Learning Apache Spark 2 :: process big data with the speed of light! /
Learn about the fastest-growing open source project in the world, and find out how it revolutionizes big data analytics About This Book Exclusive guide that covers how to get up and running with fast data processing using Apache Spark Explore and exploit various possibilities with Apache Spark using...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2017.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Learn about the fastest-growing open source project in the world, and find out how it revolutionizes big data analytics About This Book Exclusive guide that covers how to get up and running with fast data processing using Apache Spark Explore and exploit various possibilities with Apache Spark using real-world use cases in this book Want to perform efficient data processing at real time? This book will be your one-stop solution. Who This Book Is For This guide appeals to big data engineers, analysts, architects, software engineers, even technical managers who need to perform efficient data processing on Hadoop at real time. Basic familiarity with Java or Scala will be helpful. The assumption is that readers will be from a mixed background, but would be typically people with background in engineering/data science with no prior Spark experience and want to understand how Spark can help them on their analytics journey. What You Will Learn Get an overview of big data analytics and its importance for organizations and data professionals Delve into Spark to see how it is different from existing processing platforms Understand the intricacies of various file formats, and how to process them with Apache Spark. Realize how to deploy Spark with YARN, MESOS or a Stand-alone cluster manager. Learn the concepts of Spark SQL, SchemaRDD, Caching and working with Hive and Parquet file formats Understand the architecture of Spark MLLib while discussing some of the off-the-shelf algorithms that come with Spark. Introduce yourself to the deployment and usage of SparkR. Walk through the importance of Graph computation and the graph processing systems available in the market Check the real world example of Spark by building a recommendation engine with Spark using ALS. Use a Telco data set, to predict customer churn using Random Forests. In Detail Spark juggernaut keeps on rolling and getting more and more momentum each day. Spark provides key capabilities in the form of Spark SQL, Spark Streaming, Spark ML and Graph X all accessible via Java, Scala, Python and R. Deploying the key capabilities is crucial whether it is on a Standalone framework or as a part of existing Hadoop installation and configuring with Yarn and Mesos. The next part of the journey after installation is using key components, APIs, Clustering, machine learning APIs, data pipelines, parallel programming. It is important to understand why each framework component is key, how widely it is being u... |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| Bibliographie: | Includes bibliographical references. |
| ISBN: | 9781785889585 1785889583 |
Internformat
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-4-EBU-ocn984515083 | ||
| 003 | OCoLC | ||
| 005 | 20241004212047.0 | ||
| 006 | m o d | ||
| 007 | cr unu|||||||| | ||
| 008 | 170427s2017 enka ob 000 0 eng d | ||
| 040 | |a UMI |b eng |e rda |e pn |c UMI |d IDEBK |d TOH |d OCLCF |d TEFOD |d VT2 |d OCLCQ |d UOK |d CEF |d KSU |d WYU |d UAB |d DST |d OCLCO |d OCLCQ |d N$T |d OCLCO |d OCLCL |d OCLCQ | ||
| 020 | |a 9781785889585 |q (electronic bk.) | ||
| 020 | |a 1785889583 |q (electronic bk.) | ||
| 020 | |z 9781785885136 | ||
| 035 | |a (OCoLC)984515083 | ||
| 037 | |a CL0500000852 |b Safari Books Online | ||
| 037 | |a B532ED43-CF76-44DF-8402-5BE45EC31D5C |b OverDrive, Inc. |n http://www.overdrive.com | ||
| 050 | 4 | |a QA76.9.D343 | |
| 082 | 7 | |a 006.312 |2 23 | |
| 049 | |a MAIN | ||
| 100 | 1 | |a Abbasi, Muhammad Asif, |e author. | |
| 245 | 1 | 0 | |a Learning Apache Spark 2 : |b process big data with the speed of light! / |c Muhammad Asif Abbasi. |
| 246 | 3 | |a Learning Apache Spark two | |
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2017. | |
| 300 | |a 1 online resource (1 volume) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | |a Description based on online resource; title from cover (Safari, viewed April 26, 2017). | ||
| 504 | |a Includes bibliographical references. | ||
