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This video on What Is Apache Spark? covers all the basics of Apache Spark that a beginner needs to know. In this introduction to Apache Spark video, we will discuss what is Apache Spark, the history of Spark, Hadoop vs Spark, Spark features, components of Apache Spark, Spark core, Spark SQL, Spark streaming, applications of Spark, etc.

Below topics are explained in this Apache Spark Tutorial:
00.00 Introduction
00:41 History of Spark
01:22 What is Spark?
02:26 Hadoop vs Spark
05:29 Spark Features
08:27 Components of Apache Spark
10:24 Spark Core
11:28 Resilient Distributed Dataset
18:08 Spark SQL
21:28 Spark Streaming
24:57 Spark MLlib
25:54 GraphX
27:20 Spark architecture
32:16 Spark Cluster Managers
33:59 Applications of Spark
36:01 Spark use case
38:02 Conclusion

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Introduction to Apache Spark:
Apache Spark Is an opensource cluster computing framework that was initially developed at UC Berkeley in the AMPLab. As compared to the diskbased, twostage MapReduce of Hadoop, Spark provides up to 100 times faster performance for a few applications with inmemory primitives. This makes it suitable for machine learning algorithms, as it allows programs to load data into the memory of a cluster and query the data constantly. A Spark project contains various components such as Spark Core and Resilient Distributed Datasets or RDDs, Spark SQL, Spark Streaming, Machine Learning Library or Mllib, and GraphX.

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➡ About Post Graduate Program In Data Engineering
This Data Engineering course is ideal for professionals, covering critical topics like the Hadoop framework, Data Processing using Spark, Data Pipelines with Kafka, Big Data on AWS, and Azure cloud infrastructures. This program is delivered via live sessions, industry projects, IBM hackathons, and Ask Me Anything sessions.
✅ Key Features
Post Graduate Program Certificate and Alumni Association membership
Exclusive Master Classes and Ask me Anything sessions by IBM
8X higher live interaction in live Data Engineering online classes by industry experts
Capstone from 3 domains and 14+ Projects with Industry datasets from YouTube, Glassdoor, Facebook etc.
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✅ Skills Covered

RealTime Data Processing
Data Pipelining
Big Data Analytics
Data Visualization
Provisioning data storage services
Apache Hadoop
Ingesting Streaming and Batch Data
Transforming Data
Implementing Security Requirements
Data Protection
Encryption Techniques
Data Governance and Compliance Controls

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