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| Item Details | Price | ||
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Apache Spark - Tutorial
Unlock the power of Apache Spark for data engineering
| star star star star star | 5.0 (9 ratings) |
Instructor: Naresh Kumar Boddupally
Language: English
Enrolled Learners: 162
Validity Period: Lifetime
$72 47% OFF
$38
Description:
This course is designed to provide data engineers with a comprehensive understanding of Apache Spark, a powerful open-source processing engine built around speed, ease of use, and sophisticated analytics. Participants will learn how to optimize data processing tasks and explore how to efficiently process and transform data using Apache Spark.
Key Highlights:
- Master Apache Spark for big data processing
- Explore how to efficiently process and transform data using Apache Spark
- Optimize data processing tasks with Spark
- Hands-on projects and exercises
What you will learn:
- Learn Apache Spark fundamentals
Understand the core concepts and architecture of Apache Spark - Data processing with Spark
Explore how to efficiently process and transform data using Spark - Optimizing Spark applications
Discover techniques to optimize performance and efficiency in Spark applications
| Apache Spark Course Curriculum Walkthrough | |||
| PySpark Course Pre-Intro ppt | Preview | ||
| Apache Spark Course Syllabus (11 pages) | Preview | ||
| PySpark Pre Intro Session (Part-1) 32:00 | Preview | ||
| PySpark Pre Intro Live Q&A Session (Part-2) 24:00 | |||
| Join the WA Community | |||
| [01 WEEK] PySpark Session | |||
| Agenda 4:00 | Preview | ||
| History of Bigdata (Part-1) 14:00 | |||
| Monolithic Vs Distributed Systems (Part-2) 8:00 | |||
| What is Hadoop and Its History (Part-3) 9:00 | |||
| Hadoop Advantages and Disadvantages (Part-4) 6:00 | |||
| What is Apache Spark and its features (Part-5) 7:00 | |||
| Why Apache Spark is faster than MapReduce (Part-6) 3:00 | |||
| Is Apache Spark replacement of Hadoop (Part-7) 2:00 | |||
| Apache Spark Eco System (Part-8) 9:00 | |||
| Spark Context Vs Spark Session (Part-9) 10:00 | |||
| Spark Worker Node-Container-Executor (Part-10) 26:00 | |||
| Spark Worker Node-Container-Executor (Part-11) 8:00 | |||
| What is On Heap Memory (Part-12) 6:00 | |||
| What is Off Heap Memory (Part-13) 9:00 | |||
| What is Garbage Collector (Part-14) 3:00 | |||
| Bonus Q&A 3:00 | |||
| Apache Spark Week-1 Notes | |||
| [02 WEEK] PySpark Session | |||
| Previous Session Recap 12:00 | |||
| Agenda 3:00 | |||
| Types of Spark Execution Modes (Part-1) 7:00 | |||
| Different Types of Cluster Managers (Part-2) 3:00 | |||
| Spark Execution-Standalone Mode (Part-3) 2:00 | |||
| Spark Cluster-Key Components (Part-4) 5:00 | |||
| Spark Runtime Architecture-Cluster Mode (Part-5) 15:00 | |||
| Spark Runtime Architecture-Client Mode (Part-6) 6:00 | |||
| Spark Runtime Architecture-Cluster Mode Vs Client Mode (Part-7) 2:00 | |||
| Spark Driver and Executor Overhead Memory Calculations (Part-8) 19:00 | |||
| Spark Executor Memory Deep Dive (Part-9) 55:00 | |||
| Spark Submit - Different Scenario's (Part-10) 8:00 | |||
