What is after Spark?

After Spark 2.0, RDDs are replaced by Dataset, which is strongly-typed like an RDD, but with richer optimizations under the hood. However, we highly recommend you to switch to use Dataset, which has better performance than RDD. See the SQL programming guide to get more information about Dataset.

What is the future of Apache spark?

The future of Spark is one of major proliferation, where businesses of many types and sizes use it for their own big data purposes. In fact, Apache Spark may become a must-have big data tool that’s available through cloud applications, becoming a part of other tools that businesses already use.

What is the next Hadoop?

Kubernetes already surpassed Hadoop Actually, it’s pretty clear where we need to look next: Kubernetes. Kubernetes currently has higher adoption rate than Hadoop had at its peak.

Is Spark still popular?

According to Eric, the answer is yes: “Of course Spark is still relevant, because it’s everywhere. Most data scientists clearly prefer Pythonic frameworks over Java-based Spark.

Should I learn Spark in 2021?

As for whether it’s useful to learn, I’d say yes. But again, you have to have a project with a concrete problem that needs solving and that can be solved in a divide-and-conquer kind of way and a large amount of data for it to make sense to use spark.

Does Spark have a future?

Apache Spark has a bright future. Spark provides the provision to work with the streaming data, has a machine learning library called MlLib, can work on structured and unstructured data, deal with graph, etc. Apache Spark users are also increasing exponentially and there is a huge demand for Spark professionals.

What is new in big data?

No technology has been as revolutionary to big data analytics as machine learning and AI systems. AI is used by organizations of all sizes to optimize and improve their business processes. Emerging forms of data visualization are putting the power of AI-enabled analytics into the hands of even casual business users.

Is Spark still relevant 2021?

What is the next big thing after spark?

Cloud, on-premise, and embedded versions are available. Next Think after Spark would be Flink which would deal with streaming data and paralellism can be achieved much more optimized than batch processing hadoop or spark.

What should I do after spark?

Next Think after Spark would be Flink which would deal with streaming data and paralellism can be achieved much more optimized than batch processing hadoop or spark. That’s the beauty of Quora where you can ask questions that don’t give many options to answer reasonably (yet I could not have resisted to answer it :))

Why do people still use spark for machine learning?

When Spark first hit the scene, it solved a lot of problems that people using Hadoop faced, especially when it came to iteration-heavy workloads. Machine learning began a hype cycle at a somewhat similar time and ML workloads are very well suited for Spark, thereby fueling the Spark fire.