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Monitoring and Optimizing Apache Spark Workloads on Databricks

This course explores the Lakehouse architecture and Medallion design for scalable data workflows, focusing on Unity Catalog for secure data governance, access control, and lineage tracking. The curriculum includes building reliable, ACID-compliant pipelines with Delta Lake. You'll examine Spark optimization techniques, such as partitioning, caching, and query tuning, and learn performance monitoring, troubleshooting, and best practices for efficient data engineering and analytics to address real-world challenges.


Languages Available: English | 日本語

Skill Level
Associate
Duration
4h
Prerequisites

- Basic programming knowledge

- Familiarity with Python

- Basic understanding of SQL queries (SELECT, JOIN, GROUP BY)

- Familiarity with data processing concepts

- No prior Spark or Databricks experience required

Outline

Monitoring and Optimizing Apache Spark Workloads on Databricks

  • Apache Spark and Databricks
  • Using Apache Spark with Delta Lake
  • Demo: Introduction to Delta Lake
  • Lab: Introduction to Delta Lake
  • Optimizing Apache Spark
  • Demo: Optimizing Apache Spark
  • Lab: Optimizing Apache Spark

Upcoming Public Classes

Date
Time
Language
Price
Jul 28
01 PM - 05 PM (America/New_York)
English
$750.00
Aug 19
09 AM - 01 PM (Asia/Kolkata)
English
$750.00
Aug 20
09 AM - 01 PM (Europe/Paris)
English
$750.00
Aug 25
09 AM - 01 PM (America/New_York)
English
$750.00
Sep 01
01 PM - 05 PM (Europe/London)
English
$750.00
Sep 03
01 PM - 05 PM (Asia/Kolkata)
English
$750.00
Sep 05
01 PM - 05 PM (America/New_York)
English
$750.00
Oct 07
09 AM - 01 PM (Europe/London)
English
$750.00
Oct 07
01 PM - 05 PM (America/New_York)
English
$750.00
Oct 09
01 PM - 05 PM (Asia/Singapore)
English
$750.00

Public Class Registration

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Upcoming Public Classes

Data Analyst

Data Analysis with Databricks

This course provides a comprehensive introduction to Databricks SQL. Learners will ingest data, write queries, produce visualizations and dashboards, and configure alerts. This course will prepare you to take the Databricks Certified Data Analyst Associate exam.

This course consists of two four-hour modules. 

SQL Analytics on Databricks

In this course, you'll learn how to effectively use Databricks for data analytics, with a specific focus on Databricks SQL. As a Databricks Data Analyst, your responsibilities will include finding relevant data, analyzing it for potential applications, and transforming it into formats that provide valuable business insights. 

You will also understand your role in managing data objects and how to manipulate them within the Databricks Data Intelligence Platform, using tools such as Notebooks, the SQL Editor, and Databricks SQL. 

Additionally, you will learn about the importance of Unity Catalog in managing data assets and the overall platform. Finally, the course will provide an overview of how Databricks facilitates performance optimization and teach you how to access Query Insights to understand the processes occurring behind the scenes when executing SQL analytics on Databricks.

AI/BI for Data Analysts

In this course, you’ll learn how to use the features Databricks provides for business intelligence needs: AI/BI Dashboards and AI/BI Genie. As a Databricks Data Analyst, you will be tasked with creating AI/BI Dashboards and AI/BI Genie Spaces within the platform, managing the access to these assets by stakeholders and necessary parties, and maintaining these assets as they are edited, refreshed, or decommissioned over the course of their lifespan. This course intends to instruct participants on how to design dashboards for business insights, share those with collaborators and stakeholders, and maintain those assets within the platform. Participants will also learn how to utilize AI/BI Genie Spaces to support self-service analytics through the creation and maintenance of these environments powered by the Databricks Data Intelligence Engine.

Languages Available: English | 日本語 | Português BR | 한국어
Paid
8h
Lab
instructor-led
Associate

Questions?

If you have any questions, please refer to our Frequently Asked Questions page.