| Spark Executor Cores and Memory Calculations (Part-11) 17:00 | |||
| Bonus 1:00 | |||
| Apache Spark Week-2 notes pdf | |||
| [03WEEK] PySpark Session | |||
| Previous Week Recap 9:00 | |||
| Agenda 2:00 | |||
| Fat Executors in Spark (Part-1) 14:00 | Preview | ||
| Thin Executors in Spark (Part-2) 9:00 | |||
| Optimally Sized Executors in Spark (Part-3) 12:00 | |||
| Spark Transformations and Actions (Part-4) 6:00 | |||
| Spark Narrow and Wide Transformations (Part-5) 8:00 | |||
| Spark Application-Jobs-Stages-Tasks (Part-6) 10:00 | |||
| Spark Application-Jobs-Stages-Tasks -Practical Example (Part-7) 9:00 | |||
| History of Apache Spark API’s (Part-8) 11:00 | |||
| Differences Between Spark RDD Vs DataFrame Vs DataSet (Part-9) 4:00 | |||
| Databricks Introduction and its Key features (Part-10) 10:00 | |||
| Bonus Q&A 4:00 | |||
| Apache Spark Week-3 Notes pdf | |||
| [04WEEK] PySpark Session | |||
| Previous Session Recap 10:00 | |||
| Agenda 3:00 | |||
| Databricks Workspace Walkthrough | |||
| Databricks Notebook Magic Commands Overview (Part-1) 18:00 | |||
| DBUtils File System Commands (Part-2) 6:00 | |||
| DBUtils Widget Commands (Part-3) 7:00 | |||
| DBUtils Notebook Commands (Part-4) 10:00 | |||
| Ways of Creating RDD's (Part-5) 11:00 | |||
| Ways of creating of RDD's (Part-6) 4:00 | |||
| Ways of creating DataFrame's (Part-7) 23:00 | |||
| Spark SQL Operations (Part-8) 11:00 | |||
| Temp Vs Global Views in Spark (Part-9) 6:00 | |||
| Data Analysis by using the Spark SQL (Part-10) 9:00 | |||
| Managed Tables Vs External Tables (Part-11) 16:00 | |||
| Lineage Vs DAG in Spark (Part-12) 10:00 | |||
| 04 WEEK Bonus 1:00 | |||
| Apache Spark Week-4 PPT pdf | |||
| Databricks Notebooks | |||
| [05WEEK] PySpark Session | |||
| Previous Session Recap 3:00 | |||
| Agenda 3:00 | |||
| Delta Tables (Part-1) 11:00 | |||
| Data Warehouse (Part-2) 10:00 | |||
| Data Lake (Part-3) 7:00 | |||
| Data Lakehouse (Part-4) 9:00 | |||
| Data Warehouse VS Data Lake Vs Data Lakehouse (Part-5) 4:00 | |||
| Different Ways of Selecting a DataFrame Columns (Part-6) 20:00 | |||
| DataFrame Nested Columns Selection (Part-7) 13:00 | |||
| DataFrame Basic Operations (Part-8) 31:00 | |||
| Regular Expressions and String Functions (Part-9) 20:00 | |||
| Data and Time Functions (Part-10) 6:00 | |||
| Pivot and UnPivot (Part-11) 10:00 | |||
| Bad Records Handling (Part-12) 8:00 | |||
| Repartition Vs Coaleasc (Part-13) 15:00 | |||
| Apache Spark Week-5 PPT pdf | |||
| Databricks Notebooks | |||
| [06WEEK] PySpark Session | |||
| Previous Session Recap 3:00 | |||
| Agenda 2:00 | |||
| Joins in PySpark Theory (Part-1) 14:00 | |||
| Joins in PySpark Practicals (Part-2) | |||
| xxhash64 function theory and practicals (Part-3) 16:00 | |||
| union and union all (Part-4) 5:00 | |||
| RANK-DENSE_RANK-ROW_NUMBER Theory (Part-5) 5:00 | |||
| RANK-DENSE_RANK-ROW_NUMBER Practicals (Part-6) 6:00 | |||
| Lead and Lag Functions - Theory (Part-7) 6:00 | |||
| Lead and Lag Functions - Practicals (Part-8) 6:00 | |||
| Aggregate Functions (Part-9) 3:00 | |||
| Data Masking Schenario-1 (Part-10) 6:00 | |||
