In this course, you'll learn how to manage big datasets, how to load them into clusters and cloud storage, and how to apply structure to the data so that you can run queries on it using distributed SQL engines like Apache Hive and Apache Impala. You’ll learn how to choose the right data types, storage systems, and file formats based on which tools you’ll use and what performance you need.
제공자:
이 강좌에 대하여
최근 조회 51,651회
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 3개 강좌 중 3번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
초급 단계
완료하는 데 약 20시간 필요
영어
자막: 영어
배울 내용
Use different tools to browse existing databases and tables in big data systems
Use different tools to explore files in distributed big data filesystems and cloud storage
Create and manage big data databases and tables using Apache Hive and Apache Impala
Describe and choose among different data types and file formats for big data systems
귀하가 습득할 기술
Data ManagementDistributed File SystemsCloud StorageBig DataSQL
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 3개 강좌 중 3번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
초급 단계
완료하는 데 약 20시간 필요
영어
자막: 영어
제공자:
Cloudera
At Cloudera, we believe that data can make what is impossible today, possible tomorrow. We empower people to transform complex data into clear and actionable insights. Cloudera delivers an enterprise data cloud for any data, anywhere, from the Edge to AI. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 3시간 필요
Orientation to Data in Clusters and Cloud Storage
완료하는 데 3시간 필요
7개 동영상 (총 56분), 3 개의 읽기 자료, 1 개의 테스트
7개의 동영상
Browsing Tables with Hue7m
Browsing Tables with SQL Utility Statements6m
Browsing HDFS with the Hue File Browser13m
Browsing HDFS from the Command Line9m
Understanding S3 and Other Cloud Storage Platforms6m
Browsing S3 Buckets from the Command Line8m
3개의 읽기 자료
Review and Preparation30m
Instructions for Downloading and Installing the Exercise Environment30m
Troubleshooting the VM5m
1개 연습문제
Week 1 Graded Quiz30m
완료하는 데 5시간 필요
Defining Databases, Tables, and Columns
완료하는 데 5시간 필요
7개 동영상 (총 33분), 12 개의 읽기 자료, 2 개의 테스트
7개의 동영상
Introduction to the CREATE TABLE Statement5m
Using Different Schemas on the Same Data12m
Specifying TBLPROPERTIES2m
Examining, Modifying, and Removing Tables1m
Hive and Impala Interoperability2m
Impala Metadata Refresh3m
12개의 읽기 자료
Creating Databases and Tables with Hue30m
Creating Databases and Tables with SQL15m
Permissions to Create Databases and Tables5m
The ROW FORMAT Clause25m
The STORED AS Clause15m
The LOCATION Clause20m
CREATE TABLE Shortcuts10m
Using Hive SerDes15m
Working with Unstructured and Semi-Structured Data15m
Examining Table Structure10m
Dropping Databases and Tables5m
Modifying Existing Tables35m
2개 연습문제
Week 2 Practice Quiz20m
Week 2 Graded Quiz30m
완료하는 데 3시간 필요
Data Types and File Types
완료하는 데 3시간 필요
5개 동영상 (총 14분), 12 개의 읽기 자료, 2 개의 테스트
5개의 동영상
Overview of Data Types1m
Choosing the Right Data Types4m
Overview of File Types3m
Choosing the Right File Types3m
12개의 읽기 자료
Integer Data Types5m
Decimal Data Types10m
Character String Data Types10m
Other Data Types5m
Examining Data Types10m
Out-of-Range Values5m
Text Files5m
Avro Files5m
Parquet Files5m
ORC Files5m
Other File Types5m
Creating Tables with Avro and Parquet Files20m
2개 연습문제
Week 3 Practice Quiz20m
Week 3 Graded Quiz30m
완료하는 데 5시간 필요
Managing Datasets in Clusters and Cloud Storage
완료하는 데 5시간 필요
8개 동영상 (총 48분), 13 개의 읽기 자료, 3 개의 테스트
8개의 동영상
Refresh Impala's Metadata Cache after Loading Data2m
Loading Files into HDFS with Hue's Table Browser10m
Loading Files into HDFS with Hue's File Browser6m
Loading Files into HDFS from the Command Line8m
Loading Files into S3 from the Command Line10m
Using Hive and Impala to Load Data into Tables3m
Conclusion2m
13개의 읽기 자료
More about HDFS Shell Commands10m
