Create a data streaming job in Azure SQL Edge
Important
Azure SQL Edge no longer supports the ARM64 platform.
This article explains how to create a T-SQL streaming job in Azure SQL Edge. You create the external stream input and output objects, and then you define the streaming job query as part of the streaming job creation.
Configure the external stream input and output objects
T-SQL streaming uses the external data source functionality of SQL Server to define the data sources associated with the external stream inputs and outputs of the streaming job. Use the following T-SQL commands to create an external stream input or output object:
- CREATE EXTERNAL FILE FORMAT (Transact-SQL)
- CREATE EXTERNAL DATA SOURCE (Transact-SQL)
- CREATE EXTERNAL STREAM (Transact-SQL)
Additionally, if Azure SQL Edge, SQL Server, or Azure SQL Database is used as an output stream, you need the CREATE DATABASE SCOPED CREDENTIAL (Transact-SQL). This T-SQL command defines the credentials to access the database.
Supported input and output stream data sources
Azure SQL Edge currently only supports the following data sources as stream inputs and outputs.
Data source type | Input | Output | Description |
---|---|---|---|
Azure IoT Edge hub | Y | Y | Data source to read and write streaming data to an Azure IoT Edge hub. For more information, see IoT Edge Hub. |
SQL Database | N | Y | Data source connection to write streaming data to SQL Database. The database can be a local database in Azure SQL Edge, or a remote database in SQL Server or Azure SQL Database. |
Kafka | Y | N | Data source to read streaming data from a Kafka topic. |
Example: Create an external stream input/output object for Azure IoT Edge hub
The following example creates an external stream object for Azure IoT Edge hub. To create an external stream input/output data source for Azure IoT Edge hub, you first need to create an external file format for the layout of the data being read or written too.
Create an external file format of the type JSON.
CREATE EXTERNAL FILE format InputFileFormat WITH (FORMAT_TYPE = JSON); GO
Create an external data source for Azure IoT Edge hub. The following T-SQL script creates a data source connection to an IoT Edge hub that runs on the same Docker host as Azure SQL Edge.
CREATE EXTERNAL DATA SOURCE EdgeHubInput WITH (LOCATION = 'edgehub://'); GO
Create the external stream object for Azure IoT Edge hub. The following T-SQL script creates a stream object for the IoT Edge hub. In case of an IoT Edge hub stream object, the LOCATION parameter is the name of the IoT Edge hub topic or channel being read or written to.
CREATE EXTERNAL STREAM MyTempSensors WITH ( DATA_SOURCE = EdgeHubInput, FILE_FORMAT = InputFileFormat, LOCATION = N'TemperatureSensors', INPUT_OPTIONS = N'', OUTPUT_OPTIONS = N'' ); GO
Example: Create an external stream object to Azure SQL Database
The following example creates an external stream object to the local database in Azure SQL Edge.
Create a master key on the database. This is required to encrypt the credential secret.
CREATE MASTER KEY ENCRYPTION BY PASSWORD = '<<Strong_Password_For_Master_Key_Encryption>>';
Create a database-scoped credential for accessing the SQL Server source. The following example creates a credential to the external data source, with IDENTITY = username, and SECRET = password.
CREATE DATABASE SCOPED CREDENTIAL SQLCredential WITH IDENTITY = '<SQL_Login>', SECRET = '<SQL_Login_PASSWORD>'; GO
Create an external data source with CREATE EXTERNAL DATA SOURCE. The following example:
- Creates an external data source named LocalSQLOutput.
- Identifies the external data source (
LOCATION = '<vendor>://<server>[:<port>]'
). In the example, it points to a local instance of Azure SQL Edge. - Uses the credential created previously.
CREATE EXTERNAL DATA SOURCE LocalSQLOutput WITH ( LOCATION = 'sqlserver://tcp:.,1433', CREDENTIAL = SQLCredential ); GO
Create the external stream object. The following example creates an external stream object pointing to a table dbo.TemperatureMeasurements, in the database MySQLDatabase.
CREATE EXTERNAL STREAM TemperatureMeasurements WITH ( DATA_SOURCE = LocalSQLOutput, LOCATION = N'MySQLDatabase.dbo.TemperatureMeasurements', INPUT_OPTIONS = N'', OUTPUT_OPTIONS = N'' );
Example: Create an external stream object for Kafka
The following example creates an external stream object to the local database in Azure SQL Edge. This example assumes that the kafka server is configured for anonymous access.
