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Cassandra: The Definitive Guide, (Revised) Third Edition. 3rd Edition - Helion

Cassandra: The Definitive Guide, (Revised) Third Edition. 3rd Edition
ebook
Autor: Jeff Carpenter, Eben Hewitt
ISBN: 9781492097105
stron: 432, Format: ebook
Data wydania: 2022-01-24
Ksi─Ögarnia: Helion

Cena ksi─ů┼╝ki: 228,65 z┼é (poprzednio: 265,87 z┼é)
Oszczędzasz: 14% (-37,22 zł)

Dodaj do koszyka Cassandra: The Definitive Guide, (Revised) Third Edition. 3rd Edition

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This revised third edition--updated for Cassandra 4.0 and new developments in the Cassandra ecosystem, including deployments in Kubernetes with K8ssandra--provides technical details and practical examples to help you put this database to work in a production environment.

Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. Developers, DBAs, and application architects looking to solve a database scaling issue or future-proof an application will learn how to harness Cassandra's speed and flexibility.

  • Understand Cassandra's distributed and decentralized structure
  • Use the Cassandra Query Language (CQL) and cqlsh (the CQL shell)
  • Create a working data model and compare it with an equivalent relational model
  • Design and develop applications using client drivers
  • Explore cluster topology and learn how nodes exchange data
  • Maintain a high level of performance in your cluster
  • Deploy Cassandra onsite, in the cloud, or with Docker and Kubernetes
  • Integrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and Lucene

Dodaj do koszyka Cassandra: The Definitive Guide, (Revised) Third Edition. 3rd Edition

 

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Dodaj do koszyka Cassandra: The Definitive Guide, (Revised) Third Edition. 3rd Edition

Spis tre┼Ťci

Cassandra: The Definitive Guide, (Revised) Third Edition. 3rd Edition eBook -- spis treÂci

