Data & Schemas Knowledgebase
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Knowledge Base Articles

How Joins Work in Incorta

Introduction Incorta supports the following types of joins: One-to-one (1:1) Many-to-one (M:1) Many-to-many (M:M) joins using Materialized Views Example: Simple Many-to-one (M:1) Join Tables: Sales table Customer table The Sales table has mult...

KailaT by Community Manager
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Getting Started with R in Incorta Notebook

Overview R is a popular language in Data Science.  Incorta supports creating materialized views (MV) with R. Your first Spark Program The minimum requirement for creating an MV includes the following: # Read data from Incorta into Spark df <- read(...


Use SparkSQL with SparkR

Overview In this recipe, you’ll learn how to run SQL queries from SparkR. After using the read() Incorta Notebook extension function to load data in Incorta Notebook, the data is in a SparkR DataFrame. You can use sql() to write SQL queries after cr...

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suxinji by Employee
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ML with IRIS data set using Incorta

This article shows how to use a classification Machine Learning (ML) algorithm on the Iris Flower data set. It first creates a model based on a training data set and then scores the the test data set and gives the prediction of the flower based on th...

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