to read hierarchical data from complex files, such as Avro, JSON, and Parquet files. The
represents the data as an array, map, or struct.
You can use the hierarchical fields as pass-through fields to convert data from one complex file format to another. For example, you can read hierarchical data from an Avro source and write the data to a JSON target. You can also use the hierarchical fields and their child fields in expressions and conditions in downstream transformations. For information about accessing child fields, see the
You can pass hierarchical fields to the following transformations:
Rules and guidelines for reading hierarchical data
Consider the following guidelines when you read hierarchical data:
You must use an Amazon S3 V2 or Azure Data Lake Storage Gen2 connection to read hierarchical data. For more information, see the help for the appropriate connector.
You cannot use a parameter for the source connection or the source object.
If hierarchical fields contain child fields with decimal data types, the
runs using low precision.
The transformation sets the precision and scale based on the values in the first row of data. Note that this first row is sometimes referred to as row 0.
To avoid data truncation, increase the precision and scale in the first row of data. Also ensure that the first row does not include null values.