Forum Discussion
Any integration or tutorials for Spark Connect?
Hi dbeavon3 ,
Based on my understanding, since Spark connect requires remote connectivity, it needs a hostname which would be the IP address of the Spark Context. And since there is no authentication mechanism invovled with Spark-connect unless you manually setup a re-direction URL mechanism (authentication proxy), I don't believe Fabric will allow that level of configuration in their cloud system.
Using Managed Virtual networks with Fabric, you might get the URL of the Spark context and use it, but again this is just my assumption and as you said, there is no documentation, it is difficult to validate unless we do a PoC.
The following seems true after I read the description from MS site and Spark site.
Maybe someone copy/pasted from the OSS docs for Apache Spark.
>> interactive mode, how do you think it will work in terms of CU calculation. If I run my first command and after it finishes the notebook is not in running state anymo, only the session is active
If the session is active and connected to the cluster then I am 100% certain it would keep accumulating CU's. Ideally the cluster would scale down (via autoscale) to save Microsoft some money. And ideally the dynamically allocated executors woud die off as well to save the customer a bit of money in their notebooks.
... in short, the cluster (custom pool) and VM's are the resources which Microsoft has to keep running at their own expense. It is somewhat fixed. But the CU-meter is accumulated via notebook-compute which is a highly "variable cost". Microsoft probably needs to significantly increase this variable cost that they charge the customer, to ensure that it always covers their own fixed expenses. That is how I understand it.
The notebook will become idle after a period of time and both the cluster and the executors will die. That will stop the billing. And it will stop the expense to Microsoft, in regards to their cluster (custom pool)
Hi dbeavon3,
I did this experiment:
I created a new F64 capacity (so that there is no noise in the capacity metrics app) . I created a new notebook, started a standard session and set the session time out period to be 45 minutes. But I did not run anything on the notebook like you can see below.
In the below metrics app, you can see the consumption which is around 24K CU (s) and the duration to be 2758 seconds which is ~ 46 minutes. So even if we don't run the notebook, there is a CU consumption because the spark session is running (I don't think MS owns this expense as I can see the CU(s) consumed in the Capacity metrics app)
And I agree with your point of running a notebook would be a variable cost ( because there is autoscale and dynamically allocated executors), but there is a fixed cost when running the spark session and based on my understanding, CU(s) is consumed and MS doesn't own it. Unlike Databricks, where you have the option to start the cluster directly, here in Fabric the only way to turn it on is to start a notebook or run a notebook/spark job. In that way, you wouldn't be inadvertently starting a session and accumulating CU(s).