| UDF and Data Masking Schenario-2 (Part-11) 5:00 | |||
| UDF and Data Masking Schenario-3 (Part-12) 10:00 | |||
| Apache Spark Week-6 PPT pdf | |||
| 06WEEK databricks notebooks | |||
| [07WEEK] PySpark Session | |||
| Previous Session Recap 2:00 | |||
| 07 WEEK - Agenda 1:00 | |||
| Cache and Persist in Spark - Theory (Part-1) 7:00 | |||
| Cache in Spark- Practical's (Part-2) 28:00 | |||
| Persist in Spark- Practical's (Part-3) 8:00 | |||
| Partitining - Practical's (Part-4) 10:00 | |||
| BroadCastHash Join - Theory and Practical's (Part-5) 33:00 | |||
| SortMerge Join - Theory and Practical's (Part-6) 10:00 | |||
| Full Load Implementation - Practical's (Part-7) 5:00 | |||
| Incremental Load SCD Type-1 - Practical's (Part-8) 7:00 | |||
| Incremental Load SCD Type-2 Implementation Steps (Part-9) 28:00 | |||
| Incremental Load SCD Type-2 Implementation - Practical's (Part-10) 9:00 | |||
| Bonus 1:00 | |||
| PYSPARK_07WEEK_RESOURCES | |||
| [08WEEK] PySpark Session | |||
| Previous Session Recap 2:00 | |||
| PySpark Originals - Agenda 3:00 | |||
| Predicate Pushdown in Spark (Part-1) 12:00 | |||
| Projection Pushdown in Spark (Part-2) 3:00 | |||
| Dynamic Partition Pruning (DPP) in Spark (Part-3) 16:00 | |||
| Static Partition Vs DPP in Spark (Part-4) 8:00 | |||
| Catalyst Optimizer in Spark (Part-5) 17:00 | |||
| Salting Technique in Spark (Part-6) 23:00 | |||
| Adaptive Query Execution (AQE) in Spark - Theory (Part-7) 14:00 | |||
| Adaptive Query Execution (AQE) in Spark - Practical (Part-8) 5:00 | |||
| Accumulators in Spark - Theory and Practical (Part-9) 16:00 | |||
| Broadcast Variables in Spark - Theory and Practical (Part-10) 5:00 | |||
| Bonus Q&A 6:00 | |||
| PYSPARK_08WEEK_RESOURCES | |||
| [09WEEK] PySpark Session | |||
| Previous Session Agenda 1:00 | |||
| Agenda 3:00 | |||
| Spark Structured Streaming With Manual Schema Evaluation - Theory 8:00 | |||
| Spark Structured Streaming Manual Schema Evaluation - Practical 15:00 | |||
| Spark Structured Streaming Automatic Schema Evaluation - Practical 7:00 | |||
| [Min Project] Introduction (Part-1) 15:00 | |||
| [Min Project] Implementation Steps (Part-2) 5:00 | |||
| [Min Project] Infra Setup-Creation of Resource Group and SQL database (Part-3) 9:00 | |||
| [Min Project] Infra Setup-Keyvault-Secret Scope-Secrets Creation (Part-4A) 9:00 | |||
| [Mini Project]-Creating Azure Databricks Workspace (Part-4B) 3:00 | |||
| [Min Project] Setting up source tables in SQL database (Part-5) 6:00 | |||
| [Min Project]-Metadata Table Setup in Databricks (Part-6) 13:00 | |||
| [Mini Project]-Establish JDBC Connection from Databricks to SQL Server (Part-7) 17:00 | |||
| [Mini Project]-Data Full Load Implementation (Part-8) 10:00 | |||
| [Mini Project]-Delta Load SCD Type-1 Implementation (Part-9) 13:00 | |||
| [Mini Project]-Delta Load SCD Type-2 Implementation (Part-10) 7:00 | |||
| [Mini Project]-View Creation in Gold Schema (Part-11) 2:00 | |||
| [Mini Project]-Bonus 1:00 | |||
| PYSPARK_09WEEK_RESOURCES | |||
| Clever Gift | |||
| Goodwill Gesture | |||
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