Solr Technology Intelligence

What is Apache Solr?

Apache Solr is an open-source enterprise search platform built on Apache Lucene. It provides distributed indexing, replication, load-balanced querying, automated failover and recovery, and centralized configuration. Solr powers search and navigation features for many of the world's largest websites.

Originally created at CNET Networks in 2004 and donated to the Apache Software Foundation in 2006, Solr has become one of the most popular search engines for websites and applications. It handles full-text search, hit highlighting, faceted search, real-time indexing, dynamic clustering, and rich document handling. Major organizations including Netflix, Apple, Disney, and eBay use Solr for their search infrastructure.

Key Features

Search Capabilities

• Full-Text Search: Advanced text analysis and relevance scoring
• Faceted Search: Dynamic filtering with count aggregations
• Hit Highlighting: Show matching terms in context
• Spell Checking: Suggestions for misspelled queries
• More Like This: Find similar documents
• Geospatial Search: Location-based queries and filtering

Text Analysis

• Tokenizers: Split text into searchable terms
• Filters: Lowercase, stemming, synonyms, stop words
• Language Support: Analysis chains for many languages
• Phonetic Matching: Sound-alike search

Scalability

• SolrCloud: Distributed indexing and search
• Sharding: Split indexes across nodes
• Replication: High availability through copies
• ZooKeeper: Cluster coordination

Administration

• Web-based admin interface
• RESTful APIs for all operations
• Schema management and field types
• Request handlers and query parsers

Use Cases

E-commerce Product Search

Online retailers use Solr to power product search with faceted navigation. Customers filter by price, brand, size, and attributes while seeing result counts. Relevance tuning ensures popular and relevant products appear first.

Enterprise Document Search

Organizations index internal documents, wikis, and knowledge bases. Full-text search across PDFs, Word documents, and web pages helps employees find information. Access controls integrate with enterprise identity systems.

Media and Publishing

News organizations and content publishers search across article archives. Real-time indexing makes new content searchable immediately. Facets help users browse by date, author, category, and topic.

Log Analysis

IT teams index application logs for analysis and troubleshooting. The ability to search across millions of log entries with field-level filtering accelerates incident response.

Geolocation Services

Location-based applications use Solr's geospatial features. Store finders, real estate search, and delivery services query by distance, bounding boxes, and geographic regions.

Academic and Research

Libraries and research institutions provide search across digital collections. Citation databases, research papers, and archival materials become discoverable through structured and full-text search.

Code Examples

Schema Definition

<!-- schema.xml field definitions -->
<field name="id" type="string" indexed="true" stored="true" required="true"/>
<field name="title" type="text_general" indexed="true" stored="true"/>
<field name="description" type="text_general" indexed="true" stored="true"/>
<field name="price" type="pfloat" indexed="true" stored="true"/>
<field name="category" type="string" indexed="true" stored="true" multiValued="true"/>
<field name="location" type="location" indexed="true" stored="true"/>

<!-- Copy field for catch-all search -->
<copyField source="title" dest="text"/>
<copyField source="description" dest="text"/>

Indexing Documents

# Add documents via JSON
curl -X POST "http://localhost:8983/solr/products/update?commit=true" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "id": "prod-001",
      "title": "Wireless Headphones",
      "description": "Premium noise-canceling headphones",
      "price": 299.99,
      "category": ["electronics", "audio"],
      "location": "40.7128,-74.0060"
    }
  ]'

Search Queries

# Full-text search with facets
curl "http://localhost:8983/solr/products/select?q=headphones&
  fq=price:[100 TO 500]&
  facet=true&
  facet.field=category&
  fl=id,title,price,score&
  sort=score desc"

# Geospatial search
curl "http://localhost:8983/solr/stores/select?q=*:*&
  fq={!geofilt sfield=location}&
  pt=40.7128,-74.0060&
  d=10&
  sort=geodist() asc"

PHP Solarium Client

use Solarium\Client;

$client = new Client(['endpoint' => [
    'localhost' => ['host' => 'localhost', 'port' => 8983, 'path' => '/solr/products']
]]);

$query = $client->createSelect();
$query->setQuery('wireless headphones');
$query->addFilterQuery(['key' => 'price', 'query' => 'price:[0 TO 300]']);
$query->getFacetSet()->createFacetField('category');

$results = $client->select($query);
foreach ($results as $document) {
    echo $document->title . ' - $' . $document->price;
}

Comparison and Deployment

Solr vs Elasticsearch

• History: Solr older (2004), Elasticsearch newer (2010)
• Schema: Solr schema-based, Elasticsearch schema-less default
• Configuration: Solr XML files, Elasticsearch JSON APIs
• Ecosystems: Elastic has Kibana stack, Solr integrates with Hadoop
• Both: Built on Lucene, similar core capabilities

Deployment Options

• Standalone: Single server for development and small deployments
• SolrCloud: Distributed cluster with ZooKeeper
• Docker: Official container images available
• Managed: SearchStax, AWS CloudSearch alternatives

Integration Ecosystem

• Data Import: Database, file system, and HTTP sources
• Clients: SolrJ (Java), Solarium (PHP), pysolr (Python)
• CMS Integration: Drupal, WordPress, Magento plugins
• Big Data: Hadoop, Spark connectors

Best Practices

• Design schema based on query patterns
• Use SolrCloud for production scalability
• Implement request handlers for different use cases
• Monitor query performance and optimize slow queries
• Plan replication for high availability