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Field Name | Type | Description |
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Label* Default Value: Avro Formatter | String | Specify the name for the Snap. You can modify this to be more specific, especially if you have more than one of the same Snap in your Pipeline. |
Schema File* Default Value: [None] | String/Expression | Specify the path to the schema file in .avsc format |
Ignore empty stream Default value: Deselected | Checkbox | Select the checkbox to specify an action that the Snap must take if the input view contains empty documents. If selected, the Snap does not write anything to the output if no documents are received in the input. Else, the Snap writes an empty array in the output view if no documents are received in the input view. |
Snap Execution Default value: Validate & Execute | Dropdown list | Select one of the three modes in which the Snap executes. Available options are:
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Examples
Transforming CSV data to Avro format
This example pipeline demonstrates how to convert CSV data to Avro format as per the specified schema and transform it to generate reports or update a database. The output is the transformed and formatted data ready for further processing.
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Download this pipeline.
Configure the File Reader Snap to read the leads.csv file. On validation, the Snap displays the data in binary format.
2. Configure the CSV Parser Snap to parse the binary input of the leads.csv file. On validation, the Snap displays the structured data.
3. Configure the Avro Formatter Snap to convert the CSV data to Avro format as per the defined Schema file. On validation, the Snap displays the Avro-formatted data.
4. Configure the Avro Parser Snap to parse the Avro-formatted data. On validation, the Snap displays the deserialized data.
5. Configure the Mapper Snap to extract the data. On validation, the Snap displays the output based on the specified mappings.
Snap Pack History
Related Links
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