{"id":166548,"date":"2023-02-07T10:09:19","date_gmt":"2023-02-07T09:09:19","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=166548"},"modified":"2023-10-30T18:26:20","modified_gmt":"2023-10-30T17:26:20","slug":"apache-spark-its-functions-and-benefits","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits","title":{"rendered":"Apache Spark: Understanding its Functions and Benefits"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"166548\" class=\"elementor elementor-166548\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-cf4751f e-flex e-con-boxed e-con\" data-id=\"cf4751f\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-6b28571 elementor-widget elementor-widget-text-editor\" data-id=\"6b28571\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p><strong>Apache Spark is a unified, ultra-fast analytics engine for large-scale data processing. It enables large-scale analysis through cluster machines. It is mainly dedicated to Big Data and Machine Learning.<\/strong><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4ac22a9 elementor-widget elementor-widget-spacer\" data-id=\"4ac22a9\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-column .elementor-spacer-inner{height:var(--spacer-size)}.e-con{--container-widget-width:100%}.e-con-inner>.elementor-widget-spacer,.e-con>.elementor-widget-spacer{width:var(--container-widget-width,var(--spacer-size));--align-self:var(--container-widget-align-self,initial);--flex-shrink:0}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container,.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer,.e-con>.elementor-widget-spacer>.elementor-widget-container,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer{height:100%}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner{height:var(--container-widget-height,var(--spacer-size))}<\/style>\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-dda8c04 e-flex e-con-boxed e-con\" data-id=\"dda8c04\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-71ca0fc elementor-widget elementor-widget-heading\" data-id=\"71ca0fc\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h3 class=\"elementor-heading-title elementor-size-default\">What is Apache Spark?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8626f32 elementor-widget elementor-widget-text-editor\" data-id=\"8626f32\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">For the curious, let&#8217;s go back to the creation of Apache Spark!<\/span><\/p><p><span style=\"font-weight: 400;\">It all started in 2009. <\/span><span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/spark.apache.org\/\">Spark<\/a><\/strong><\/span><span style=\"font-weight: 400;\"> was designed by Matei Zaharia, a Canadian computer scientist, during his PhD at the University of California at Berkeley. Initially, its development is a solution to <\/span><b>accelerate the processing of Hadoop systems<\/b><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Today it is a project of the Apache Foundation. Since 2009, more than 1200 developers have contributed to the project. Some of them are from well-known companies like Intel, Facebook, IBM, Netflix&#8230;<\/span><\/p><p><span style=\"font-weight: 400;\">In 2014, Spark officially set a new record in large-scale sorting. It won the Daytona Grey Sort competition by<\/span><b> sorting 100 TB of data in just 23 minutes<\/b><span style=\"font-weight: 400;\">. The previous world record was 72 minutes set by Yahoo using a 2100-node MapReduce Hadoop cluster, while Spark uses only 206 nodes. This means it sorted the same data three times faster using ten times fewer machines.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Furthermore, while there is no official petabyte sorting competition, Spark goes even further by sorting 1 PB of data, which is equivalent to 10 trillion records, on 190 machines in less than four hours.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">This was one of the <\/span><b>first petabyte-scale sorts<\/b><span style=\"font-weight: 400;\"> ever done in a public cloud. Achieving this benchmark marks a significant milestone for the Spark project. It proves that Spark is delivering on its promise to serve as <\/span><b>a faster, more scalable engine<\/b><span style=\"font-weight: 400;\"> for processing data of all sizes, from GBs to TBs even going to PBs.