I have to set a pipe line to get data's into "stream analytics job service" from sql database directedly( should not use other layers/components Ex: Data factory, Event hubs etc between sql db and stream analytics job ) . But no stream input in my use case. Tried by using this link with by adding reference data input option
"https://learn.microsoft.com/en-us/azure/stream-analytics/sql-reference-data "
But received "Query must refer to at least one data stream input" this error. Query expects always at least one stream input.
Please let me know to to achieve this with out using code only through pipelines.
Thank You.
To set up a process where you must stream data directly from SQL to Azure Stream Analysis is directly not available. As SQL is only used as reference input not as a stream input and there only below three Stream inputs which you can opt:
Azure Event Hubs
Azure IoT Hub
Azure Blob storage
Azure Data Lake Storage Gen2
And could use as SQL as a reference input i.e. A reference data set / Lookup Table is a finite data collection that is either static or slowly changing in nature, and it is used to execute a search or to supplement your data streams.
Hence, in this scenario the only way out is to Stream SQL data using Apache Kafka and then integrating with Azure Event Hubs which could then directly be a Steam input for Azure Stream Analytics.
Stream data as input into Stream Analytics
Use Azure Event Hubs from Apache Kafka applications
Related
We are trying to use our Dataverse data as reference data for our Azure Stream Analytics. The idea is to couple customer acitivities with their CRM profile to create meaningful actions for them. We are currently moving from DES to the Dataverse Synapse Link, and have created the data lake where data gets dumped and can see it in Synapse Studio. However, Stream Analytics does not take CDM format out-of-the-box. It seems it can only handle CSV (with headers) and Json formats.
What is the best approach to get our Dataverse data in as reference for Stream Analytics (and in real time as possible)? Should we create a custom deserializer, or use ADF or something else?
We have a few SQL Azure instances which have a bunch of databases (like one for each department in an org) . We want to do stream processing on the data as and when there are updates to data in these individual databases.
From a scale perspective, we are looking at 10K events/day across all the databases, with a possible SLA of a few seconds to stream process an event.
We want to push data to Azure Event Hubs. Any existing Azure product offering can help here?
Just some suggestions for feasible solutions.
If you are looking for a solution for Azure services, then logic app should be able to meet your needs, this is the official doc of sql server trigger in logic app:
https://learn.microsoft.com/en-us/azure/connectors/connectors-create-api-sqlazure#add-a-sql-trigger
https://learn.microsoft.com/en-us/connectors/sql/#when-an-item-is-modified-(v2)
Or, if you can send web request from sql server when items changed like this:
https://www.botreetechnologies.com/blog/how-to-fire-a-web-request-from-microsoft-sql-server
Then you can send it to a endpoint like azure function, and use the event hub output binding, or just use the event hub sdk to send to event hub.
We are using azure iot hub and azure iot edge devices for multiple of our customers. The devices are sending their telemetry data using iot hub telemetry messages. In the iot hub we use message routing -> enrich messages to add the customer id to the messages application properties. This works pretty good if we forward the messages to service bus topics and consume them using azure functions as the application properties are easily accessable there.
Instead of using Azure functions, we now want to store all the telemetry data directly in azure data explorer databases and we want to split the messages to one dedicated database per customer (the name of the database is the customer-id).
So far I could not figure out how to access the application properties from iot hub when importing data to the data explorer? I am not even sure that it is possible, but i really hope it is.
Unfortunately automatically routing messages to different databases is not currently supported, please add a request to Azure Data Explorer user voice. For now, you can do the message routing to a dedicated event hub per customer (i.e. per database) and create one Azure Data Explorer data connection per database.
Please note that within a data connection you can dynamically route the messages to different tables by adding the table information to the event properties, see sample here
I have a Stream Analytics Job with Use System-assigned Managed Identity enabled and which I would like to output its results to a Data Lake Storage Gen2.
As far as I understand I should only need to go into the Storage Account's IAM settings and add the Stream Analytics Identity as a Stroage Blob Data Owner. However, I don't see the Category of Stream Ananlytics Jobs in the dropdown and I can't seem to find the service principal in any of the other ones.
Am I missing something here or is this scenario just not supported yet?
Just choose the options like below, in the Select option, search for the name of your Stream Analytics Job, then you can find it and add it.
How to make Stream Analytics output shown in Azure SQL database, do I have to create a new table? If so, what data name and type should I input, refering to Raspberry Pi Azure IoT Web Simulator
https://azure-samples.github.io/raspberry-pi-web-simulator/
I'm new to Azure iot and Stream Analytics.
Currently I'm using Raspberry Pi Azure IoT Web Simulator as a learning material, I followed Microsoft doc and succeeded making the simulator message shown in the blob of storage account.
How to make Stream Analytics output shown in Azure SQL database, do I
have to create a new table? If so, what data name and type should I
input
Yes,you need to create tables in Azure Sql Database so that you could configure that as output.
You could follow this official document to configure the output in Azure Stream Analytics.
Since you already have input data, then just use the output alias in the query sql to parse the data. The input data types need to match the output column data types.