{"id":5240,"date":"2015-04-06T07:00:41","date_gmt":"2015-04-06T15:00:41","guid":{"rendered":"http:\/\/formtek.com\/blog\/?p=5240"},"modified":"2015-02-26T09:23:06","modified_gmt":"2015-02-26T17:23:06","slug":"apache-spark-turbocharging-past-hadoops-mapreduce","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/apache-spark-turbocharging-past-hadoops-mapreduce\/","title":{"rendered":"Apache Spark: Turbocharging Past Hadoop&#8217;s MapReduce"},"content":{"rendered":"<p><a title=\"Apache Spark\" href=\"https:\/\/spark.apache.org\/\" target=\"_blank\">Apache Spark<\/a> appears to be igniting Big Data projects in 2015. \u00a0Spark is an Apache open source engine built for Hadoop to perform sophisticated data analysis and analytics. \u00a0Compared to Hadoop-only applications, Spark applications are as much as 10 to 100 times faster, and they&#8217;re easier to program. \u00a0But Spark isn&#8217;t an alternative to Hadoop, it&#8217;s a tool that turbocharges what Hadoop does.<\/p>\n<p><a href=\"http:\/\/formtek.com\/blog\/wp-content\/uploads\/2015\/01\/spark-logo.png\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-5241 alignleft\" alt=\"spark-logo\" src=\"http:\/\/formtek.com\/blog\/wp-content\/uploads\/2015\/01\/spark-logo.png\" width=\"206\" height=\"110\" \/><\/a>Recently TypeSafe took a survey of how popular Spark has become and asked developers how they&#8217;re using it. \u00a0Some of the findings from<a title=\"Typesafe report on Apache Spark\" href=\"http:\/\/info.typesafe.com\/COLL-20XX-Spark-Survey-Report_TY.html\" target=\"_blank\"> that report <\/a>are as follows:<\/p>\n<ul>\n<li>Spark is very <strong>popular<\/strong> now. \u00a071 percent of businesses surveyed by TypeSafe said that had done at least some amount of hands-on evaluation with Spark, and 35 percent of businesses are using it or planning to use it.<\/li>\n<li>Spark is <strong>fast<\/strong>. \u00a0Spark has significantly faster performance and event stream processing compared to Hadoop&#8217;s standard MapReduce.<\/li>\n<li><strong>Few barriers<\/strong> to adoption. \u00a0Developers said the major barrier currently is just lack of deep experience with the technology and a lack of support for and integration with other middleware, like message queues and databases.<\/li>\n<\/ul>\n<p><a title=\"Dr. Dean Wampler bio\" href=\"https:\/\/www.linkedin.com\/in\/deanwampler\" target=\"_blank\">Dr. Dean Wampler<\/a>, Big Data architect at Typesafe, <a title=\"Typesafe on Big Data and Spark\" href=\"http:\/\/www.marketwired.com\/press-release\/survey-indicates-apache-spark-gaining-developer-adoption-as-big-datas-projects-require-1986162.htm\" target=\"_blank\">said that<\/a>\u00a0&#8220;the need to process Big Data faster has largely fueled the intense developer interest in Spark. \u00a0Hadoop&#8217;s historic focus on batch processing of data was well supported by MapReduce, but there is an appetite for more flexible developer tools to support 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