
    AWS Clean Rooms now enables users to configure compute resources for PySpark jobs, allowing flexible instance type and cluster size selection to optimize performance and cost for data analysis.


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<p>
AWS Clean Rooms has introduced configurable compute size for PySpark jobs, providing enhanced flexibility for data analysis and collaboration.
</p>
<ul>
<li>Customers can now customize instance type and cluster size for PySpark jobs</li>
<li>Enables performance optimization for complex data sets</li>
<li>Allows cost management by selecting appropriate instance sizes</li>
<li>Supports runtime configuration of compute resources</li>
<li>Enhances AWS Clean Rooms' data collaboration capabilities</li>
</ul>
<p>
This update empowers organizations to fine-tune their data analysis workflows by dynamically adjusting compute resources to match specific performance and cost requirements.
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AWS Clean Rooms supports configurable compute size for PySpark jobs

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