- Ocena:
- Bądź pierwszym, który oceni tę książkę
- Stron:
- 316
- Dostępne formaty:
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ePubMobi
Opis ebooka: Spring Data
You can choose several data access frameworks when building Java enterprise applications that work with relational databases. But what about big data? This hands-on introduction shows you how Spring Data makes it relatively easy to build applications across a wide range of new data access technologies such as NoSQL and Hadoop.
Through several sample projects, you’ll learn how Spring Data provides a consistent programming model that retains NoSQL-specific features and capabilities, and helps you develop Hadoop applications across a wide range of use-cases such as data analysis, event stream processing, and workflow. You’ll also discover the features Spring Data adds to Spring’s existing JPA and JDBC support for writing RDBMS-based data access layers.
- Learn about Spring’s template helper classes to simplify the use ofdatabase-specific functionality
- Explore Spring Data’s repository abstraction and advanced query functionality
- Use Spring Data with Redis (key/value store), HBase(column-family), MongoDB (document database), and Neo4j (graph database)
- Discover the GemFire distributed data grid solution
- Export Spring Data JPA-managed entities to the Web as RESTful web services
- Simplify the development of HBase applications, using a lightweight object-mapping framework
- Build example big-data pipelines with Spring Batch and Spring Integration
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This practical guide to implementing DeFi in your projects guides you through building full-stack DeFi solutions with popular tools and teaches you how to leverage blockchain technologies to manage crypto assets.
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The Definitive Guide to Data Integration is for data eclectics looking to explore the modern data stack. Complete with practical examples and insights, it covering tools, techniques, and best practices to unleash your data's potential.
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Ebooka "Spring Data" przeczytasz na:
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czytnikach Inkbook, Kindle, Pocketbook, Onyx Boox i innych
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systemach Windows, MacOS i innych
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systemach Windows, Android, iOS, HarmonyOS
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Audiobooka "Spring Data" posłuchasz:
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w aplikacji Ebookpoint na Android, iOS, HarmonyOs
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na systemach Windows, MacOS i innych
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na dowolnych urządzeniach i aplikacjach obsługujących format MP3 (pliki spakowane w ZIP)
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Kurs Video "Spring Data" zobaczysz:
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Szczegóły ebooka
- ISBN Ebooka:
- 978-14-493-3188-7, 9781449331887
- Data wydania ebooka:
- 2012-10-12 Data wydania ebooka często jest dniem wprowadzenia tytułu do sprzedaży i może nie być równoznaczna z datą wydania książki papierowej. Dodatkowe informacje możesz znaleźć w darmowym fragmencie. Jeśli masz wątpliwości skontaktuj się z nami sklep@ebookpoint.pl.
- Język publikacji:
- angielski
- Rozmiar pliku ePub:
- 6.2MB
- Rozmiar pliku Mobi:
- 6.2MB
Spis treści ebooka
- Spring Data
- Dedication
- Dedication
- SPECIAL OFFER: Upgrade this ebook with OReilly
- Foreword
- Preface
- Overview of the New Data Access Landscape
- How to Read This Book
- Conventions Used in This Book
- Using Code Examples
- Safari Books Online
- How to Contact Us
- Acknowledgments
- I. Background
- 1. The Spring Data Project
- NoSQL Data Access for Spring Developers
- General Themes
- The Domain
- The Sample Code
- Importing the Source Code into Your IDE
- STS/Eclipse
- IntelliJ IDEA
- Importing the Source Code into Your IDE
- 1. The Spring Data Project
- 2. Repositories: Convenient Data Access Layers
- Quick Start
- Defining Query Methods
- Query Lookup Strategies
- Query Derivation
- Property expressions
- Pagination and Sorting
- Defining Repositories
- Fine-Tuning Repository Interfaces
- Manually Implementing Repository Methods
- IDE Integration
- IntelliJ IDEA
- 3. Type-Safe Querying Using Querydsl
- Introduction to Querydsl
- Generating the Query Metamodel
- Build System Integration
- Supported Annotation Processors
- Querying Stores Using Querydsl
- Integration with Spring Data Repositories
- Executing Predicates
- Manually Implementing Repositories
- II. Relational Databases
- 4. JPA Repositories
- The Sample Project
- The Traditional Approach
- Bootstrapping the Sample Code
- Using Spring Data Repositories
- Transactionality
- Repository Querydsl Integration
- 4. JPA Repositories
- 5. Type-Safe JDBC Programming with Querydsl SQL
- The Sample Project and Setup
- The HyperSQL Database
- The SQL Module of Querydsl
- Build System Integration
- The Database Schema
- The Domain Implementation of the Sample Project
- The Sample Project and Setup
- The QueryDslJdbcTemplate
- Executing Queries
- The Beginning of the Repository Implementation
- Querying for a Single Object
- The OneToManyResultSetExtractor Abstract Class
- The CustomerListExtractor Implementation