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bd677c7 elementor-widget elementor-widget-spacer\" data-id=\"bd677c7\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-14c53e3 e-flex e-con-boxed e-con\" data-id=\"14c53e3\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-df8bc17 elementor-widget elementor-widget-heading\" data-id=\"df8bc17\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Apache Spark: the largest open source Big Data project\n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-256e81d elementor-widget elementor-widget-text-editor\" data-id=\"256e81d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Originally developed at UC Berkeley in 2009, Apache Spark is a unified analytical engine for Big Data and <\/span><span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/datascientest.com\/en\/machine-learning-what-is-it-and-why-does-it-change-the-world\">Machine Learning<\/a><\/strong><\/span><span style=\"font-weight: 400;\">. The tool is distinguished by its impressive speed and ease of use.<\/span><\/p><p><span style=\"font-weight: 400;\">Since its launch, <\/span><b>Apache Spark has been adopted by many companies<\/b><span style=\"font-weight: 400;\"> in a wide variety of industries. Internet giants like Netflix, Yahoo and eBay have deployed Spark and are processing multiple petabytes of data on clusters of over 8,000 nodes.<\/span><\/p><p><span style=\"font-weight: 400;\">In just a few years, Apache Spark has quickly become the largest open source <\/span><b>Big Data project<\/b><span style=\"font-weight: 400;\">. It has over 1000 contributors from more than 250 organizations.<\/span><\/p><p><span style=\"font-weight: 400;\">This 100% open source project is hosted by the Apache Software Foundation. However, Apache Spark, Spark and the Spark logo are trademarks of the ASF.<\/span><\/p><p><span style=\"font-weight: 400;\">As a non-profit organization, the ASF must take precautions about h<\/span><b>ow its trademarks are used<\/b><span style=\"font-weight: 400;\"> by organizations. In particular, it must ensure that its software products are clearly distinguishable from all potential third-party products.<\/span><\/p><p><span style=\"font-weight: 400;\">Companies wishing to provide Apache Spark-based software, services, events, and other products should refer to the foundation&#8217;s trademark policy and FAQ.<\/span><\/p><p><span style=\"font-weight: 400;\">Commercial or open source software products are <\/span><b>not allowed to use Spark in their name<\/b><span style=\"font-weight: 400;\">, except as &#8220;powered by Apache Spark&#8221; or &#8220;for Apache Spark&#8221;. Strict rules must be followed.<\/span><\/p><p><span style=\"font-weight: 400;\">Names derived from &#8220;Spark&#8221; such as &#8220;Sparkly&#8221; are also not allowed, and company names may not include &#8220;Spark&#8221;. Package identifiers may contain the word &#8220;spark&#8221;, but the full name used for the software package must follow the rules.<\/span><\/p><p><span style=\"font-weight: 400;\">Written material must <\/span><b>refer to the project as &#8220;Apache Spark&#8221;<\/b><span style=\"font-weight: 400;\"> in the first mention, and logos derived from Spark&#8217;s are not allowed. Finally, domain names containing &#8220;Spark&#8221; are not allowed without written permission from Apache Spark PMC.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a96a78a elementor-widget elementor-widget-spacer\" data-id=\"a96a78a\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-958776f e-flex e-con-boxed e-con\" data-id=\"958776f\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-9907e6c elementor-widget elementor-widget-heading\" data-id=\"9907e6c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What are the benefits of Spark?\n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-72aa82f elementor-widget elementor-widget-text-editor\" data-id=\"72aa82f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">As you might have guessed, the main advantage of Spark is <\/span><b>its speed<\/b><span style=\"font-weight: 400;\">. Spark was designed from the ground up with performance in mind. It uses in-memory computing and other optimizations for this.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Today it is estimated to be <\/span><b>100 times faster than Hadoop<\/b><span style=\"font-weight: 400;\"> for data processing, uses fewer resources than Hadoop and has a simpler programming model.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Developers mainly highlight the speed of the product in terms of task execution compared to MapReduce.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Spark is also known for its <\/span><b>ease of use<\/b><span style=\"font-weight: 400;\"> and <\/span><b>sophisticated analytics<\/b><span style=\"font-weight: 400;\">. Indeed, it has easy-to-use APIs to work on large data sets.\u00a0\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">In addition, Spark has some versatility. It has software for processing data in streams, a graph processing system. It also allows you to develop applications in Java, Scala, Python and R in a simplified way as well as to perform SQL queries.