What is the difference between spark vs pyspark?

605 Asked by ashish_1000 in Spark , Asked on Dec 20, 2023

I have been recently assigned a task which is related to processing large-scale data by using Apache Spark. During the workflow, I was confused about choosing between Spark and Pyspark. Highlight for me what are the differences between Spark and Pyspark for data processing and analysis.

Answered by Unnati gautam

In the context of big data analysis or big data Hadoop, the difference between Spark vs Pyspark is minor. Spark is mainly used for the overall framework, on the other hand, the pyspark specifically provides the Python API for Spark. Therefore, the pyspark allows the Python programming language to interact with the spark functionalities well. PySpark generally is a Python library that enables seamless integration with spark distributed computing capabilities.

Here is the basic example given to showcase the difference between Spark and Pyspark:-

Using spark in scala:-

// Spark code in Scala

Val textFile = sc.textFile(“hdfs://path/to/your/file.txt”)

Val counts = textFile.flatMap(line => line. split(“ “))

                     .map(word => (word, 1))

                     .reduceByKey(_ + _)

Counts.saveAsTextFile(“hdfs://path/to/save/wordCountOutput”)

Using Pyspark in Python:- 

# PySpark code in Python

From pyspark import SparkContext

Sc = SparkContext(appName=” WordCount”)

textFile = sc.textFile(“hdfs://path/to/your/file.txt”)

counts = textFile.flatMap(lambda line: line. split(“ “)) 

                 .map(lambda word: (word, 1)) 

                 .reduceByKey(lambda a, b: a + b)

Counts.saveAsTextFile(“hdfs://path/to/save/wordCountOutput”)

Your Answer

Answer (1)

outuvore

If you are familiar with Python and want to leverage the power of Spark without learning a new language, PySpark is a good choice. On the other hand, if you need optimal performance and are able to work with Scala, fnf or Java, Spark is a better choice.

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