Redshift Schema Evolution
Understand how Upsolver manages changes to your source schema to keep your jobs running successfully.
When writing data from Upsolver to Amazon Redshift, schema evolution is enabled for the following job types:
Ingestion Job: Directly writing data to a Redshift table using the
COPY FROM
syntax.Transformation Job: Using a
SELECT *
expression mapped to the root, for example:
Replication Job: Continuously replicating CDC data to Redshift.
Schema Evolution Overview
Schema evolution in Upsolver means that the system will dynamically create and modify Redshift tables to accommodate changes in the incoming schema. Specifically, Upsolver handles the addition of new columns when new data types are encountered.
Type Mapping
Upsolver maps its primitive types to Redshift column types as follows:
Nested fields and arrays are mapped to the Redshift type SUPER
.
Handling Conflicts
A key challenge in schema evolution is resolving data type conflicts. For instance, if a field initially ingested as BIGINT
changes to VARCHAR
, Upsolver must handle this discrepancy.
Upsolver resolves data type conflicts in the following way:
If the new type is narrower than the original type e.g., varchar to bigint, the value will be inserted into the original column if casting is possible.
If the new type is wider than the original type e.g. bigint to varchar, a new column of the new type will be created with a suffix indicating the new type e.g.
_varchar
for string data. The new value will be written to both the new column and the previous column if a cast is possible. For example, in the case of bigint to varchar, if the value of the varchar is'2'
, it will also be written as2
to the original bigint column.
Example
Initial Data:
{"my_field": 1.2}
Redshift Column:
my_field
of typeFLOAT8
.
New Data:
{"my_field": "str"}
Redshift Columns:
my_field
remainsFLOAT8
, withNULL
for the new string data.my_field_varchar
is created to store the value "str".
Special Cast Handling
Other types will be cast using Redshift's CAST
expression.
The following type tuples will not be cast:
Float8 - Timestamp
Float8 - Date
Float8 - Boolean
Boolean - Date
Boolean - Timestamp
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