The documented minimum permissions required for using the synapsesql connector for spark to read or write data from Synapse SQL Pools is giving high privileges to spark users even though the required operation is only read. In this article, I’ll provide a workaround
Azure Synapse Analytics’ most appealing feature at first glance is the Synapse Studio. One unified UX across data stores, notebooks and pipelines. Notebook experience is appreciated the most among folks who read a load of data that takes minutes or hours to load then do operations on it whether in data engineering, feature engineering or ML training. The ability to divide your code into smaller chunks that you control which to execute when is a powerful productivity tool.
Added value that the notebook stores not only code by also the results of your code so to speak, it has now a data storage capacity that makes some organizations that are highly regulated or handles high confidential information worried about it.
Workload management for cloud data warehouses is one of the most important administrative task for DBAs/Data Engineers (depends who manage the data warehouse). With cloud offerings fully or partially automating many other administrative tasks, the workload management becomes one of the few tasks that need special attention.
Also for customers who are trying Azure Synapse for the first time and got disappointed because of the performance is not as expected. In my experience, the main reason is not configuring workload management.
If I got your attention let’s dive in :) The discussion here will focus only on one part of Azure Synapse which is the Dedicated SQL Pools
TLDR; The documented minimum permissions required for using the synapsesql connector for spark to read or write data from Synapse SQL Pools is giving high privileges to spark users even though the required operation is only read. In this article,...
Notebooks in Synapse Azure Synapse Analytics’ most appealing feature at first glance is the Synapse Studio. One unified UX across data stores, notebooks and pipelines. Notebook experience is appreciated the most among folks who read a load of data that...
Workload management for cloud data warehouses is one of the most important administrative task for DBAs/Data Engineers (depends who manage the data warehouse). With cloud offerings fully or partially automating many other administrative tasks, the workload management becomes one of...
TLDR; Don’t assume that your SQL MI database is protected from deletion by using Azure TLDR2; if you prefer video, here’s the demo
Last year I published a series of youtube videos to explain with demos and whiteboard the Azure SQL Database Networking. I used SQL DB as an example for PaaS service however the same concepts apply on many other PaaS services....
