Apache Spark: Working with external data sources | PySpark Tutorial | Lecture 10
In this lecture, we're going to learn all about how to work with external data sources in Apache Spark(PySpark) where we will learn about user-defined functions and how to implement them and ways to integrate Apache PySpark with external databases like RDBMS(SQL Server, MySQL, Postgre etc) as well as NoSQL databases like MongoDB and Cassandra.
PySpark Jupyter Notebook: https://github.com/ashaypatil11/spark...
Anaconda Distributions Installation link:
https://www.anaconda.com/products/dis...
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PySpark installation steps on MAC: https://sparkbyexamples.com/pyspark/h...
Apache Spark Installation links:
1. Download JDK: https://www.oracle.com/in/java/techno...
2. Download Python: https://www.python.org/downloads/
3. Download Spark: https://spark.apache.org/downloads.html
Environment Variables:
HADOOP_HOME- C:\hadoop
JAVA_HOME- C:\java\jdk
SPARK_HOME- C:\spark\spark-3.3.1-bin-hadoop2
PYTHONPATH- %SPARK_HOME%\python;%SPARK_HOME%\python\lib\py4j-0.10.9-src;%PYTHONPATH%
Required Paths:
%SPARK_HOME%\bin
%HADOOP_HOME%\bin
%JAVA_HOME%\bin
Also check out our full Apache Hadoop course:
• Big Data Hadoop Full Course
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Apache Spark Installation links:
1. Download JDK: https://www.oracle.com/in/java/techno...
2. Download Python: https://www.python.org/downloads/
3. Download Spark: https://spark.apache.org/downloads.html
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Audience
This tutorial has been prepared for professionals/students aspiring to learn deep knowledge of Big Data Analytics using Apache Spark and become a Spark Developer and Data Engineer roles. In addition, it would be useful for Analytics Professionals and ETL developers as well.
Prerequisites
Before proceeding with this full course, it is good to have prior exposure to Python programming, database concepts, and any of the Linux operating system flavors.
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