【2022年】十大Apache Spark課程熱門排行推薦與優惠精選！

課程介紹

This course does not require any prior knowledge of Apache Spark or Hadoop. We have taken enough care to explain Spark Architecture and fundamental concepts to help you come up to speed and grasp the content of this course.

About the Course

I am

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哪些人適合這堂課？

• Software Engineers and Architects who are willing to design and develop a Bigdata Engineering Projects using Apache Spark
• Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark

學習目標

• Apache Spark Foundation and Spark Architecture
• Data Engineering and Data Processing in Spark
• Working with Data Sources and Sinks
• Working with Data Frames, Data Sets and Spark SQL
• Using IntelliJ Idea for Spark Development and Debugging
• Unit Testing, Managing Application Logs and Cluster Deployment

課程介紹

UPDATED FOR SPARK 3.0

In this course, we will learn how to write big data applications with Apache Spark 3 and Scala. You’ll write 2000+ lines of Spark code yourself, with guidance, and you will become a rockstar.

This course is for Scala programme

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哪些人適合這堂課？

• Future data scientists
• Programmers getting into the field of Big Data
• Engineers wanting to learn Spark in Scala, its native language

學習目標

• apply Spark big data principles
• practice Spark DataFrames operations with 100+ examples and exercises
• practice type-safe data processing with Spark Datasets
• work with low-level Spark APIs with RDDs
• use Spark SQL for data processing
• migrate data from various data sources, including databases

課程介紹

Get started with the amazing Apache Spark parallel computing framework – this course is designed especially for Java Developers.

If you’re new to Data Science and want to find out about how massive datasets are processed in parallel, then the Java A

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哪些人適合這堂課？

• Anyone who already knows Java and would like to explore Apache Spark
• Anyone new to Data Science who want a fast way to get started, without learning Python, Scala or R!

學習目標

• Use functional style Java to define complex data processing jobs
• Learn the differences between the RDD and DataFrame APIs
• Use an SQL style syntax to produce reports against Big Data sets
• Use Machine Learning Algorithms with Big Data and SparkML
• Connect Spark to Apache Kafka to process Streams of Big Data
• See how Structured Streaming can be used to build pipelines with Kafka

課程介紹

This course does not require any prior knowledge of Apache Spark or Hadoop. We have taken enough care to explain Spark Architecture and fundamental concepts to help you come up to speed and grasp the content of this course.

About the Course

I am

…瞭解更多細節

哪些人適合這堂課？

• Software Engineers and Architects who are willing to design and develop a Bigdata Engineering Projects using Apache Spark
• Programmers and developers who are aspiring to grow and learn Data Engineering using Apache Spark

學習目標

• Apache Spark Foundation and Spark Architecture
• Data Engineering and Data Processing in Spark
• Working with Data Sources and Sinks
• Working with Data Frames and Spark SQL
• Using PyCharm IDE for Spark Development and Debugging
• Unit Testing, Managing Application Logs and Cluster Deployment

課程介紹

CCA 175 Spark and Hadoop Developer is one of the well recognized Big Data certification. This scenario based certification exam demands basic programming using Python or Scala along with Spark and other Big Data technologies.

This comprehensive cou

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哪些人適合這堂課？

• Any IT aspirant/professional willing to learn Big Data and give CCA 175 certification

學習目標

• Entire curriculum of CCA Spark and Hadoop Developer
• HDFS Commands
• Scala Fundamentals
• Core Spark – Transformations and Actions
• Spark SQL and Data Frames

課程介紹

What is this course about:

This course covers all the fundamentals about Apache Spark with Java and teaches you everything you need to know about developing Spark applications with Java. At the end of this course, you will gain in-depth knowledge ab

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哪些人適合這堂課？

• Anyone who want to fully understand how Apache Spark technology works and learn how Apache Spark is being used in the field.
• Software engineers who want to develop Apache Spark 2.0 applications using Spark Core and Spark SQL.
• Data scientists or data engineers who want to advance their career by improving their big data processing skills.

學習目標

• An overview of the architecture of Apache Spark.
• Work with Apache Spark’s primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets.
• Develop Apache Spark 2.0 applications using RDD transformations and actions and Spark SQL.
• Scale up Spark applications on a Hadoop YARN cluster through Amazon’s Elastic MapReduce service.
• Analyze structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding about Spark SQL.
• Share information across different nodes on a Apache Spark cluster by broadcast variables and accumulators.
• Advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs.
• Best practices of working with Apache Spark in the field.

