Redis Row Format

The RDI pipelines support two separate row formats which you can specify in the source section of the job file:

partial - (Default) Contains the current value of the row only.
full - Contains all information available for the row, including the key, the before and after values, and the operation code.

The full row format is useful when you want to access the metadata associated with the row, such as the operation code, and the before and after values. The structure of the data passed to the transform and output sections is different depending on the row format you choose. Consider which row format you are using when you reference keys. The following two examples demonstrate the difference between the two row formats.

Default row format

With the default row format, the input value is a JSON object containing the current value of the row, and fields can be referenced directly by their name.

Usage example:

yaml

name: Default row format example
source:
  table: addresses
transform:
  - uses: add_field
    with:
      field: city_state
      expression: concat([CITY, ', ', STATE])
      language: jmespath
  - uses: add_field
    with:
      field: op_code_value
      # Operation code is not available in standard row format
      # so the following expression will result in `op_code - None`
      expression: concat(['op_code', ' - ', opcode])
      language: jmespath
output:
  - uses: redis.write
    with:
      data_type: hash
      key:
        expression: concat(['addresses', '#', ID])
        language: jmespath

Full row format {#full}

With row_format: full the input value is a JSON object with the following structure:

key - An object containing the attributes of the primary key. For example, key.id will give you the value of the id column as long as it is part of the primary key.
before - An object containing the previous value of the row.
after - An object containing the current value of the row.
opcode - The operation code. See [Using the operation code]({{< relref "/integrate/redis-data-integration/data-pipelines/transform-examples/redis-opcode-example" >}}) for more information about the possible opcode values and how to use them.
db - The database name.
table - The table name.
schema - The schema name.

Note: The db and schema fields are database-specific and may not be available in all databases. For example, MySQL doesn't use schema and uses db as the database name.

Usage example:

yaml

name: Full row format example
source:
  table: addresses
  row_format: full
transform:
  - uses: add_field
    with:
      # opcode is only available in full row format and can be used in the transformations
      field: after.op_code_value
      expression: address
      language: jmespath
  - uses: add_field
    with:
      field: after.city_state
      # Note that we need to use the `after` prefix to access the current value of the row
      # or `before` to access the previous value
      expression: concat([after.CITY, ', ', after.STATE])
      language: jmespath
output:
  - uses: redis.write
    with:
      data_type: hash
      key:
        # There are different ways to express the key
        # If the `ID` column is the primary key the following expressions
        # are equivalent - `key.ID`, `after.ID`, `values(key)[0]`
        expression: concat(['addresses-full', '#', values(key)[0]])
        language: jmespath

Important notes when using `row_format: full`

The before object will be null for insert and create operations, and the after object will be null for delete operations. If you are building the output key manually, you should account for this and ensure that you are not trying to access fields from a null object, as shown in the example below:

yaml

name: Handle delete operations with full row format
source:
  table: addresses
  row_format: full

output:
  - uses: redis.write
    with:
      key:
        language: jmespath
        # The following pattern will fail for delete operations. In those cases `after` is null, the resulting key will
        # be 'addresses:None' and the key won't be removed from the target
        # expression: concat(['addresses:', after.ID])

        # This pattern works for all operations, by using the ID from the `after` object if it is available,
        # and falling back to the ID from the `before` object if not.
        expression: concat(['addresses:', after.ID || before.ID])

        # Another option is to use the ID from the `key` object
        # expression: concat(['addresses:', values(key)[0]])

Please note that you should not use key in combination with row_format: full and more than one output, as the key object will be overwritten by the previous output. This is a known limitation of the current implementation and is subject to change in future versions.

The final result of the processing (which is what will be stored in the output) is the value of the after object. This means you must reference the fields using the after prefix unless you change the output structure in a transformation step. Also, when you add new fields, you must prefix them with after. to ensure that they are added to the correct part of the output:

yaml

name: Add fields with full row format
source:
  table: addresses
  row_format: full

transform:
  - uses: add_field
    with:
      field: after.city_state  # use this to add the new field to the final output
      # field: city_state  # use this if you need a temporary field in the transformation steps, but not in the final output
      expression: concat([after.CITY, ', ', after.STATE])
      language: jmespath

Default row format

Full row format {#full}

Important notes when using row_format: full

Important notes when using `row_format: full`