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33 lines
1.4 KiB
Markdown
33 lines
1.4 KiB
Markdown
# Big Data
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## Prerequisites
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- Basics of Linux File systems.
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- Basic understanding of System Design.
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## What to expect from this course
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This course covers the basics of Big Data and how it has evolved to become what it is today. We will take a look at a few realistic scenarios where Big Data would be a perfect fit. An interesting assignment on designing a Big Data system is followed by understanding the architecture of Hadoop and the tooling around it.
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## What is not covered under this course
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Writing programs to draw analytics from data.
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## Course Content
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### Table of Contents
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1. [Overview of Big Data](https://linkedin.github.io/school-of-sre/big_data/overview/)
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2. [Usage of Big Data techniques](https://linkedin.github.io/school-of-sre/big_data/overview/)
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3. [Evolution of Hadoop](https://linkedin.github.io/school-of-sre/big_data/evolution/)
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4. [Architecture of hadoop](https://linkedin.github.io/school-of-sre/big_data/architecture/)
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1. HDFS
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2. Yarn
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5. [MapReduce framework](https://linkedin.github.io/school-of-sre/big_data/architecture/#mapreduce-framework)
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6. [Other tooling around hadoop](https://linkedin.github.io/school-of-sre/big_data/architecture/#other-tooling-around-hadoop)
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1. Hive
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2. Pig
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3. Spark
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4. Presto
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7. [Data Serialisation and storage](https://linkedin.github.io/school-of-sre/big_data/architecture/#data-serialisation-and-storage)
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