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Big Data in Construction. Store and Process Project Data and Big Data. From Excel to MySQL and Spark. ⏱ 1 Hour πŸ“š 8 Lessons

Distributed Data Storage. Quick start guide to MySQL and Spark.
$89.00 $39.00

Description

In this course, we will step by step, using the example of real data, we will go through the main processes related to the topic “Big data and machine learning”.

πŸŽ“ In this part  we will consider the main options for storing big data.

βœ”οΈ In practical lesson we will install the MySQL server on computer and learn how to work and edit MySQL databases.
In the fifth lesson we will take one regular exel table and transfer the information from this table to the MySql server.

βœ”οΈ Then we will install the spark in order to work with datasets in a distributed manner.Then, to process the distributed data, we export the data from MySQL into spark. And with the help of Jupiter Notebook, we prepare the data for visualization of this data.

✏️ In this course, you will be guided through the basics of using:

  • Spark
  • MySQL
  • Jupyter Notebook
  • Spark


πŸ”Ž Topics covered in this course:

πŸ“ Lecture 2. Big Data Storage. Three ways to store digital data.
  • What is big data?
  • What storage options we have today?
  • Public Cloud and Private Cloud.
  • Distribute you data

πŸ“ Lecture 3. MySql. SQL. Introduction. How it works?
  • What is MySQL?
  • How Does MySQL Work?
  • Why is MySQL so Popular?

πŸ“ Lecture 4. Installing and Launching MySQL Workbench. How to Get Started with MySQL Workbench
  • MySQL server setup
  • Initial settings
  • Getting Started with MySQL
πŸ“ Lecture 5. Practice. Excel table into MySql. Import Excel data into a MySQL database.
  • Import Excel data into a MySQL
  • Create a new MySQL table.
  • Most Common Queries.
  • SELECT, DROP, UPDATE query mysql
πŸ“ Lecture 6. Spark. Hadoop. Data’s Distribution. A Storage System for Big Data.
  • What is Hadoop?
  • Spark vs MySql
  • Spark. Analytics engine for big data processing
πŸ“ Lecture 7. Installing and Launching Apache Spark. Download and Get Started.
  • Installing Apache Spark
  • updating PATH environment
  • Getting Started with Spark
  • Launching Apache Spark
πŸ“ Lecture 8. Practice. Connecting Python To The Spark. Get Started with PySpark and Jupyter Notebook
  • Installing Anaconda On Windows
  • Running the Jupyter Notebook
  • Connecting Jupyter notebook to Spark
πŸ“ Lecture 9. Practice. Connecting MySQL with Spark. Export Data from Mysql to Spark.
  • Connecting Jupyter notebook to Spark
  • How to set up PySpark for your Jupyter Notebook
  • Export Data from Mysql to Spark
  • Importing Spark Dataframes from MySQL on Jupyter notebooks

What Will I Learn?

  • What is big data?
  • What storage options we have today?
  • Public Cloud and Private Cloud.
  • Distribute you data
  • What is MySQL?
  • How Does MySQL Work?
  • Why is MySQL so Popular?
  • MySQL server setup
  • MySQL initial settings
  • Getting Started with MySQL
  • Import Excel data into a MySQL
  • Create a new MySQL table
  • Most Common Queries
  • SELECT, DROP, UPDATE query mysql
  • What is Hadoop?
  • Spark vs MySql
  • Spark. Analytics engine for big data processing
  • Installing Apache Spark
  • updating PATH environment
  • Getting Started with Spark
  • Launching Apache Spark
  • Installing Anaconda On Windows
  • Running the Jupyter Notebook
  • Connecting Jupyter notebook to Spark
  • Connecting Jupyter notebook to Spark
  • How to set up PySpark for your Jupyter Notebook
  • Export Data from Mysql to Spark
  • Importing Spark Dataframes from MySQL on Jupyter notebooks

Topics for this course

9 Lessons01h 11m

Introduction

Big Data Storage and MySQL.

Practice. Export Excel worksheet data to a MySQL table

A Storage System for Big Data. Hadoop.

Practice. How Apache Spark makes your slow MySQL queries 10x faster.

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Course Details

  • Level: Beginner
  • Categories: Big DataMachine Learning
  • Total Hour: 01h 11m
  • Total Lessons: 9
  • Last Update: October 30, 2020

Requirements

  • You need only the installed Windows System
  • You do not need any special programming knowledge or theoretical knowledge of Python

Target Audience

  • Beginners who are interested in Big Data and Machine Learning using Python.
  • Who already have Python programming skills but want to practice with a hands-on, real-world data project.
  • This course can be opted by anyone (students, developer, manager) who is interested to learn big data.
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