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">The analysis engine includes numerous high-level libraries that support SQL queries, streaming data, machine learning and graph processing. These standard libraries allow developers to be <\/span><b>more productive<\/b><span style=\"font-weight: 400;\">. They can easily be combined in the same application to create complex workflows.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Finally, spark achieves high performance for batch and streaming data with a DAG scheduler, a query optimizer and a physical execution engine.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-75c55d3 elementor-widget elementor-widget-spacer\" data-id=\"75c55d3\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-43ed282 e-flex e-con-boxed e-con\" data-id=\"43ed282\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-524463d elementor-widget elementor-widget-heading\" data-id=\"524463d\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">The differences between Spark and MapReduce<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7690acc elementor-widget elementor-widget-text-editor\" data-id=\"7690acc\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Let&#8217;s quickly define what MapReduce is:<\/span><\/p><p><span style=\"font-weight: 400;\">It is a programming model <\/span><b>launched by Google<\/b><span style=\"font-weight: 400;\">. MapReduce allows the manipulation of large amounts of data. To process them, it distributes them in a cluster of machines.\u00a0<\/span><\/p><p><b>MapReduce<\/b><span style=\"font-weight: 400;\"> is very popular with companies with large data processing centers, such as Amazon or Facebook. Various frameworks have been created to implement it. The best known is Hadoop, developed by <\/span><span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/www.apache.org\/\">Apache Software Foundation<\/a><\/strong><\/span><span style=\"font-weight: 400;\">.<\/span><\/p><p><span style=\"font-weight: 400;\">Moreover, with <\/span><b>MapReduce<\/b><span style=\"font-weight: 400;\">, the specification of the iteration remains the responsibility of the programmer. Processes specific to failure recovery management result in poor performance. Spark uses a very different method. It places the datasets in RAM and avoids the penalty of disk writes.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e765f74 elementor-widget__width-initial elementor-widget elementor-widget-image\" data-id=\"e765f74\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"533\" src=\"https:\/\/datascientest.com\/en\/files\/2023\/02\/gui-g9422e4c54_1280-1024x682.png\" class=\"attachment-large size-large wp-image-166565\" alt=\"Data analytics\" srcset=\"https:\/\/datascientest.com\/en\/files\/2023\/02\/gui-g9422e4c54_1280-1024x682.png 1024w, https:\/\/datascientest.com\/en\/files\/2023\/02\/gui-g9422e4c54_1280-300x200.png 300w, https:\/\/datascientest.com\/en\/files\/2023\/02\/gui-g9422e4c54_1280-768x512.png 768w, https:\/\/datascientest.com\/en\/files\/2023\/02\/gui-g9422e4c54_1280.png 1280w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a0f3d85 elementor-widget elementor-widget-spacer\" data-id=\"a0f3d85\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0144eb0 elementor-widget elementor-widget-text-editor\" data-id=\"0144eb0\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Thus, Spark supports In-memory processing, which increases the performance of\u00a0<b>Big-Data analytics<\/b>\u00a0applications and thus increases speed. It performs all data analysis operations in memory in real time and relies on disks only when memory is not sufficient. In contrast, <strong>Hadoop writes directly to disks<\/strong> after each operation and works in stages.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-802e114 elementor-widget elementor-widget-spacer\" data-id=\"802e114\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-a486a08 e-flex e-con-boxed e-con\" data-id=\"a486a08\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b5059d0 elementor-widget elementor-widget-heading\" data-id=\"b5059d0\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Who uses Spark?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-94f2b50 elementor-widget elementor-widget-text-editor\" data-id=\"94f2b50\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Since its release, the unified analytics engine has seen rapid adoption by companies in various industries. Internet stalwarts such as Netflix, Yahoo and eBay have developed Spark on a massive scale.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">Currently, Spark has more than 1200 contributors such as Intel, Facebook, IBM&#8230; and is now the <\/span><b>most important community in the world of Big Data<\/b><span style=\"font-weight: 400;\">.