  • Foreword
  • Preface
    • Why Apache Cassandra?
    • Is This Book for You?
    • Whats in This Book?
    • New for the Third Edition
      • Note on the Revised Third Edition
    • Conventions Used in This Book
    • Using Code Examples
    • OReilly Interactive Katacoda Scenarios
    • OReilly Online Learning
    • How to Contact Us
    • Acknowledgments
  • 1. Beyond Relational Databases
    • Whats Wrong with Relational Databases?
    • A Quick Review of Relational Databases
      • Transactions, ACID-ity, and Two-Phase Commit
      • Schema
      • Sharding and Shared-Nothing Architecture
    • Web Scale
    • The Rise of NoSQL
    • Summary
  • 2. Introducing Cassandra
    • The Cassandra Elevator Pitch
      • Cassandra in 50 Words or Less
      • Distributed and Decentralized
      • Elastic Scalability
      • High Availability and Fault Tolerance
      • Tuneable Consistency
      • Brewers CAP Theorem
      • Row-Oriented
      • High Performance
    • Where Did Cassandra Come From?
    • Is Cassandra a Good Fit for My Project?
      • Large Deployments
      • Lots of Writes, Statistics, and Analysis
      • Geographical Distribution
      • Hybrid Cloud and Multicloud Deployment
    • Getting Involved
    • Summary
  • 3. Installing Cassandra
    • Installing the Apache Distribution
      • Extracting the Download
      • Whats in There?
    • Building from Source
      • Additional Build Targets
    • Running Cassandra
      • Setting the Environment
      • Starting the Server
      • Stopping Cassandra
    • Other Cassandra Distributions
    • Running the CQL Shell
    • Basic cqlsh Commands
      • cqlsh Help
      • Describing the Environment in cqlsh
      • Creating a Keyspace and Table in cqlsh
      • Writing and Reading Data in cqlsh
    • Running Cassandra in Docker
    • Summary
  • 4. The Cassandra Query Language
    • The Relational Data Model
    • Cassandras Data Model
      • Clusters
      • Keyspaces
      • Tables
      • Columns
        • Timestamps
        • Time to live (TTL)
    • CQL Types
      • Numeric Data Types
      • Textual Data Types
      • Time and Identity Data Types
      • Other Simple Data Types
      • Collections
      • Tuples
      • User-Defined Types
    • Summary
  • 5. Data Modeling
    • Conceptual Data Modeling
    • RDBMS Design
      • Design Differences Between RDBMS and Cassandra
        • No joins
        • No referential integrity
        • Denormalization
        • Query-first design
        • Designing for optimal storage
        • Sorting is a design decision
    • Defining Application Queries
    • Logical Data Modeling
      • Hotel Logical Data Model
      • Reservation Logical Data Model
    • Physical Data Modeling
      • Hotel Physical Data Model
      • Reservation Physical Data Model
    • Evaluating and Refining
      • Calculating Partition Size
      • Calculating Size on Disk
      • Breaking Up Large Partitions
    • Defining Database Schema
      • Cassandra Data Modeling Tools
    • Summary
  • 6. The Cassandra Architecture
    • Data Centers and Racks
    • Gossip and Failure Detection
    • Snitches
    • Rings and Tokens
    • Virtual Nodes
    • Partitioners
    • Replication Strategies
    • Consistency Levels
    • Queries and Coordinator Nodes
    • Hinted Handoff
    • Anti-Entropy, Repair, and Merkle Trees
    • Lightweight Transactions and Paxos
    • Memtables, SSTables, and Commit Logs
    • Bloom Filters
    • Caching
    • Compaction
    • Deletion and Tombstones
    • Managers and Services
      • Cassandra Daemon
      • Storage Engine
      • Storage Service
      • Storage Proxy
      • Messaging Service
      • Stream Manager
      • CQL Native Transport Server
    • System Keyspaces
    • Summary
  • 7. Designing Applications with Cassandra
    • Hotel Application Design
      • Cassandra and Microservice Architecture
      • Microservice Architecture for a Hotel Application
      • Identifying Bounded Contexts
      • Identifying Services
      • Designing Microservice Persistence
        • Polyglot persistence
        • Representing other database models in CQL
    • Extending Designs
      • Secondary Indexes
      • Materialized Views
    • Reservation Service: A Sample Microservice
      • Design Choices for a Java Microservice
    • Deployment and Integration Considerations
      • Services, Keyspaces, and Clusters
      • Data Centers and Load Balancing
      • Interactions Between Microservices
    • Summary
  • 8. Application Development with Drivers
    • DataStax Java Driver
      • Development Environment Configuration
      • Connecting to a Cluster
      • Statements
      • Simple Statements
      • Prepared Statements
        • Bound statement
      • Query Builder
      • Object Mapper
      • Asynchronous Execution
      • Driver Configuration
        • File-based configuration
        • Basic configuration options
        • Load balancing
        • Retrying failed queries
        • Speculative execution
        • Connection pooling
        • Protocol version
        • Compression
        • Driver security
        • Execution profiles
      • Metadata
        • Node discovery
        • Schema access
      • Debugging and Monitoring
        • Driver logging
        • Driver metrics
    • DataStax Python Driver
    • DataStax Node.js Driver
    • DataStax C# Driver
    • Other Cassandra Drivers
    • Summary
  • 9. Writing and Reading Data
    • Writing
      • Write Consistency Levels
      • The Cassandra Write Path
      • Writing Files to Disk
