#LEARN SCALA CODE#
You can stick to basic language features like if, class, and object, write code that looks exactly like Python, and enjoy the benefits of the Scala ecosystem. You don’t need to “learn Scala” or “learn functional programming” to write Spark code with Scala. They don’t know that Spark code can be written with basic Scala language features that you can learn in a day. Many programmers are terrified of Scala because of its reputation as a super-complex language.More people are familiar with Python, so PySpark is naturally their first choice when using Spark.PySpark is a great option for most workflows. Python is a first class citizen in Spark. PySpark used to be buggy and poorly supported, but that’s not true anymore.Making the right choice is difficult because of common misconceptions like “Scala is 10x faster than Python”, which are completely misleading when comparing Scala Spark and PySpark. It’s hard to switch once you develop core libraries with one language.
Spark lets you write elegant code to run jobs on massive datasets – it’s an amazing technology.Ĭhoosing the right language API is an important decision. This blog post performs a detailed comparison of writing Spark with Scala and Python and helps users choose the language API that’s best for their team.īoth language APIs are great options for most workflows. Scala and Python are the most popular APIs. Apache Spark code can be written with the Scala, Java, Python, or R APIs.
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