Practical real-time data processing and analytics :: distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka /
A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and framework...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2017.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to dep ... |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| ISBN: | 1787289869 9781787289864 |
Internformat
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-4-EBA-on1008968663 | ||
| 003 | OCoLC | ||
| 005 | 20241004212047.0 | ||
| 006 | m o d | ||
| 007 | cr unu|||||||| | ||
| 008 | 171102s2017 enka o 000 0 eng d | ||
| 040 | |a UMI |b eng |e rda |e pn |c UMI |d IDEBK |d STF |d COO |d OCLCF |d UOK |d CEF |d KSU |d WYU |d C6I |d UAB |d N$T |d QGK |d OCLCQ |d OCLCO |d OCLCQ |d OCL |d OCLCO |d OCLCL | ||
| 020 | |a 1787289869 | ||
| 020 | |a 9781787289864 |q (electronic bk.) | ||
| 020 | |z 9781787281202 | ||
| 035 | |a (OCoLC)1008968663 | ||
| 037 | |a CL0500000908 |b Safari Books Online | ||
| 050 | 4 | |a QA76.9.D343 | |
| 082 | 7 | |a 004 |2 23 | |
| 049 | |a MAIN | ||
| 100 | 1 | |a Saxena, Shilpi, |e author. | |
| 245 | 1 | 0 | |a Practical real-time data processing and analytics : |b distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka / |c Shilpi Saxena, Saurabh Gupta. |
| 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 | 0 | |a Online resource; title from title page (Safari, viewed October 31, 2017). | |
| 520 | |a A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to dep ... | ||
| 630 | 0 | 0 | |a Spark (Electronic resource : Apache Software Foundation) |0 http://id.loc.gov/authorities/names/no2015027445 |
| 630 | 0 | 0 | |a Storm (Electronic resource) |0 http://id.loc.gov/authorities/names/no2012126170 |
| 630 | 0 | 7 | |a Storm (Electronic resource) |2 fast |
| 630 | 0 | 7 | |a Spark (Electronic resource : Apache Software Foundation) |2 fast |
| 650 | 0 | |a Big data. |0 http://id.loc.gov/authorities/subjects/sh2012003227 | |
| 650 | 0 | |a Data mining. |0 http://id.loc.gov/authorities/subjects/sh97002073 | |
| 650 | 0 | |a Electronic data processing |x Distributed processing |x Management. |0 http://id.loc.gov/authorities/subjects/sh2010014266 | |
| 650 | 6 | |a Données volumineuses. | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 7 | |a Big data |2 fast | |
| 650 | 7 | |a Data mining |2 fast | |
| 650 | 7 | |a Electronic data processing |x Distributed processing |x Management |2 fast | |
| 700 | 1 | |a Gupta, Saurabh, |e author. | |
| 758 | |i has work: |a Practical Real-time Data Processing and Analytics (Text) |1 https://id.oclc.org/worldcat/entity/E39PD3FgFf3hKtfqQRppfRJWwy |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 856 | 4 | 0 | |l FWS01 |p ZDB-4-EBA |q FWS_PDA_EBA |u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1607851 |3 Volltext |
| 938 | |a EBSCOhost |b EBSC |n 1607851 | ||
| 938 | |a ProQuest MyiLibrary Digital eBook Collection |b IDEB |n cis39023464 | ||
| 994 | |a 92 |b GEBAY | ||
| 912 | |a ZDB-4-EBA | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBA-on1008968663 |
|---|---|
| _version_ | 1816882405089214466 |
| adam_text | |
| any_adam_object | |
| author | Saxena, Shilpi Gupta, Saurabh |
| author_facet | Saxena, Shilpi Gupta, Saurabh |
| author_role | aut aut |
| author_sort | Saxena, Shilpi |
| author_variant | s s ss s g sg |
| 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-EBA |
| ctrlnum | (OCoLC)1008968663 |
| dewey-full | 004 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 004 - Computer science |
| dewey-raw | 004 |
| dewey-search | 004 |
| dewey-sort | 14 |
| 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>05053cam a2200529 i 4500</leader><controlfield tag="001">ZDB-4-EBA-on1008968663</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">171102s2017 enka o 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">STF</subfield><subfield code="d">COO</subfield><subfield code="d">OCLCF</subfield><subfield code="d">UOK</subfield><subfield code="d">CEF</subfield><subfield code="d">KSU</subfield><subfield code="d">WYU</subfield><subfield code="d">C6I</subfield><subfield code="d">UAB</subfield><subfield code="d">N$T</subfield><subfield code="d">QGK</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCQ</subfield><subfield code="d">OCL</subfield><subfield code="d">OCLCO</subfield><subfield code="d">OCLCL</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1787289869</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781787289864</subfield><subfield code="q">(electronic bk.)</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">9781787281202</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1008968663</subfield></datafield><datafield tag="037" ind1=" " ind2=" "><subfield code="a">CL0500000908</subfield><subfield code="b">Safari Books Online</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">004</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">Saxena, Shilpi,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Practical real-time data processing and analytics :</subfield><subfield code="b">distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka /</subfield><subfield code="c">Shilpi Saxena, Saurabh Gupta.</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="0" ind2=" "><subfield code="a">Online resource; title from title page (Safari, viewed October 31, 2017).</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to dep ...</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="0"><subfield code="a">Storm (Electronic resource)</subfield><subfield code="0">http://id.loc.gov/authorities/names/no2012126170</subfield></datafield><datafield tag="630" ind1="0" ind2="7"><subfield code="a">Storm (Electronic resource)</subfield><subfield code="2">fast</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">Big data.</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh2012003227</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Data mining.</subfield><subfield code="0">http://id.loc.gov/authorities/subjects/sh97002073</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="6"><subfield code="a">Données volumineuses.