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Microsoft Azure Machine Learning

You're reading from  Microsoft Azure Machine Learning

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781784390792
Pages 212 pages
Edition 1st Edition
Languages
Authors (2):
Sumit Mund Sumit Mund
Profile icon Sumit Mund
Christina Storm Christina Storm
Profile icon Christina Storm
View More author details
Toc

Table of Contents (21) Chapters close

Microsoft Azure Machine Learning
Credits
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Introduction ML Studio Inside Out Data Exploration and Visualization Getting Data in and out of ML Studio Data Preparation Regression Models Classification Models Clustering A Recommender System Extensibility with R and Python Publishing a Model as a Web Service Case Study Exercise I Case Study Exercise II Index

The Apply SQL Transformation module


The Apply SQL Transformation module lets you run a SQL query on the input dataset(s) and get the desired result. You can find it under Data Transformation | Manipulation in the module palette. The module can take one, two, or three datasets as inputs. The dataset coming from input 1 can be referenced as t1. Similarly, you can refer to datasets from input 2 and input 3 as t2 and t3, respectively. On the properties of the module, the Apply SQL Transformation module takes only a parameter as a SQL query. The syntax of the SQL it supports is based on the SQLite standard.

In the following illustration, the module takes data from two datasets, joins them, and selects fewer columns. It also generates calculated columns by applying an aggregation function, AVG.

If you are already familiar with SQL, you may find this module very handy for data transformation.

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