PowerExchange for Amazon Redshift User Guide

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Troubleshooting for PowerExchange for Amazon Redshift

How to enable Metadata Access Service for PowerExchange for Amazon Redshift?: You can optionally enable Metadata Access Service to import metadata from Amazon Redshift. For information on how to enable Metadata Access Service, see https://knowledge.informatica.com/s/article/HOW-TO-Enable-Metadata-Access-Service-to-import-metadata-from-Amazon-S3-and-Amazon-Redshift?language=en_US
How to configure performance tuning and sizing guidelines for PowerExchange for Amazon Redshift on the Spark engine?: For information about performance tuning and sizing guidelines, see https://docs.informatica.com/data-integration/powerexchange-adapters-for-informatica/h2l/1111-performance-tuning-and-sizing-guidelines-for-powerexchange-/abstract.html
How to solve the following error that occurs while running an Amazon Redshift mapping on the Spark engine to write a table that contains more than 500 columns: "java.lang.StackOverflowError": For information about the issue, see https://kb.informatica.com/solution/23/Pages/67/544565.aspx?myk=544565
How to solve the following error that occurs while running an Amazon Redshift mapping on the Spark engine to read from a table that contains more than 510 columns: "java.lang.StackOverflowError": For information about the issue, see https://kb.informatica.com/solution/23/Pages/62/516323.aspx?myk=516323
How to solve the following error that occurs while running an Amazon Redshift mapping on the Spark engine to read or write data: "No space available in any of the local directories": For information about the issue, see https://kb.informatica.com/solution/23/Pages/62/516324.aspx?myk=516324
How to solve the following error that occurs while running an Amazon Redshift mapping on the Spark engine to read or write data: "Container is running beyond physical memory limits in EMR cluster": For information about the issue, see https://kb.informatica.com/solution/23/Pages/62/516326.aspx?myk=516326
How to solve the following error that occurs while running an Amazon Redshift mapping on the Spark engine to read data: "com.amazonaws.AmazonClientException: Unable to execute HTTP request: Read timed out": For information about the issue, see https://kb.informatica.com/solution/23/Pages/62/516327.aspx?myk=516327
How to solve the out of disk space error that occurs when you use PoweExchange for Amazon Redshift to read and preview data?: For information about the issue, see https://kb.informatica.com/solution/23/Pages/62/516321.aspx?myk=516321
Mapping on the Spark engine fails with an error when you use the Amazon S3 staging bucket with a dot (.) in the bucket name for CDP 7.1 distribution.: If you run a mapping on the Spark engine with such configurations, the mapping fails with the following error message:
Unable to execute HTTP request: Certificate for xxxx doesn't match any of the subject alternative names

Perform the following steps to run the mapping successfully:
In the CDP cluster, go to
HDFS
.
Click
Configuration
.
In
Cluster-wide Advanced Configuration Snippet (Safety Valve) for core-site.xml
, add the property
fs.s3a.path.style.access
and set the value to
true
.
Restart the cluster.
Refresh the cluster configuration object.
Restart the Data Integration Service.

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Table of Contents

PowerExchange for Amazon Redshift User Guide

PowerExchange for Amazon Redshift User Guide

Troubleshooting for PowerExchange for Amazon Redshift

Troubleshooting for PowerExchange for Amazon Redshift