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Udemy - Course Cloudera Data Engineer Certification CDP-DE 2026 and Book

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Udemy - Course Cloudera Data Engineer Certification CDP-DE 2026 and Book (Size: 1.7 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Spark (48%)
  1. Module 1 Fundamentals of Spark on Kubernetes with Cloudera Data Engineering.mp4 42.7 MB
  1. Module 1 Fundamentals of Spark on Kubernetes with Cloudera Data Engineering.pdf 203.5 KB
  10. Module 10 Mastering Complex Data Types in Apache Spark.mp4 36 MB
  10. Module 10 Mastering Complex Data Types in Apache Spark.pdf 144.2 KB
  2 - Airflow (10%)
  11. Module 11 Implementing Incremental Extraction in Apache Airflow on Cloudera Data Engineering.pdf 160.6 KB
  11. Module 11 Implementing Incremental Extraction in Apache Airflow on Cloudera Data.mp4 34 MB
  12. Module 12 Orchestrating ETL Pipelines with Apache Airflow in Cloudera Data Engin.mp4 45.1 MB
  12. Module 12 Orchestrating ETL Pipelines with Apache Airflow in Cloudera Data Engineering.pdf 173 KB
  13. Module 13 Automating Data Quality Checks with Apache Airflow in Cloudera Data En.mp4 42.4 MB
  13. Module 13 Automating Data Quality Checks with Apache Airflow in Cloudera Data Engineering.pdf 154 KB
  14. Module 14 Orchestrating Workflows in Cloudera Data Engineering with Apache Airfl.mp4 36.9 MB
  14. Module 14 Orchestrating Workflows in Cloudera Data Engineering with Apache Airflow.pdf 175.8 KB
  15. Module 15 Configuring Airflow Pipelines and Data Passing in Cloudera Data Engine.mp4 38.2 MB
  15. Module 15 Configuring Airflow Pipelines and Data Passing in Cloudera Data Engineering.pdf 157.8 KB
  16. Module 16 Implementing Airflow Operators and Hooks in Cloudera Data Engineering.mp4 40.9 MB
  16. Module 16 Implementing Airflow Operators and Hooks in Cloudera Data Engineering.pdf 167.6 KB
  17. Module 17 Managing Connections and Secrets in CDE Airflow.mp4 32.1 MB
  17. Module 17 Managing Connections and Secrets in CDE Airflow.pdf 163.2 KB
  18. Module 18 Utilizing Dynamic DAG Generation in Cloudera Data Engineering.mp4 40.8 MB
  18. Module 18 Utilizing Dynamic DAG Generation in Cloudera Data Engineering.pdf 160.6 KB
  19. Module 19 Optimizing Airflow in CDE SLAs Alerts and Callbacks.mp4 33.6 MB
  19. Module 19 Optimizing Airflow in CDE SLAs Alerts and Callbacks.pdf 170.6 KB
  3 - Deployment (10%)
  20. Module 20 Basic Tools for Spark Performance Tuning in Cloudera Data Engineering.mp4 35.4 MB
  20. Module 20 Basic Tools for Spark Performance Tuning in Cloudera Data Engineering.pdf 176.4 KB
  21. Module 21 Performance Tuning Optimization Frameworks and Explain Plans.mp4 36 MB
  21. Module 21 Performance Tuning Optimization Frameworks and Explain Plans.pdf 171.5 KB
  22. Module 22 Performance Tuning Understanding and Managing Schema Inference.mp4 38 MB
  22. Module 22 Performance Tuning Understanding and Managing Schema Inference.pdf 178.4 KB
  23. Module 23 Performance Tuning Improving Join Performance in Cloudera Data Platfor.mp4 44.7 MB
  23. Module 23 Performance Tuning Improving Join Performance in Cloudera Data Platform.pdf 194.6 KB
  24. Module 24 Performance Tuning Leveraging Data Caching for Reuse.mp4 35.9 MB
  24. Module 24 Performance Tuning Leveraging Data Caching for Reuse.pdf 179.6 KB
  25. Module 25 Performance Tuning Partitioned and Bucketed Tables.mp4 40 MB
  25. Module 25 Performance Tuning Partitioned and Bucketed Tables.pdf 179.4 KB
  26. Module 26 Performance Tuning Mitigating Data Skew with Salting in CDE.mp4 32.5 MB
  26. Module 26 Performance Tuning Mitigating Data Skew with Salting in CDE.pdf 156.6 KB
  27. Module 27 Spark Performance Tuning Shuffle Partitions and Memory.mp4 35.3 MB
  27. Module 27 Spark Performance Tuning Shuffle Partitions and Memory.pdf 189.7 KB
