Sunspot is a Ruby library for expressive, powerful interaction with the Solr search engine. Sunspot is built on top of the RSolr library, which provides a low-level interface for Solr interaction; Sunspot provides a simple, intuitive, expressive DSL backed by powerful features for indexing objects and searching for them.
Sunspot is designed to be easily plugged in to any ORM, or even non-database-backed objects such as the filesystem.
This README provides a high level overview; class-by-class and method-by-method documentation is available in the API reference.
For questions about how to use Sunspot in your app, please use the Sunspot Mailing List or search Stack Overflow.
Add to Gemfile:
gem'sunspot_rails'gem'sunspot_solr'# optional pre-packaged Solr distribution for use in development. Not for use in production.Bundle it!
bundle installGenerate a default configuration file:
rails generate sunspot_rails:installIf sunspot_solr was installed, start the packaged Solr distribution
with:
bundle exec rake sunspot:solr:start # or sunspot:solr:run to start in foregroundThis will generate a /solr folder with default configuration files and indexes.
If you're using source control, it's recommended that the files generated for indexing and running (PIDs) are not checked in. You can do this by adding the following lines to .gitignore:
solr/data
solr/test/data
solr/development/data
solr/default/data
solr/pids
Add a searchable block to the objects you wish to index.
classPost < ActiveRecord::Basesearchabledotext:title,:bodytext:commentsdocomments.map{ |comment| comment.body}endboolean:featuredinteger:blog_idinteger:author_idinteger:category_ids,:multiple=>truedouble:average_ratingtime:published_attime:expired_atstring:sort_titledotitle.downcase.gsub(/^(an?|the)/,'')endendendtext fields will be full-text searchable. Other fields (e.g.,
integer and string) can be used to scope queries.
Post.searchdofulltext'best pizza'with:blog_id,1with(:published_at).less_thanTime.nowfield_list:blog_id,:titleorder_by:published_at,:descpaginate:page=>2,:per_page=>15facet:category_ids,:author_idendGiven an object Post setup in earlier steps ...
# All posts with a `text` field (:title, :body, or :comments) containing 'pizza'Post.search{fulltext'pizza'}# Posts with pizza, scored higher if pizza appears in the titlePost.searchdofulltext'pizza'doboost_fields:title=>2.0endend# Posts with pizza, scored higher if featuredPost.searchdofulltext'pizza'doboost(2.0){with(:featured,true)}endend# Posts with pizza *only* in the titlePost.searchdofulltext'pizza'dofields(:title)endend# Posts with pizza in the title (boosted) or in the body (not boosted)Post.searchdofulltext'pizza'dofields(:body,:title=>2.0)endendSolr allows searching for phrases: search terms that are close together.
In the default query parser used by Sunspot (edismax), phrase searches are represented as a double quoted group of words.
# Posts with the exact phrase "great pizza"Post.searchdofulltext'"great pizza"'endIf specified, query_phrase_slop sets the number of words that may appear between the words in a phrase.
# One word can appear between the words in the phrase, so "great big pizza"# also matches, in addition to "great pizza"Post.searchdofulltext'"great pizza"'doquery_phrase_slop1endendPhrase boosts add boost to terms that appear in close proximity; the terms do not have to appear in a phrase, but if they do, the document will score more highly.
# Matches documents with great and pizza, and scores documents more# highly if the terms appear in a phrase in the title fieldPost.searchdofulltext'great pizza'dophrase_fields:title=>2.0endend# Matches documents with great and pizza, and scores documents more# highly if the terms appear in a phrase (or with one word between them)# in the title fieldPost.searchdofulltext'great pizza'dophrase_fields:title=>2.0phrase_slop1endendFields not defined as text (e.g., integer, boolean, time,
etc...) can be used to scope (restrict) queries before full-text
matching is performed.
