Snowflake Data Cloud Connector

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Hierarchy Processor transformation

In advanced mode, you can configure a Hierarchy Processor transformation to read hierarchical or relational input from the Amazon S3 V2 or Microsoft Azure Data Lake Storage Gen2 source and write as relational or hierarchical output to the Snowflake target.

The Hierarchy Processor transformation processes hierarchical fields that represent a struct or an array.

You can configure a Hierarchy Processor transformation with the following restrictions:

If the array element of the hierarchical output field contains the fixed-point Number data type, the mapping runs without SQL ELT optimization.

Decimal values of the Double data type are written in exponential notation.

For example, when you write a Double data type 2341.6789 to an output field in the Snowflake target, the output appears as 2.341678900000000e+03.

If you select

Use input group or incoming fields

as a data source and read hierarchical or relational input from the source that contains more than one row and write as hierarchical output to a Snowflake target, Data Integration duplicates records for each row.

To avoid writing duplicate rows to the target, either select

Inherit parent's data sources

as a data source or filter child fields from the data source using the filter condition.

To write Integer or Bigint data type from a Struct field to a Snowflake target, select

advanced.custom.property

from the

Session Property Name

list, and then enter the following value in the mapping task:

DisableAdvancedMappingRuntimeValidation=true

You can't write data from an Avro or Parquet file that contains multi-level struct fields to a Snowflake target.

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Snowflake Data Cloud Connector

Snowflake Data Cloud Connector

Hierarchy Processor transformation

Hierarchy Processor transformation