What is Apache Spark?
Apache Spark is a unified analytics engine for large-scale data processing. The project is being developed by the free community, currently, it is the most active of the Apache projects. Comparing to Hadoop MapReduce, another data processing platform, Spark accelerates the programs operating in memory by more than 100 times, and on drive – by more than 10 times. Furthermore, the code is written faster because here in Spark we have more high-level operators at our disposal. Natively Spark supports Scala, Python, and Java. It is well integrated with the Hadoop ecosystem and data sources.Here we can see the role of Apache spark in Bigdata project.
The Scope of Apache Spark application
Potentially, the coverage of Spark is very extensive. Here is an indicative (but not exhaustive) selection of some practical situations where a high-speed, diverse and volumetric processing of big data is required for which Spark is so well suited
Online Marketing
- ETL
- Creation of analytical reports
- Profiles classification
- Behavior analysis
- Profiles segmentation
- Targeted advertising
- Semantic search systems
Media and Entertainment
- Recommendation systems
- Schedule optimization
- Expansion and retention of the audience
- Targeted advertising
- Content monetization
Government
- Intelligence and cybersecurity
- Felony prediction and prevention
- Weather forecasting
- Tax implementation
Healthcare
- Pharmaceutical drug assessment
- Scientific research
- Data processing of:
- patient records
- CRM
- weather forecasting
- fitness trackers
- demographic data
- research data
- data from devices and sensors
Finance
- Employee surveillance
- Predictive modeling
- Financial markets forecasting
- Auto insurance
- Consumer credit operations
- Loans
Manufacturing
- Behavior analysis
- Creation of analytical reports
- Data processing from devices and sensors
- Targeted advertising
- CRM
- Employee monitoring
Logistics & Mobility
- ETL of sensors data
- Weather forecasting
- Predictive analytics
- Creation of analytical reports
Agricultural
- Weather forecasting
- ETL from
- Soil sensors
- Drones
- Monitoring gadgets
Where is Spark heading?
Spark is a very dynamic platform. That was relevant a year or two ago, now it has been replaced by more optimal components. If you buy a book about Spark, you risk getting outdated knowledge. Because while this book was being written, many changes in Spark happened. For example, there are three APIs for working with data now. They all appeared not immediately, but consistently. Each of these APIs was better than the previous ones. As a result, you often have to work with several of these interfaces in parallel that is a certain disadvantage. I think in the future there will be a single API for all components. Spark is also following the path of strong integration with Machine Learning and Deep Learning.
Conclusion
So, Spark helps to simplify non-trivial tasks related to the high computational load, the processing of big data (both in real time and archived), both structured and unstructured. Spark provides seamless integration of complex features — for example, machine learning and algorithms for working with graphs. Spark carries the processing of Big Data to the masses. Try it in your project – and you will not regret!
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