  28. Module 28 Optimizing File I O Parquet Avro and Storage Strategies.mp4 42.8 MB
  28. Module 28 Optimizing File I O Parquet Avro and Storage Strategies.pdf 166.1 KB
  29. Module 29 Identifying Spark Bottlenecks via Spark UI and Event Logs in CDE.mp4 35.7 MB
  29. Module 29 Identifying Spark Bottlenecks via Spark UI and Event Logs in CDE.pdf 191.3 KB
  30. Module 30 Performance Tuning Predicate Pushdown & Column Projection.mp4 38.3 MB
  30. Module 30 Performance Tuning Predicate Pushdown Column Projection.pdf 177.1 KB
  31. Module 31 Performance Tuning Managing Small Files and Compaction in CDP.mp4 39.3 MB
  31. Module 31 Performance Tuning Managing Small Files and Compaction in CDP.pdf 187.3 KB
  32. Module 32 Programmatic Deployment in CDP Mastering API and CLI.mp4 43.8 MB
  32. Module 32 Programmatic Deployment in CDP Mastering API and CLI.pdf 201 KB
  33. Module 33 Deployment Workflows in Cloudera Data Engineering.mp4 34.8 MB
  33. Module 33 Deployment Workflows in Cloudera Data Engineering.pdf 167.4 KB
  34. Module 34 Implementing CI CD Pipelines for Data Artifacts in CDP.mp4 42.6 MB
  34. Module 34 Implementing CI CD Pipelines for Data Artifacts in CDP.pdf 191.6 KB
  35. Module 35 Managing Secret Storage and Environment Configurations in CDP.mp4 39.1 MB
  35. Module 35 Managing Secret Storage and Environment Configurations in CDP.pdf 168.9 KB
  36. Module 36 Monitoring Workloads in CDP with Prometheus and Grafana.mp4 46.3 MB
  36. Module 36 Monitoring Workloads in CDP with Prometheus and Grafana.pdf 192.5 KB
  4 - Iceberg (10%)
  37. Module 37 Mastering Apache Iceberg in Cloudera Data Platform.mp4 45.6 MB
  37. Module 37 Mastering Apache Iceberg in Cloudera Data Platform.pdf 179 KB
  38. Module 38 Mastering Iceberg Schema and Partition Evolution.mp4 39.4 MB
  38. Module 38 Mastering Iceberg Schema and Partition Evolution.pdf 188.6 KB
  39. Module 39 Implementing Time Travel and Snapshot Maintenance in Iceberg.mp4 35.5 MB
  39. Module 39 Implementing Time Travel and Snapshot Maintenance in Iceberg.pdf 161.5 KB
  40. Module 40 Optimizing Iceberg Tables with Hidden Partitioning.mp4 38.3 MB
  40. Module 40 Optimizing Iceberg Tables with Hidden Partitioning.pdf 196 KB
  5 - Practice Paper for Cloudera Data Engineer Certification
  1. Practice Paper 1.html 165.3 KB
  2. Practice Paper 2.html 169.8 KB
  6 - eBook Download (PDF) format In Resource Section
  41. Download eBook from Resource Section of this Module.mp4 42.7 MB
  41. udemy book.pdf 64.6 MB
  2. Module 2 Mastering Apache Spark DataFrames The Core of Data Engineering.mp4 38.6 MB
  2. Module 2 Mastering Apache Spark DataFrames The Core of Data Engineering.pdf 172.5 KB
  3. Module 3 Mastering Spark Understanding Distributed Processing.mp4 47 MB
  3. Module 3 Mastering Spark Understanding Distributed Processing.pdf 165 KB
  4. Module 4 Spark and Hive Integration Implementing the Hive Warehouse Connector.mp4 37.8 MB
  4. Module 4 Spark and Hive Integration Implementing the Hive Warehouse Connector.pdf 146.7 KB
  5. Module 5 Mastering Spark Distributed Persistence.mp4 48.6 MB
  5. Module 5 Mastering Spark Distributed Persistence.pdf 187.4 KB
  6. Module 6 Mastering Spark Structured Streaming for Real time Data.mp4 47 MB
  6. Module 6 Mastering Spark Structured Streaming for Real time Data.pdf 158.5 KB
  7. Module 7 Implementing Error Handling and Dead Letter Queues in Spark.mp4 45.3 MB
  7. Module 7 Implementing Error Handling and Dead Letter Queues in Spark.pdf 200.9 KB
  8. Module 8 Optimising Spark Broadcast Variables and Accumulators.mp4 40.9 MB
  8. Module 8 Optimising Spark Broadcast Variables and Accumulators.pdf 177.9 KB
  9. Module 9 Mastering Spark Dynamic Resource Allocation.mp4 37.3 MB
  9. Module 9 Mastering Spark Dynamic Resource Allocation.pdf 209.3 KB