| 520 | |a Learn about the fastest-growing open source project in the world, and find out how it revolutionizes big data analytics About This Book Exclusive guide that covers how to get up and running with fast data processing using Apache Spark Explore and exploit various possibilities with Apache Spark using real-world use cases in this book Want to perform efficient data processing at real time? This book will be your one-stop solution. Who This Book Is For This guide appeals to big data engineers, analysts, architects, software engineers, even technical managers who need to perform efficient data processing on Hadoop at real time. Basic familiarity with Java or Scala will be helpful. The assumption is that readers will be from a mixed background, but would be typically people with background in engineering/data science with no prior Spark experience and want to understand how Spark can help them on their analytics journey. What You Will Learn Get an overview of big data analytics and its importance for organizations and data professionals Delve into Spark to see how it is different from existing processing platforms Understand the intricacies of various file formats, and how to process them with Apache Spark. Realize how to deploy Spark with YARN, MESOS or a Stand-alone cluster manager. Learn the concepts of Spark SQL, SchemaRDD, Caching and working with Hive and Parquet file formats Understand the architecture of Spark MLLib while discussing some of the off-the-shelf algorithms that come with Spark. Introduce yourself to the deployment and usage of SparkR. Walk through the importance of Graph computation and the graph processing systems available in the market Check the real world example of Spark by building a recommendation engine with Spark using ALS. Use a Telco data set, to predict customer churn using Random Forests. In Detail Spark juggernaut keeps on rolling and getting more and more momentum each day. Spark provides key capabilities in the form of Spark SQL, Spark Streaming, Spark ML and Graph X all accessible via Java, Scala, Python and R. Deploying the key capabilities is crucial whether it is on a Standalone framework or as a part of existing Hadoop installation and configuring with Yarn and Mesos. The next part of the journey after installation is using key components, APIs, Clustering, machine learning APIs, data pipelines, parallel programming. It is important to understand why each framework component is key, how widely it is being u... | ||
| 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 |
| 650 | 0 | |a Electronic data processing |x Distributed processing |x Management. |0 http://id.loc.gov/authorities/subjects/sh2010014266 | |
| 650 | 0 | |a Big data. |0 http://id.loc.gov/authorities/subjects/sh2012003227 | |
| 650 | 0 | |a Machine learning. |0 http://id.loc.gov/authorities/subjects/sh85079324 | |
| 650 | 6 | |a Données volumineuses. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 7 | |a Big data |2 fast | |
| 650 | 7 | |a Electronic data processing |x Distributed processing |x Management |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 758 | |i has work: |a Learning Apache Spark 2 (Text) |1 https://id.oclc.org/worldcat/entity/E39PCXQFfPJfdmKyT9cBhmHMxC |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 856 | 4 | 0 | |l FWS01 |p ZDB-4-EBU |q FWS_PDA_EBU |u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1495816 |3 Volltext |
| 938 | |a ProQuest MyiLibrary Digital eBook Collection |b IDEB |n cis36983548 | ||
| 938 | |a EBSCOhost |b EBSC |n 1495816 | ||
| 994 | |a 92 |b GEBAY | ||
| 912 | |a ZDB-4-EBU | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBU-ocn984515083 |
|---|---|
| _version_ | 1816796927022333952 |
| adam_text | |
| any_adam_object | |
| author | Abbasi, Muhammad Asif |
| author_facet | Abbasi, Muhammad Asif |
| author_role | aut |
| author_sort | Abbasi, Muhammad Asif |
| author_variant | m a a ma maa |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.9.D343 |
| callnumber-search | QA76.9.D343 |
| callnumber-sort | QA 276.9 D343 |
| callnumber-subject | QA - Mathematics |
| collection | ZDB-4-EBU |
| ctrlnum | (OCoLC)984515083 |
| dewey-full | 006.312 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.312 |
| dewey-search | 006.312 |