\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">It allows unifying all spark Big Data applications. Spark is also suitable for real-time marketing campaigns, online product recommendations or cybersecurity.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a307090 elementor-widget elementor-widget-spacer\" data-id=\"a307090\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-585559b e-flex e-con-boxed e-con\" data-id=\"585559b\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-010deac elementor-widget elementor-widget-heading\" data-id=\"010deac\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What are the different tools in Spark?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9bddb38 elementor-widget elementor-widget-text-editor\" data-id=\"9bddb38\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Spark SQL<\/b><span style=\"font-weight: 400;\"> allows users to execute SQL queries to change and transform data.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Spark streaming <\/b><span style=\"font-weight: 400;\">offers its user a data processing stream. It uses real-time data.\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Spark graphX<\/b><span style=\"font-weight: 400;\"> processes information from graphs.\u00a0<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><b>Spark MLlib<\/b><span style=\"font-weight: 400;\"> is a machine learning library containing all the classical learning algorithms and utilities such as classification, regression, clustering, collaborative filtering and dimension reduction.\u00a0<\/span><\/li><\/ul><p>\u00a0<\/p><p><span style=\"font-weight: 400;\">The <\/span><b>Apache spark project<\/b><span style=\"font-weight: 400;\"> is still alive and kicking! Many companies worldwide use it on a daily basis. It is an <\/span><b>essential tool <\/b><span style=\"font-weight: 400;\">in the field of Big data and Data Science!\u00a0<\/span><\/p><p><span style=\"font-weight: 400;\">If you are interested in this field, do not hesitate to contact our experts to learn more about <span style=\"text-decoration: underline;\"><strong><a href=\"https:\/\/datascientest.com\/en\/data-courses\">our training courses<\/a><\/strong><\/span> in Data Science and Big Data !<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2b03dc7 elementor-align-center button-principal elementor-widget elementor-widget-button\" data-id=\"2b03dc7\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-md\" href=\"https:\/\/datascientest.com\/en\/appointment\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Book an appointment<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-e0c0940 e-flex e-con-boxed e-con\" data-id=\"e0c0940\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-f2a7792 elementor-widget elementor-widget-html\" data-id=\"f2a7792\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\r\n{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"FAQPage\",\r\n  \"mainEntity\": [{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"What is Apache Spark?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"It all started in 2009. Spark was designed by Matei Zaharia, a Canadian computer scientist, during his PhD at the University of California at Berkeley. Initially, its development is a solution to accelerate the processing of Hadoop systems. Today it is a project of the Apache Foundation. Since 2009, more than 1200 developers have contributed to the project. Some of them are from well-known companies like Intel, Facebook, IBM, Netflix...\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"What are the benefits of Spark?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"As you might have guessed, the main advantage of Spark is its speed. Spark was designed from the ground up with performance in mind. It uses in-memory computing and other optimizations for this. Today it is estimated to be 100 times faster than Hadoop for data processing, uses fewer resources than Hadoop and has a simpler programming model.\"\r\n    }\r\n  },{\r\n    \"@type\": \"Question\",\r\n    \"name\": \"Who uses Spark?\",\r\n    \"acceptedAnswer\": {\r\n      \"@type\": \"Answer\",\r\n      \"text\": \"Since its release, the unified analytics engine has seen rapid adoption by companies in various industries. Internet stalwarts such as Netflix, Yahoo and eBay have developed Spark on a massive scale.  Currently, Spark has more than 1200 contributors such as Intel, Facebook, IBM... and is now the most important community in the world of Big Data.