Difference between revisions of "Data Sources Specification"

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== Deployment ==
 
== Deployment ==
Usually, a subsystem consists of a number of number of components. This section describes the setting governing components deployment, e.g. the hardware components where software components are expected to be deployed. In particular, two deployment scenarios should be discussed, i.e. Large deployment and Small deployment if appropriate. If it not appropriate, one deployment diagram has to be produced.  
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Data Sources are deployed over [https://gcore.wiki.gcube-system.org/gCube/index.php/Main_Page gCore] containers. The [[gRS2]] pipelining mechanism must also be part of the node.  
  
 
=== Large deployment ===
 
=== Large deployment ===

Revision as of 21:47, 2 March 2012

Overview

The Data Sources Subsystem constitutes the framework we provide in order to integrate heterogeneous data from different providers in our Information Retrieval(IR) process. Using an Indexing Layer and the OpenSearch standard, Data Sources framework provides fast access and direct connection to the information hosted in the heterogeneous environment.

Key features

Unification of heterogenous Data and different IR capabilities
Using the CQL standard, different gCube IR providers that host data with diverse representations and semantics, can be involved the overall IR process.
Indexing Layer for advanced IR functionality
Full-text retrieval, Multidimensional Range queries and Spatiotemporal search functionality
Access to the information hosted by external Providers
External providers can provide their results during the IR process through the OpenSearch standard.

Design

Philosophy

The Data Sources framework is implemented in order to:

  • simplify the integration of different IR providers in the gCube IR framework, using the appropriate standards.
  • provide Replication and High Availability through a distributed architecture.
  • exploit the information and IR capabilities of external providers.

Architecture

The Data Sources framework is composed by the Index and OpenSearch Systems. The architecture is depicted in the following figure:

The Index System is designed using a distributed architecture that involves three entities:

  • Updater: An Updater instance enables the on-the-fly update on an Index partition. It applies the preprocessing steps required to transform the data to be indexed into an appropriate format.
  • Manager: A Manager instance ensures the correct synchronization and application of update actions on all the Replicas of a specific Index partition. Moreover, it handles abnormal conditions that affect the operation of the related Index partition.
  • Replica: A Replica hosts the actual data being indexed for an Index partition. It dynamically applies update actions on the index structure it maintains, without ceasing its operation.

The OpenSearch framework uses the OpenSearch specification in order to connect to external IR providers and exploit their information. A different OpenSearch instance is used to connect to each provider. In such way, the IR capabilities of external providers are published to gCube infrastructure and can be utilized by the gCube IR framework.

On the top layer of the Index and OpenSearch Sources the CQL standard provides the link to the gCube Search System. While only Index and OpenSearch Sources are internal parts of gCube, other IR providers can be wrapped as Data Sources, as long as they support CQL.

Deployment

Data Sources are deployed over gCore containers. The gRS2 pipelining mechanism must also be part of the node.

Large deployment

A deployment diagram suggesting the deployment schema that maximizes scalability should be described here.

Small deployment

A deployment diagram suggesting the "minimal" deployment schema should be described here.

Use Cases

The subsystem has been conceived to support a number of use cases moreover it will be used to serve a number of scenarios. This area will collect these "success stories".

Well suited Use Cases

Describe here scenarios where the subsystem proves to outperform other approaches.

Less well suited Use Cases

Describe here scenarios where the subsystem partially satisfied the expectations.