| dewey-sort | 16.312 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04996cam a2200529 i 4500</leader><controlfield tag="001">ZDB-4-EBU-ocn984515083</controlfield><controlfield tag="003">OCoLC</controlfield><controlfield tag="005">20241004212047.0</controlfield><controlfield tag="006">m o d </controlfield><controlfield tag="007">cr unu||||||||</controlfield><controlfield tag="008">170427s2017 enka ob 000 0 eng d</controlfield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">UMI</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">UMI</subfield><subfield code="d">IDEBK</subfield><subfield code="d">TOH</subfield><subfield code="d">OCLCF</subfield><subfield code="d">TEFOD</subfield><subfield code="d">VT2</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">UOK</subfield><subfield code="d">CEF</subfield><subfield code="d">KSU</subfield><subfield code="d">WYU</subfield><subfield code="d">UAB</subfield><subfield code="d">DST</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">N$T</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCL</subfield><subfield code="d">OCLCQ</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781785889585</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1785889583</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">9781785885136</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)984515083</subfield></datafield><datafield tag="037" ind1=" " ind2=" "><subfield code="a">CL0500000852</subfield><subfield code="b">Safari Books Online</subfield></datafield><datafield tag="037" ind1=" " ind2=" "><subfield code="a">B532ED43-CF76-44DF-8402-5BE45EC31D5C</subfield><subfield code="b">OverDrive, Inc.</subfield><subfield code="n">http://www.overdrive.com</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QA76.9.D343</subfield></datafield><datafield tag="082" ind1="7" ind2=" "><subfield code="a">006.312</subfield><subfield code="2">23</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">MAIN</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Abbasi, Muhammad Asif,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Learning Apache Spark 2 :</subfield><subfield code="b">process big data with the speed of light! /</subfield><subfield code="c">Muhammad Asif Abbasi.</subfield></datafield><datafield tag="246" ind1="3" ind2=" "><subfield code="a">Learning Apache Spark two</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Birmingham, UK :</subfield><subfield code="b">Packt Publishing,</subfield><subfield code="c">2017.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (1 volume) :</subfield><subfield code="b">illustrations</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on online resource; title from cover (Safari, viewed April 26, 2017).</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Learn about the fastest-growing open source project in the world, and find out how it revolutionizes big data analytics About This Book Exclusive guide that covers how to get up and running with fast data processing using Apache Spark Explore and exploit various possibilities with Apache Spark using real-world use cases in this book Want to perform efficient data processing at real time? This book will be your one-stop solution. Who This Book Is For This guide appeals to big data engineers, analysts, architects, software engineers, even technical managers who need to perform efficient data processing on Hadoop at real time. Basic familiarity with Java or Scala will be helpful. The assumption is that readers will be from a mixed background, but would be typically people with background in engineering/data science with no prior Spark experience and want to understand how Spark can help them on their analytics journey. What You Will Learn Get an overview of big data analytics and its importance for organizations and data professionals Delve into Spark to see how it is different from existing processing platforms Understand the intricacies of various file formats, and how to process them with Apache Spark. Realize how to deploy Spark with YARN, MESOS or a Stand-alone cluster manager. Learn the concepts of Spark SQL, SchemaRDD, Caching and working with Hive and Parquet file formats Understand the architecture of Spark MLLib while discussing some of the off-the-shelf algorithms that come with Spark. Introduce yourself to the deployment and usage of SparkR. Walk through the importance of Graph computation and the graph processing systems available in the market Check the real world example of Spark by building a recommendation engine with Spark using ALS. Use a Telco data set, to predict customer churn using Random Forests. In Detail Spark juggernaut keeps on rolling and getting more and more momentum each day. Spark provides key capabilities in the form of Spark SQL, Spark Streaming, Spark ML and Graph X all accessible via Java, Scala, Python and R. Deploying the key capabilities is crucial whether it is on a Standalone framework or as a part of existing Hadoop installation and configuring with Yarn and Mesos. The next part of the journey after installation is using key components, APIs, Clustering, machine learning APIs, data pipelines, parallel programming. It is important to understand why each framework component is key, how widely it is being u...