Hadoop Happenings: Spark Escalates

By February 3, 2015


Grab the latest news and commentary about Hadoop all in one place in this week’s Hadoop Happenings. This week focus turned to Apache Spark as it continues to gain interest as a faster more flexible alternative to MapReduce. There was also discussion on the growing role of data scientists and whether the role should be included in the C-Suite.

1. Choosing the Right Big Data Execution Framework: Why One Size Doesn’t Fit All Tools in the Hadoop ecosystem are built for specific use cases, and businesses should be prepared to switch between them as necessary. Read More

2. Survey reveals a few interesting numbers about Apache Spark The biggest use cases for Spark are faster batch processing and stream processing according to a survey from Databricks and Typesafe. Read More

3. Hortonworks and 3 large users launch a project to secure Hadoop Hortonworks is teaming up with three of its customers to create the Data Governance Initiative, which will address enterprises’ security concerns with Hadoop. Read More

4. Why the Hadoop big data bubble will continue to expand in 2015 In this post, the author argues that the big data bubble still has some room to grow in 2015. Read More

5. The Big Data Tool Spark May be Hotter than Hadoop, but It Still Has Issues An interview with Typesafe’s Dean Wampler discusses challenges to adopting Apache Spark and how it differs from MapReduce. Read More

6. Spark promises to up-end Hadoop, but in a good way This article discusses how Spark simplifies and speeds up Hadoop and may replace MapReduce as Hadoop’s core engine. Read More

7. Big Data Needs More ‘Creative Types’ In this post, the author argues data scientists should be referred to as data artists due to the nuance that goes into the job. Read More

8. Chief Data Science Officers Won’t Supplant CIOs The role of data scientist is quickly growing in prestige, but some feel having a data scientist in the executive suite will be detrimental. Read More

9. Data preparation is the unsung hero of big data analytics Data preparation is a critical step in big data analytics, and tools that streamline this process will grow in value. Read More

10. Hadoop’s new role: Adjunct data warehouse Hadoop’s role fits into three broad use cases: core data warehouse, data lake or the adjunct data warehouse. Read More


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