# Posts with a blog_id of 1Post.searchdowith(:blog_id,1)end# Posts with an average rating between 3.0 and 5.0Post.searchdowith(:average_rating,3.0..5.0)end# Posts with a category of 1, 3, or 5Post.searchdowith(:category_ids,[1,3,5])end# Posts published since a week agoPost.searchdowith(:published_at).greater_than(1.week.ago)end# Posts not in category 1 or 3Post.searchdowithout(:category_ids,[1,3])end# All examples in "positive" also work negated using `without`# Passing an empty array is equivalent to a no-op, allowing you to replace this...Post.searchdowith(:category_ids,id_list)ifid_list.present?end# ...with thisPost.searchdowith(:category_ids,id_list)end# Posts with a blog_id of 1Post.searchdowith(:blog_id,1)field_list[:title]endPost.searchdowithout(:category_ids,[1,3])field_list[:title,:author_id]end# Posts that do not have an expired time or have not yet expiredPost.searchdoany_ofdowith(:expired_at).greater_than(Time.now)with(:expired_at,nil)endend# Posts with blog_id 1 and author_id 2Post.searchdoall_ofdowith(:blog_id,1)with(:author_id,2)endend# Posts scoring with any of the two fields.Post.searchdoanydofulltext"keyword1",:fields=>:titlefulltext"keyword2",:fields=>:bodyendendDisjunctions and conjunctions may be nested
Post.searchdoany_ofdowith(:blog_id,1)all_ofdowith(:blog_id,2)with(:category_ids,3)endendanydoalldofulltext"keyword",:fields=>:titlefulltext"keyword",:fields=>:bodyendalldofulltext"keyword",:fields=>:first_namefulltext"keyword",:fields=>:last_nameendfulltext"keyword",:fields=>:descriptionendendScopes/restrictions can be combined with full-text searching. The scope/restriction pares down the objects that are searched for the full-text term.
# Posts with blog_id 1 and 'pizza' in the titlePost.searchdowith(:blog_id,1)fulltext("pizza")endAll results from Solr are paginated
The results array that is returned has methods mixed in that allow it to operate seamlessly with common pagination libraries like will_paginate and kaminari.
By default, Sunspot requests the first 30 results from Solr.
search=Post.searchdofulltext"pizza"end# Imagine there are 60 *total* results (at 30 results/page, that is two pages)results=search.results# => Array with 30 Post elementssearch.total# => 60results.total_pages# => 2results.first_page?# => trueresults.last_page?# => falseresults.previous_page# => nilresults.next_page# => 2results.out_of_bounds?# => falseresults.offset# => 0To retrieve the next page of results, recreate the search and use the
paginate method.
search=Post.searchdofulltext"pizza"paginate:page=>2end# Again, imagine there are 60 total results; this is the second pageresults=search.results# => Array with 30 Post elementssearch.total# => 60results.total_pages# => 2results.first_page?# => falseresults.last_page?# => trueresults.previous_page# => 1results.next_page# => nilresults.out_of_bounds?# => falseresults.offset# => 30A custom number of results per page can be specified with the
:per_page option to paginate:
search=Post.searchdofulltext"pizza"paginate:page=>1,:per_page=>50endSolr 4.7 and above
With default Solr pagination it may turn that same records appear on different pages (e.g. if many records have the same search score). Cursor-based pagination allows to avoid this.
Useful for any kinds of export, infinite scroll, etc.
Cursor for the first page is "*".
search=Post.searchdofulltext"pizza"paginate:cursor=>"*"endresults=search.results# Results will contain cursor for the next pageresults.next_page_cursor# => "AoIIP4AAACxQcm9maWxlIDEwMTk="# Imagine there are 60 *total* results (at 30 results/page, that is two pages)results.current_cursor# => "*"results.total_pages# => 2results.first_page?# => trueresults.last_page?# => falseTo retrieve the next page of results, recreate the search and use the paginate method with cursor from previous results.
search=Post.searchdofulltext"pizza"paginate:cursor=>"AoIIP4AAACxQcm9maWxlIDEwMTk="endresults=search.results# Again, imagine there are 60 total results; this is the second pageresults.next_page_cursor# => "AoEsUHJvZmlsZSAxNzY5"results.current_cursor# => "AoIIP4AAACxQcm9maWxlIDEwMTk="results.total_pages# => 2results.first_page?# => false# Last page will be detected only when current page contains less then per_page elements or contains nothingresults.last_page?# => false:per_page option is also supported.
Faceting is a feature of Solr that determines the number of documents that match a given search and an additional criterion. This allows you to build powerful drill-down interfaces for search.
Each facet returns zero or more rows, each of which represents a particular criterion conjoined with the actual query being performed. For field facets, each row represents a particular value for a given field. For query facets, each row represents an arbitrary scope; the facet itself is just a means of logically grouping the scopes.
By default Sunspot will only return the first 100 facet values. You can increase this limit, or force it to return all facets by setting limit to -1.
# Posts that match 'pizza' returning counts for each :author_idsearch=Post.searchdofulltext"pizza"facet:author_idendsearch.facet(:author_id).rows.eachdo |facet|
puts"Author #{facet.value} has #{facet.count} pizza posts!"endIf you are searching by a specific field and you still want to see all the options available in that field you can exclude it in the faceting.
