Apache Spark with Python : big data with PySpark and Spark /

Saved in:
Bibliographic Details
Author / Creator:Magalhães Bernardo, Pedro, speaker.
Imprint:[Place of publication not identified] : Packt Publishing, 2018.
Description:1 online resource (1 streaming video file (3 hr., 18 min., 17 sec.))
Language:English
Subject:
Format: E-Resource Video
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/13671758
Hidden Bibliographic Details
Varying Form of Title:Title on title screen: Learning Apache Spark with Python
Other authors / contributors:Tao W, author.
Lee, James, author.
Notes:Title from resource description page (Safari, viewed July 1, 2019).
Summary:"This course covers all the fundamentals of Apache Spark with Python and teaches you everything you need to know about developing Spark applications using PySpark, the Python API for Spark. At the end of this course, you will gain in-depth knowledge about Apache Spark and general big data analysis and manipulations skills to help your company to adopt Apache Spark for building big data processing pipeline and data analytics applications. This course covers 10+ hands-on big data examples. You will learn valuable knowledge about how to frame data analysis problems as Spark problems. Together we will learn examples such as aggregating NASA Apache weblogs from different sources; we will explore the price trend by looking at the real estate data in California; we will write Spark applications to find out the median salary of developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how maker spaces are distributed across different regions in the United Kingdom. And much much more."--Resource description page

MARC

LEADER 00000cgm a2200000 i 4500
001 13671758
006 m o c
007 cr cna||||||||
007 vz czazuu
008 190702s2018 xx 199 o vleng d
005 20241126143231.7
035 9 |a (OCLCCM-CC)1107052666 
035 |a (OCoLC)1107052666 
037 |a CL0501000057  |b Safari Books Online 
040 |a UMI  |b eng  |e rda  |e pn  |c UMI  |d OCLCF  |d OCLCQ  |d OCLCO 
049 |a MAIN 
050 4 |a QA76.9.D343 
100 1 |a Magalhães Bernardo, Pedro,  |e speaker. 
245 1 0 |a Apache Spark with Python :  |b big data with PySpark and Spark /  |c Pedro Magalhães Bernardo, Tao W, James Lee. 
246 1 |i Title on title screen:  |a Learning Apache Spark with Python 
264 1 |a [Place of publication not identified] :  |b Packt Publishing,  |c 2018. 
300 |a 1 online resource (1 streaming video file (3 hr., 18 min., 17 sec.)) 
336 |a two-dimensional moving image  |b tdi  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
337 |a video  |b v  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
500 |a Title from resource description page (Safari, viewed July 1, 2019). 
520 |a "This course covers all the fundamentals of Apache Spark with Python and teaches you everything you need to know about developing Spark applications using PySpark, the Python API for Spark. At the end of this course, you will gain in-depth knowledge about Apache Spark and general big data analysis and manipulations skills to help your company to adopt Apache Spark for building big data processing pipeline and data analytics applications. This course covers 10+ hands-on big data examples. You will learn valuable knowledge about how to frame data analysis problems as Spark problems. Together we will learn examples such as aggregating NASA Apache weblogs from different sources; we will explore the price trend by looking at the real estate data in California; we will write Spark applications to find out the median salary of developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how maker spaces are distributed across different regions in the United Kingdom. And much much more."--Resource description page 
630 0 0 |a Spark (Electronic resource : Apache Software Foundation)  |0 http://id.loc.gov/authorities/names/no2015027445 
630 0 7 |a Spark (Electronic resource : Apache Software Foundation)  |2 fast  |0 (OCoLC)fst01938143 
650 0 |a Data mining.  |0 http://id.loc.gov/authorities/subjects/sh97002073 
650 0 |a Python (Computer program language)  |0 http://id.loc.gov/authorities/subjects/sh96008834 
650 0 |a Big data.  |0 http://id.loc.gov/authorities/subjects/sh2012003227 
650 0 |a Electronic data processing.  |0 http://id.loc.gov/authorities/subjects/sh85042288 
650 2 |a Data Mining  |0 https://id.nlm.nih.gov/mesh/D057225 
650 6 |a Exploration de données (Informatique) 
650 6 |a Python (Langage de programmation) 
650 6 |a Données volumineuses. 
650 7 |a Big data.  |2 fast  |0 (OCoLC)fst01892965 
650 7 |a Data mining.  |2 fast  |0 (OCoLC)fst00887946 
650 7 |a Electronic data processing.  |2 fast  |0 (OCoLC)fst00906956 
650 7 |a Python (Computer program language)  |2 fast  |0 (OCoLC)fst01084736 
700 0 |a Tao W,  |e author. 
700 1 |a Lee, James,  |e author. 
856 4 0 |u https://go.oreilly.com/uchicago/library/view/-/9781789133394/?ar  |y O'Reilly 
929 |a oclccm 
999 f f |s 83e8db08-7ea8-4c70-8d2b-866fdd497d00  |i b95c1da3-6960-457e-8e76-6afa13efcda8 
928 |t Library of Congress classification  |a QA76.9.D343  |l Online  |c UC-FullText  |u https://go.oreilly.com/uchicago/library/view/-/9781789133394/?ar  |z O'Reilly  |g ebooks  |i 13814696