Overview

The Query processor executes a Spark SQL query statement on the input datasets.

Spark SQL brings native support for SQL to Spark and streamlines the process of querying data stored both in RDDs (Spark’s distributed datasets) and in external sources. 

More information about Spark SQL.

Input

The Query processor operates on two input datasets containing any type of data.

Configuration

NOTE THAT the input tables must be called firstInputTable and secondInputTable, respectively, when calling them in the SQL statement.

Supported SQL features can be found in the Spark SQL documentation.

Output

Once the query is executed, the response can be visualised in the output table.

Example

Workflow

Input data

firstInputTable

secondInputTable

Example Configuration

We use the following SQL statement to query our data set:

SELECT  f.ContactName, f.City, s.OrderDate
FROM firstInputTable f, secondInputTable s
WHERE  f.CustomerID =  s.CustomerID
AND  f.Country <> 'Sweden'