOP.

You can specify reject parameters that determine how PolyBase will handle dirty records it retrieves from the external data source. A data record is considered 'dirty' if it actual data types or the number of columns don't match the column definitions of the external table.

When you don't specify or change reject values, PolyBase uses default values. This information about the reject parameters is stored as additional metadata when you create an external table with CREATE EXTERNAL TABLE statement. When a future SELECT statement or SELECT INTO SELECT statement selects data from the external table, PolyBase will use the reject options to determine the number or percentage of rows that can be rejected before the actual query fails. The query will return (partial) results until the reject threshold is exceeded. It then fails with the appropriate error message.

REJECT_TYPE = value | percentage

Clarifies whether the REJECT_VALUE option is specified as a literal value or a percentage.

value

REJECT_VALUE is a literal value, not a percentage. The query will fail when the number of rejected rows exceeds reject_value.

For example, if REJECT_VALUE = 5 and REJECT_TYPE = value, the SELECT query will fail after five rows have been rejected.

percentage

REJECT_VALUE is a percentage, not a literal value. A query will fail when the percentage of failed rows exceeds reject_value. The percentage of failed rows is calculated at intervals.

REJECT_VALUE = reject_value

Specifies the value or the percentage of rows that can be rejected before the query fails.

For REJECT_TYPE = value, reject_value must be an integer between 0 and 2,147,483,647.

For REJECT_TYPE = percentage, reject_value must be a float between 0 and 100.

REJECT_SAMPLE_VALUE = reject_sample_value

This attribute is required when you specify REJECT_TYPE = percentage. It determines the number of rows to attempt to retrieve before the PolyBase recalculates the percentage of rejected rows.

The reject_sample_value parameter must be an integer between 0 and 2,147,483,647.

For example, if REJECT_SAMPLE_VALUE = 1000, PolyBase will calculate the percentage of failed rows after it has attempted to import 1000 rows from the external data file. If the percentage of failed rows is less than reject_value, PolyBase will attempt to retrieve another 1000 rows. It continues to recalculate the percentage of failed rows after it attempts to import each additional 1000 rows.

Note

Since PolyBase computes the percentage of failed rows at intervals, the actual percentage of failed rows can exceed reject_value.

Example:

This example shows how the three REJECT options interact with each other. For example, if REJECT_TYPE = percentage, REJECT_VALUE = 30, and REJECT_SAMPLE_VALUE = 100, the following scenario could occur:

• PolyBase attempts to retrieve the first 100 rows; 25 fail and 75 succeed.
• Percent of failed rows is calculated as 25%, which is less than the reject value of 30%. As a result, PolyBase will continue retrieving data from the external data source.
• PolyBase attempts to load the next 100 rows; this time 25 rows succeed and 75 rows fail.
• Percent of failed rows is recalculated as 50%. The percentage of failed rows has exceeded the 30% reject value.
• The PolyBase query fails with 50% rejected rows after attempting to return the first 200 rows. Notice that matching rows have been returned before the PolyBase query detects the reject threshold has been exceeded.

REJECTED_ROW_LOCATION = Directory Location

Applies to: SQL Server 2019 CU6 and later versions, Azure Synapse Analytics.

Specifies the directory within the External Data Source that the rejected rows and the corresponding error file should be written.

If the specified path doesn't exist, PolyBase will create one on your behalf. A child directory is created with the name "_rejectedrows". The "_" character ensures that the directory is escaped for other data processing unless explicitly named in the location parameter. Within this directory, there's a folder created based on the time of load submission in the format YearMonthDay -HourMinuteSecond (Ex. 20230330-173205). In this folder, two types of files are written, the _reason file and the data file. This option can be used only with external data sources where TYPE = HADOOP and for external tables using DELIMITEDTEXT FORMAT_TYPE. For more information, see CREATE EXTERNAL DATA SOURCE and CREATE EXTERNAL FILE FORMAT.

The reason files and the data files both have the queryID associated with the CTAS statement. Because the data and the reason are in separate files, corresponding files have a matching suffix.

Permissions

Requires these user permissions:

• CREATE TABLE
• ALTER ANY SCHEMA
• ALTER ANY EXTERNAL DATA SOURCE
• ALTER ANY EXTERNAL FILE FORMAT (only applies to Hadoop and Azure Storage external data sources)
• CONTROL DATABASE (only applies to Hadoop and Azure Storage external data sources)

Note, the remote login specified in the DATABASE SCOPED CREDENTIAL used in the CREATE EXTERNAL TABLE command must have read permission for the path/table/collection on the external data source specified in the LOCATION parameter. If you're planning to use this EXTERNAL TABLE to export data to a Hadoop or Azure Storage external data source, then the login specified must have write permission on the path specified in LOCATION. Note that Hadoop is not currently supported in SQL Server 2022 (16.x).

