Getting started with Apache Solr Search Server shows you how to implement the world’s leading open-source search solution with advice from an expert in the field. You will discover Solr’s many hidden features via interactive learning and configure your own Solr instance according to your business needs. This course can be followed along at home with an open-source web application you can download and run. Make search interactive and proactive with faceting, match highlighting, spell-checking, and result grouping.
Getting started with Apache Solr Search Server uses a combination of walk throughs and interactive exercises to impart end-to-end understanding of Solr’s role in a web application’s ecosystem.
You will first learn how to install Solr on your machine, configure it according to the data structures you need to search over, and integrate it into your application. This video course shows the viewer how to use, activate, and configure Solr’s many features. To keep the course interactive, an open-source example is included with detail on how to integrate Solr into an application, ranging from simple querying to advanced grouping and faceting.
Enterprise Search for Apache Solr empowers you to become your organization’s search guru with expertise in search.
Robert Elwell is a search expert living in the San Francisco Bay Area, where he currently works for Wikia. He has an M.A. in Linguistics from the University of Texas at Austin, where he studied machine learning, information retrieval, and discourse parsing. Robert’s enthusiasm for a variety of topics in web application development and computational linguistics are documented at his personal website
This video introduces you to what this course is all about and who it is for.
Understand the basic mechanics behind Solr.
There are simpler cases where Solr may not be necessary. We evaluate situations that would merit Solr's robustness
Getting Solr downloaded and running can be tricky. You'll learn where to get it and how to start it.
The Admin interface can be complicated. Get to know where to go to make changes as users.
You need to know how to work with the schema file to set up your search solution. See where the schema file is located and learn how to alter it.
It's useful to be able to review your changes on a given Solr host. The config file link makes that easy.
Sometimes we need some graphical information about what's in our index. The schema browser shows this to us.
It's useful to know certain aspects of your index or Solr instance without querying the index or reading XML.
We need to get data into our index. Solr allows updating through HTTP end points.
Some documents need to be updated or removed. Solr handles updation using unique IDs, and removal by using a query.
There's a high cost for constructing XML-based queries in Solr for updates. The Data Import Handler allows us to put data into the search engine with less development effort.
Querying the index requires knowledge of Lucene's query syntax. We provide an outline of its core behaviors.
In order to use the response data, we need to know where to look for it. The response is neatly divided into informative groups.
We need additional control over our results rather than just querying for the entire result set. Additional query parameters allow for these options.
User queries can be difficult to parse into Lucene's query syntax. The Dismax query parser provides a robust solution for user-provided queries.
Properly defining a schema requires understanding what field types are already available. We review the off-the-shelf field types available for creating new schema fields.
It's difficult to identify what kind of analyzers and filters should be used when creating a new field type. We explain how they work and where to implement them.
For an effective search, we must define an appropriate document schema. We describe the example schema to give a stronger understanding of how to properly define a document for your needs.
Some use cases (particularly i18n) require creating new field types and schema fields. We show how to do this in the schema file.
Getting your search solution right sometimes requires configuring certain components of your Solr install. We show you where to go and what options are available.
Knowing how to access certain capabilities of Solr requires understanding what a request handler is and how it works. We outline them here.
Many request handlers are introduced by default in the config.xml file. We examine them and explain what they do.
Solr has a number of request handlers available but not defined in config.xml. Learn how to access them.
We want to create a site that allows us to search and compare beers. We will use Django and Solr to build a web app.
We need to not only be able to search and compare beer, but also group by breweries. We create a schema that is sensitive to these business requirements.
Some data can be grouped by certain facets. We show an implementation of faceting for an example use case.
Our business requirements indicate a need to recommend similar beers. We use the MoreLikeThis component to accomplish this easily.
One way of delivering results is to group by unique terms in a given field. We show how this is accomplished using facet grouping.
Highlighting relevant text from a search can be difficult. We show how Solr makes it easy using the built-in highlighting parameters.
Search queries can include typos. Solr Spelling Suggest allows for robust handling of this.
Sometimes we want to recover what terms make a document interesting. The MoreLikeThis handler accomplishes this.
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