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DocumentationParsing Errors

Parsing Errors

Parsing errors indicate the row(s) in your source data that do not comply with either the type defined for the column or the operation applied to it. These errors are identified and logged by Etleap during transformation of your pipeline.

Etleap isolates these row(s) that failed to comply (i.e., parsing errors) and will not attempt to load the failed rows into the destination, until the parsing errors are resolved.

Managing Parsing Errors

When Etleap detects a parsing error, the pipeline either completely stops or the invalid row(s) that caused the error are isolated and not loaded into the destination. How Etleap handles your parsing errors depends on your parsing error settings. You will receive parsing error notifications from Etleap via one of the following ways:

  1. The “Heads Up!” warning section of your home page dashboard.
  2. An individual pipeline’s overview page.
  3. The transform report from the pipeline’s activity page.
  4. Email notification if the pipeline was run for the first time.

Once identified, Etleap suggests a transform in the Wrangler to resolve the issue. The suggested transform is added to end of the pipeline’s script. You have the option to accept the suggested resolution or add your own step to resolve.

Note

The suggested resolution that Etleap provides is based on the idea of widening the column type to handle the new data, which may not always be the required resolution. If the suggested resolution is not acceptable, you can modify the script or the source data to handle these changes.

Once the resolution is applied to the script, the pipeline begins refreshing to reflect this change.

For a detailed tutorial on resolving parsing errors, visit our how-to guide here.

Types of Parsing Errors

There are two major categories of parsing errors. Type errors happen when the output data type of a transform differs from the type defined for that column. Operation errors happen when a transform could not be completed due to some invalid data or data in an unexpected format.

CategoryParsing ErrorDescriptionSuggested resolution
TypeInvalid Data TypeColumn is of the type X, but there are row(s) of data in the source that are not of that type.Add a script step to expand the column datatype to a wider one to capture all the source data.
TypeData Out of RangeColumn value exceeds the range of the specified column data type.Drop the failing row(s) in the source or edit the values.
TypeDestination Type RestrictionThe length of the string exceeds the 65535 characters, which is the max length that Amazon Redshift supportsDrop the failing row(s) in the source or edit the values.
TypeUnsupported Values’NaN’, ‘Infinity’, and ‘-Infinity’ are not supported by Redshift or SnowflakeDrop the failing row(s) in the source or edit the values.
OperationFailed transformWhen the input data to a transform operation is invalid.Deactivate the failing script step.
Example of a Invalid Data Type parsing error
Example of an Invalid Data Type parsing error
Example of a Data out of Range parsing error
Example of a Data out of Range parsing error
Example of a Failed Transform parsing error
Example of a Failed Transform parsing error

Parsing Error Settings

Since parsing error tolerance is case-specific, Etleap provides the ability to define your own parsing error settings. You can specify how the pipeline should deal with the parsing errors in the Overview → Parsing Errors → Settings tab.

Parsing error settings
Parsing errors settings

Threshold

Depending on your use-case, a small percentage of parsing errors might be acceptable or even expected. In other cases, a portion of parsing errors might be unacceptable.

The threshold setting allows to define the percentage of rows per transformation that can have parsing errors. If you want zero tolerance for parsing errors set the threshold to 0%, whereas if some parsing errors are acceptable, set it to a higher percentage.

Action

You can define the action taken on your pipeline when the defined threshold is crossed. The Notify setting lets the pipeline processing continue, isolates the invalid rows, and sends you a notification. The Stop setting pauses pipeline processing until the parsing errors are addressed.