MARC details
000 -LEADER |
fixed length control field |
04869nam a22004455i 4500 |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20230419134606.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
200611s2020 xxu| o |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781484257814 |
024 7# - OTHER STANDARD IDENTIFIER |
Standard number or code |
10.1007/978-1-4842-5781-4 |
Source of number or code |
doi |
040 ## - CATALOGING SOURCE |
Modifying agency |
WaSeSS |
Transcribing agency |
AIMIT LIBRARY |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
HF5548.125-5548.6 |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
KJQ |
Source |
bicssc |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
BUS070030 |
Source |
bisacsh |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
KJQ |
Source |
thema |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
005.76821 |
Item number |
ILIR |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Ilijason, Robert. |
9 (RLIN) |
31912 |
245 10 - TITLE STATEMENT |
Title |
Beginning Apache spark using azure databricks : |
Remainder of title |
unleashing large cluster analytics in the cloud / |
Statement of responsibility, etc. |
By Robert Ilijason. |
250 ## - EDITION STATEMENT |
Edition statement |
1st ed. |
Remainder of edition statement |
2022. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. |
Place of publication, distribution, etc. |
London : |
Name of publisher, distributor, etc. |
Apress , |
Date of publication, distribution, etc. |
2022. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
xvii,274p. ; |
Other physical details |
PB |
Dimensions |
26cm. |
347 ## - DIGITAL FILE CHARACTERISTICS |
File type |
text file |
Encoding format |
PDF |
Source |
rda |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Chapter 1: Introduction to Large-Scale Data Analytics -- Chapter 2: Spark and Databricks -- Chapter 3: Getting Started with Databricks -- Chapter 4: Workspaces, Clusters, and Notebooks -- Chapter 5: Getting Data into Databricks -- Chapter 6: Querying Data Using SQL -- Chapter 7: The Power of Python -- Chapter 8: ETL and Advanced Data Wrangling -- Chapter 9: Connecting to and from Afar -- Chapter 10: Running in Production -- Chapter 11: Bits and Pieces. |
506 ## - RESTRICTIONS ON ACCESS NOTE |
Terms governing access |
Requires an SPL library card. |
520 ## - SUMMARY, ETC. |
Summary, etc. |
Analyze vast amounts of data in record time using Apache Spark with Databricks in the Cloud. Learn the fundamentals, and more, of running analytics on large clusters in Azure and AWS, using Apache Spark with Databricks on top. Discover how to squeeze the most value out of your data at a mere fraction of what classical analytics solutions cost, while at the same time getting the results you need, incrementally faster. This book explains how the confluence of these pivotal technologies gives you enormous power, and cheaply, when it comes to huge datasets. You will begin by learning how cloud infrastructure makes it possible to scale your code to large amounts of processing units, without having to pay for the machinery in advance. From there you will learn how Apache Spark, an open source framework, can enable all those CPUs for data analytics use. Finally, you will see how services such as Databricks provide the power of Apache Spark, without you having to know anything about configuring hardware or software. By removing the need for expensive experts and hardware, your resources can instead be allocated to actually finding business value in the data. This book guides you through some advanced topics such as analytics in the cloud, data lakes, data ingestion, architecture, machine learning, and tools, including Apache Spark, Apache Hadoop, Apache Hive, Python, and SQL. Valuable exercises help reinforce what you have learned. What You Will Learn Discover the value of big data analytics that leverage the power of the cloud Get started with Databricks using SQL and Python in either Microsoft Azure or AWS Understand the underlying technology, and how the cloud and Spark fit into the bigger picture See how these tools are used in the real world Run basic analytics, including machine learning, on billions of rows at a fraction of a cost or free This book is for data engineers, data scientists, and cloud architects who want or need to run advanced analytics in the cloud. It is assumed that the reader has data experience, but perhaps minimal exposure to Apache Spark and Azure Databricks. The book is also recommended for people who want to get started in the analytics field, as it provides a strong foundation. Robert Ilijason is a 20-year veteran in the business intelligence (BI) segment. He has worked as a contractor for some of Europe's biggest companies and has conducted large-scale analytics projects within the areas of retail, telecom, banking, government, and more. Robert has seen his share of analytic trends come and go over the years, but unlike most of them, he strongly believes that Apache Spark in the cloud, especially with Azure Databricks, is a game changer. |
538 ## - SYSTEM DETAILS NOTE |
System details note |
Mode of access: World Wide Web. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Getting started with databricks |
9 (RLIN) |
31913 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Querying data using sql |
9 (RLIN) |
31914 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Power of python |
9 (RLIN) |
31915 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Running in production |
9 (RLIN) |
31916 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Bits and pieces |
9 (RLIN) |
31917 |
655 #7 - INDEX TERM--GENRE/FORM |
Genre/form data or focus term |
Electronic books. |
Source of term |
local |
9 (RLIN) |
31918 |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
9 (RLIN) |
31919 |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
O'Reilly (Firm) |
9 (RLIN) |
31920 |
710 20 - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
Serials Solutions |
9 (RLIN) |
31921 |
773 0# - HOST ITEM ENTRY |
Title |
Springer Nature eBook |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Relationship information |
Printed edition: |
International Standard Book Number |
9781484257807 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Relationship information |
Printed edition: |
International Standard Book Number |
9781484257821 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Link text |
View this electronic item in O'Reilly Online Learning: Academic/Public Library Edition. |
Uniform Resource Identifier |
<a href="https://ezproxy.spl.org/login?url=https://learning.oreilly.com/library/view/~/9781484257814/?ar">https://ezproxy.spl.org/login?url=https://learning.oreilly.com/library/view/~/9781484257814/?ar</a> |
Public note |
An e-book available through full-text database. |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Koha item type |
Book |
Edition |
1st ed. |
Call number prefix |
005.76821 ILIR |