For Azure Blob Storage, when configuring the access keys and shared access signature (SAS) in the Azure portal, the Azure Blob Storage or ADLS Gen2 storage accounts, configure the Allowed permissions to grant at least Read and Write permissions. List permission might also be required when searching across folders. You must also select both Container and Object as the allowed resource types.

Important

The ALTER ANY EXTERNAL DATA SOURCE permission grants any principal the ability to create and modify any external data source object, and therefore, it also grants the ability to access all database scoped credentials on the database. This permission must be considered as highly privileged, and therefore must be granted only to trusted principals in the system.

Error handling

While executing the CREATE EXTERNAL TABLE statement, PolyBase attempts to connect to the external data source. If the attempt to connect fails, the statement will fail and the external table won't be created. It can take a minute or more for the command to fail since PolyBase retries the connection before eventually failing the query.

Remarks

In ad hoc query scenarios, such as SELECT FROM EXTERNAL TABLE, PolyBase stores the rows that are retrieved from the external data source in a temporary table. After the query completes, PolyBase removes and deletes the temporary table. No permanent data is stored in SQL tables.

In contrast, in the import scenario, such as SELECT INTO FROM EXTERNAL TABLE, PolyBase stores the rows that are retrieved from the external data source as permanent data in the SQL table. The new table is created during query execution when PolyBase retrieves the external data.

PolyBase can push some of the query computation to Hadoop to improve query performance. This action is called predicate pushdown. To enable it, specify the Hadoop resource manager location option in CREATE EXTERNAL DATA SOURCE.

You can create many external tables that reference the same or different external data sources.

Limitations and restrictions

Since the data for an external table is not under the direct management control of SQL Server, it can be changed or removed at any time by an external process. As a result, query results against an external table aren't guaranteed to be deterministic. The same query can return different results each time it runs against an external table. Similarly, a query might fail if the external data is moved or removed.

You can create multiple external tables that each reference different external data sources. If you simultaneously run queries against different Hadoop data sources, then each Hadoop source must use the same 'hadoop connectivity' server configuration setting. For example, you can't simultaneously run a query against a Cloudera Hadoop cluster and a Hortonworks Hadoop cluster since these use different configuration settings. For the configuration settings and supported combinations, see PolyBase Connectivity Configuration.

When the external table is using DELIMITEDTEXT, CSV, PARQUET, or DELTA as data types, external tables only support statistics for one column per CREATE STATISTICS command.

Only these Data Definition Language (DDL) statements are allowed on external tables:

• CREATE TABLE and DROP TABLE
• CREATE STATISTICS and DROP STATISTICS
• CREATE VIEW and DROP VIEW

Constructs and operations not supported:

• The DEFAULT constraint on external table columns
• Data Manipulation Language (DML) operations of delete, insert, and update

Query limitations

PolyBase can consume a maximum of 33k files per folder when running 32 concurrent PolyBase queries. This maximum number includes both files and subfolders in each HDFS folder. If the degree of concurrency is less than 32, a user can run PolyBase queries against folders in HDFS that contain more than 33k files. We recommend that you keep external file paths short and use no more than 30k files per HDFS folder. When too many files are referenced, a Java Virtual Machine (JVM) out-of-memory exception might occur.

Table width limitations

PolyBase in SQL Server 2016 has a row width limit of 32 KB based on the maximum size of a single valid row by table definition. If the sum of the column schema is greater than 32 KB, PolyBase can't query the data.

Data type limitations

The following data types cannot be used in PolyBase external tables:

• geography
• geometry
• hierarchyid
• image
• text
• nText
• xml
• Any user-defined type

Data source specific limitations

Oracle

Oracle synonyms are not supported for usage with PolyBase.

External tables to MongoDB collections that contain arrays

To create external tables to MongoDB collections that contain arrays, you should use the Data Virtualization extension for Azure Data Studio to produce a CREATE EXTERNAL TABLE statement based on the schema detected by the PolyBase ODBC Driver for MongoDB. The flattening actions are performed automatically by the driver. Alternatively, you can use sp_data_source_objects (Transact-SQL) to detect the collection schema (columns) and manually create the external table. The sp_data_source_table_columns stored procedure also automatically performs the flattening via the PolyBase ODBC Driver for MongoDB driver. The Data Virtualization extension for Azure Data Studio and sp_data_source_table_columns use the same internal stored procedures to query the external schema.

Locking

Shared lock on the SCHEMARESOLUTION object.

