Hyper Parser

This page is no longer maintained (Nov 8, 2023). For the most current information, go to https://docs.snaplogic.com/snaps/snaps-analytics/sp-tableau/snap-tableau-hyper-parser.html.

In this article

Overview

You can use this Snap to parse Tableau extract (hyper) file and convert it into documents.

Support for Ultra Pipelines

Works in Ultra Pipelines

Limitations

None.

Known Issues

None.

Snap Input and Output

Input/Output

Type of View

Number of Views

Examples of Upstream and Downstream Snaps

Description

Input/Output

Type of View

Number of Views

Examples of Upstream and Downstream Snaps

Description

Input 

Document

  • Min:1

  • Max:1

  • S3 File Reader

  • File Reader

Data in document format.

Output

Binary

  • Min:1

  • Max:∞

  • JSON Formatter

  • CSV Formatter

  • Mapper

  • Copy

Document in binary format.

Snap Settings

Field Name

Field Dependency

Description

Field Name

Field Dependency

Description

Label*

None.

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.

Default ValueHyper Parser
ExampleHyper Parser

Schema Name

N/A

Specify a schema name for the Tableau extract. If left empty, the Snap uses the default schema name Extract.

Default ValueExtract
ExampleExtract

Routes

Use this field set to define table names and the output views to send documents. You must specify each route in a separate row. Click + to add a new row.

This field set consists of the following fields:

  • Table Name

  • Output view name

Table Name

N/A

Specify a name for the hyper table.

A table must exist in the incoming data of the hyper file. Else, an error is displayed upon validation.

Output view name

N/A

Specify a name for the output view to which the documents should be routed.

Example

Reading And Parsing Tableau Hyper Data

This example Pipeline demonstrates reading and parsing Tableau Hyper data using Tableau Hyper Formatter and Hyper Parser Snaps.

First, we configure the JSON Generator and CSV Generator Snaps to pass JSON and CSV data. Upon validation, we get the JSON and CSV data respectively in the output preview of the Snaps.

JSON Generator Snap

JSON Generator Output

JSON Generator Snap

JSON Generator Output

 

 

CSV Generator Snap

CSV Generator Output

Next, we configure the Hyper Formatter Snap to transform the JSON and CSV output into hyper extract format. We configure two input views, json_data and csv_data—this creates target tables with the same names in the Hyper database of Tableau.

Hyper Formatter Snap

Hyper Formatter Views

Hyper Formatter Snap

Hyper Formatter Views

 

 

Next, we configure the Hyper Parser Snap to parse the transformed Hyper data into two tables, one each for json_data and csv_data. Upon validation, we get JSON and CSV outputs in the two output previews.

Hyper Parser Snap

Hyper Parser Snap

 

Hyper Parser JSON Output

Hyper Parser CSV Output

 

 

Finally, we configure two Mapper Snaps to transform the incoming JSON and CSV data. Upon validation, we get the output data for each format (JSON and CSV).

Mapper Snap - JSON Data

Mapper Snap - CSV Data

Mapper Snap - JSON Data

Mapper Snap - CSV Data

 

Mapper -JSON Data Output

Mapper - CSV Data Output

 

 

Download this Pipeline.

Downloads

  File Modified

File Example_Hyper_Parser.slp

Jul 26, 2021 by Kalpana Malladi

Snap Pack History


See Also