Jumpstart Spark: Your 7-Day Apache Spark Quick Learning
Welcome to the Spark Quick Start course—a rapid and comprehensive dive into the powerhouse that is Apache Spark. If you're eager to harness the capabilities of Spark and kickstart your big data journey, this course is tailored just for you!
Why Spark Quick Start?
In today's fast-paced tech landscape, efficiency and speed are paramount. Our Spark Quick Start course is crafted to equip you with the fundamental skills needed to leverage Apache Spark quickly and effectively. No lengthy tutorials, no exhaustive documentation—just the essential knowledge to get you up and running with Spark in no time.
What You'll Learn:
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Apache Spark Introduction:
- Demystify the world of distributed computing and understand how Spark fits into the big data ecosystem.
- Explore the key features that make Spark the preferred choice for processing large datasets.
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Installation Made Easy:
- Learn how to install Spark in various modes, from standalone to cluster mode.
- Navigate through the installation process effortlessly with step-by-step guidance.
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Spark SQL, DataFrame, and Dataset Magic:
- Unleash the power of Spark SQL for querying structured data seamlessly.
- Dive into DataFrames and Datasets, the versatile abstractions that make Spark data manipulation a breeze.
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Interactive Spark Shell Sessions:
- Get hands-on with Spark through interactive sessions in Spark Shell and PySpark.
- Execute Spark SQL queries, manipulate DataFrames, and harness the full potential of Spark right from your shell.
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Demystifying Parallelization:
- Understand the intricacies of Spark's parallel processing model.
- Grasp how Spark divides and conquers, allowing you to process data in parallel for optimal performance.
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Programming with PySpark and Scala:
- Explore the fundamentals of Spark programming using PySpark for Python enthusiasts.
- Delve into Scala for a seamless integration with Spark, unleashing the full power of the Spark ecosystem.
Course Highlights:
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Quick and Practical:
- Learn the essentials without the fluff. This course is designed for quick, practical application.
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Step-by-Step Tutorials:
- Follow along with step-by-step tutorials for installation and hands-on exercises.
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Real-world Applications:
- Apply your knowledge immediately to real-world scenarios with practical examples.
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Supportive Community:
- Join a community of learners for discussions, problem-solving, and collaboration.
Who Should Enroll?
- Data Analysts, Data Engineers, Data scientists
- Software Developers
- IT Professionals
- Anyone Keen on Fast-Tracking Spark Skills
Transform Your Data Journey—Enroll Now!
Don't miss out on the opportunity to jumpstart your big data journey with Spark Quick Start. Spark the change you want to see in your career—enroll today and fast-track your way to mastering Apache Spark!
Quick Start, Big Impact—Enroll Now!
Satisfaction Guarantee
We're so confident that you'll love this course that we offer a 100% satisfaction guarantee. If you're not happy with the course for any reason, simply contact us within 30 days for a full refund.
Contact Information
Still have questions? Contact us at sales@comrite.com for assistance.
Curriculum
- 7 Sections
- 28 Lessons
- 8h Duration
Apache Spark Introduction
- Introduction to Spark
- Spark clustser and Architecture
- Spark Pros, cons, and typical use cases
Spark Installation Made Easy
- Sparl Cluster type
- Deploy spark using standalone mode
- Install and Running Spark on Kubernets
- Spark on Hadoop YARN
- Run Spark one sample job on Hadoop YARN
- How spark can use the data locality with hadoopy/yarn?
Spark SQL, DataFrame, and Dataset Magic, Interactive Spark Shell Sessions ( Spark-shell, PySpark )
- What are SparkSQL, dataframe, dataset, RRD?
- Spark-shell example: SQL, Dataframe
- Pyspark examples
Demystifying Spark Parallelization
- How spark parallelizes workload?
- About number of Spark RDD partitions and number of Executors in cluster
- How Spark Handles Dataset Bigger than Available Memory ?
- Spark Performance tuning
- How Spark Handles Dataset Bigger than Available Memory in cluster ?
- Spark partition size vs executor memory size
- --num-executors, --executor-cores, and --executor-memory
Spark Programming
- Spark Programming vs using interactive spark shell
- Programming in Python API ( PySpark) - count char in local file and hadoop/hdfs file
- PySpark Example - pi.py ( map/reduce )
- Sample spark application/programming using scala
- Which one to choose Scala or Python?
- Spark streaming: structured streaming and Spark streaming?
- Spark Structured Streaming sample code
Documents
- List of useful documents
Summary
- What we learned
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