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Pyspark Crash Course - Learn Spark, Quickly! - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Pyspark Crash Course - Learn Spark, Quickly! (/Thread-Pyspark-Crash-Course-Learn-Spark-Quickly--266916) |
Pyspark Crash Course - Learn Spark, Quickly! - OneDDL - 12-17-2023 ![]() Free Download Pyspark Crash Course - Learn Spark, Quickly! 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! What you'll learn 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) Requirements Some basic Python knowledge is desirable but not entirely necessary Description 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 Discover ![]() ![]() 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 Homepage Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live No Password - Links are Interchangeable |