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    Data Source Discovery


    Upsolver persists all incoming events to Amazon S3 and auto-generates a schema.

    Upsolver's schema:

    • Maintains the data's hierarchical format.
    • Contains the event's content under "data" and the event's headers under "headers".
    • Includes an Upsolver processing time - "time" field.
    • Can be enriched using Calculated Fields or Materialized View Lookup.

    Determining data types

    Fields' data type may vary by file format:

    • JSON/AVRO - fields' types are determined according to the data type seen in the event.
    • CSV/TSV/x-www-form-urlencoded - the user can choose between 2 options when creating the data source:

      • All fields are treated as STRING (default).
      • Auto detect types - Upsolver tries to assign a DOUBLE/LONG data type if possible. If not, the data type is STRING.

      Upsolver Schema

    * Note that a field may appear twice with the same name but with different data types. Upsolver reflects the schema as seen in the data.

    Ingestion Errors

    If there were any parsing error during the ingestion process Upsolver will display these errors under the Parser Errors tab. An example of this can be seen in the following image: Parse Errors
    In the case above the json string is missing the starting { and therefore Upsolver is unable to parse the event.


    The Samples tab allows you to view some sample raw events as JSON. You can choose to download one of these samples by clicking the Export button.


    The Properties tab will show you the definition of the Data Source along with some useful information depending on the Data Source type. For example, the Properties of the HTTP Data Source will include the ingest URL to be used to send data to this source.

    Data Source Statistics

    At the top of the screen you will be able to see some details and statistics about this data source.

    • Cluster - The Compute Cluster running this Data Source.
    • Total Events - How many events this data source has ingested in total.
    • Parse Errors - How many parse errors this data source had in total.
    • Ingest Rate - The current ingestion rate of data in this data source.
    • Ingest Delay - If this data source has a backlog of data to ingest you will see how far behind it is here.

    Field statistics

    When you click on a field in the Schema tab you will get some statistics and information about that field.

    • Occurrences In Events - How many times this field existed in the ingested events. Next to this number you will see the percentage out of the total ingested events in which this field exists.
    • Distinct Values - How many uniquely different values this field contains across all events.
    • Value Distribution - This will show the most common values in this field alongside a percentage representing how common this value is across all events.
    • Field Content - Here you will see a sample of some of the latest values in this field.

    Archive and Delete

    If you would like to stop your Data Source you can select Archive Data Source from the drop down menu in the top right:

    Once you do this the input will stop ingesting data. You can later Un-Archive your Data Source which will cause it to start ingesting data once again.

    If you would like to completely delete your data source you can click Delete once it's archived. Be careful this will completely delete the Data Source along with any data it has ingested and will not be recoverable.