Security

The data files for an external table are stored in Hadoop or Azure Blob Storage. These data files are created and managed by your own processes. It is your responsibility to manage the security of the external data.

Examples

A. Create an external table with data in text-delimited format

This example shows all the steps required to create an external table that has data formatted in text-delimited files. It defines an external data source mydatasource and an external file format myfileformat. These database-level objects are then referenced in the CREATE EXTERNAL TABLE statement. For more information, see CREATE EXTERNAL DATA SOURCE and CREATE EXTERNAL FILE FORMAT.

CREATE EXTERNAL DATA SOURCE mydatasource
WITH (
    TYPE = HADOOP,
    LOCATION = 'hdfs://xxx.xxx.xxx.xxx:8020'
)

CREATE EXTERNAL FILE FORMAT myfileformat
WITH (
    FORMAT_TYPE = DELIMITEDTEXT,
    FORMAT_OPTIONS (FIELD_TERMINATOR ='|')
);

CREATE EXTERNAL TABLE ClickStream (
    url varchar(50),
    event_date date,
    user_IP varchar(50)
)
WITH (
        LOCATION='/webdata/employee.tbl',
        DATA_SOURCE = mydatasource,
        FILE_FORMAT = myfileformat
    )
;

B. Create an external table with data in RCFile format

This example shows all the steps required to create an external table that has data formatted as RCFiles. It defines an external data source mydatasource_rc and an external file format myfileformat_rc. These database-level objects are then referenced in the CREATE EXTERNAL TABLE statement. For more information, see CREATE EXTERNAL DATA SOURCE and CREATE EXTERNAL FILE FORMAT.

CREATE EXTERNAL DATA SOURCE mydatasource_rc
WITH (
    TYPE = HADOOP,
    LOCATION = 'hdfs://xxx.xxx.xxx.xxx:8020'
)

CREATE EXTERNAL FILE FORMAT myfileformat_rc
WITH (
    FORMAT_TYPE = RCFILE,
    SERDE_METHOD = 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe'
)
;

CREATE EXTERNAL TABLE ClickStream_rc (
    url varchar(50),
    event_date date,
    user_ip varchar(50)
)
WITH (
        LOCATION='/webdata/employee_rc.tbl',
        DATA_SOURCE = mydatasource_rc,
        FILE_FORMAT = myfileformat_rc
    )
;

C. Create an external table with data in ORC format

This example shows all the steps required to create an external table that has data formatted as ORC files. It defines an external data source mydatasource_orc and an external file format myfileformat_orc. These database-level objects are then referenced in the CREATE EXTERNAL TABLE statement. For more information, see CREATE EXTERNAL DATA SOURCE and CREATE EXTERNAL FILE FORMAT.

CREATE EXTERNAL DATA SOURCE mydatasource_orc
WITH (
    TYPE = HADOOP,
    LOCATION = 'hdfs://xxx.xxx.xxx.xxx:8020'
)

CREATE EXTERNAL FILE FORMAT myfileformat_orc
WITH (
    FORMAT = ORC,
    COMPRESSION = 'org.apache.hadoop.io.compress.SnappyCodec'
)
;

CREATE EXTERNAL TABLE ClickStream_orc (
    url varchar(50),
    event_date date,
    user_ip varchar(50)
)
WITH (
        LOCATION='/webdata/',
        DATA_SOURCE = mydatasource_orc,
        FILE_FORMAT = myfileformat_orc
    )
;

D. Query Hadoop data

ClickStream is an external table that connects to the employee.tbl delimited text file on a Hadoop cluster. The following query looks just like a query against a standard table. However, this query retrieves data from Hadoop and then computes the results.

SELECT TOP 10 (url) FROM ClickStream WHERE user_ip = 'xxx.xxx.xxx.xxx';

E. Join Hadoop data with SQL data

This query looks just like a standard JOIN on two SQL tables. The difference is that PolyBase retrieves the clickstream data from Hadoop and then joins it to the UrlDescription table. One table is an external table and the other is a standard SQL table.

SELECT url.description
FROM ClickStream cs
JOIN UrlDescription url ON cs.url = url.name
WHERE cs.url = 'msdn.microsoft.com';

F. Import data from Hadoop into a SQL table

This example creates a new SQL table ms_user that permanently stores the result of a join between the standard SQL table user and the external table ClickStream.

SELECT DISTINCT user.FirstName, user.LastName
INTO ms_user
FROM user INNER JOIN (
    SELECT * FROM ClickStream WHERE cs.url = 'www.microsoft.com'
    ) AS ms
ON user.user_ip = ms.user_ip;

G. Create an external table for SQL Server

Before you create a database scoped credential, the user database must have a master key to protect the credential. For more information, see CREATE MASTER KEY and CREATE DATABASE SCOPED CREDENTIAL.

