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Cassandra high availability : harness the power of Apache Cassandra to build scalable, fault-tolerant, and readily available applications /

If you are a developer or DevOps engineer who understands the basics of Cassandra and are ready to take your knowledge to the next level, then this book is for you. An understanding of the essentials of Cassandra is needed.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Strickland, Robbie (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, 2014.
Colección:Community experience distilled.
Temas:
Acceso en línea:Texto completo
Texto completo

MARC

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100 1 |a Strickland, Robbie,  |e author. 
245 1 0 |a Cassandra high availability :  |b harness the power of Apache Cassandra to build scalable, fault-tolerant, and readily available applications /  |c Robbie Strickland. 
246 3 0 |a Harness the power of Apache Cassandra to build scalable, fault-tolerant, and readily available applications 
264 1 |a Birmingham, UK :  |b Packt Publishing,  |c 2014. 
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 
347 |a text file 
490 1 |a Community experience distilled 
588 0 |a Online resource; title from cover page (Safari, viewed January 23, 2015). 
500 |a Includes index. 
505 0 |a Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Cassandra's Approach to High Availability; ACID; The monolithic architecture; The master-slave architecture; Sharding; Master failover; Cassandra's solution; Cassandra architecture; Distributed hash table; Replication; Replication across data centers; Tunable consistency; The CAP theorem; Summary; Chapter 2: Data Distribution; Hash table fundamentals; Distributing hash tables; Consistent hashing; The mechanics of consistent hashing; Token assignment 
505 8 |a Manually assigned tokensvnodes; How vnodes improve availability; Partitioners; Hotspots; Effects of scaling out using the ByteOrderedPartitioner; A time-series example; Summary; Chapter 3: Replication; The replication factor; Replication strategies; SimpleStrategy; NetworkTopologyStrategy; Snitches; Maintaining the replication factor when a node fails; Consistency conflicts; Consistency levels; Repairing data; Balancing the replication factor with consistency; Summary; Chapter 4: Data Centers; Use cases for multiple data centers; Live backup; Failover; Load balancing; Geographic distribution 
505 8 |a Online analysisAnalysis using Hadoop; Analysis using Spark; Data center setup; RackInferringSnitch; PropertyFileSnitch; GossipingPropertyFileSnitch; Cloud snitches; Replication across data centers; Setting the replication factor; Consistency in a multiple data center environment; The anatomy of a replicated write; Achieving stronger consistency between data centers; Summary; Chapter 5: Scaling Out; Choosing the right hardware configuration; Scaling out versus scaling up; Growing your cluster; Adding nodes without vnodes; Adding nodes with vnodes; How to scale out; Adding a data center 
505 8 |a How to scale upUpgrading in place; Scaling up using data center replication; Removing nodes; Removing nodes within a data center; Decommissioning a data center; Other data migration scenarios; Snitch changes; Summary; Chapter 6: High Availability Features in the Native Java Client; Thrift versus the native protocol; Setting up the environment; Connecting to the cluster; Executing statements; Prepared statements; Batched statements; Caution with batches; Handling asynchronous requests; Running queries in parallel; Load balancing; Failing over to a remote data center 
505 8 |a Downgrading the consistency levelDefining your own retry policy; Token awareness; Tying it all together; Falling back to QUORUM; Summary; Chapter 7: Modeling for High Availability; How Cassandra stores data; Implications of a log-structured storage; Understanding compaction; Size-tiered compaction; Leveled compaction; Date-tiered compaction; CQL under the hood; Single primary key; Compound keys; Partition keys; Clustering columns; Composite partition keys; The importance of the storage model; Understanding queries; Query by key; Range queries; Denormalizing with collections 
520 |a If you are a developer or DevOps engineer who understands the basics of Cassandra and are ready to take your knowledge to the next level, then this book is for you. An understanding of the essentials of Cassandra is needed. 
546 |a English. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
630 0 0 |a Apache Cassandra. 
630 0 7 |a Apache Cassandra.  |2 fast  |0 (OCoLC)fst01911569 
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