A data geek by profession - started as a Support Engineer at Microsoft CSS with SQL Server team and grew to Escalation Engineer. Later moved to field teams as a Premier Field Engineer and then to Data and AI Consultant with MCS. Worked through entire Data and Analytics Platform suite on Microsoft technologies with in-depth expertise on SQL Server and Azure SQL, specialized in SQL Performance. Currently, working as an Engineering Architect with the Azure Data team helping customers to unblock and accelerate complex workload migrations and making customer migrations successful on Azure Cloud & Data platform.
This article showcases how to take advantage of a highly distributed framework provided by spark engine, to load data into a Clustered Columnstore Index of a relational database like SQL Server or Azure SQL Database, by carefully partitioning the data before insertion.