{"id":259725,"date":"2024-02-21T04:36:22","date_gmt":"2024-02-21T04:36:22","guid":{"rendered":"https:\/\/imarticus.org\/blog\/?p=259725"},"modified":"2024-07-18T09:30:06","modified_gmt":"2024-07-18T09:30:06","slug":"apache-spark-for-big-data","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/apache-spark-for-big-data\/","title":{"rendered":"Apache Spark for Big Data"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Harnessing the immense power of data has become the cornerstone of business, research and innovation. And this is where Apache\u2019s big data framework comes to the rescue. Apache Software Foundation introduced Spark to boost the computational computing software process of the Hadoop. Spark has its own cluster management that negates its dependency on Hadoop. Spark is not an upgraded version of Hadoop. Hadoop is used as one of the ways to implement Spark. Spark uses Hadoop for storage as it owns cluster management computation.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you are an aspiring Data Scientist, pursuing a <\/span><a href=\"https:\/\/imarticus.org\/postgraduate-program-in-data-science-analytics\/\"><strong>data science course<\/strong><\/a><span style=\"font-weight: 400;\"> will help you gather in-depth knowledge of this open-source distributed processing system. Meanwhile, this article covers the important aspects of Apache Spark, such as benefits and components that will help you build a <\/span><span style=\"font-weight: 400;\">career in data science <\/span><span style=\"font-weight: 400;\">and data analytics. Read through the article to unlock the potential of Apache Spark for big data.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">What is Apache Spark?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Apache Spark is a data processing framework used to perform processing tasks instantly on enormous data sets. It can also give out data processing operations across multiple computer systems, either with the help of other computing tools or on its own. These two qualities of Spark make it stand out in the world of big data. Spark makes it easier to assemble massive computing power. Spark uses an easy-to-use API to reduce the programming burden of developers by minimising the work of distributed computing and big data processing.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Apache Spark: Evolution\u00a0<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">One of the sub-projects of Hadoop, Spark, was developed in 2009 by Matei Zaharia in UC Berkeley\u2019s AMPLab. In 2010, it was open-sourced under a BSD license. In 2013, Spark was donated to the Apache Software Foundation. Apache Spark has now claimed the top position as an Apache project.\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Apache Spark: Benefits<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Below are the features of Apache Spark:\u00a0<\/span><b><\/b><\/p>\n<ul>\n<li aria-level=\"1\"><b>Multi-language support<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Spark&#8217;s built-in APIs in Python, Java, or Scala help write applications in multiple languages.<\/span><\/p>\n<ul>\n<li aria-level=\"1\"><b>Speed<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">An application in the Hadoop cluster can run up to 100 times faster in memory with the help of Spark. When running on disk, an application runs 10 times faster.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The intermediate processing data is stored in the memory.\u00a0<\/span><b><\/b><\/p>\n<ul>\n<li aria-level=\"1\"><b>Advanced Analytics<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">In addition to &#8216;Map&#8217; and &#8216;reduce&#8217;, Spark also supports SQL queries, machine learning (ML), streaming data, and graph algorithms.\u00a0<\/span><b><\/b><\/p>\n<ul>\n<li aria-level=\"1\"><b>Augments the accessibility of big data<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">A recent survey conducted by IBM states that Apache Spark is liable to open up several opportunities for<\/span><a href=\"https:\/\/blog.imarticus.org\/big-data\/\"><span style=\"font-weight: 400;\"> big data<\/span><\/a><span style=\"font-weight: 400;\"> by conducting<\/span><span style=\"font-weight: 400;\"> data science training<\/span><span style=\"font-weight: 400;\"> and<\/span><span style=\"font-weight: 400;\"> data<\/span> <span style=\"font-weight: 400;\">analytics courses<\/span><span style=\"font-weight: 400;\"> for over 1 million aspirants. Hence, the scope for <\/span><span style=\"font-weight: 400;\">becoming a Data Analyst <\/span><span style=\"font-weight: 400;\">will get higher.<\/span><span style=\"font-weight: 400;\">\u00a0<\/span><b><\/b><\/p>\n<ul>\n<li aria-level=\"1\"><b>Apache Spark is dynamic in nature<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Spark has 80 high-level operators for interactive querying. These help develop parallel applications with ease.\u00a0<\/span><b><\/b><\/p>\n<ul>\n<li aria-level=\"1\"><b>Potential to handle challenges<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Apache Spark is designed to mitigate various analytics challenges due to its low-latency in-memory data processing capability.\u00a0<\/span><b><\/b><\/p>\n<ul>\n<li aria-level=\"1\"><b>Spark developers are in demand<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Besides benefiting organisations, Apache Spark holds scope for a <\/span><span style=\"font-weight: 400;\">career in data analytics<\/span><span style=\"font-weight: 400;\"> and data science. The demand for Spark developers is huge in companies. Some companies offer several benefits to attract highly skilled experts in Apache Spark.\u00a0<\/span><b><\/b><\/p>\n<ul>\n<li aria-level=\"1\"><b>Apache Spark is open-source<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">One of the major significance of Apache Spark is that it has an immense open-source community.