# Posts that match 'pizza' and author with id 42# Returning counts for each :author_id (even those not in the search result)search=Post.searchdofulltext"pizza"author_filter=with(:author_id,42)facet:author_id,exclude: [author_filter]endsearch.facet(:author_id).rows.eachdo |facet|
puts"Author #{facet.value} has #{facet.count} pizza posts!"end# Posts faceted by ranges of average ratingssearch=Post.searchdofacet(:average_rating)dorow(1.0..2.0)dowith(:average_rating,1.0..2.0)endrow(2.0..3.0)dowith(:average_rating,2.0..3.0)endrow(3.0..4.0)dowith(:average_rating,3.0..4.0)endrow(4.0..5.0)dowith(:average_rating,4.0..5.0)endendend# e.g.,# Number of posts with rating within 1.0..2.0: 2# Number of posts with rating within 2.0..3.0: 1search.facet(:average_rating).rows.eachdo |facet|
puts"Number of posts with rating within #{facet.value}: #{facet.count}"end# Posts faceted by range of average ratingsSunspot.search(Post)dofacet:average_rating,:range=>1..5,:range_interval=>1endThe json facet can be used with the following syntax:
Sunspot.search(Post)dojson_facet(:title)endThere are some options you can pass to the json facet:
:limit
:minimum_count
:sort
:prefix
:missing
:all_buckets
:method
Some examples
# limit the results to 10Sunspot.search(Post)dojson_facet(:title,limit: 10)end# returns only the results with a minimum count of 10Sunspot.search(Post)dojson_facet(:title,minimum_count: 10)end# sort by countSunspot.search(Post)dojson_facet(:title,sort: :count)end# filter titles by prefix 't'Sunspot.search(Post)dojson_facet(:title,prefix: 't')end# compute the total number of records in all buckets# accessible via search.other_count('allBuckets')search=Sunspot.search(Post)dojson_facet(:title,all_buckets: true)end# compute the total number of records that do not have a title value# accessible via search.other_count('missing')search=Sunspot.search(Post)dojson_facet(:title,missing: true)end# force usage of the dv faceting algorithmsearch=Sunspot.search(Post)dojson_facet(:title,method: 'dv')endRange facets are supported on numeric, date, or time fields. The range
parameter is required. gap may be optionally specified to control the size
of each bucket (defaults to 86400):
# minimum of 1 and maximum of 10 in steps of 3# by default the lower bound is inclusive and the upper bound is exclusive# [1-4], [4-7], [7-9], [9-10]search=Sunspot.search(Post)dojson_facet(:blog_id,range: [1,10],gap: 3)endThe other parameter may also be specified to compute additional counts besides
the ones in each bucket:
# compute total count of records with blog_id less than 1search=Sunspot.search(Post)dojson_facet(:blog_id,range: [1,10],gap: 3,other: 'before')endsearch.other_count('before')# 3# compute total count of records with blog_id 10 or greatersearch=Sunspot.search(Post)dojson_facet(:blog_id,range: [1,10],gap: 3,other: 'after')endsearch.other_count('after')# 2# compute total count of records between the specified rangesearch=Sunspot.search(Post)dojson_facet(:blog_id,range: [1,10],gap: 3,other: 'between')endsearch.other_count('between')# 4# compute before/between/after countssearch=Sunspot.search(Post)dojson_facet(:blog_id,range: [1,10],gap: 3,other: 'all')endsearch.other_count('before')# 3search.other_count('after')# 2search.other_count('between')# 4For date or time fields, you may also specify gap_unit, which controls how
gap is interpreted. A list of supported units can be found here.
Defaults to SECONDS:
# minimum of 2 years ago, maximum of 1 year ago# group into buckets of 3 months eachsearch=Sunspot.search(Post)dojson_facet(:published_at,range: [2.years.ago,1.year.ago],gap: 3,gap_unit: 'MONTHS')endThe json facet count distinct can be used with the following syntax:
# Get posts with distinct title# available stategies: :unique, :hllSunspot.search(Post)dojson_facet(:blog_id,distinct: {group_by: :title,strategy: :unique})endThe nested facets can be used with the following syntax:
Sunspot.search(Post)dojson_facet(:title,nested: {field: :author_name})endYou can nest the nested facet also recursively:
Sunspot.search(Post)dojson_facet(:title,nested: {field: :author_name,nested: {field: :title})endNested facets have the same options of json facets
By default, Sunspot orders results by "score": the Solr-determined
relevancy metric. Sorting can be customized with the order_by method:
# Order by average rating, descendingPost.searchdofulltext("pizza")order_by(:average_rating,:desc)end# Order by relevancy score and in the case of a tie, average ratingPost.searchdofulltext("pizza")order_by(:score,:desc)order_by(:average_rating,:desc)end# Randomized orderingPost.searchdofulltext("pizza")order_by(:random)endSolr 3.1 and above
Solr supports sorting on multiple fields using custom functions. Supported operators and more details are available on the Solr Wiki
To sort results by a custom function use the order_by_function method.
