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  • PowerExchange Adapters for Informatica H2L
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  1. Abstract
  2. Supported Versions
  3. Performance Tuning and Sizing Guidelines for PowerExchange for Amazon Redshift on the Spark Engine

Performance Tuning and Sizing Guidelines for PowerExchange for Amazon Redshift on the Spark Engine

Performance Tuning and Sizing Guidelines for PowerExchange for Amazon Redshift on the Spark Engine

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Overview

Overview

Performance tuning is an iterative process where you analyze the performance, use guidelines to estimate and define parameters that impact the performance, monitor, and adjust the results as required. Sizing is a process where you analyze the data set and use the recommended hardware to improve the performance.
This document describes the key data size, hardware, and Spark tuning parameters that you can tune to optimize the performance of PowerExchange for Amazon Redshift on the Spark engine.
The performance testing results listed in this article are based on observations in an internal Informatica environment using data from real-world scenarios. The performance of PowerExchange for Amazon Redshift might vary based on individual environments and other parameters even when you use the same data.
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