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Apache Spark Tutorials

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Overview

This course aims to teach learners the fundamentals of Apache Spark, an efficient big data processing framework. By the end of the course, students will be able to set up their Spark environment, understand Spark's architecture, work with dataframes, utilize Spark SQL, connect to various data sources, and create and submit Spark applications. The course primarily focuses on programming in Scala for Spark. The intended audience for this course includes developers, data engineers, and data scientists looking to enhance their big data processing skills using Apache Spark.

Syllabus

Apache Spark Course | Spark Programming in Scala.
Apache Spark-01- Setup your environment.
Apache Spark - 02 - Introduction.
Google Cloud Tutorial - Hadoop | Spark Multinode Cluster | DataProc.
Apache Spark - 03 - Architecture - Part 1.
Apache Spark - 04 - Architecture - Part 2.
Spark Tutorial - Introduction to Dataframes.
Spark Tutorials - Spark Dataframe | Deep dive.
Spark Tutorial - SQL over dataframes.
Spark Tutorial - What's Next in Spark Batch Processing?.
Spark Tutorial - Data Sources | How to load data in Spark.
Spark Tutorial - JDBC Source and Sink.
Spark Tutorial - Cassandra Connector.
Spark Tutorial - Spark SQL | Database and Tables.
Spark Tutorial - Zeppelin | JDBC | Other Clients.
Spark Tutorials - Spark Data Types | Metadata | Functions.
Spark Tutorial - Create | Package | Submit Spark Applications.
Spark Tutorials - Spark Language Selection | Scala vs Python.
Spark Tutorial - Scala and Python UDF in Apache Spark.
Delta Lake for Apache Spark - Why do we need Delta Lake for Spark?.
Delta Lake for apache Spark | How does it work | How to use delta lake | Delta Lake for Spark ACID.

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