\"\r\n    }\r\n  }]\r\n}\r\n<\/script>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Apache Spark is a unified, ultra-fast analytics engine for large-scale data processing. It enables large-scale analysis through cluster machines. It is mainly dedicated to Big Data and Machine Learning. What is Apache Spark? For the curious, let&#8217;s go back to the creation of Apache Spark! It all started in 2009. Spark was designed by Matei [&hellip;]<\/p>\n","protected":false},"author":63,"featured_media":88946,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2425],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Apache Spark: Understanding its Functions and Benefits<\/title>\n<meta name=\"description\" content=\"Apache Spark is a unified, ultra-fast analytics engine for large-scale data processing. It enables large-scale analysis through cluster machines.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Apache Spark: Understanding its Functions and Benefits\" \/>\n<meta property=\"og:description\" content=\"Apache Spark is a unified, ultra-fast analytics engine for large-scale data processing. It enables large-scale analysis through cluster machines. It is\" \/>\n<meta property=\"og:url\" content=\"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits\" \/>\n<meta property=\"og:site_name\" content=\"Data Science Courses | DataScientest\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/DataScientestEN\" \/>\n<meta property=\"article:published_time\" content=\"2023-02-07T09:09:19+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-10-30T17:26:20+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/datascientest.com\/en\/files\/2021\/08\/illu_apache_spark-28.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1024\" \/>\n\t<meta property=\"og:image:height\" content=\"562\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DataScientest__\" \/>\n<meta name=\"twitter:site\" content=\"@DataScientest__\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"\" \/>\n\t<meta name=\"twitter:label2\" content=\"Estimated reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits#article\",\"isPartOf\":{\"@id\":\"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits\"},\"author\":{\"name\":\"\",\"@id\":\"\"},\"headline\":\"Apache Spark: Understanding its Functions and Benefits\",\"datePublished\":\"2023-02-07T09:09:19+00:00\",\"dateModified\":\"2023-10-30T17:26:20+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits\"},\"wordCount\":1152,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/datascientest.com\/en\/#organization\"},\"articleSection\":[\"Data Science\"],\"inLanguage\":\"en-GB\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits#respond\"]}],\"copyrightYear\":\"2023\",\"copyrightHolder\":{\"@id\":\"https:\/\/datascientest.com\/#organization\"}},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits\",\"url\":\"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits\",\"name\":\"Apache Spark: Understanding its Functions and Benefits\",\"isPartOf\":{\"@id\":\"https:\/\/datascientest.com\/en\/#website\"},\"datePublished\":\"2023-02-07T09:09:19+00:00\",\"dateModified\":\"2023-10-30T17:26:20+00:00\",\"description\":\"Apache Spark is a unified, ultra-fast analytics engine for large-scale data processing. It enables large-scale analysis through cluster machines.\",\"inLanguage\":\"en-GB\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits\"]}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/datascientest.com\/en\/#website\",\"url\":\"https:\/\/datascientest.com\/en\/\",\"name\":\"Data Science Courses | DataScientest\",\"description\":\"Leader in Data Science Courses\",\"publisher\":{\"@id\":\"https:\/\/datascientest.com\/en\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/datascientest.com\/en\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-GB\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/datascientest.com\/en\/#organization\",\"name\":\"DataScientest\",\"url\":\"https:\/\/datascientest.com\/en\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-GB\",\"@id\":\"https:\/\/datascientest.com\/en\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/datascientest.com\/en\/wp-content\/blogs.dir\/9\/files\/2024\/02\/DataScientest_icon_blue-2.png\",\"contentUrl\":\"https:\/\/datascientest.com\/en\/wp-content\/blogs.dir\/9\/files\/2024\/02\/DataScientest_icon_blue-2.png\",\"width\":301,\"height\":301,\"caption\":\"DataScientest\"},\"image\":{\"@id\":\"https:\/\/datascientest.com\/en\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.facebook.com\/DataScientestEN\",\"https:\/\/twitter.com\/DataScientest__\",\"https:\/\/www.linkedin.com\/school\/datascientest\/mycompany\/\",\"https:\/\/www.tiktok.com\/@datascientest\"]},{\"@type\":\"Person\",\"@id\":\"\",\"url\":\"https:\/\/datascientest.com\/en\/author\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Apache Spark: Understanding its Functions and Benefits","description":"Apache Spark is a unified, ultra-fast analytics engine for large-scale data processing. It enables large-scale analysis through cluster machines.