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Admittedly, figure 1.3 is a little overwhelming at first glance. Take a moment to scan over
the diagram to get a feel for some of the terminology. Don’t worry if you’re not familiar with
all of the terms and concepts represented in the diagram--after reading this book, you
should have a strong understanding of the all concepts presented in figure 1.3.
As we mentioned in the introduction to this chapter, the Solr designers recognized that
Solr fits better as a complementary technology that works within existing architectures. In
fact, you’ll be hard-pressed to find an environment where Solr doesn't drop right in. As we'll
see in chapter 2, you can start the example Solr server in a couple of minutes after you
finish the download.
To achieve the goal of easy integration, Solr’s core services need to be accessible from
many different applications and languages. Solr provides simple REST-like services based on
proven standards of XML, JSON, and HTTP. As a brief aside, we avoid the “RESTful” label for
Solr’s HTTP-based API as it doesn’t strictly adhere to all REST (representational state
transfer) principles. For instance, in Solr you use HTTP POST to delete documents instead of
HTTP DELETE.
A REST-like interface is nice as a foundation, but often times, developers like to have
access to a client library in their language of choice to abstract away some of the boilerplate
machinery of invoking a web service and processing the response. The good news here is
that most popular languages have a Solr client library including Python, PHP, Java, .NET, and
Ruby.
1.2.4 Multiple indexes in one server
One hallmark of modern application architectures is the need for flexibility in the face of
rapidly changing requirements. One of the ways Solr helps this situation is that you don’t
have to do all things in Solr with one index, because Solr supports running multiple cores in
a single engine. In figure 1.3, we’ve depicted multiple cores as separate layers all running in
the same Java web application environment.
Think of each core as a separate index and configuration and there can be many cores in
a single Solr instance. This allows you to manage multiple cores from one server so that you
can share server resources and administration tasks like monitoring and maintenance. Solr
provides an API for creating and managing multiple cores.
One use of Solr’s multicore support is data partitioning, such as having one core for
recent documents and another core for older documents, known as chronological sharding.
Another use of Solr’s multicore support is to support multitenant applications.
In our real estate application, we might use multiple cores to manage different types of
listings that are different enough to justify having different indexes for each. Consider real
estate listings for rural land instead of homes. Buying rural land is a different process than
buying a home in a city, so it stands to reason that we might want to manage our land
listings in a separate core.
13
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