課程介紹

New! Updated for Spark 3.0.0!

“Big Data” analysis is a hot and highly valuable skill. Thing is, “big data” never stops flowing! Spark Streaming is a new and quickly developing technology for processing massive data sets as they are created – why wai

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哪些人適合這堂課？

• Students with some prior programming or scripting ability SHOULD take this course.
• If you’re working for a company with “big data” that is being generated continuously, or hope to work for one, this course is for you.
• Students with no prior software engineering or programming experience should seek an introductory programming course first.

學習目標

• Process massive streams of real-time data using Spark Streaming
• Integrate Spark Streaming with data sources, including Kafka, Flume, and Kinesis
• Use Spark 2’s Structured Streaming API
• Create Spark applications using the Scala programming language
• Output transformed real-time data to Cassandra or file systems
• Integrate Spark Streaming with Spark SQL to query streaming data in real time
• Train machine learning models with streaming data, and use those models for real-time predictions
• Ingest Apache access log data and transform streams of it
• Receive real-time streams of Twitter feeds
• Maintain stateful data across a continuous stream of input data
• Query streaming data across sliding windows of time

課程介紹

Learn how to utilize some of the most valuable tech skills on the market today, Scala and Spark! In this course we will show you how to use Scala and Spark to analyze Big Data.

Scala and Spark are two of the most in demand skills right now, and wit

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哪些人適合這堂課？

• Someone who already knows how to program and is interested in learning Big Data Technologies
• Interested in using Spark with Scala for Machine Learning with Large Data Sets

學習目標

• Use Scala for Programming
• Use Spark 2.0 DataFrames to read and manipulate data
• Use Spark to Process Large Datasets
• Understand hot to use Spark on AWS and DataBricks

課程介紹

New! Updated for Spark 3, more hands-on exercises, and a stronger focus on DataFrames and Structured Streaming.

“Big data” analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark.

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哪些人適合這堂課？

• People with some software development background who want to learn the hottest technology in big data analysis will want to check this out. This course focuses on Spark from a software development standpoint; we introduce some machine learning and data mining concepts along the way, but that’s not the focus. If you want to learn how to use Spark to carve up huge datasets and extract meaning from them, then this course is for you.
• If you’ve never written a computer program or a script before, this course isn’t for you – yet. I suggest starting with a Python course first, if programming is new to you.
• If your software development job involves, or will involve, processing large amounts of data, you need to know about Spark.
• If you’re training for a new career in data science or big data, Spark is an important part of it.

學習目標

• Use DataFrames and Structured Streaming in Spark 3
• Frame big data analysis problems as Spark problems
• Use Amazon’s Elastic MapReduce service to run your job on a cluster with Hadoop YARN
• Install and run Apache Spark on a desktop computer or on a cluster
• Use Spark’s Resilient Distributed Datasets to process and analyze large data sets across many CPU’s
• Implement iterative algorithms such as breadth-first-search using Spark
• Use the MLLib machine learning library to answer common data mining questions
• Understand how Spark SQL lets you work with structured data
• Understand how Spark Streaming lets your process continuous streams of data in real time
• Tune and troubleshoot large jobs running on a cluster
• Share information between nodes on a Spark cluster using broadcast variables and accumulators
• Understand how the GraphX library helps with network analysis problems

課程介紹

New! Completely updated and re-recorded for Spark 3, IntelliJ, Structured Streaming, and a stronger focus on the DataSet API.

“Big data” analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data:

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哪些人適合這堂課？

• Software engineers who want to expand their skills into the world of big data processing on a cluster
• If you have no previous programming or scripting experience, you’ll want to take an introductory programming course first.

學習目標

• Frame big data analysis problems as Apache Spark scripts
• Develop distributed code using the Scala programming language
• Optimize Spark jobs through partitioning, caching, and other techniques
• Build, deploy, and run Spark scripts on Hadoop clusters
• Process continual streams of data with Spark Streaming
• Transform structured data using SparkSQL, DataSets, and DataFrames
• Traverse and analyze graph structures using GraphX
• Analyze massive data set with Machine Learning on Spark