2.79 GB | 25min 35s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
1 -Why Spark Solves Real ETL Problems.mp4 (8.02 MB)
2 -Spark's Role in Data Pipelines.mp4 (9.6 MB)
3 -Spark Jobs, Stages, DAGs - Quick Intro.mp4 (21.59 MB)
1 -What You'll Set Up - Spark + Airflow + HDFS in Docker.mp4 (9.36 MB)
2 -Install WSL2 + Docker.mp4 (27.72 MB)
3 -Create Docker Compose Setup.mp4 (18.83 MB)
4 -One Command Launch Spark, Airflow, HDFS, Jupyter.mp4 (134.66 MB)
5 -Explore Spark UI, Airflow UI, HDFS UI.mp4 (45.49 MB)
6 -Explore HDFS.mp4 (85.02 MB)
7 -Use PySpark Shell.mp4 (30.47 MB)
1 -Load & Explore Files in Jupyter and PySpark Shell.mp4 (108.33 MB)
2 -Build ETL Logic Using DataFrame API (Joins, Transforms, Write).mp4 (141.33 MB)
3 -Perform Same ETL in Spark SQL.mp4 (98.59 MB)
4 -Write Clean PySpark Scripts.mp4 (81.95 MB)
5 -Submit Jobs Using spark-submit.mp4 (36.93 MB)
6 -(Optional)How to Navigate Spark-apps.mp4 (100.06 MB)
1 -Understand Sales ETL Requirement.mp4 (64.89 MB)
2 -Build the Sales ETL Pipeline Using Pyspark Shell.mp4 (180.8 MB)
3 -Create a Reusable PySpark Script.mp4 (99.09 MB)
4 -Dynamic Shell Script for Deployment.mp4 (82.95 MB)
5 -Schedule Daily Run with Cron (Simulate Lightweight Prod).mp4 (78.8 MB)
6 -Wrap-Up and Key Learnings.mp4 (106.43 MB)
1 -Understand Customer ETL Requirement.mp4 (70.55 MB)
2 -Build Pipeline using Jupyter notebook.mp4 (186.06 MB)
3 -Convert Workflow into Pipeline Script.mp4 (107.21 MB)
4 -Create Shell Wrapper script.mp4 (136.55 MB)
5 -Automate Pipeline with Airflow.mp4 (221.99 MB)
6 -Wrap-Up and Lessons Learned.mp4 (38.26 MB)
1 -Why Dev vs Prod Matters - Company Best Practices.mp4 (58.64 MB)
2 -Create Env shell to make Pipeline Dynamic.mp4 (26.87 MB)
3 -Switch Between Dev and Prod.mp4 (226.7 MB)
4 -Your Production-Ready Pipeline Setup.mp4 (43.58 MB)
1 -Real Git Workflows (Dev, QA, Prod).mp4 (117.21 MB)
2 -Simulate Ticket-Based Team Handoffs.mp4 (36.5 MB)
1 -Thank you.mp4 (11.56 MB)]
Screenshot
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DDownload
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