Introduction to The Solr Enterprise Search Server

Introduction to The Solr Enterprise Search Server

Solr in a Nutshell


Solr is a standalone enterprise search server with a web-services like API. You put documents in it (called “indexing”) via XML over HTTP. You query it via HTTP GET and receive XML results.



  • Advanced Full-Text Search Capabilities
  • Optimized for High Volume Web Traffic
  • Standards Based Open Interfaces – XML and HTTP
  • Comprehensive HTML Administration Interfaces
  • Scalability – Efficient Replication to other Solr Search Servers
  • Flexible and Adaptable with XML configuration
  • Extensible Plugin Architecture

Solr Uses the Lucene Search Library and Extends it!




  • A Real Data Schema, with Dynamic Fields, Unique Keys
  • Powerful Extensions to the Lucene Query Language
  • Support for Dynamic Result Grouping and Filtering
  • Advanced, Configurable Text Analysis
  • Highly Configurable and User Extensible Caching
  • Performance Optimizations
  • External Configuration via XML
  • An Administration Interface
  • Monitorable Logging
  • Fast Incremental Updates and Snapshot Distribution

Detailed Features


Schema




  • Defines the field types and fields of documents
  • Can drive more intelligent processing
  • Declarative Lucene Analyzer specification
  • Dynamic Fields enables on-the-fly addition of fields
  • CopyField functionality allows indexing a single field multiple ways, or combining multiple fields into a single searchable field
  • Explicit types eliminates the need for guessing types of fields
  • External file-based configuration of stopword lists, synonym lists, and protected word lists

Query



  • HTTP interface with configurable response formats (XML/XSLT, JSON, Python, Ruby)
  • Highlighted context snippets
  • Faceted Searching based on field values and explicit queries
  • Sort specifications added to query language
  • Constant scoring range and prefix queries – no idf, coord, or lengthNorm factors, and no restriction on the number of terms the query matches.
  • Function Query – influence the score by a function of a field’s numeric value or ordinal
  • Performance Optimizations

Core



  • Pluggable query handlers and extensible XML data format
  • Document uniqueness enforcement based on unique key field
  • Batches updates and deletes for high performance
  • User configurable commands triggered on index changes
  • Searcher concurrency control
  • Correct handling of numeric types for both sorting and range queries
  • Ability to control where docs with the sort field missing will be placed
  • Support for dynamic grouping of search results

Caching



  • Configurable Query Result, Filter, and Document cache instances
  • Pluggable Cache implementations
  • Cache warming in background

    • When a new searcher is opened, configurable searches are run against it in order to warm it up to avoid slow first hits. During warming, the current searcher handles live requests.

  • Autowarming in background

    • The most recently accessed items in the caches of the current searcher are re-populated in the new searcher, enabing high cache hit rates across index/searcher changes.

  • Fast/small filter implementation
  • User level caching with autowarming support

Replication



  • Efficient distribution of index parts that have changed via rsync transport
  • Pull strategy allows for easy addition of searchers
  • Configurable distribution interval allows tradeoff between timeliness and cache utilization

Admin Interface



  • Comprehensive statistics on cache utilization, updates, and queries
  • Text analysis debugger, showing result of every stage in an analyzer
  • Web Query Interface w/ debugging output

    • parsed query output
    • Lucene explain() document score detailing
    • explain score for documents outside of the requested range to debug why a given document wasn’t ranked higher.

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