Apache Spark Training in Hyderabad

• Apache Spark has a bright future.. Anyone using hadoop uses apache spark in real time use cases in the industry in any field.
• Very importantly Mapreduse can be achieved far better in apache spark
• Spark can run independently. Apart from that it can run on hadoop 2’s YARN cluster manager, and can read any existing hadoop data.

Apache Spark has a really good future. Apache Spark is a powerful open source engine that provides real-time stream processing, interactive processing, graph processing, in-memory processing as well as batch processing with very fast speed, ease of use and standard interface.

Apache Spark is a fascinating platform for data scientists with use cases spanning across exploratory and operational analytics. Data scientist's square measure exhibiting interest in operating with Spark attributable to its ability to store information resident in memory that helps.

If you are a fresher, then with the basic knowledge from Edureka courses you can land a decent job in the same field.If you are experienced, then I would suggest you to look for opportunities in your current organization, as it is easier than looking outside.

If it is difficult to get opportunity in your current organization, then you can do some POCs on your own. There are several blogs/websites that can help you in this.Practice will make you more sound in any domain. So keep practicing.

We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings for Apache Spark. Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.

Spark Core is the underlying general execution engine for spark platform that all other functionality is built upon. It provides In-Memory computing and referencing datasets in external storage systems.

Before you start proceeding with this tutorial, we assume that you have prior exposure to Scala programming, database concepts, and any of the Linux operating system flavors.

You can use spark without knowing Apache Spark, and develop everything in Python, but you might miss out on some features. ... Apache Spark is number one framework in Big data. To implement any framework, we must have experience of any programming language. Like to implement Hadoop framework, must have Apache Spark experience.

Our course ware is designed to give a hands-on approach to the students in Apache Spark. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.

Nowadays Apache Spark is in high demand and worth big data processing engine. Its run-time processing and 100 x faster speed which sets the tone for things to come in the future. However, Spark has several areas on which it needs to improve to realize its full potential.

• It depends on the Big Data concepts that you know. Say, you are a Hadoop developer - then learning Spark is just like learning another concept for Big Data analysis. It will hardly take a few weeks at max to master the Apache Spark concepts.
• Now if you are not a Hadoop developer or if you have not used Scala language for your programming needs, then it will take a while. You will need to know Hadoop concepts like HDFS, HBase, etc. to understand how Spark will run and then you will need to learn Scala programming for Spark. A 40–50 hour course should sufficent for this.

• Highly compatible with Hadoop.
• Spark is overlapping Hadoop Mapreduce.
• Easier access to Bigdata.
• High market demand of Spark Developer.
• Diverse Nature.
• To make big money.