</subfield></datafield><datafield tag="630" ind1="0" ind2="0"><subfield code="a">Spark (Electronic resource : Apache Software Foundation)</subfield><subfield code="0">http://id.loc.gov/authorities/names/no2015027445</subfield></datafield><datafield tag="630" ind1="0" ind2="7"><subfield code="a">Spark (Electronic resource : Apache Software Foundation)</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Electronic data processing</subfield><subfield code="x">Distributed processing</subfield><subfield code="x">Management.</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh2010014266</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Big data.</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh2012003227</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Machine learning.</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh85079324</subfield></datafield><datafield tag="650" ind1=" " ind2="6"><subfield code="a">Données volumineuses.</subfield></datafield><datafield tag="650" ind1=" " ind2="6"><subfield code="a">Apprentissage automatique.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Big data</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Electronic data processing</subfield><subfield code="x">Distributed processing</subfield><subfield code="x">Management</subfield><subfield code="2">fast</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Machine learning</subfield><subfield code="2">fast</subfield></datafield><datafield tag="758" ind1=" " ind2=" "><subfield code="i">has work:</subfield><subfield code="a">Learning Apache Spark 2 (Text)</subfield><subfield code="1">https://id.oclc.org/worldcat/entity/E39PCXQFfPJfdmKyT9cBhmHMxC</subfield><subfield code="4">https://id.oclc.org/worldcat/ontology/hasWork</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="l">FWS01</subfield><subfield code="p">ZDB-4-EBU</subfield><subfield code="q">FWS_PDA_EBU</subfield><subfield code="u">https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1495816</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">ProQuest MyiLibrary Digital eBook Collection</subfield><subfield code="b">IDEB</subfield><subfield code="n">cis36983548</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">EBSCOhost</subfield><subfield code="b">EBSC</subfield><subfield code="n">1495816</subfield></datafield><datafield tag="994" ind1=" " ind2=" "><subfield code="a">92</subfield><subfield code="b">GEBAY</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-4-EBU</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-863</subfield></datafield></record></collection> |
| id | ZDB-4-EBU-ocn984515083 |
| illustrated | Illustrated |
| indexdate | 2024-11-26T14:49:27Z |
| institution | BVB |
| isbn | 9781785889585 1785889583 |
| language | English |
| oclc_num | 984515083 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (1 volume) : illustrations |
| psigel | ZDB-4-EBU |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Packt Publishing, |
| record_format | marc |
| spelling | Abbasi, Muhammad Asif, author. Learning Apache Spark 2 : process big data with the speed of light! / Muhammad Asif Abbasi. Learning Apache Spark two Birmingham, UK : Packt Publishing, 2017. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Description based on online resource; title from cover (Safari, viewed April 26, 2017). Includes bibliographical references. Learn about the fastest-growing open source project in the world, and find out how it revolutionizes big data analytics About This Book Exclusive guide that covers how to get up and running with fast data processing using Apache Spark Explore and exploit various possibilities with Apache Spark using real-world use cases in this book Want to perform efficient data processing at real time? This book will be your one-stop solution. Who This Book Is For This guide appeals to big data engineers, analysts, architects, software engineers, even technical managers who need to perform efficient data processing on Hadoop at real time. Basic familiarity with Java or Scala will be helpful. The assumption is that readers will be from a mixed background, but would be typically people with background in engineering/data science with no prior Spark experience and want to understand how Spark can help them on their analytics journey. What You Will Learn Get an overview of big data analytics and its importance for organizations and data professionals Delve into Spark to see how it is different from existing processing platforms Understand the intricacies of various file formats, and how to process them