The main focus of this book will be a gradual introduction to Solr that can be used by a beginner without too much code at the beginning, even if we will introduce some coding near the end. In this approach, I hope that you'll find the chance to share what you read and your ideas with your teammates also if you want, and hopefully you'll have the freedom to find your own way of adopting this technology.

I would also like to suggest the adoption of Solr at an earlier stage of development, as a prototype tool. We will see that indexing data is easy; it doesn't matter if we do not have a final design for our data model yet. Hence, providing filters and faceting capabilities that can be adopted at the beginning of the user experience design. A Solr configuration can be improved at every stage of an incremental development (not necessarily when all the actual data already exists, as you might think), without "breaking" functionalities and giving us a fast view of the data that is near to the user perspective. This can be useful to construct a working preview for our customers, which is flexible enough to be improved fast later.

In order to use the scripts available in the repository for the book examples that we will use in the next chapters, we have defined a SOLR_DIST environment variable that will be available for some useful scripts you will find in the repository. The code can be downloaded as a zipped package from https://bitbucket.org/seralf/solrstarterbook. If you are familiar with Mercurial, you can download it directly as the source. We will use some of the scripts used to download the toy data for our indexing tests that are written using the Scala language. So, you can directly add the Scala library to the system CLASSPATH variable for you convenience, although it's not needed. We will discuss our scripts and example later in Chapter 3, Indexing Example Data from DBpedia – Paintings.