The Minimum duration for Auto Stop is 10 minutes ( in practise, you should increase it to 1 Hour, a user waiting 5 minutes for his report to Start is not fun)ĭatabricks at least in Azure is a platform as a service, when you create a new cluster it will use your own resources to Provision a new VM (CPU, Disk etc), no surprise it take so long to start a new Cluster. It is really slow to start a Cluster ( around 4 minute) When you explore a new SQL Database, the first thing you check is the sample Data, Strangely, it will ask for a Compute to be running to even have a look at the metadata.Ĭreating a new Compute is very simple, I really like that you can select which version of the engine you want to run, Current or Preview, Auto Stop works as expected, but I run one instance of the report, I like to use play slicer to simulate user interaction, then a second instance etc, and see how the Engine behave Setup Databricks SQLĭatabricks has made an amazing job, The Workspace is very neat and intuitive, there is no Mention of the word Spark at all, they hided all the complexity, as far as I am concerned, it act like any Cloud Data warehouse, I had some hiccups though, Azure did complain about some Cpu Quota, it was easy to fix, but very annoying, Google Cloud setup was easier, but as of this writing, there is no SQL interface yet and you have to pay a 100-200 $ cost for Kubernetes, I end up Using Azure The approach is the same, Build a simple PowerBI report using Direct Query, you can use Tableau with Live connection too or you favorite BI tool. This is another short blog on a series of my first impression of using different Data warehouse Engine and how they behave when used for a BI Workload, I am particular interested in small dataset and Mainly looking at concurrency and latency. Edit :, Shant Hovsepian from Databricks was kind enough and gave me some suggestion, Blog Updated.Įdit :, added a note regarding Delta Lake open storage format.
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