MapReduce
Your Self-Driving Car – How Did It Get So Smart?
Destination Autonomous The march towards autonomous vehicles continues to accelerate. While expert opinion differs on the specific timing and use cases that will emerge first, few deny that self-driving cars are in our future. Not surprisingly, when reviewing Big Data…
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MapReduce and Spark
About a week ago, I posted an article on Cloudera’s strategy on SQL in the Apache Hadoop ecosystem. In the article, I argued that a special-purpose distributed query processing engine will perform better than one that translates work into a…
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Apache Spark – Welcome to the CDH family
The neatest part about being part of our market is the rapid rate of innovation we experience. Ideas from a variety of sources – industry, academia and sometimes industry spawned from academia (in the case of our partner Databricks) –…
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Waves of Adoption – Evolution of Hadoop Users
Over the last eight years of Hadoop’s existence we have seen what can be described as “waves of adoption” – there are distinguishable groups of users who adopted Hadoop at similar times and under similar circumstances. Each wave of users…
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Rethink Analytics: Insights from a Data Scientist – Part II
Previously, I talked about the three insights I gained from Josh Wills, Cloudera’s Director of Data Science, in preparation of the Rethink Analytics, with an Enterprise Data Hub webinar. In addition to my personal revelation during the preparation of the…
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What Open Source Leadership Means for Customers
Users of Cloudera’s platform get all the expected benefits of open source. At the same time, they get others that only deep and wide community involvement can provide. Today, software for every layer of the enterprise stack is available under…
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Apache Spark and the Next-Generation Developer
One of the characteristics that makes the Big Data technology space so vibrant and compelling is the rapid rate of change, powered by the dedicated open-source community. With every ecosystem innovation, Hadoop becomes more and more entrenched at the center…
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Our Commitment to Accelerating Apache Spark
When Cloudera became the first vendor to ship and support Apache Spark in February 2014, Spark was already well on its way toward becoming the framework of choice for faster batch processing, machine learning, advanced analytics, and stream processing. Today…
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Apache Flume, Apache Spark, Cloudera, Crunch, Databricks, ETL, HDFS caching, hive, IBM, Intel, MapR, MapReduce, Pig, Solr, Spark, Spark Streaming, YARN
A Look Back at Spark as the Open Standard
This blog post was jointly written by Cloudera (Alex Gutow), Intel (Weihua Jiang), and MapR (Nitin Bandugula) – all companies that are part of the Hive-on-Spark Team As one of the most popular tools in the Apache Hadoop ecosystem, there’s been…
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Hadoop MapReduce or Spark: What if you don’t have to decide now?
This blog was penned by Tendü Yo?urtçu, General Manager, Big Data at Syncsort 2014 was a tipping point for Apache Hadoop: it graduated from being simply a distributed file system and the MapReduce engine for high-performance batch processing to becoming…
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