Prerequisites: CMC instance is up and runningNode agent instance(s) are up and runningZookeeper is up and running (either shipped with incorta or a clustered zookeeper)An empty schema is created (either oracle metadata or MySQL metadata)A common/shar...
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.
We would like to get the current hour, how can we get it in Spark SQL? We also need the time as of one hour ago, how do we do that?
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...
A snapshot table holds the same transactional data as its source system, with additional fields for tracking the snapshot date.
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...
Use external sql query tools like DbVisualizer or PSequel to connect to Incorta and run postgres sqls against Incorta data.
This python script takes an unzipped tenant export file or an unzipped schema export file and produces a csv file which has all the table column details like datatype, etc... in a schema. This csv file can then be imported into Incorta and a dashboar...
