However, the unprecedented rise of the in-memory stack has introduced the big data ecosystem to a new alternative for analytics. The MapReduce way of analytics is being replaced by a new approach which allows analytics both within the Hadoop framework and outside of it. Apache Spark is the fresh new face of big data analytics.
Big data enthusiasts have certified Apache Spark as the hottest data compute engine for big data in the world. It is fast ejecting MapReduce and Java from their positions, and job trends are reflecting this change. According to a survey by TypeSafe, 71% of global Java developers are currently evaluating or researching around Spark, and 35% of them have already started to use it. Spark experts are currently in demand, and in the weeks to follow, the number of Spark related job opportunities is only expected to go through the roof.
So, what is it about Apache Spark that makes it appear on top of every CIOs to-do list?
Here are some of the interesting features of Apache Spark:
- Hadoop Integration – Spark can work with files stored in HDFS.
- Spark’s Interactive Shell – Spark is written in Scala, and has its own version of the Scala interpreter.
- Spark’s Analytic Suite – Spark comes with tools for interactive query analysis, large-scale graph processing and analysis and real-time analysis.
- Resilient Distributed Datasets (RDDs) – RDDs are distributed objects that can be cached in-memory, across a cluster of compute nodes. They are the primary data objects used in Spark.
- Distributed Operators – Besides MapReduce, there are many other operators one can use on RDD’s.
Organizations like NASA, Yahoo, and Adobe have committed themselves to Spark. This is what John Tripier, Alliances and Ecosystem Lead at Databricks has to say, “The adoption of Apache Spark by businesses large and small is growing at an incredible rate across a wide range of industries, and the demand for developers with certified expertise is quickly following suit”. There has never been a better time to Learn Spark if you have a background in Hadoop.