Create an external data source with CREATE EXTERNAL DATA SOURCE. The following example:
CREATE EXTERNAL DATA SOURCE [KafkaInput] WITH (LOCATION = N'kafka://<kafka_bootstrap_server_name_ip>:<port_number>'); GO
Create an external file format for the Kafka input. The following example created a JSON file format with GZipped Compression.
CREATE EXTERNAL FILE FORMAT JsonGzipped WITH ( FORMAT_TYPE = JSON, DATA_COMPRESSION = 'org.apache.hadoop.io.compress.GzipCodec' ); GO
Create the external stream object. The following example creates an external stream object pointing to Kafka topic
TemperatureMeasurement
.CREATE EXTERNAL STREAM TemperatureMeasurement WITH ( DATA_SOURCE = KafkaInput, FILE_FORMAT = JsonGzipped, LOCATION = 'TemperatureMeasurement', INPUT_OPTIONS = 'PARTITIONS: 10' ); GO
Create the streaming job and the streaming queries
Use the sys.sp_create_streaming_job
system stored procedure to define the streaming queries and create the streaming job. The sp_create_streaming_job
stored procedure takes the following parameters:
@job_name
: The name of the streaming job. Streaming job names are unique across the instance.@statement
: Stream Analytics Query Language-based streaming query statements.
The following example creates a simple streaming job with one streaming query. This query reads the inputs from the IoT Edge hub, and writes to dbo.TemperatureMeasurements
in the database.
EXEC sys.sp_create_streaming_job @name = N'StreamingJob1',
@statement = N'Select * INTO TemperatureMeasurements from MyEdgeHubInput'
The following example creates a more complex streaming job with multiple different queries. These queries include one that uses the built-in AnomalyDetection_ChangePoint
function to identify anomalies in the temperature data.
EXEC sys.sp_create_streaming_job @name = N'StreamingJob2',
@statement = N'
SELECT *
INTO TemperatureMeasurements1
FROM MyEdgeHubInput1
SELECT *
INTO TemperatureMeasurements2
FROM MyEdgeHubInput2
SELECT *
INTO TemperatureMeasurements3
FROM MyEdgeHubInput3
SELECT timestamp AS [Time],
[Temperature] AS [Temperature],
GetRecordPropertyValue(AnomalyDetection_ChangePoint(Temperature, 80, 1200) OVER (LIMIT DURATION(minute, 20)), '' Score '') AS ChangePointScore,
GetRecordPropertyValue(AnomalyDetection_ChangePoint(Temperature, 80, 1200) OVER (LIMIT DURATION(minute, 20)), '' IsAnomaly '') AS IsChangePointAnomaly
INTO TemperatureAnomalies
FROM MyEdgeHubInput2;
';
GO
Start, stop, drop, and monitor streaming jobs
To start a streaming job in Azure SQL Edge, run the sys.sp_start_streaming_job
stored procedure. The stored procedure requires the name of the streaming job to start, as input.
EXEC sys.sp_start_streaming_job @name = N'StreamingJob1';
GO
To stop a streaming job, run the sys.sp_stop_streaming_job
stored procedure. The stored procedure requires the name of the streaming job to stop, as input.
EXEC sys.sp_stop_streaming_job @name = N'StreamingJob1';
GO
To drop (or delete) a streaming job, run the sys.sp_drop_streaming_job
stored procedure. The stored procedure requires the name of the streaming job to drop, as input.
EXEC sys.sp_drop_streaming_job @name = N'StreamingJob1';
GO
To get the current status of a streaming job, run the sys.sp_get_streaming_job
stored procedure. The stored procedure requires the name of the streaming job to drop, as input. It outputs the name and the current status of the streaming job.
EXEC sys.sp_get_streaming_job @name = N'StreamingJob1'
WITH RESULT SETS (
(
name NVARCHAR(256),
status NVARCHAR(256),
error NVARCHAR(256)
)
);
GO
The streaming job can have any one of the following statuses:
Status | Description |
---|---|
Created | The streaming job was created, but hasn't yet been started. |
Starting | The streaming job is in the starting phase. |
Idle | The streaming job is running, but there's no input to process. |
Processing | The streaming job is running, and is processing inputs. This state indicates a healthy state for the streaming job. |
Degraded | The streaming job is running, but there were some non-fatal errors during input processing. The input job continues to run, but will drop inputs that encounter errors. |
Stopped | The streaming job has been stopped. |
Failed | The streaming job failed. This is generally an indication of a fatal error during processing. |
Note
Since the streaming job is executed asynchronously, the job might encounter errors at runtime. In order to troubleshoot a streaming job failure, use the sys.sp_get_streaming_job
stored procedure, or review the Docker log from the Azure SQL Edge container, which can provide the error details from the streaming job.
Next steps
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