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Intermediate Apache Spark 3
Duration
3.5
Course
ACC-110
Available Formats
Classroom Training, Online Training
Course Description
Overview
Apache Spark is a powerful, open-source processing engine for big data processing. It is optimized for speed, ease of use, and sophisticated analytics.This hands-on course in Apache Spark is geared for technical business professional who wish to solve real-world data problems using Apache Spark.
This class is taught with Python language and using Jupyter environment. This course covers latest features in Spark version 3.
Objectives
In this course, students will learn:
- ecosystem
- features in Spark3
- Shell
- Data structures (RDD / Dataframe / Dataset)
- SQL
- data formats and Spark
- API
Audience
Developers, Data analysts and business analysts
Prerequisites
- with Big Data use cases and ecosystem
- experience with data warehousing, ETL processing
- knowledge of Python language and Jupyter notebooks is preferred but not mandatory
- with Spark basics is welcome, but not required.
- lab environment will be provided to students, no need to install anything on the laptop
- reasonably modern laptop with unrestricted connection to the Internet. Laptops with overly restrictive VPNs or firewalls may not work properly
- modern browser
Topics
Spark Introduction
- Data stacks, Hadoop, Spark
- new features
- concepts and architecture
- components overview
- tour of Databricks cloud environment
- shell
- web UIs
- dataset – part 1
- Spark shell exploration
- execution
- transformations and actions
- Unstructured data analytics
- overview
- caching mechanisms available in Spark
- memory file systems
- use cases and best practices
- Benchmark of caching performance
- Intro
- structured data (json, CSV) using Dataframes
- schema for Dataframes
- Dataframes, Datasets, Schema
- SQL concepts and overview
- tables and importing datasets
- data using SQL
- various storage formats : JSON / Parquet / ORC
- Query Engine (AQE) (Spark 3 feature)
- querying structured data using SQL; evaluating data formats
- will do multiple workshops along the way to reinforce the concepts
- of Spark APIs in Scala / Python
- cycle of a Spark application
- APIs
- Spark applications on YARN
- Developing and deploying a Spark application
- practices for Spark programming
- pitfalls to watch out for
- optimizers in Spark3
- Tuning Spark queries
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Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
- Learn more about e-Learning
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title
Please take a moment to fill out this form. We will get back to you as soon as possible.
All fields marked with an asterisk (*) are mandatory.