     -- Create a Master Key
      CREATE MASTER KEY ENCRYPTION BY PASSWORD = 'S0me!nfo';
    GO
     /*  specify credentials to external data source
     *  IDENTITY: user name for external source.
     *  SECRET: password for external source.
     */
     CREATE DATABASE SCOPED CREDENTIAL SqlServerCredentials
     WITH IDENTITY = 'username', Secret = 'password';
    GO

Create a new external data source named SQLServerInstance, and external table named sqlserver.customer:

    /* LOCATION: Location string should be of format '<vendor>://<server>[:<port>]'.
    * PUSHDOWN: specify whether computation should be pushed down to the source. ON by default.
    * CREDENTIAL: the database scoped credential, created above.
    */
    CREATE EXTERNAL DATA SOURCE SQLServerInstance
    WITH (
    LOCATION = 'sqlserver://SqlServer',
    -- PUSHDOWN = ON | OFF,
      CREDENTIAL = SQLServerCredentials
    );
    GO

    CREATE SCHEMA sqlserver;
    GO

     /* LOCATION: sql server table/view in 'database_name.schema_name.object_name' format
     * DATA_SOURCE: the external data source, created above.
     */
     CREATE EXTERNAL TABLE sqlserver.customer(
     C_CUSTKEY INT NOT NULL,
     C_NAME VARCHAR(25) NOT NULL,
     C_ADDRESS VARCHAR(40) NOT NULL,
     C_NATIONKEY INT NOT NULL,
     C_PHONE CHAR(15) NOT NULL,
     C_ACCTBAL DECIMAL(15,2) NOT NULL,
     C_MKTSEGMENT CHAR(10) NOT NULL,
     C_COMMENT VARCHAR(117) NOT NULL
      )
      WITH (
      LOCATION='tpch_10.dbo.customer',
      DATA_SOURCE=SqlServerInstance
     );

I. Create an external table for Oracle

  -- Create a Master Key
   CREATE MASTER KEY ENCRYPTION BY PASSWORD = 'password';
   /*
   * Specify credentials to external data source
   * IDENTITY: user name for external source.
   * SECRET: password for external source.
   */
   CREATE DATABASE SCOPED CREDENTIAL credential_name
   WITH IDENTITY = 'username', Secret = 'password';

   /*
   * LOCATION: Location string should be of format '<vendor>://<server>[:<port>]'.
   * PUSHDOWN: specify whether computation should be pushed down to the source. ON by default.
   * CONNECTION_OPTIONS: Specify driver location
   * CREDENTIAL: the database scoped credential, created above.
   */
   CREATE EXTERNAL DATA SOURCE external_data_source_name
   WITH (
     LOCATION = 'oracle://<server address>[:<port>]',
     -- PUSHDOWN = ON | OFF,
     CREDENTIAL = credential_name)

   /*
   * LOCATION: Oracle table/view in '<database_name>.<schema_name>.<object_name>' format. Note this may be case sensitive in the Oracle database.
   * DATA_SOURCE: the external data source, created above.
   */
   CREATE EXTERNAL TABLE customers(
   [O_ORDERKEY] DECIMAL(38) NOT NULL,
   [O_CUSTKEY] DECIMAL(38) NOT NULL,
   [O_ORDERSTATUS] CHAR COLLATE Latin1_General_BIN NOT NULL,
   [O_TOTALPRICE] DECIMAL(15,2) NOT NULL,
   [O_ORDERDATE] DATETIME2(0) NOT NULL,
   [O_ORDERPRIORITY] CHAR(15) COLLATE Latin1_General_BIN NOT NULL,
   [O_CLERK] CHAR(15) COLLATE Latin1_General_BIN NOT NULL,
   [O_SHIPPRIORITY] DECIMAL(38) NOT NULL,
   [O_COMMENT] VARCHAR(79) COLLATE Latin1_General_BIN NOT NULL
   )
   WITH (
    LOCATION='DB1.mySchema.customer',
    DATA_SOURCE= external_data_source_name
   );

J. Create an external table for Teradata

  -- Create a Master Key
   CREATE MASTER KEY ENCRYPTION BY PASSWORD = 'password';

   /*
   * Specify credentials to external data source
   * IDENTITY: user name for external source.
   * SECRET: password for external source.
   */
   CREATE DATABASE SCOPED CREDENTIAL credential_name
   WITH IDENTITY = 'username', Secret = 'password';

