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Big Dataand Machine Learning. Distributed Data Storage. Quick start guide to MySQL and Spark.
An excellent training about Other It & Software
Store and Process Big Data. Excel, MySQL, Spark.
This course is intended to be an initiation to learn #BigData and #MachineLearning with #Python programming for absolute beginners that have no background in programming. 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”. Since the material turned out to be voluminous, I divided the course into five parts. In this part we will consider the main options for storing big data. 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. 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: SparkMySQLJupyter Notebook Spark Topics covered in this course: 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 dataLecture 3. MySql. SQL. Introduction. How it works?What is MySQL?How Does MySQL Work?Why is MySQL so Popular?Lecture 4. Installing and Launching MySQL Workbench. How to Get Started with MySQL Workbench. MySQL server setupInitial settingsGetting Started with MySQLLecture 5. Practice. Excel table into MySql. Import Excel data into a MySQL database. Import Excel data into a MySQLCreate a new MySQL table. Most Common Queries. SELECT, DROP, UPDATE query mysqlLecture 6. Spark. Hadoop. Data’s Distribution. A Storage System for Big Data. What is Hadoop?Spark vs MySqlSpark. Analytics engine for big data processingLecture 7. Installing and Launching Apache Spark. Download and Get Started. Installing Apache Sparkupdating PATH environmentGetting Started with SparkLaunching Apache SparkLecture 8. Practice. Connecting Python To The Spark. Get Started with PySpark and Jupyter Notebook. Installing Anaconda On WindowsRunning the Jupyter NotebookConnecting Jupyter notebook to SparkLecture 9. Practice. Connecting MySQL with Spark. Export Data from Mysql to Spark. Distributed Computing with Spark. Connecting Jupyter notebook to SparkHow to set up PySpark for your Jupyter NotebookExport Data from Mysql to SparkImporting Spark Dataframes from MySQL on Jupyter notebooksThe course is best-suited for learners who are interested in Big Data and Machine Learning (using Python) or for learners who already have Python programming skills but want to practice with a hands-on, real-world data project can also benefit from this course.
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