</subfield></datafield><datafield tag="650" ind1=" " ind2="6"><subfield code="a">Exploration de données (Informatique)</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">Data mining</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="700" ind1="1" ind2=" "><subfield code="a">Gupta, Saurabh,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="758" ind1=" " ind2=" "><subfield code="i">has work:</subfield><subfield code="a">Practical Real-time Data Processing and Analytics (Text)</subfield><subfield code="1">https://id.oclc.org/worldcat/entity/E39PD3FgFf3hKtfqQRppfRJWwy</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-EBA</subfield><subfield code="q">FWS_PDA_EBA</subfield><subfield code="u">https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1607851</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">EBSCOhost</subfield><subfield code="b">EBSC</subfield><subfield code="n">1607851</subfield></datafield><datafield tag="938" ind1=" " ind2=" "><subfield code="a">ProQuest MyiLibrary Digital eBook Collection</subfield><subfield code="b">IDEB</subfield><subfield code="n">cis39023464</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-EBA</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-863</subfield></datafield></record></collection> |
| id | ZDB-4-EBA-on1008968663 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:28:05Z |
| institution | BVB |
| isbn | 1787289869 9781787289864 |
| language | English |
| oclc_num | 1008968663 |
| 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-EBA |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Packt Publishing, |
| record_format | marc |
| spelling | Saxena, Shilpi, author. Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka / Shilpi Saxena, Saurabh Gupta. Birmingham, UK : Packt Publishing, 2017. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Online resource; title from title page (Safari, viewed October 31, 2017). A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to dep ... Spark (Electronic resource : Apache Software Foundation) http://id.loc.gov/authorities/names/no2015027445 Storm (Electronic resource) http://id.loc.gov/authorities/names/no2012126170 Storm (Electronic resource) fast Spark (Electronic resource : Apache Software Foundation) fast Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Electronic data processing Distributed processing Management. http://id.loc.gov/authorities/subjects/sh2010014266 Données volumineuses. Exploration de données (Informatique) Big data fast Data mining fast Electronic data processing Distributed processing Management fast Gupta, Saurabh, author. has work: Practical Real-time Data Processing and Analytics (Text) https://id.oclc.org/worldcat/entity/E39PD3FgFf3hKtfqQRppfRJWwy https://id.oclc.org/worldcat/ontology/hasWork FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1607851 Volltext |
| spellingShingle | Saxena, Shilpi Gupta, Saurabh Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka / Spark (Electronic resource : Apache Software Foundation) http://id.loc.gov/authorities/names/no2015027445 Storm (Electronic resource) http://id.loc.gov/authorities/names/no2012126170 Storm (Electronic resource) fast Spark (Electronic resource : Apache Software Foundation) fast Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Electronic data processing Distributed processing Management. http://id.loc.gov/authorities/subjects/sh2010014266 Données volumineuses. Exploration de données (Informatique) Big data fast Data mining fast Electronic data processing Distributed processing Management fast |
| subject_GND | http://id.loc.gov/authorities/names/no2015027445 http://id.loc.gov/authorities/names/no2012126170 http://id.loc.gov/authorities/subjects/sh2012003227 http://id.loc.gov/authorities/subjects/sh97002073 http://id.loc.gov/authorities/subjects/sh2010014266 |
| title | Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka / |
| title_auth | Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka / |
| title_exact_search | Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka / |
| title_full | Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka / Shilpi Saxena, Saurabh Gupta. |
| title_fullStr | Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka / Shilpi Saxena, Saurabh Gupta. |
| title_full_unstemmed | Practical real-time data processing and analytics : distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka / Shilpi Saxena, Saurabh Gupta. |
| title_short | Practical real-time data processing and analytics : |
| title_sort | practical real time data processing and analytics distributed computing and event processing using apache spark flink storm and kafka |
| title_sub | distributed computing and event processing using Apache Spark, Flink, Storm, and Kafka / |
| topic | Spark (Electronic resource : Apache Software Foundation) http://id.loc.gov/authorities/names/no2015027445 Storm (Electronic resource) http://id.loc.gov/authorities/names/no2012126170 Storm (Electronic resource) fast Spark (Electronic resource : Apache Software Foundation) fast Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Electronic data processing Distributed processing Management. http://id.loc.gov/authorities/subjects/sh2010014266 Données volumineuses. Exploration de données (Informatique) Big data fast Data mining fast Electronic data processing Distributed processing Management fast |
| topic_facet | Spark (Electronic resource : Apache Software Foundation) Storm (Electronic resource) Big data. Data mining. Electronic data processing Distributed processing Management. Données volumineuses. Exploration de données (Informatique) Big data Data mining Electronic data processing Distributed processing Management |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1607851 |
| work_keys_str_mv | AT saxenashilpi practicalrealtimedataprocessingandanalyticsdistributedcomputingandeventprocessingusingapachesparkflinkstormandkafka AT guptasaurabh practicalrealtimedataprocessingandanalyticsdistributedcomputingandeventprocessingusingapachesparkflinkstormandkafka |