    /* LOCATION: Location string should be of format '<vendor>://<server>[:<port>]'.
    * PUSHDOWN: specify whether computation should be pushed down to the source. ON by default.
    * CONNECTION_OPTIONS: Specify driver location
    * CREDENTIAL: the database scoped credential, created above.
    */
    CREATE EXTERNAL DATA SOURCE external_data_source_name
    WITH (
    LOCATION = teradata://<server address>[:<port>],
   -- PUSHDOWN = ON | OFF,
    CREDENTIAL =credential_name
    );


     /* LOCATION: Teradata table/view in '<database_name>.<object_name>' format
      * DATA_SOURCE: the external data source, created above.
      */
     CREATE EXTERNAL TABLE customer(
      L_ORDERKEY INT NOT NULL,
      L_PARTKEY INT NOT NULL,
     L_SUPPKEY INT NOT NULL,
     L_LINENUMBER INT NOT NULL,
     L_QUANTITY DECIMAL(15,2) NOT NULL,
     L_EXTENDEDPRICE DECIMAL(15,2) NOT NULL,
     L_DISCOUNT DECIMAL(15,2) NOT NULL,
     L_TAX DECIMAL(15,2) NOT NULL,
     L_RETURNFLAG CHAR NOT NULL,
     L_LINESTATUS CHAR NOT NULL,
     L_SHIPDATE DATE NOT NULL,
     L_COMMITDATE DATE NOT NULL,
     L_RECEIPTDATE DATE NOT NULL,
     L_SHIPINSTRUCT CHAR(25) NOT NULL,
     L_SHIPMODE CHAR(10) NOT NULL,
     L_COMMENT VARCHAR(44) NOT NULL
     )
     WITH (
     LOCATION='customer',
     DATA_SOURCE= external_data_source_name
     );

K. Create an external table for MongoDB

  -- Create a Master Key
   CREATE MASTER KEY ENCRYPTION BY PASSWORD = 'password';

   /*
   * Specify credentials to external data source
   * IDENTITY: user name for external source.
   * SECRET: password for external source.
   */
   CREATE DATABASE SCOPED CREDENTIAL credential_name
   WITH IDENTITY = 'username', Secret = 'password';

     /* LOCATION: Location string should be of format '<type>://<server>[:<port>]'.
    * PUSHDOWN: specify whether computation should be pushed down to the source. ON by default.
    * CONNECTION_OPTIONS: Specify driver location
    * CREDENTIAL: the database scoped credential, created above.
    */
    CREATE EXTERNAL DATA SOURCE external_data_source_name
    WITH (
    LOCATION = mongodb://<server>[:<port>],
    -- PUSHDOWN = ON | OFF,
      CREDENTIAL = credential_name
    );

     /* LOCATION: MongoDB table/view in '<database_name>.<schema_name>.<object_name>' format
     * DATA_SOURCE: the external data source, created above.
     */
     CREATE EXTERNAL TABLE customers(
     [O_ORDERKEY] DECIMAL(38) NOT NULL,
     [O_CUSTKEY] DECIMAL(38) NOT NULL,
     [O_ORDERSTATUS] CHAR COLLATE Latin1_General_BIN NOT NULL,
     [O_TOTALPRICE] DECIMAL(15,2) NOT NULL,
     [O_ORDERDATE] DATETIME2(0) NOT NULL,
     [O_COMMENT] VARCHAR(79) COLLATE Latin1_General_BIN NOT NULL
     )
     WITH (
     LOCATION='customer',
     DATA_SOURCE= external_data_source_name
     );

L. Query S3-compatible object storage via external table

Applies to: SQL Server 2022 (16.x) and later

The following example demonstrates using T-SQL to query a parquet file stored in S3-compatible object storage via querying external table. The sample uses a relative path within the external data source.

CREATE EXTERNAL DATA SOURCE s3_ds
WITH
(   LOCATION = 's3://<ip_address>:<port>/'
,   CREDENTIAL = s3_dc
);
GO
CREATE EXTERNAL FILE FORMAT ParquetFileFormat WITH(FORMAT_TYPE = PARQUET);
GO
CREATE EXTERNAL TABLE Region(
r_regionkey BIGINT,
r_name CHAR(25),
r_comment VARCHAR(152) )
WITH (LOCATION = '/region/', DATA_SOURCE = 's3_ds',
FILE_FORMAT = ParquetFileFormat);
GO

Next steps

Learn more about related concepts in the following articles:

• CREATE EXTERNAL DATA SOURCE
• CREATE EXTERNAL FILE FORMAT
• sp_data_source_objects (Transact-SQL)
• Data Virtualization extension for Azure Data Studio