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Book Overview & Buying
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Table Of Contents
Building Modern Data Applications Using Databricks Lakehouse
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In this chapter, we’re going to look at several methods for scaling your Delta Live Tables (DLT) pipelines to handle the processing demands of a typical production environment. We’ll cover several aspects of tuning your DLT pipelines, from optimizing the DLT cluster settings so that your pipelines can quickly scale to handle the spikes of heavy processing demand to looking at ways we can optimize the data layout of the underlying tables in cloud storage. By the end of this chapter, you should have mastered how DLT clusters can automatically scale out to handle demand. You should also have a good understanding of the impact that table maintenance tasks, which are automatically run in the background by the DLT system, have on the performance of your data pipelines. Lastly, you should understand how to leverage Delta Lake optimization techniques to further improve the execution performance of your DLT pipelines.
We’re going to cover the following...