Spark Application

The Apache Spark Application are as fallows.

1Spark supports Machine Learning.

  • Apache Spark is having scalable MLlib(Machine Learning Library) it supports advanced analytics such as clustering, classification and dimensionality reduction.
  • It also used to performs advanve analytics jobs like predictive analysis, customer segmentation and sentiment analysis.
  • Spark is an intelligent technology.

2Spark is used in Fog computing.

  • By the influence of Bigdata concept, Iot(internet of things) becomes one of the most advanced technology and Iot devices generates huge amount of data, it requires parallel processing that is not supported in cloud computing. Therefore Fog computing which decentralizes the data and storage uses Spark streaming as a solution to this problem.

3. Spark is used in Event detection.

  • Due to the Spark streaming feature, It is used in protection systems to keep track of rare and unusual behavior in financial institutions, security organizations, and health organizations.
  • It also used to detect the potential risk.

4. Spark supports in Interactive analysis.

  • Because of this application Spark can process huge variety of data very fastly unlike Mapreduce.
  • It can also process queries without sampling.

5. Spark Supports for Data integration and Data processing.

  • It is used to integrate different data sources and make the results usable for services and applications.
  • It is used to process different data like noisy data,geospatial data and real-time image for parallel, distributed and real time processing.

Spark Application Diagram

 

Figure: Applications of Spark

Conclusion

By glancing all the above Apache Spark Application we can conclude that, The Hadoop processing engine Spark has risen to become one of the hottest big data technologies.

References

https://spark.apache.org/docs/2.2.0/programming-guide.html