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Apache Spark for Azure Synapse Guidance

This document outlines best practices Guidance for developing Spark applications with Azure Synapse Analytics. It is composed of four sections: Reading Data reading data into Spark Writing Data writing data out of Spark Developing Code developing optimized Spark code Production Readiness best practices for scalability, reproducibility and monitoring Reading Data Whether you are reading in data from an ADLS Gen2 data lake, an Azure Synapse Dedicated SQL pool, or other databases in Azure there are several important steps to take to optimize reading data into Apache Spark for Synapse .

example reads in the entire file. Once read, a tmp table is created and a “WHERE” statement is executed on the partitioned column. Example 1 shows how the file partitioning is done on the initial read from storage. Example 2 the file partition is occurring as a result of the WHERE clauses in the spark SQL statement. Both accomplish the same ...

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