\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Components of Spark<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">The different components of Spark are discussed below:\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Apache Spark Core<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Spark Core is considered the platform on which all other functionality is built. Hence, this general execution engine underlies the entire distributed processing system. Data Analysts can conduct dataset referencing and in-memory computing in external storage systems thanks to the Spark Core.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Spark Streaming\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Using the fast scheduling ability of Spark Core, Spark Streaming executes streaming analytics. It imports data in small batches and conducts RDD transformations (resilient distributed datasets).\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">GraphX\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">GraphX is a graph processing framework that is distributed on top of Spark. It has an API that is used to express graph computation. It can model the user-defined graphs using Pregel abstraction API. GraphX\u2018s offered runtime also optimises abstraction.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Spark SQL<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">A component on top of Spark Core, Spark SQL, brings in a new data abstraction known as SchemaRDD. It supports structured and semi-structured data.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">MLlib (Machine Learning Library)\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Owing to the distributed memory-based Spark architecture, MLlib acts as a distributed machine learning framework. According to benchmarks, MLlib is done by the developers against the ALS (Alternating Least Squares) implementations<\/span><span style=\"font-weight: 400;\">.\u00a0<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">MLflow (Machine Learning Flow)<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">MLflow is an open-source platform used to handle the life cycle of machine learning. It is not technically considered a part of the Apache Spark project. However, it is a product in the Apache Spark community. The community attempts to amalgamate MLflow with Apache Spark to provide <a href=\"https:\/\/www.databricks.com\/glossary\/mlops\"><strong>MLOps features<\/strong><\/a>. These features include experiment tracking, packaging, model registries, and UDFs that can be imported at Apache Spark scale with much convenience for interference with traditional SQL statements.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Delta Lake<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Like MLflow, Delta Lake is considered a separate project not directly under Apache Spark. Nevertheless, due to its significance, Delta Lake has gained prominence in the Spark ecosystem. Delta Lake eliminates the requirement of a data warehouse separately for BI users.\u00a0<\/span><\/p>\n<h4><span style=\"font-weight: 400;\">Conclusion <\/span><span style=\"font-weight: 400;\">\u00a0<\/span><\/h4>\n<p><span style=\"font-weight: 400;\">The remarkable advantages and components of Apache Spark for big data help promote the operational growth of the companies. Hence, companies look for expert Spark developers to scale up in the business world.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Given the opportunities, opting for a<\/span><span style=\"font-weight: 400;\"> data science certification <\/span><span style=\"font-weight: 400;\">or a <\/span><a href=\"https:\/\/imarticus.org\/postgraduate-program-in-data-science-analytics\/\"><strong>data analytics\u00a0course<\/strong><\/a><span style=\"font-weight: 400;\"> is a prudent choice to stand out in the job market. The <\/span><span style=\"font-weight: 400;\">Postgraduate Programme in Data Science and Analytics <\/span><span style=\"font-weight: 400;\">brought to you by <\/span><a href=\"https:\/\/imarticus.org\/\"><span style=\"font-weight: 400;\">Imarticus Learning <\/span><\/a><span style=\"font-weight: 400;\">is one such course for fresh graduates and career professionals from tech backgrounds. It is a 6-month programme with 10 guaranteed interviews. Head to their website to learn more!<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Harnessing the immense power of data has become the cornerstone of business, research and innovation. And this is where Apache\u2019s big data framework comes to the rescue. Apache Software Foundation introduced Spark to boost the computational computing software process of the Hadoop. Spark has its own cluster management that negates its dependency on Hadoop. Spark [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":264916,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_mo_disable_npp":"","_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[23],"tags":[],"class_list":["post-259725","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analytics"],"acf":[],"aioseo_notices":[],"modified_by":"Imarticus Learning","_links":{"self":[{"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/posts\/259725","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/comments?post=259725"}],"version-history":[{"count":2,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/posts\/259725\/revisions"}],"predecessor-version":[{"id":259728,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/posts\/259725\/revisions\/259728"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/media\/264916"}],"wp:attachment":[{"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/media?parent=259725"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/categories?post=259725"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/imarticus.org\/blog\/wp-json\/wp\/v2\/tags?post=259725"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}