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Improving Parquet External Table Performance in Dedicated SQL Pools

Jovan Popovic shows us two ways of accessing data in Parquet files in Azure Synapse Analytics dedicated SQL pools:

Azure Synapse Analytics enables you to read Parquet files stored in the Azure Data Lake storage using the T-SQL language and high-performance Parquet readers. The key characteristic of these high-performance Parquet readers is that they are using the native (C++) code for reading Parquet files, unlike the existing Polybase Parquet reader technology that uses the Java code. These native readers are introduced in the serverless SQL pools in Azure Synapse Analytics workspaces.

In many experiments, this native technology that is used in the serverless SQL pools demonstrated better performance compared to the existing Polybase external table in the dedicated SQL pools.

This native technology for reading Parquet files is now also available in the dedicated SQL pools. In the dedicated Pools in Azure Synapse Analytics, you can create external tables that use native code to read Parquet files and improve performance of your queries that access external Parquet files.

Click through for the process, as well as what kind of performance differences you can see. Some of the queries ended up being worse for native tables versus PolyBase tables, but the majority were a good bit better.

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