Coursera

Optimizing Spark and Cloud Data Storage for Analytics

Coursera

Optimizing Spark and Cloud Data Storage for Analytics

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深入了解一个主题并学习基础知识。
初级 等级

推荐体验

1 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
深入了解一个主题并学习基础知识。
初级 等级

推荐体验

1 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Optimize Spark job performance through strategic partitioning and caching, achieving 30%+ runtime improvements using data access analysis.

  • Implement transactional data lakes with Delta format, enabling versioning, ACID operations, and schema evolution for reliable datasets.

  • Provision secure cloud data infrastructure using IAM policies, private networks, and encrypted storage following security best practices.

  • Evaluate and benchmark storage formats (Parquet, ORC, Avro) to select optimal solutions for analytical workloads and cost efficiency.

要了解的详细信息

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授课语言:英语(English)
最近已更新!

March 2026

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积累 Data Analysis 领域的专业知识

本课程是 Open source Data Engineering with Spark, dbt & Airflow 专业证书 专项课程的一部分
在注册此课程时,您还会同时注册此专业证书。
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  • 通过实践项目培养工作相关技能
  • 通过 Coursera 获得可共享的职业证书

该课程共有11个模块

You will discover why systematic performance analysis beats random configuration changes and master reading Spark UI metrics to identify bottlenecks.

涵盖的内容

3个视频1篇阅读材料1个作业

You will implement partitioning and caching strategies to achieve measurable performance improvements in distributed data processing.

涵盖的内容

3个视频1篇阅读材料2个作业1个非评分实验室

You will develop foundational skills for analyzing distributed execution plans to identify performance bottlenecks caused by data shuffle and skew patterns in Spark applications.

涵盖的内容

3个视频3篇阅读材料1个作业1个非评分实验室

You will apply advanced optimization strategies to resolve identified performance bottlenecks through partition tuning, broadcast joins, and configuration optimization techniques.

涵盖的内容

1个视频1篇阅读材料3个作业

You will understand why transactional features are essential for data lake reliability, explore the fundamental concepts of ACID transactions and versioning, and learn how to convert existing Parquet tables to transactional Delta format.

涵盖的内容

2个视频1篇阅读材料2个作业

You will execute atomic write and delete operations with conditions, query historical table versions for audit purposes, verify rollback capabilities through version history, and demonstrate mastery through hands-on lab work and comprehensive assessment.

涵盖的内容

2个视频2个作业1个非评分实验室

You will understand fundamental cloud security principles, encryption methods, and access control concepts needed to provision secure data infrastructure using Infrastructure as Code.

涵盖的内容

3个视频1篇阅读材料2个作业

You will implement secure cloud data infrastructure using Terraform, creating encrypted storage with proper access controls and network isolation that demonstrates practical application of security principles.

涵盖的内容

2个视频1篇阅读材料2个作业1个非评分实验室

You will establish foundational understanding of storage format trade-offs and begin evaluating columnar versus row-oriented approaches for analytical workloads.

涵盖的内容

3个视频1篇阅读材料1个作业

You will conduct hands-on performance benchmarking of storage formats and create evidence-based recommendations that mirror professional data engineering decision-making processes.

涵盖的内容

1个视频2篇阅读材料3个作业

You will create a comprehensive data infrastructure optimization project that integrates Spark performance tuning, cloud security provisioning, and storage architecture evaluation. This project synthesizes distributed computing optimization, cloud infrastructure design, and data warehousing principles into a realistic enterprise solution.

涵盖的内容

4篇阅读材料1个作业

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位教师

Professionals from the Industry
376 门课程54,291 名学生

提供方

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人们为什么选择 Coursera 来帮助自己实现职业发展

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自 2018开始学习的学生
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Jennifer J.

自 2020开始学习的学生
''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

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自 2021开始学习的学生
''如果我的大学不提供我需要的主题课程,Coursera 便是最好的去处之一。'

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''学习不仅仅是在工作中做的更好:它远不止于此。Coursera 让我无限制地学习。'

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¹ 本课程的部分作业采用 AI 评分。对于这些作业,将根据 Coursera 隐私声明使用您的数据。