Chaining and Scripting with HDFS Commands5m
HDFS Permissions5m
Other Ways to Load Files into S35m
S3 Permissions10m
Missing Values15m
Character Sets5m
Using Sqoop to Import Data15m
More Sqoop Import Options5m
Using Sqoop to Export Data5m
SQL LOAD DATA Statements10m
SQL INSERT Statements10m
SQL INSERT ... SELECT and CTAS Statements15m
2개 연습문제
Week 4 Practice Quiz20m
Week 4 Graded Quiz30m
검토
MANAGING BIG DATA IN CLUSTERS AND CLOUD STORAGE의 최상위 리뷰
SY 제공2020년 2월 29일
This is Very good course for a beginners, it gives you lots of exercises to practice in vm and course material is Really really good but only thing is you have to read a lot ,
AM 제공2019년 12월 15일
It would have been nice if videos would have been present instead of reading. Also a more deep diving would have been done in concepts like bucketing and indexing.
MA 제공2020년 4월 13일
This is one of the systematic specializations which makes the harder and otherwise overwhelming subject so easy to navigate, follow and learn.
AZ 제공2020년 5월 3일
Although more reading than video, I found readings to be more convenient when you need to get back to a particular lesson and recap something.
Modern Big Data Analysis with SQL 특화 과정 정보
This Specialization teaches the essential skills for working with large-scale data using SQL.
Maybe you are new to SQL and you want to learn the basics. Or maybe you already have some experience using SQL to query smaller-scale data with relational databases. Either way, if you are interested in gaining the skills necessary to query big data with modern distributed SQL engines, this Specialization is for you.
Most courses that teach SQL focus on traditional relational databases, but today, more and more of the data that’s being generated is too big to be stored there, and it’s growing too quickly to be efficiently stored in commercial data warehouses. Instead, it’s increasingly stored in distributed clusters and cloud storage. These data stores are cost-efficient and infinitely scalable.
To query these huge datasets in clusters and cloud storage, you need a newer breed of SQL engine: distributed query engines, like Hive, Impala, Presto, and Drill. These are open source SQL engines capable of querying enormous datasets. This Specialization focuses on Hive and Impala, the most widely deployed of these query engines.
This Specialization is designed to provide excellent preparation for the Cloudera Certified Associate (CCA) Data Analyst certification exam. You can earn this certification credential by taking a hands-on practical exam using the same SQL engines that this Specialization teaches—Hive and Impala.
자주 묻는 질문
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Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
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환불 규정은 어떻게 되나요?
구독하는 경우, 취소해도 요금이 청구되지 않는 7일간의 무료 평가판을 이용할 수 있습니다. 해당 기간이 지난 후에는 환불이 되지 않지만, 언제든 구독을 취소할 수 있습니다. 전체 환불 정책 보기.
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예, Coursera에서는 수업료를 낼 수 없는 학습자를 위해 재정 지원을 제공합니다. 왼쪽에 있는 등록 버튼 아래 재정 지원 링크를 클릭하면 지원할 수 있습니다. 신청서를 작성하라는 메시지가 표시되며 승인되면 알림을 받습니다. 성취 프로젝트를 포함하여 전문 분야의 각 강좌에서 이 단계를 완료해야 합니다. 자세히 알아보기.
What are the hardware and software requirements for the exercise environment?
• Windows, macOS, or Linux operating system (iPads and Android tablets will not work) • 64-bit operating system (32-bit operating systems will not work) • 8 GB RAM or more • 25GB free disk space or more • Intel VT-x or AMD-V virtualization support enabled (on Mac computers with Intel processors, this is always enabled; on Windows and Linux computers, you might need to enable it in the BIOS) • For Windows XP computers only: You must have an unzip utility such as 7-Zip or WinZip installed (Windows XP’s built-in unzip utility will not work)
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