Getting started with Hazelcast :: get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application /
This book is a great introduction for Java developers, software architects, or DevOps looking to enable scalable and agile data within their applications. Providing in-memory object storage, cluster-wide state and messaging, or even scalable task execution, Hazelcast helps solve a number of issues t...
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2015.
|
Ausgabe: | Second edition. |
Schriftenreihe: | Community experience distilled.
|
Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | This book is a great introduction for Java developers, software architects, or DevOps looking to enable scalable and agile data within their applications. Providing in-memory object storage, cluster-wide state and messaging, or even scalable task execution, Hazelcast helps solve a number of issues that have troubled technologists for years. |
Beschreibung: | Includes index. |
Beschreibung: | 1 online resource (145 pages) : illustrations |
ISBN: | 9781783554058 1783554053 |
Internformat
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245 | 1 | 0 | |a Getting started with Hazelcast : |b get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application / |c Mat Johns. |
246 | 3 | 0 | |a Get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application |
250 | |a Second edition. | ||
264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2015. | |
300 | |a 1 online resource (145 pages) : |b illustrations | ||
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588 | 0 | |a Print version record. | |
505 | 0 | |a Cover -- Copyright -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: What is Hazelcast? -- Starting out as usual -- Data deciding to hang around -- Therein lies the problem -- Breaking the mould -- Moving to new ground -- Playing around with our data -- Summary -- Chapter 2: Getting off the Ground -- Let's get started -- Showing off straightaway -- Mapping back to the real world -- Sets, lists, and queues -- Many things at a time -- Searching and indexing | |
505 | 8 | |a What happens when we reach our limits?Summary -- Chapter 3: Going Concurrent -- Atomic control -- Distributed locking -- Tactical locking -- Transactionally rolling on -- Differences when queuing -- Enterprising onwards -- Collectively counting up -- Spreading the word -- Summary -- Chapter 4: Divide and Conquer -- Divvying up the data -- Backups everywhere and nowhere -- Scaling up the cluster -- Having some of our data everywhere -- Grouping and separating nodes -- Network partitioning -- Maintaining quorum -- Summary | |
505 | 8 | |a Chapter 5: Listening OutListening to the goings-on -- The sound of our own data -- Continuously querying -- Listeners racing into action -- Keyless collections -- Programmatic configuration ahead of time -- Events unfolding in the wider world -- Moving data around the place -- Extending quorum -- Summary -- Chapter 6: Spreading the Load -- All power to the compute -- Giving up when tasks take too long -- Running once, running everywhere -- Placing tasks next to the data -- Partitioning control by name -- Self-updating results | |
505 | 8 | |a In-place entry processingSummary -- Chapter 7: Gathering Results -- What is this big data hype all about? -- Trying to make sense of it all -- Combining data where possible -- Putting theory into practice -- Combining results as we go -- Simplifying just aggregating up -- Summary -- Chapter 8: Typical Deployments -- All heap and nowhere to go -- Stepping back from the cluster -- Serialization and classes -- Getting straight to the point -- Architectural overview -- Peer-to-peer clusters -- Smart clients and server clusters | |
505 | 8 | |a Dummy client proxying through a single nodeSummary -- Chapter 9: From the Outside Looking In -- What about the rest of us? -- Memcache -- Going RESTful -- Cluster status via REST -- REST resilience -- Summary -- Chapter 10: Going Global -- Getting set up in the cloud -- Under manual control -- Discovery � the Amazonian way -- Filtering the possibilities -- Spreading out around the globe -- Summary -- Chapter 11: Playing Well with Others -- Don't pass what you need, depend on it -- Simplifying collection access -- Transparently caching others' data | |
520 | |a This book is a great introduction for Java developers, software architects, or DevOps looking to enable scalable and agile data within their applications. Providing in-memory object storage, cluster-wide state and messaging, or even scalable task execution, Hazelcast helps solve a number of issues that have troubled technologists for years. | ||
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contents | Cover -- Copyright -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: What is Hazelcast? -- Starting out as usual -- Data deciding to hang around -- Therein lies the problem -- Breaking the mould -- Moving to new ground -- Playing around with our data -- Summary -- Chapter 2: Getting off the Ground -- Let's get started -- Showing off straightaway -- Mapping back to the real world -- Sets, lists, and queues -- Many things at a time -- Searching and indexing What happens when we reach our limits?Summary -- Chapter 3: Going Concurrent -- Atomic control -- Distributed locking -- Tactical locking -- Transactionally rolling on -- Differences when queuing -- Enterprising onwards -- Collectively counting up -- Spreading the word -- Summary -- Chapter 4: Divide and Conquer -- Divvying up the data -- Backups everywhere and nowhere -- Scaling up the cluster -- Having some of our data everywhere -- Grouping and separating nodes -- Network partitioning -- Maintaining quorum -- Summary Chapter 5: Listening OutListening to the goings-on -- The sound of our own data -- Continuously querying -- Listeners racing into action -- Keyless collections -- Programmatic configuration ahead of time -- Events unfolding in the wider world -- Moving data around the place -- Extending quorum -- Summary -- Chapter 6: Spreading the Load -- All power to the compute -- Giving up when tasks take too long -- Running once, running everywhere -- Placing tasks next to the data -- Partitioning control by name -- Self-updating results In-place entry processingSummary -- Chapter 7: Gathering Results -- What is this big data hype all about? -- Trying to make sense of it all -- Combining data where possible -- Putting theory into practice -- Combining results as we go -- Simplifying just aggregating up -- Summary -- Chapter 8: Typical Deployments -- All heap and nowhere to go -- Stepping back from the cluster -- Serialization and classes -- Getting straight to the point -- Architectural overview -- Peer-to-peer clusters -- Smart clients and server clusters Dummy client proxying through a single nodeSummary -- Chapter 9: From the Outside Looking In -- What about the rest of us? -- Memcache -- Going RESTful -- Cluster status via REST -- REST resilience -- Summary -- Chapter 10: Going Global -- Getting set up in the cloud -- Under manual control -- Discovery � the Amazonian way -- Filtering the possibilities -- Spreading out around the globe -- Summary -- Chapter 11: Playing Well with Others -- Don't pass what you need, depend on it -- Simplifying collection access -- Transparently caching others' data |
ctrlnum | (OCoLC)918862372 |
dewey-full | 005.13 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 005 - Computer programming, programs, data, security |
dewey-raw | 005.13 |
dewey-search | 005.13 |
dewey-sort | 15.13 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
edition | Second edition. |
format | Electronic eBook |
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series | Community experience distilled. |
series2 | Community experience distilled |
spelling | Johns, Mat, author. Getting started with Hazelcast : get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application / Mat Johns. Get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application Second edition. Birmingham, UK : Packt Publishing, 2015. 1 online resource (145 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier Community experience distilled Online resource; title from cover (Safari, viewed August 12, 2015). Includes index. Print version record. Cover -- Copyright -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: What is Hazelcast? -- Starting out as usual -- Data deciding to hang around -- Therein lies the problem -- Breaking the mould -- Moving to new ground -- Playing around with our data -- Summary -- Chapter 2: Getting off the Ground -- Let's get started -- Showing off straightaway -- Mapping back to the real world -- Sets, lists, and queues -- Many things at a time -- Searching and indexing What happens when we reach our limits?Summary -- Chapter 3: Going Concurrent -- Atomic control -- Distributed locking -- Tactical locking -- Transactionally rolling on -- Differences when queuing -- Enterprising onwards -- Collectively counting up -- Spreading the word -- Summary -- Chapter 4: Divide and Conquer -- Divvying up the data -- Backups everywhere and nowhere -- Scaling up the cluster -- Having some of our data everywhere -- Grouping and separating nodes -- Network partitioning -- Maintaining quorum -- Summary Chapter 5: Listening OutListening to the goings-on -- The sound of our own data -- Continuously querying -- Listeners racing into action -- Keyless collections -- Programmatic configuration ahead of time -- Events unfolding in the wider world -- Moving data around the place -- Extending quorum -- Summary -- Chapter 6: Spreading the Load -- All power to the compute -- Giving up when tasks take too long -- Running once, running everywhere -- Placing tasks next to the data -- Partitioning control by name -- Self-updating results In-place entry processingSummary -- Chapter 7: Gathering Results -- What is this big data hype all about? -- Trying to make sense of it all -- Combining data where possible -- Putting theory into practice -- Combining results as we go -- Simplifying just aggregating up -- Summary -- Chapter 8: Typical Deployments -- All heap and nowhere to go -- Stepping back from the cluster -- Serialization and classes -- Getting straight to the point -- Architectural overview -- Peer-to-peer clusters -- Smart clients and server clusters Dummy client proxying through a single nodeSummary -- Chapter 9: From the Outside Looking In -- What about the rest of us? -- Memcache -- Going RESTful -- Cluster status via REST -- REST resilience -- Summary -- Chapter 10: Going Global -- Getting set up in the cloud -- Under manual control -- Discovery � the Amazonian way -- Filtering the possibilities -- Spreading out around the globe -- Summary -- Chapter 11: Playing Well with Others -- Don't pass what you need, depend on it -- Simplifying collection access -- Transparently caching others' data This book is a great introduction for Java developers, software architects, or DevOps looking to enable scalable and agile data within their applications. Providing in-memory object storage, cluster-wide state and messaging, or even scalable task execution, Hazelcast helps solve a number of issues that have troubled technologists for years. Electronic data processing. http://id.loc.gov/authorities/subjects/sh85042288 Information retrieval. http://id.loc.gov/authorities/subjects/sh85066148 Information Storage and Retrieval https://id.nlm.nih.gov/mesh/D016247 Recherche de l'information. information retrieval. aat COMPUTERS Programming Languages General. bisacsh Electronic data processing fast Information retrieval fast Print version: Johns, Mat. Getting started with Hazelcast. Second edition 9781783554058 Community experience distilled. http://id.loc.gov/authorities/names/no2011030603 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1046857 Volltext |
