Use Incorta to prepare data and create an ML model in DataRobot. You can then send the data as part of an Incorta data pipeline to DataRobot for making predictions. The DataRobot Batch Prediction API can be called from an Incorta MV to complete the prediction job.
String matching is a very common problem in business. You will learn how to perform address matching using FuzzyWuzzy in Incorta.
use as.DataFrame()and createDataFrame()to convert R data frame into Spark DataFrame.
Use collect() to collect the data from Spark DataFrame to R DataFrame.
Run SQL queries to do interactive analysis in Incorta Notebook with SparkR.
Use select(), filter(), arrange(), and group_by() functions to handle Spark DataFrame on R.
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(...
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...
Introduction Incorta Materialized Views are a powerful way to enrich data contained in Incorta tables. Leveraging Spark's processing engine, Materialized Views (MVs) can be defined to introduce enrichments and advanced analytics to reshape your dat...