Description


Course Cloudera Data Engineer Certification CDP-DE 2026&Book

https://WebToolTip.com

Published 1/2026
Created by HadoopExam Learning Resources
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 41 Lectures ( 5h 4m ) | Size: 1.66 GB

Exam style Q&A covering Spark on Kubernetes, Apache Airflow, Iceberg, Performance Tuning, Pipelines & Product + eBook

What you'll learn
✓ Design reliable data models on Cloudera Data Platform (CDP) using Apache Iceberg with ACID, time-travel, and schema evolution.
✓ Build and optimize Apache Spark pipelines (DataFrame/Spark SQL) on Kubernetes, with correct executor sizing and shuffle strategy.
✓ Implement incremental ETL/CDC patterns and idempotent upserts using Spark MERGE, checkpoints, and watermarking.
✓ Tune Spark jobs for performance: fix skewed joins, enable AQE, prune partitions/columns, and reduce small files via compaction.
✓ Choose effective partitioning, bucketing, and file-size targets for large fact tables to balance cost and speed.
✓ Orchestrate pipelines with Apache Airflow: production-grade DAG design, retries/SLAs, alerts, and pre/post-load data quality checks.
✓ Secure and operate pipelines on CDP with least-privilege access, secrets management, monitoring dashboards, and auditability.
✓ Deploy and promote jobs via the CDP Data Engineering Service (DES) CLI/API, including blue/green and canary releases.
✓ Diagnose failures quickly from Spark UI and Airflow logs; run safe rollbacks and targeted backfills.
✓ Apply real exam patterns for the CDP Data Engineer certification: topic weightings, common traps, and time-saving strategies.
✓ Map business queries to efficient table formats (Parquet vs Iceberg) and choose the right catalog/integration approach.
✓ Measure success with concrete KPIs: wall-clock time, shuffle MB, task p95, data freshness, and DQ pass rates.

Requirements
● No strict prerequisites — this course is interview-style and exam-focused. You can join as a motivated beginner.
● Basic knowledge of SQL (SELECT, JOIN, GROUP BY) and data warehousing terms. (optional)
● Familiarity with Apache Spark concepts (DataFrames, transformations vs. actions). (optional)
● High-level understanding of Apache Airflow (DAGs, retries, alerts) and CI/CD ideas. (optional)
● Comfort reading technical artifacts like Spark UI screenshots or Airflow logs. (optional)

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