with Apache Spark. Realize how to deploy Spark with YARN, MESOS or a Stand-alone cluster manager. Learn the concepts of Spark SQL, SchemaRDD, Caching and working with Hive and Parquet file formats Understand the architecture of Spark MLLib while discussing some of the off-the-shelf algorithms that come with Spark. Introduce yourself to the deployment and usage of SparkR. Walk through the importance of Graph computation and the graph processing systems available in the market Check the real world example of Spark by building a recommendation engine with Spark using ALS. Use a Telco data set, to predict customer churn using Random Forests. In Detail Spark juggernaut keeps on rolling and getting more and more momentum each day. Spark provides key capabilities in the form of Spark SQL, Spark Streaming, Spark ML and Graph X all accessible via Java, Scala, Python and R. Deploying the key capabilities is crucial whether it is on a Standalone framework or as a part of existing Hadoop installation and configuring with Yarn and Mesos. The next part of the journey after installation is using key components, APIs, Clustering, machine learning APIs, data pipelines, parallel programming. It is important to understand why each framework component is key, how widely it is being u... Spark (Electronic resource : Apache Software Foundation) http://id.loc.gov/authorities/names/no2015027445 Spark (Electronic resource : Apache Software Foundation) fast Electronic data processing Distributed processing Management. http://id.loc.gov/authorities/subjects/sh2010014266 Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Données volumineuses. Apprentissage automatique. Big data fast Electronic data processing Distributed processing Management fast Machine learning fast has work: Learning Apache Spark 2 (Text) https://id.oclc.org/worldcat/entity/E39PCXQFfPJfdmKyT9cBhmHMxC https://id.oclc.org/worldcat/ontology/hasWork FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1495816 Volltext |
| spellingShingle | Abbasi, Muhammad Asif Learning Apache Spark 2 : process big data with the speed of light! / Spark (Electronic resource : Apache Software Foundation) http://id.loc.gov/authorities/names/no2015027445 Spark (Electronic resource : Apache Software Foundation) fast Electronic data processing Distributed processing Management. http://id.loc.gov/authorities/subjects/sh2010014266 Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Données volumineuses. Apprentissage automatique. Big data fast Electronic data processing Distributed processing Management fast Machine learning fast |
| subject_GND | http://id.loc.gov/authorities/names/no2015027445 http://id.loc.gov/authorities/subjects/sh2010014266 http://id.loc.gov/authorities/subjects/sh2012003227 http://id.loc.gov/authorities/subjects/sh85079324 |
| title | Learning Apache Spark 2 : process big data with the speed of light! / |
| title_alt | Learning Apache Spark two |
| title_auth | Learning Apache Spark 2 : process big data with the speed of light! / |
| title_exact_search | Learning Apache Spark 2 : process big data with the speed of light! / |
| title_full | Learning Apache Spark 2 : process big data with the speed of light! / Muhammad Asif Abbasi. |
| title_fullStr | Learning Apache Spark 2 : process big data with the speed of light! / Muhammad Asif Abbasi. |
| title_full_unstemmed | Learning Apache Spark 2 : process big data with the speed of light! / Muhammad Asif Abbasi. |
| title_short | Learning Apache Spark 2 : |
| title_sort | learning apache spark 2 process big data with the speed of light |
| title_sub | process big data with the speed of light! / |
| topic | Spark (Electronic resource : Apache Software Foundation) http://id.loc.gov/authorities/names/no2015027445 Spark (Electronic resource : Apache Software Foundation) fast Electronic data processing Distributed processing Management. http://id.loc.gov/authorities/subjects/sh2010014266 Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Données volumineuses. Apprentissage automatique. Big data fast Electronic data processing Distributed processing Management fast Machine learning fast |
| topic_facet | Spark (Electronic resource : Apache Software Foundation) Electronic data processing Distributed processing Management. Big data. Machine learning. Données volumineuses. Apprentissage automatique. Big data Electronic data processing Distributed processing Management Machine learning |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1495816 |
| work_keys_str_mv | AT abbasimuhammadasif learningapachespark2processbigdatawiththespeedoflight AT abbasimuhammadasif learningapachesparktwo |