PySpark Tutorial 2, Pyspark Installations On Windows,

Опубликовано: 06 Май 2020
на канале: TechLake

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PySpark Tutorial, Pyspark Installations On Windows,#PysparkInstallation, #PysparkTutorial, #Pyspark

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PySpark Installation Steps:

1) install JAV1) install JAVA 1.7 or 1.8

https://www.oracle.com/java/technolog...

2) Install Anaconda

https://repo.anaconda.com/archive/Ana...

3) Install Apache Spark

Download spark and extract with in one of the folder.
create folder with any name and i have created pyspark
then extract spark zip file.

C:\pyspark\ extracted folder "spark-2.4.5-bin-hadoop2.7" here like

C:\pyspark\spark-2.4.5-bin-hadoop2.7\

4) Download winutils.exe file
Download winutils.exe and place into C:\pyspark\spark-2.4.5-bin-hadoop2.7\bin\ folder.

https://github.com/steveloughran/winu...

5) set environment variables.

set JAVA_HOME=C:\Java\jdk1.7.0_80
set SPARK_HOME=C:\pyspark\spark-2.4.5-bin-hadoop2.7
set HADOOP_HOME=C:\pyspark\spark-2.4.5-bin-hadoop2.7
set PATH=C:\pyspark\spark-2.4.5-bin-hadoop2.7\bin;
set PATH=C:\Java\jdk1.7.0_80\bin;
set PATH=C:\Windows\System32;

6) Install jupyter

Click on Windows and search “Anacoda Prompt”.
Open Anaconda prompt and type “python -m pip install findspark”.
This package is necessary to run spark from Jupyter notebook.

Now, from the same Anaconda Prompt, type “jupyter notebook” and hit enter.
This would open a jupyter notebook from your browser. From Jupyter notebookàNewàSelect Python3, as shown below.

7) Open CMD with Admin and run below command for granting access to C:\tmp\hive

winutils.exe chmod -R 777 C:\tmp\hive
winutils.exe ls -F C:\tmp\hive

open anaconda prompt and Type pyspark enter.....

python --version

#import findspark module for Pyspark initialization in Jupyter Notebook.
import findspark

findspark.init()

#import SparkContext
from pyspark import SparkContext

#create SparkContext
sc = SparkContext.getOrCreate()
print("SparkContext :",sc)

Please watch Spark Introduction Video.

   • PySpark Tutorial 1, Introduction To A...

What is Pyspark?
PySpark has been released in order to support the collaboration of Apache Spark and Python, it actually is a Python API for Spark. In addition, PySpark, helps you interface with Resilient Distributed Datasets (RDDs) in Apache Spark and Python programming language. This has been achieved by taking advantage of the Py4j library.

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