spellingShingle | Johns, Mat Getting started with Hazelcast : get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application / Community experience distilled. Cover -- Copyright -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: What is Hazelcast? -- Starting out as usual -- Data deciding to hang around -- Therein lies the problem -- Breaking the mould -- Moving to new ground -- Playing around with our data -- Summary -- Chapter 2: Getting off the Ground -- Let's get started -- Showing off straightaway -- Mapping back to the real world -- Sets, lists, and queues -- Many things at a time -- Searching and indexing What happens when we reach our limits?Summary -- Chapter 3: Going Concurrent -- Atomic control -- Distributed locking -- Tactical locking -- Transactionally rolling on -- Differences when queuing -- Enterprising onwards -- Collectively counting up -- Spreading the word -- Summary -- Chapter 4: Divide and Conquer -- Divvying up the data -- Backups everywhere and nowhere -- Scaling up the cluster -- Having some of our data everywhere -- Grouping and separating nodes -- Network partitioning -- Maintaining quorum -- Summary Chapter 5: Listening OutListening to the goings-on -- The sound of our own data -- Continuously querying -- Listeners racing into action -- Keyless collections -- Programmatic configuration ahead of time -- Events unfolding in the wider world -- Moving data around the place -- Extending quorum -- Summary -- Chapter 6: Spreading the Load -- All power to the compute -- Giving up when tasks take too long -- Running once, running everywhere -- Placing tasks next to the data -- Partitioning control by name -- Self-updating results In-place entry processingSummary -- Chapter 7: Gathering Results -- What is this big data hype all about? -- Trying to make sense of it all -- Combining data where possible -- Putting theory into practice -- Combining results as we go -- Simplifying just aggregating up -- Summary -- Chapter 8: Typical Deployments -- All heap and nowhere to go -- Stepping back from the cluster -- Serialization and classes -- Getting straight to the point -- Architectural overview -- Peer-to-peer clusters -- Smart clients and server clusters Dummy client proxying through a single nodeSummary -- Chapter 9: From the Outside Looking In -- What about the rest of us? -- Memcache -- Going RESTful -- Cluster status via REST -- REST resilience -- Summary -- Chapter 10: Going Global -- Getting set up in the cloud -- Under manual control -- Discovery � the Amazonian way -- Filtering the possibilities -- Spreading out around the globe -- Summary -- Chapter 11: Playing Well with Others -- Don't pass what you need, depend on it -- Simplifying collection access -- Transparently caching others' data Electronic data processing. http://id.loc.gov/authorities/subjects/sh85042288 Information retrieval. http://id.loc.gov/authorities/subjects/sh85066148 Information Storage and Retrieval https://id.nlm.nih.gov/mesh/D016247 Recherche de l'information. information retrieval. aat COMPUTERS Programming Languages General. bisacsh Electronic data processing fast Information retrieval fast |
subject_GND | http://id.loc.gov/authorities/subjects/sh85042288 http://id.loc.gov/authorities/subjects/sh85066148 https://id.nlm.nih.gov/mesh/D016247 |
title | Getting started with Hazelcast : get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application / |
title_alt | Get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application |
title_auth | Getting started with Hazelcast : get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application / |
title_exact_search | Getting started with Hazelcast : get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application / |
title_full | Getting started with Hazelcast : get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application / Mat Johns. |
title_fullStr | Getting started with Hazelcast : get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application / Mat Johns. |
title_full_unstemmed | Getting started with Hazelcast : get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application / Mat Johns. |
title_short | Getting started with Hazelcast : |
title_sort | getting started with hazelcast get acquainted with the highly scalable data grid hazelcast and learn how to bring its powerful in memory features into your application |
title_sub | get acquainted with the highly scalable data grid, Hazelcast, and learn how to bring its powerful in-memory features into your application / |
topic | Electronic data processing. http://id.loc.gov/authorities/subjects/sh85042288 Information retrieval. http://id.loc.gov/authorities/subjects/sh85066148 Information Storage and Retrieval https://id.nlm.nih.gov/mesh/D016247 Recherche de l'information. information retrieval. aat COMPUTERS Programming Languages General. bisacsh Electronic data processing fast Information retrieval fast |
topic_facet | Electronic data processing. Information retrieval. Information Storage and Retrieval Recherche de l'information. information retrieval. COMPUTERS Programming Languages General. Electronic data processing Information retrieval |
url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1046857 |
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