Are you looking for a good framework for Big Data processing? Apache Spark is one of the most popular frameworks of its kind. It is used by large companies such as Amazon and eBay. Is it really so great?
Apache Spark for data analysis
If your company needs to process a massive amount of data and you need a professional solution, you should consider Apache Spark.
This unified analytics engine is one of the most known Apache projects nowadays, and it is used by many enterprises for big data analytics. It is much faster than other solutions of this type. Spark’s got its speed thanks to well written code – performing in-memory processes way faster than other frameworks.
This framework supports Python, Java and Scala. It is an open-source framework for big data processing and its speed is just one of its many features which make it great for data science. But this is not the only application of Apache Spark.
Apache Spark – what can it be used for?
Even complicated tools may become great solutions for your company if you know their requirements and strengths. Among the many services of DS Stream, you’ll find Apache Spark Optimization. We’ll help you take advantage of the full potential of this tool.
Here are some tasks that Apache Spark can perform.
Streaming data is now the most important part of almost any businesses (although this term is mainly associated with video and music streaming services like Spotify, Netflix or Daily Motion).
Companies everywhere need to stream and analyze data in real time to operate and offer high quality services. Apache Spark is a very powerful engine and with it developers don’t need any other tool to accommodate all their processing needs.
Spark can perform really advanced analytics and process machine learning algorithms. Thanks to these capabilities it can be used for predictive intelligence, customer segmentation (for example, for managing marketing campaigns) or sentiment analysis.
Spark consists of many components, but we have to point out that it has a scalable machine learning library. There are really a lot of things that can be done using this library, like, for example, dimensionality reduction. Apache spark is not only fast, but also provides users with high security.
With Apache Spark, getting business intelligence is easier and faster than ever. Imagine a sort of process that allows you to find the answers to your questions in the real world, using the data you possess.
Spark is capable of performing interactive analysis – as it supports many development languages, it can be combined with visualization tools to process and visualize data sets interactively.
The benefits of Apache Spark
All data processing frameworks have their pros and cons. We would like to focus on the benefits of using Apache Spark for Big Data analytics and other tasks.
Spark is admired most for its speed. It is often compared favorably to the other tools for data processing by experts in this matter. Its performance has made it extremely popular among data scientists, who require high speed.
It was said a few years ago that Spark was 100 times faster than Hadoop for in-memory big data processing, and it still remains one of the most frequently chosen tools for data processing.
It is a great, powerful tool for advanced analytics and other tasks. You can take advantage of its capability to support “MAP” and “reduce”, machine learning, data streaming, SQL queries and Graph algorithms. It supports a lot of languages like Python or Java and has many useful libraries.
Its open-source community is another important advantage of Apache Spark. You’ll be able to get advice any time if any questions occur.
Nowadays, many applications are being moved to Spark because it offers developers great efficiency. The experts at DS Stream will be happy to provide your company with the best possible solutions for your industry. Don’t hesitate if you want to ensure your business growth.