        • Commit log files
        • SSTable files
      • Lightweight Transactions
      • Batches
    • Reading
      • Read Consistency Levels
      • The Cassandra Read Path
      • Read Repair
      • Range Queries, Ordering and Filtering
      • Paging
    • Deleting
    • Summary
  • 10. Configuring and Deploying Cassandra
    • Cassandra Cluster Manager
      • Creating a Cluster
      • Adding Nodes to a Cluster
      • Dynamic Ring Participation
    • Node Configuration
      • Seed Nodes
      • Snitches
      • Partitioners
      • Tokens and Virtual Nodes
      • Network Interfaces
      • Data Storage
      • Startup and JVM Settings
    • Planning a Cluster Deployment
      • Cluster Topology and Replication Strategies
      • Sizing Your Cluster
      • Selecting Instances
      • Storage
      • Network
    • Cloud Deployment
      • Amazon Web Services
      • Google Cloud Platform
      • Microsoft Azure
    • Summary
  • 11. Monitoring
    • Monitoring Cassandra with JMX
    • Cassandras MBeans
      • Database MBeans
        • Storage Service MBean
        • Storage Proxy MBean
        • Hints Service MBean
        • Column Family Store MBean
        • Commit Log MBean
        • Compaction Manager MBean
        • Cache Service MBean
      • Cluster-Related MBeans
        • Gossiper MBean
        • Failure Detector MBean
        • Snitch MBeans
        • Stream Manager MBean
        • Messaging Service MBean
      • Internal MBeans
        • Thread Pool MBeans
        • Garbage Collection MBeans
        • Security MBeans
        • Metrics MBeans
    • Monitoring with nodetool
      • Getting Cluster Information
        • describecluster
        • status
        • info
        • ring
      • Getting Statistics
        • Using tpstats
        • Using tablestats
    • Virtual Tables
      • System Virtual Schema
      • System Views
    • Metrics
    • Logging
      • Examining Log Files
      • Full Query Logging
    • Summary
  • 12. Maintenance
    • Health Check
    • Common Maintenance Tasks
      • Flush
      • Cleanup
      • Repair
        • Full repair, incremental repair, and anti-compaction
        • Sequential and parallel repair
        • Partitioner range repair
        • Subrange repair
        • Best practices for repair
      • Rebuilding Indexes
      • Moving Tokens
    • Adding Nodes
      • Adding Nodes to an Existing Data Center
      • Adding a Data Center to a Cluster
    • Handling Node Failure
      • Repairing Failed Nodes
        • Recovering from disk failure
      • Replacing Nodes
      • Removing Nodes
        • Decommissioning a node
        • Removing a node
        • Assassinating a node
        • Removing a data center
    • Upgrading Cassandra
    • Backup and Recovery
      • Taking a Snapshot
      • Clearing a Snapshot
      • Enabling Incremental Backup
      • Restoring from Snapshot
    • SSTable Utilities
    • Maintenance Tools
      • Netflix Priam
      • DataStax OpsCenter
      • Cassandra Sidecars
      • Cassandra Kubernetes Operators
    • Summary
  • 13. Performance Tuning
    • Managing Performance
      • Setting Performance Goals
      • Benchmarking and Stress Testing
        • Using cassandra-stress
        • Additional load testing tools
      • Monitoring Performance
      • Analyzing Performance Issues
      • Tracing
      • Tuning Methodology
    • Caching
      • Key Cache
      • Row Cache
      • Chunk Cache
      • Counter Cache
      • Saved Cache Settings
    • Memtables
    • Commit Logs
    • SSTables
    • Hinted Handoff
    • Compaction
    • Concurrency and Threading
    • Networking and Timeouts
    • JVM Settings
      • Memory
      • Garbage Collection
        • Default configuration (JDK 8 or JDK 11)
        • Garbage-First garbage collector (JDK 8 or JDK 11)
        • Z Garbage Collector (JDK 11 and later)
        • Shenandoah Garbage Collector (JDK12)
    • Summary
  • 14. Security
    • Authentication and Authorization
      • Password Authenticator
        • Configuring the authenticator
        • Additional authentication providers
        • Adding users
        • Authenticating via the DataStax Java Driver
      • Using CassandraAuthorizer
      • Role-Based Access Control
    • Encryption
      • SSL, TLS, and Certificates
        • Generating Certificates for Development Clusters
        • Generating Certificates for Production Clusters
      • Node-to-Node Encryption
      • Client-to-Node Encryption
    • JMX Security
      • Securing JMX Access
      • Security MBeans
        • Authentication cache MBean
    • Audit Logging
    • Summary
  • 15. Migrating and Integrating
    • Knowing When to Migrate
    • Adapting the Data Model
      • Translating Entities
      • Translating Relationships
    • Adapting the Application
      • Refactoring Data Access
      • Maintaining Consistency
      • Migrating Stored Procedures
        • User-defined functions
        • User-defined aggregates
        • Built-in functions and aggregates
    • Planning the Deployment
    • Migrating Data
      • Zero-Downtime Migration
      • Bulk Loading
    • Common Integrations
      • Managing Data Flow with Apache Kafka
      • Searching with Apache Lucene, SOLR, and Elasticsearch
      • Analyzing Data with Apache Spark
        • Use cases for Spark with Cassandra
        • Deploying Spark with Cassandra
        • The spark-cassandra-connector
    • Summary
  • Index

Dodaj do koszyka Cassandra: The Definitive Guide, (Revised) Third Edition. 3rd Edition

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