Load processors in ONE DATA are used to forward data as input within workflows for further manipulation. This data can be either internal (Custom input table, Data tables, etc.) or external (Databases, APIs, etc.).
The following part contains an introduction to the various load processors used in ONE DATA. Links to the detailed explanation for each processor is also provided.
Multi URL API Load
The Multi URL API Load processor fetches data from REST APIs that can be targeted with GET requests. A path through the retrieved JSON can be provided to further specify the content of the created rows.
The processor operates on any input data containing a valid JSON URL and has
Custom Input Table
The Custom Input Table Processor allows the user to set up a new customizable data table with various options.
The processor needs no input and has one output node that forwards the created table.
Data Table Load
The Data Table Load processor is used to fetch the selected Data Table into the Workflow. The processor needs no predecessor and
The Dataset Load Processor is a deprecated version of the Data Table Load Processor.
Flexible ETL Load
The Flexible ETL Load Processor (DEPRECATED) operates on a special type of dataset, namely a pre-defined ETL source.
The processor needs no predecessor and has as output the configured data table to be forwarded for further use.
Database Connection Load
The Database Connection Load processor operates on database connections. The processor needs no predecessor and provides the configured SELECT query result as output.
Flexible REST API
Random Number Generator
The Random Number Generator Processor
The Cassandra Load processor loads a dataset from a Key-Space of an Apache Cassandra database, the loaded data can be further pre-processed using a custom SQL query.
After searching for the dataset in the given Key-Space and applying the specified preprocessing, this processor will generate the dataset which can be used by other processors.
Data Type Recommendation
The Data Type Recommendation Processor generates a JSON result containing type recommendations for each column of a selected dataset. The processor does not accept direct input, neither it does produce direct output.
Type recommendations are shown in a JSON format under "Result" and "JSON Result" in the processor.