- The Implementations for the RowMappers
- Querying for a List of Objects
- Insert, Update, and Delete Operations
- Inserting with the SQLInsertClause
- Updating with the SQLUpdateClause
- Deleting Rows with the SQLDeleteClause
- III. NoSQL
- 6. MongoDB: A Document Store
- MongoDB in a Nutshell
- Setting Up MongoDB
- Using the MongoDB Shell
- The MongoDB Java Driver
- MongoDB in a Nutshell
- Setting Up the Infrastructure Using the Spring Namespace
- The Mapping Subsystem
- The Domain Model
- Addresses and email addresses
- Customers
- Products
- Orders and line items
- The Domain Model
- Setting Up the Mapping Infrastructure
- Using the Spring namespace
- In Spring JavaConfig
- 6. MongoDB: A Document Store
- Indexing
- Customizing Conversion
- Implementing custom converters
- Registering custom converters
- MongoTemplate
- Mongo Repositories
- Infrastructure Setup
- Repositories in Detail
- Mongo Querydsl Integration
- 7. Neo4j: A Graph Database
- Graph Databases
- Neo4j
- Spring Data Neo4j Overview
- Modeling the Domain as a Graph
- Persisting Domain Objects with Spring Data Neo4j
- Neo4jTemplate
- Combining Graph and Repository Power
- Basic Graph Repository Operations
- Derived and Annotated Finder Methods
- Annotated finder methods
- Result handling
- Derived finder methods
- Advanced Graph Use Cases in the Example Domain
- Multiple Roles for a Single Node
- Product Categories and Tags as Examples for In-Graph Indexes
- Leverage Similar Interests (Collaborative Filtering)
- Recommendations
- Transactions, Entity Life Cycle, and Fetch Strategies
- Advanced Mapping Mode
- Working with Neo4j Server
- Continuing From Here
- 8. Redis: A Key/Value Store
- Redis in a Nutshell
- Setting Up Redis
- Using the Redis Shell
- Redis in a Nutshell
- Connecting to Redis
- Object Conversion
- Object Mapping
- Atomic Counters
- Pub/Sub Functionality
- Listening and Responding to Messages
- Using Springs Cache Abstraction with Redis
- IV. Rapid Application Development
- 9. Persistence Layers with Spring Roo
- A Brief Introduction to Roo
- Roos Persistence Layers
- Quick Start
- Using Roo from the Command Line
- Using Roo with Spring Tool Suite
- A Spring Roo JPA Repository Example
- Creating the Project
- Setting Up JPA Persistence
- Creating the Entities
- Defining the Repositories
- Creating the Web Layer
- Running the Example
- 9. Persistence Layers with Spring Roo
- A Spring Roo MongoDB Repository Example
- Creating the Project
- Setting Up MongoDB Persistence
- Creating the Entities
- Defining the Repositories
- Creating the Web Layer
- Running the Example
- 10. REST Repository Exporter
- The Sample Project
- Interacting with the REST Exporter
- Accessing Products
- Accessing Customers
- Accessing Orders
- The Sample Project
- V. Big Data
- 11. Spring for Apache Hadoop
- Challenges Developing with Hadoop
- Hello World
- Hello World Revealed
- Hello World Using Spring for Apache Hadoop
- Scripting HDFS on the JVM
- Combining HDFS Scripting and Job Submission
- Job Scheduling
- Scheduling MapReduce Jobs with a TaskScheduler
- Scheduling MapReduce Jobs with Quartz
- 11. Spring for Apache Hadoop
- 12. Analyzing Data with Hadoop
- Using Hive
- Hello World
- Running a Hive Server
- Using the Hive Thrift Client
- Using the Hive JDBC Client
- Apache Logfile Analysis Using Hive
- Using Hive
- Using Pig
- Hello World
- Running a PigServer
- Controlling Runtime Script Execution
- Calling Pig Scripts Inside Spring Integration Data Pipelines
- Apache Logfile Analysis Using Pig
- Using HBase
- Hello World
- Using the HBase Java Client
- 13. Creating Big Data Pipelines with Spring Batch and Spring Integration
- Collecting and Loading Data into HDFS
- An Introduction to Spring Integration
- Copying Logfiles
- Event Streams
- Event Forwarding
- Management
- An Introduction to Spring Batch
- Processing and Loading Data from a Database
- Collecting and Loading Data into HDFS
- Hadoop Workflows
- Spring Batch Support for Hadoop
- Wordcount as a Spring Batch Application
- Hive and Pig Steps
- Exporting Data from HDFS
- From HDFS to JDBC
- From HDFS to MongoDB
- Collecting and Loading Data into Splunk
- VI. Data Grids
- 14. GemFire: A Distributed Data Grid
- GemFire in a Nutshell
- Caches and Regions
- How to Get GemFire
- Configuring GemFire with the Spring XML Namespace
- Cache Configuration
- Region Configuration
- Cache Client Configuration
- Cache Server Configuration
- WAN Configuration
- Disk Store Configuration
- Data Access with GemfireTemplate
- Repository Usage
- POJO Mapping
- Creating a Repository
- PDX Serialization
- 14. GemFire: A Distributed Data Grid
- Continuous Query Support
- Bibliography
- Index
- About the Authors
- Colophon
- SPECIAL OFFER: Upgrade this ebook with OReilly
- Copyright
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- cena książki może być wyższa od początkowej ceny detalicznej, co jest spowodowane kosztami druku cyfrowego (wyższymi niż koszty tradycyjnego druku offsetowego). Obowiązująca cena jest zawsze podawana na stronie WWW książki;
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Książka drukowana
Oceny i opinie klientów: Spring Data Mark Pollack, Oliver Gierke, Thomas Risberg (0) Weryfikacja opinii następuję na podstawie historii zamówień na koncie Użytkownika umieszczającego opinię. Użytkownik mógł otrzymać punkty za opublikowanie opinii uprawniające do uzyskania rabatu w ramach Programu Punktowego.