Locating Error Logs - AWS Data Pipeline

Locating Error Logs

This section explains how to find the various logs that AWS Data Pipeline writes, which you can use to determine the source of certain failures and errors.

Pipeline Logs

We recommend that you configure pipelines to create log files in a persistent location, such as in the following example where you use the pipelineLogUri field on a pipeline's Default object to cause all pipeline components to use an Amazon S3 log location by default (you can override this by configuring a log location in a specific pipeline component).


Task Runner stores its logs in a different location by default, which may be unavailable when the pipeline finishes and the instance that runs Task Runner terminates. For more information, see Verifying Task Runner Logging.

To configure the log location using the AWS Data Pipeline CLI in a pipeline JSON file, begin your pipeline file with the following text:

{ "objects": [ { "id":"Default", "pipelineLogUri":"s3://mys3bucket/error_logs" }, ...

After you configure a pipeline log directory, Task Runner creates a copy of the logs in your directory, with the same formatting and file names described in the previous section about Task Runner logs.

Hadoop Job and Amazon EMR Step Logs

With any Hadoop-based activity such as HadoopActivity, HiveActivity, or PigActivity you can view Hadoop job logs at the location returned in the runtime slot, hadoopJobLog. EmrActivity has its own logging features and those logs are stored using the location chosen by Amazon EMR and returned by the runtime slot, emrStepLog. For more information, see View Log Files in the Amazon EMR Developer Guide.