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Guides and Tutorials for CDAP

Getting Started

Using the Getting Started Guide is recommended by the Cask team for those who don’t have previous experience using CDAP. It is designed to get you quickly started with CDAP, show you how it works and what it can do for you.

How-To Guides

Designed to be completed in 15-30 minutes, these guides provide quick, hands-on instructions for building the “Hello World” of any development task with CDAP.

Consuming Data from Kafka

Learn how to reliably consume data from Kafka in realtime and process it with CDAP

Ingesting Data with Flume

Learn how to use Flume to ingest data into CDAP in realtime

Consuming Twitter Data in Realtime

Learn how to use Flow to consume and process Twitter data in realtime

Realtime Data Processing with Flow

Learn how to build a Flow to process data in realtime with exactly once guarantee and transactional persistence

Iterative Data Processing with Spark

Learn how to run Spark program to process data in CDAP

Batch Data Processing with MapReduce

Learn how to run MapReduce jobs to process data in CDAP

Storing Timeseries Data

Learn how to store timeseries data in CDAP Datasets

Accessing Data with Business Intelligence tools

Learn how to integrate CDAP Datasets with Business Intelligence tools to perform data analysis

Tutorials

Designed to be completed in 2-3 hours, these tutorials provide deeper, in-context explorations of big data application development topics, leaving you ready to implement real-world solutions.

WISE: Web Analytics

Learn how to build CDAP application to analyze web site’s users behavior

Netlens: Network Analytics

Learn how to build CDAP application to analyze network packets to provide traffic stats and detect anomalies in the traffic patterns in real-time

TwitterSentiment: Social Analytics

Learn how build CDAP application to perform sentiment analysis on Twitter data to understand consumer feelings and attitudes towards brands or topics in online conversations

MovieRecommender: Recommender System

Learn how to build CDAP application that uses collaborative filtering to provide movie recommendations for users

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