소장자료
LDR | 00848nam a2200241 a 4500 | ||
001 | 0100825131▲ | ||
005 | 20241105135246▲ | ||
007 | ta▲ | ||
008 | 240124s2024 enka 001 0 eng d▲ | ||
020 | ▼a9781804612583 (pbk.)▲ | ||
020 | ▼a1804612588 (pbk.)▲ | ||
020 | ▼a9781804614327 (ebk.)▲ | ||
020 | ▼a1804614327 (ebk.)▲ | ||
035 | ▼a(KERIS)BIB000017009314▲ | ||
040 | ▼a211043▼c211043▼d221016▲ | ||
082 | 0 | 4 | ▼a005.1▼223▲ |
090 | ▼a005.1▼bT656d▲ | ||
100 | 1 | ▼aTome, Eric.▲ | |
245 | 1 | 0 | ▼aData enginerring with Scala and Spark :▼bbuild streaming and batch... pipelines that process massive amounts of data using Scala /▼cby Eric Tome, Rupam Bhattachiarjee, David Radford.▲ |
260 | ▼aBirmingham, UK :▼bPackt Publishing,▼c2024.▲ | ||
300 | ▼axvi, 283 p. :▼bill. ;▼c24 cm.▲ | ||
336 | ▼atext▼btxt▼2rdacontent▲ | ||
337 | ▼aunmediated▼bn▼2rdamedia▲ | ||
338 | ▼avolume▼bnc▼2rdacarrier▲ | ||
500 | ▼aIncludes index.▲ | ||
520 | ▼aTake your data engineering skills to the next level by learning how to utilize Scala and functional programming to create continuous and scheduled pipelines that ingest, transform, and aggregate data Key Features Transform data into a clean and trusted source of information for your organization using Scala Build streaming and batch-processing pipelines with step-by-step explanations Implement and orchestrate your pipelines by following CI/CD best practices and test-driven development (TDD) Purchase of the print or Kindle book includes a free PDF eBook Book Description Most data engineers know that performance issues in a distributed computing environment can easily lead to issues impacting the overall efficiency and effectiveness of data engineering tasks. While Python remains a popular choice for data engineering due to its ease of use, Scala shines in scenarios where the performance of distributed data processing is paramount. This book will teach you how to leverage the Scala programming language on the Spark framework and use the latest cloud technologies to build continuous and triggered data pipelines. You'll do this by setting up a data engineering environment for local development and scalable distributed cloud deployments using data engineering best practices, test-driven development, and CI/CD. You'll also get to grips with DataFrame API, Dataset API, and Spark SQL API and its use. Data profiling and quality in Scala will also be covered, alongside techniques for orchestrating and performance tuning your end-to-end pipelines to deliver data to your end users. By the end of this book, you will be able to build streaming and batch data pipelines using Scala while following software engineering best practices. What you will learn Set up your development environment to build pipelines in Scala Get to grips with polymorphic functions, type parameterization, and Scala implicits Use Spark DataFrames, Datasets, and Spark SQL with Scala Read and write data to object stores Profile and clean your data using Deequ Performance tune your data pipelines using Scala Who this book is for This book is for data engineers who have experience in working with data and want to understand how to transform raw data into a clean, trusted, and valuable source of information for their organization using Scala and the latest cloud technologies.▲ | ||
650 | 0 | ▼aSoftware engineering.▲ | |
650 | 0 | ▼aProgramming languages (Electronic computers).▲ | |
700 | 1 | ▼aBhattachiarjee, Rupam.▲ | |
700 | 1 | ▼aRadford, David E.▲ |

Data enginerring with Scala and Spark : build streaming and batch... pipelines that process massive amounts of data using Scala
자료유형
국외단행본
서명/책임사항
Data enginerring with Scala and Spark : build streaming and batch... pipelines that process massive amounts of data using Scala / by Eric Tome, Rupam Bhattachiarjee, David Radford.
발행사항
Birmingham, UK : Packt Publishing , 2024.
형태사항
xvi, 283 p. : ill. ; 24 cm.
일반주기
Includes index.
요약주기
Take your data engineering skills to the next level by learning how to utilize Scala and functional programming to create continuous and scheduled pipelines that ingest, transform, and aggregate data Key Features Transform data into a clean and trusted source of information for your organization using Scala Build streaming and batch-processing pipelines with step-by-step explanations Implement and orchestrate your pipelines by following CI/CD best practices and test-driven development (TDD) Purchase of the print or Kindle book includes a free PDF eBook Book Description Most data engineers know that performance issues in a distributed computing environment can easily lead to issues impacting the overall efficiency and effectiveness of data engineering tasks. While Python remains a popular choice for data engineering due to its ease of use, Scala shines in scenarios where the performance of distributed data processing is paramount. This book will teach you how to leverage the Scala programming language on the Spark framework and use the latest cloud technologies to build continuous and triggered data pipelines. You'll do this by setting up a data engineering environment for local development and scalable distributed cloud deployments using data engineering best practices, test-driven development, and CI/CD. You'll also get to grips with DataFrame API, Dataset API, and Spark SQL API and its use. Data profiling and quality in Scala will also be covered, alongside techniques for orchestrating and performance tuning your end-to-end pipelines to deliver data to your end users. By the end of this book, you will be able to build streaming and batch data pipelines using Scala while following software engineering best practices. What you will learn Set up your development environment to build pipelines in Scala Get to grips with polymorphic functions, type parameterization, and Scala implicits Use Spark DataFrames, Datasets, and Spark SQL with Scala Read and write data to object stores Profile and clean your data using Deequ Performance tune your data pipelines using Scala Who this book is for This book is for data engineers who have experience in working with data and want to understand how to transform raw data into a clean, trusted, and valuable source of information for their organization using Scala and the latest cloud technologies.
ISBN
9781804612583 (pbk.) 1804612588 (pbk.) 9781804614327 (ebk.) 1804614327 (ebk.)
청구기호
005.1 T656d
소장정보
예도서예약
서서가에없는책 신고
보보존서고신청
캠캠퍼스대출
우우선정리신청
배자료배달신청
문문자발송
출청구기호출력
학소장학술지 원문서비스
등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 서비스 |
---|
북토크
자유롭게 책을 읽고
느낀점을 적어주세요
글쓰기
느낀점을 적어주세요
청구기호 브라우징
관련 인기대출 도서