Pyspark Crash Course - Learn Spark, Quickly!

[BaDshaH]

Published 12/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.23 GB | Duration: 2h 1m

Accelerate Your Data Skills: Dive into PySpark!

[b]What you'll learn[/b]
Learn to load data into PySpark dataframes
Learn to wrangle your data to clean, handle nulls & handle duplicates
Learn to create calculated fields, aggregate your data & extract insights
Learn to implement advanced PySpark techniques such as window functions and user-defined functions (UDFs)

[b]Requirements[/b]
Some basic Python knowledge is desirable but not entirely necessary

[b]Description[/b]
Ready to dive into the fascinating world of Apache Spark (PySpark)? This course is your ticket to unraveling the mysteries of Spark, starting from the ground up and zooming all the way into some seriously cool stuff like window functions and user-defined functions (UDFs).What You'll Discoverlaying with Data: Get your hands dirty with Spark SQL and learn how to wield DataFrames like a pro, mastering the art of manipulating, filtering, and crunching data.Next-Level Tricks: Ever heard of window functions or UDFs? We'll guide you through these advanced concepts, empowering you to perform super-smart analytics and craft custom functions for your data.Why This Course Rocks: We're all about making it count! Instead of dragging things out, we're here to give you the essential skills pronto. We believe that having the core knowledge means you can jump right into action. Who's Welcome Hereata wizards (and those aspiring to be one)Tech enthusiasts hungry for big data actionAnyone itching to explore Spark and take their data skills up a notchHow We Roll:Short and Sweet: Bite-sized modules for quick learning bursts.Hands-On Fun: Dive into real-world examples and projects for that practical edge.What's in Store for You: Once you've completed this ride, you'll be armed with a solid Spark foundation. You'll confidently handle data, wield window functions like a champ, and even create your own custom UDFs. Get ready to tackle real-world data puzzles and unearth meaningful insights from big datasets.Ap

Overview
Section 1: Introduction
Lecture 1 Course Intro
Lecture 2 Exploring The Data
Lecture 3 Our Development Environment
Section 2: Basics
Lecture 4 Ingesting Our Data
Lecture 5 Inspecting Our Dataframe
Lecture 6 Creating a custom schema
Lecture 7 Handling Null Values
Lecture 8 Running SQL on our dataframes
Lecture 9 Group by & Aggregation
Lecture 10 Creating Calculated Fields
Lecture 11 Handling Duplicates
Lecture 12 Writing to Files
Section 3: Case Statements (When)
Lecture 13 Case Statements: Section 1
Lecture 14 Case Statements: Section 2
Lecture 15 Case Statements: Section 3
Lecture 16 Case Statements: Section 4
Lecture 17 Case Statement: Challenge
Lecture 18 Case Statement: Solution
Section 4: Window Functions
Lecture 19 Rank Window Function
Lecture 20 Row Number Window Function
Lecture 21 Lead / Lag Window Function
Lecture 22 Sum Window Function
Lecture 23 Window Function Challenge
Lecture 24 Window Function Challenge Solution
Section 5: Filtering Dataframes
Lecture 25 Filtering Dataframes: 1
Lecture 26 Filtering Dataframes: 2
Lecture 27 Filtering Dataframes: 3
Lecture 28 Filtering Dataframes: 4
Section 6: UDFs (User Defined Functions)
Lecture 29 UDFs: 1
Lecture 30 UDFs: 2
Lecture 31 UDF: Challenge
Lecture 32 UDF: Challenge Solution
Section 7: Working With Datetimes
Lecture 33 Working with Datetimes
Lecture 34 Datetime: Challenge
Lecture 35 Datetime: Solution
Section 8: Wrapping Up
Lecture 36 Congratulations!
Lecture 37 Next Steps
Anyone with a desire to learn Apache Spark - to enhance their careers or break into the field of data engineering

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