Working with PySpark SQL Tables and Views | Managed vs Unmanaged Tables
In this lecture, we're going to learn all about Apache Spark/ PySpark SQL Tables and Views where we will discuss about what are managed vs unmanaged tables in PySpark SQL as well difference between Spark SQL Views and Tables as well as Temporary views and Global Temp Views in PySpark along with hands on tutorial.
Data file: https://github.com/ashaypatil11/spark...
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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