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits","og_locale":"en_GB","og_type":"article","og_title":"Apache Spark: Understanding its Functions and Benefits","og_description":"Apache Spark is a unified, ultra-fast analytics engine for large-scale data processing. It enables large-scale analysis through cluster machines. It is","og_url":"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits","og_site_name":"Data Science Courses | DataScientest","article_publisher":"https:\/\/www.facebook.com\/DataScientestEN","article_published_time":"2023-02-07T09:09:19+00:00","article_modified_time":"2023-10-30T17:26:20+00:00","og_image":[{"width":1024,"height":562,"url":"https:\/\/datascientest.com\/en\/files\/2021\/08\/illu_apache_spark-28.png","type":"image\/png"}],"twitter_card":"summary_large_image","twitter_creator":"@DataScientest__","twitter_site":"@DataScientest__","twitter_misc":{"Written by":"","Estimated reading time":"6 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits#article","isPartOf":{"@id":"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits"},"author":{"name":"","@id":""},"headline":"Apache Spark: Understanding its Functions and Benefits","datePublished":"2023-02-07T09:09:19+00:00","dateModified":"2023-10-30T17:26:20+00:00","mainEntityOfPage":{"@id":"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits"},"wordCount":1152,"commentCount":0,"publisher":{"@id":"https:\/\/datascientest.com\/en\/#organization"},"articleSection":["Data Science"],"inLanguage":"en-GB","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits#respond"]}],"copyrightYear":"2023","copyrightHolder":{"@id":"https:\/\/datascientest.com\/#organization"}},{"@type":"WebPage","@id":"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits","url":"https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits","name":"Apache Spark: Understanding its Functions and Benefits","isPartOf":{"@id":"https:\/\/datascientest.com\/en\/#website"},"datePublished":"2023-02-07T09:09:19+00:00","dateModified":"2023-10-30T17:26:20+00:00","description":"Apache Spark is a unified, ultra-fast analytics engine for large-scale data processing. It enables large-scale analysis through cluster machines.","inLanguage":"en-GB","potentialAction":[{"@type":"ReadAction","target":["https:\/\/datascientest.com\/en\/apache-spark-its-functions-and-benefits"]}]},{"@type":"WebSite","@id":"https:\/\/datascientest.com\/en\/#website","url":"https:\/\/datascientest.com\/en\/","name":"Data Science Courses | DataScientest","description":"Leader in Data Science Courses","publisher":{"@id":"https:\/\/datascientest.com\/en\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/datascientest.com\/en\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-GB"},{"@type":"Organization","@id":"https:\/\/datascientest.com\/en\/#organization","name":"DataScientest","url":"https:\/\/datascientest.com\/en\/","logo":{"@type":"ImageObject","inLanguage":"en-GB","@id":"https:\/\/datascientest.com\/en\/#\/schema\/logo\/image\/","url":"https:\/\/datascientest.com\/en\/wp-content\/blogs.dir\/9\/files\/2024\/02\/DataScientest_icon_blue-2.png","contentUrl":"https:\/\/datascientest.com\/en\/wp-content\/blogs.dir\/9\/files\/2024\/02\/DataScientest_icon_blue-2.png","width":301,"height":301,"caption":"DataScientest"},"image":{"@id":"https:\/\/datascientest.com\/en\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/DataScientestEN","https:\/\/twitter.com\/DataScientest__","https:\/\/www.linkedin.com\/school\/datascientest\/mycompany\/","https:\/\/www.tiktok.com\/@datascientest"]},{"@type":"Person","@id":"","url":"https:\/\/datascientest.com\/en\/author"}]}},"_links":{"self":[{"href":"https:\/\/datascientest.com\/en\/wp-json\/wp\/v2\/posts\/166548"}],"collection":[{"href":"https:\/\/datascientest.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/datascientest.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/datascientest.com\/en\/wp-json\/wp\/v2\/users\/63"}],"replies":[{"embeddable":true,"href":"https:\/\/datascientest.com\/en\/wp-json\/wp\/v2\/comments?post=166548"}],"version-history":[{"count":0,"href":"https:\/\/datascientest.com\/en\/wp-json\/wp\/v2\/posts\/166548\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/datascientest.com\/en\/wp-json\/wp\/v2\/media\/88946"}],"wp:attachment":[{"href":"https:\/\/datascientest.com\/en\/wp-json\/wp\/v2\/media?parent=166548"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/datascientest.com\/en\/wp-json\/wp\/v2\/categories?post=166548"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/datascientest.com\/en\/wp-json\/wp\/v2\/tags?post=166548"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}