Nitin Bandugula, Sr. Product Manager at MapR is responsible for strategy and go-to-market for MapR Worldwide Services covering Professional Services, Education and Support Services. Nitin leverages his experience in Engineering, Management Consulting and Marketing to bring new big data services and solutions to the Hadoop market. Nitin has a master's degree in Computer Science and holds an MBA from the Johnson School at Cornell University.
The recent Attunity and MapR webinar ”Give your Enterprise a Spark: How to Deploy Hadoop with Spark in Production” proved to be highly interactive and engaging. As promised, Nitin and Rodan have provided follow-up answers your questions.
Apache Spark on Hadoop is great for processing large amounts of data quickly. The story gets even better when you get into the realm of real time applications.
In this blog, I’d like to talk about the differences between Apache Spark and MapReduce, why it’s easier to develop on Spark, and the top five use cases.
You already know Hadoop as one of the best, cost-effective platforms for deploying large-scale big data applications. But Hadoop is even more powerful when combined with execution capabilities provided by Apache Spark. Although Spark can be used with a number of big data platforms, with the right Hadoop distribution, you can build big data applications quickly using tools you already know.
This is the third and final entry in our three-part series focused on building basic skill sets for use in data analysis. The series is aimed at those who have some familiarity with using SQL to query data but limited or no experience with Apache Drill.
This is the second in our three-part series focused on building basic skill sets for use in data analysis. The material is intended for those who have no prior, or very limited, experience with Apache Drill, but do have some familiarity with running SQL queries.
Big Data analysis is intimidating to some people. They assume you need a background in statistics, deep technical knowledge, and other complex skills. But you don’t need to be a data scientist to extract insights and value from Big Data with Hadoop and Apache Drill.
We are pleased to announce the availability of the Apache Drill Essentials course as part of MapR Hadoop On-Demand Training.
So you’ve researched the general capabilities of Hadoop, and have worked with your colleagues to identify the first set of big data use cases to tackle. Now, you’re ready to take the plunge and select the right Hadoop solution to invest in. After thoroughly doing your homework, you might think the final selection step would be simple, knowing that open source packages appear to be the same across the different Hadoop distributions out there. Unfortunately, that is not the case.
We recently wrapped up a webinar series, covering global audience, on the topic of “Apache Drill: Introduction, Differentiation and Use Cases” that proved to be highly interactive and engaging.The webinar provided a quick introduction to Drill, covered key Drill differentiators for SQL specialists and business analysts, and provided an overview of new Hadoop use cases that were uncovered during the Drill Beta at MapR.
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