Intro to Big Data
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Jon Bloom, a senior consultant from Agile Bay, Inc., will present on big data and Hadoop. The session agenda includes definitions of big data and Hadoop, a comparison of BI and Hadoop, and a demo. Hadoop is an open source Apache project for distributed computing across commodity servers using batch processing. It includes HDFS, YARN, MapReduce and an ecosystem of tools like HBase and Hive. While Hadoop extends BI capabilities to massive datasets, BI is suited for datasets up to hundreds of gigabytes versus Hadoop which handles terabytes to petabytes of data.
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Intro to Big Data
- 1. Presented by: Jon Bloom Senior Consultant, Agile Bay, Inc.
- 2. Customers & Partners Jon Bloom Blog: http://www.bloomconsultingbi.com Twitter: @sqljon Linked-in: http://www.linkedin.com/in/BloomConsultingBI Email: jbloom@AgileBay.com
- 3. w w w . a g i l e b a y. c o m
- 4. Session Agenda What is Big Data? What is Hadoop? BI vs. Hadoop Demo:
- 5. Terms and Acronyms Hadoop: Apache project (open source) project to develop software for reliable, scalable, distributed computing. Cluster: A group of computers (nodes) linked together to perform a highly-available and high computation work HDFS distributed file system that provides high-throughput access to application data. YARN A framework for job scheduling and cluster resource management. MapReduce A system for parallel processing of large data sets.
- 7. What is Big Data? Volume, Velocity, Variety
- 9. What is Hadoop Apache open source project Batch Oriented Parallel Processing across Commodity Servers Ecosystem • • • • • Ambari HBase Avro Cassandra Chukwa • • • • Hive Mahout Pig ZooKeeper
- 12. BI vs. Hadoop Hadoop not a replacement of BI Extends BI capabilities BI = Scale up to 100s of Gigabytes Hadoop = From 100s of Gygabytes to Terabytes (1,000s og Gygabytes) and Terabytes (1,000,000 Gigabytes)