What Are Some Good Uses For Apache Spark?


Apache Spark is an open source, in-memory data processing engine. It was originally developed in 2009, at University of California, AMP lab, which was later donated to Apache Software Foundation. 



Apache Spark is quickly gaining momentum not only in the headlines but also in real world adoption. Today, it has grown to the extent that, customers from all the industries are using it to improve their businesses with the HDP. Clients are detecting patterns and proving insight which is changing some facets of life and driving organizational change. 

Apache Spark has grown to become the largest open source community for large data with its own in-memory processing framework.

There are various engines within Hadoop system. Every engines works best for certain cases. Here are some of the uses for Apache Spark:

  • Fog Computing and Apache Spark: Internet of Things- This concept sparks the tech community’s imagination. The Internet of Things embeds device with sensors and client can create an interconnected world. This collects a huge amount of data and delivers new features and application for clients to use in everyday life. IoT expands varieties of machines and sensor data. It is difficult to manage with the current analytics in the cloud. To make it easy Fog compute and Apache Spark are used.

  • Streaming data: Large amount of data is being processed on daily basis. It becomes essential for companies to analyze and stream this large data on daily basis. Spark streaming has the capacity to share this work load.
  • Complex session analysis: This is basically used by networking firms. Spark streaming allows you to detect live sessions. As soon as the user log in into any website, you can analyze the session information and this can be used to update your machine learning models. 
  • Enrich your live data: Spark streaming helps you to enrich your live data with your static data. This helps organizations to conduct real time data analysis. Advertisers use this concept. 
  • Visualized Interactive Analysis: Interactive analysis is the most notable feature of Apache Spark. MapReduce, SQL on Hadoop, Hive or pig are actually too slow for analysis. Apache Spark interfaces with many other languages and is fast enough for interactive analysis. If Spark is combined with visualization tools, complex data set can be visualized interactively.


Today spark is being used by almost every business industry- starting from insurance to internet companies. 

Some of the famous companies that use Spark are as follows:  
  1. Insurance sector: Various insurance companies use Apache Spark’s machine to analyze their reimbursements and all their claims.
  2. Banking sector: Uses Apache Spark’s machine for retail banking and financial products.
  3. Twitter: Uses Apache Spark’s machine to analyze positive and negative sentiments for specific products.
  4. Government sector: Uses Apache Spark’s machine to analyze spending across scientific research, time and geography.
  5. Retail sector: Uses Apache Spark’s machine to analyze the financial status and coupon usage.
  6. Airlines: Uses Apache Spark’s machine for predicting delays in flights.
  7. Health care sector: Uses Apache Spark’s machine to build a Patient health care system.

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