From 2bbd9132b8a377b4a16d2fca7406bda38b4828a1 Mon Sep 17 00:00:00 2001 From: David Montag Date: Wed, 13 Apr 2011 14:22:07 -0700 Subject: [PATCH] Removed unused files. --- src/docbkx/introduction/get-started.xml | 93 ------------------------ src/docbkx/introduction/introduction.xml | 14 ---- src/docbkx/introduction/requirements.xml | 18 ----- src/docbkx/introduction/why-sd-graph.xml | 39 ---------- 4 files changed, 164 deletions(-) delete mode 100644 src/docbkx/introduction/get-started.xml delete mode 100644 src/docbkx/introduction/introduction.xml delete mode 100644 src/docbkx/introduction/requirements.xml delete mode 100644 src/docbkx/introduction/why-sd-graph.xml diff --git a/src/docbkx/introduction/get-started.xml b/src/docbkx/introduction/get-started.xml deleted file mode 100644 index 47f259c05..000000000 --- a/src/docbkx/introduction/get-started.xml +++ /dev/null @@ -1,93 +0,0 @@ - - - - Getting Started - - NOSQL databases have only recently come to prominence, even though some of them have existed for a few years now. - That's why this document will not only guide you through the relevant parts of the Spring Data Graph - API, but also explain some key concepts of graph databases. - - - After reading this document, you should be able to integrate Spring Data Graph into your applications. - If there are any inaccuracies, issues or if you just think the explanations are too complicated, please feed that back to us. Your input will also benefit future readers of this documentation. For details on how to get help - and provide feedback, see . - - -
- First Steps - - As explained in , Spring Data Graph provides integration - between the Spring framework and graph databases. As we said in the introduction , familiarity with the Spring framework is assumed to get the most out of this book. - But we will explain graph databases and Neo4j in particular in a little more detail. - The main focus of this document is to explain the steps needed to get an interesting Spring Data Graph application up and running. - - -
- Knowing Spring - Spring Data Graph makes heavy use of Spring Framework's core functionality, - such as the IoC container, - converter API and the - AOP infrastructure. While it is less important - to know the Spring APIs, understanding the concepts behind them is essential. - The Spring Framework documentation - home page is a good starting point for - developers who want to become more familiar with the Spring Framework. -
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- Knowing NOSQL and graph databases - The recent interest in NOSQL databases has been driven by the need to find the better storage solutions for different kinds of data and access patterns. The NOSQL mantra is that databases should fit the data, not the other way round. - The NOSQL space is overflowing with interesting and useful technology. But as a consequence, each store tends to implement its own data access API, leading to a steep learning curve for developers intent on using polyglot persistence. Spring Data aims to ease this burden by - providing consistent abstractions over those underlying data access APIs. - - - Graph databases are a particularly good fit for large networks of connected information (objects). They map objects to nodes and connections to - relationships. Examples of such datasets are social networks, geospatial information, network layouts, and hardware or dependency graphs. - Neo4j is the first graph database that is tightly integrated with the Spring Data Graph project. - -
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- Trying Out The Samples - Spring Data Graph comes with a number of samples - and unit test cases (if you accessed the sources via - github or Maven). - - For more information on the samples, see . -
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- Need Help? - - If you encounter issues or you are just looking for advice, feel free to use one of the links below: - -
- Spring Data homepage - The Spring Data homepage provides all the necessary links for information, community forums and code repositories. - -
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- Professional Support - Professional, from-the-source support, with guaranteed response time, is available from SpringSource, - the company behind Spring Data and the Spring Framework. - -
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- Follow the Development - - For information on the Spring Data source code repository, nightly builds and snapshot artifacts please see the Spring Data home - page. - - You can help make Spring Data better serve the needs of the Spring community by interacting with developers through the - community forums. - If you find a bug or want to suggest an improvement, - please create a ticket on the Spring Data Graph issue tracker. - To stay up to date with the latest news and announcements in the Spring eco system, subscribe to the - Spring Community Portal. - Lastly, you can follow the SpringSource Data blog or the project team on Twitter - (@SpringData) -
- - diff --git a/src/docbkx/introduction/introduction.xml b/src/docbkx/introduction/introduction.xml deleted file mode 100644 index 6d4495a35..000000000 --- a/src/docbkx/introduction/introduction.xml +++ /dev/null @@ -1,14 +0,0 @@ - - - - - - This document is the reference guide for Spring Data Graph. - It explains the underlying concepts, usage, infrastructure of the framework and the behaviour of the underlying graph database. - - - For an introduction to graph databases, Spring, or Spring Data examples, please refer to - . This documentation refers only to Spring Data Graph and - assumes that the reader is familiar with Spring concepts. - diff --git a/src/docbkx/introduction/requirements.xml b/src/docbkx/introduction/requirements.xml deleted file mode 100644 index cb016d702..000000000 --- a/src/docbkx/introduction/requirements.xml +++ /dev/null @@ -1,18 +0,0 @@ - - - - Requirements - - Spring Data Graph 1.x requires JDK level 6.0 or higher, - and Spring Framework - 3.0.x or higher. - - For the graph database, Neo4j 1.2 or higher is required. - Neo4j has a dependency on Apache Lucene for indexing. Users are encouraged to use the latest version of Neo4j - available. - - - For building the project, Apache Maven (version 2.10 and above) is recommended. - - diff --git a/src/docbkx/introduction/why-sd-graph.xml b/src/docbkx/introduction/why-sd-graph.xml deleted file mode 100644 index 1a932be31..000000000 --- a/src/docbkx/introduction/why-sd-graph.xml +++ /dev/null @@ -1,39 +0,0 @@ - - - - Why Spring Data Graph? - - NOSQL - stores provide novel storage solutions to suit the - data storage requirements of modern applications. - - - Graph databases provide excellent support for connected data - that is data that easily can - be structured as connected nodes in a network. - Property graph databases like Neo4j support an arbitrary number of named properties on - nodes and relationships. Neo4j is highly performant when traversing large, highly-connected datasets with - millions of nodes and relationships, even on commodity hardware. - - - Neo4j is an open source graph database written in Java. It has excellent performance characteristics while providing ACID - semantics and full transactional support (both JTA and XA transactions). Neo4j can run as a lightweight embedded database as well as a standalone - server that exposes the API via a rich REST interface. - - - The Spring Data Graph framework makes it easy to - integrate graph databases in existing or new Spring applications. It provides - infrastructure that reduces boilerplate data access code and uses - common patterns and idioms that are well-known in the Spring community, such as declarative transaction management. - Those practices are based on a simple POJO programming model that leverages - annotations to add metadata. It can be integrated in any part of a Spring application, - including the Web or service layers. - - - A special use case of Spring Data Graph is the cross-store functionality that can extend - existing JPA data models with new, graph database backed parts (properties, entities, relationships). - These parts are stored exclusively in the graph database while being transparently - integrated with the JPA entities. This enables easy and seamless addition of new features - that have not been available to JPA-based applications previously. - -