Upsolver
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Data formats
This page goes over the different data formats available in Upsolver and, if applicable, their corresponding configuration options.
When creating a data source, the content format is typically auto detected, but you can manually select a format and specify additional details, as required.
The following content formats are supported:

The schema is auto detected.

The schema is auto detected.

The schema is auto detected.

The schema is auto detected. The body should contain the message itself, which should not be url-encoded.
Store JSON as String
(Optional) Whether to store the JSON in native format in a separate field.

Infer Types
Header
Delimiter
Null Value
(Optional) Select whether to auto detect the types. If not selected, Upsolver will read all fields as strings.
(Optional) The content header.
If you only add details for one column, additional columns will be labeled as overflow columns.
(Optional) The delimiter between columns of data.
(Optional) The value to be interpreted as a null value.

Infer Types
Header
(Optional) Whether to auto detect the types.
(Optional) The content header.
If you only add details for one column, additional columns will be labeled as overflow columns.

The body should contain the message itself, which should not be url-encoded.

Schema files
Main File
Message Type
(Optional) Click Select to choose the required schema files.
(Optional) The main file from the list of selected schema files.
(Optional) The message type.

For Amazon S3, Azure Blob Storage, Google Cloud Storage or File Upload data sources.
Avro Record Schema
(Optional) The Avro record schema.

For Amazon Kinesis, Kafka, S3 Over SQS.
Avro Record Schema
Bytes Parsers
Additional Schemas
The Avro record schema.
(Optional) A parser for JSON-format schemas.
(Optional) Additional Avro record schemas.

Schema Registry URL
(Optional) The URL to the schema registry.

The schema is auto-detected.
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Avro
Parquet
ORC
JSON
CSV
TSV
x-www-form-urlencoded
Protobuf
Avro-record
Avro-record
Avro with Schema Registry
XML