Functions are defined with prefix notation:
# Order by sum of two example fields: rating1 + rating2Post.searchdofulltext("pizza")order_by_function(:sum,:rating1,:rating2,:desc)end# Order by nested functions: rating1 + (rating2*rating3)Post.searchdofulltext("pizza")order_by_function(:sum,:rating1,[:product,:rating2,:rating3],:desc)end# Order by fields and constants: rating1 + (rating2 * 5)Post.searchdofulltext("pizza")order_by_function(:sum,:rating1,[:product,:rating2,'5'],:desc)end# Order by average of three fields: (rating1 + rating2 + rating3) / 3Post.searchdofulltext("pizza")order_by_function(:div,[:sum,:rating1,:rating2,:rating3],'3',:desc)endSolr 3.3 and above
Solr supports grouping documents, similar to an SQL GROUP BY. More
information about result grouping/field collapsing is available on the
Solr Wiki.
Grouping is only supported on string fields that are not
multivalued. To group on a field of a different type (e.g., integer),
add a denormalized string type
classPost < ActiveRecord::Basesearchabledo# Denormalized `string` field because grouping can only be performed# on string fieldsstring(:blog_id_str){ |p| p.blog_id.to_s}endend# Returns only the top scoring document per blog_idsearch=Post.searchdogroup:blog_id_strendsearch.group(:blog_id_str).matches# Total number of matches to the querysearch.group(:blog_id_str).groups.eachdo |group|
putsgroup.value# blog_id of the each document in the group# By default, there is only one document per group (the highest# scoring one); if `limit` is specified (see below), multiple# documents can be returned per groupgroup.results.eachdo |result|
# ...endendAdditional options are supported by the DSL:
# Returns the top 3 scoring documents per blog_idPost.searchdogroup:blog_id_strdolimit3ngroupsfalse# If you don't need the total groups counterendend# Returns document ordered within each group by published_at (by# default, the ordering is score)Post.searchdogroup:blog_id_strdoorder_by(:average_rating,:desc)endend# Facet count is based on the most relevant document of each group# matching the query (>= Solr 3.4)Post.searchdogroup:blog_id_strdotruncateendfacet:blog_id_str,:extra=>:anyendIt is also possible to group by arbitrary queries instead of on a specific field, much like using query facets instead of field facets. For example, we can group by average rating.
# Returns the top post for each range of average ratingssearch=Post.searchdogroupdoquery("1.0 to 2.0")dowith(:average_rating,1.0..2.0)endquery("2.0 to 3.0")dowith(:average_rating,2.0..3.0)endquery("3.0 to 4.0")dowith(:average_rating,3.0..4.0)endquery("4.0 to 5.0")dowith(:average_rating,4.0..5.0)endendendsearch.group(:queries).matches# Total number of matches to the queriessearch.group(:queries).groups.eachdo |group|
putsgroup.value# The argument to query - "1.0 to 2.0", for examplegroup.results.eachdo |result|
# ...endendThis can also be used to query multivalued fields, allowing a single item to be in multiple groups.
# This finds the top 10 posts for each category in category_ids.search=Post.searchdogroupdolimit10category_ids.eachdo |category_id|
querycategory_iddowith(:category_id,category_id)endendendendSunspot 2.0 only
Sunspot 2.0 supports geospatial features of Solr 3.1 and above.
Geospatial features require a field defined with latlon:
classPost < ActiveRecord::Basesearchabledo# ...latlon(:location){Sunspot::Util::Coordinates.new(lat,lon)}endend# Searches posts within 100 kilometers of (32, -68)Post.searchdowith(:location).in_radius(32, -68,100)end# Searches posts within 100 kilometers of (32, -68) with `bbox`. This is# an approximation so searches run quicker, but it may include other# points that are slightly outside of the required distancePost.searchdowith(:location).in_radius(32, -68,100,:bbox=>true)end# Searches posts within the bounding box defined by the corners (45,# -94) to (46, -93)Post.searchdowith(:location).in_bounding_box([45, -94],[46, -93])end# Orders documents by closeness to (32, -68)Post.searchdoorder_by_geodist(:location,32, -68)endSolr 4 and above
Solr joins allow you to filter objects by joining on additional documents. More information can be found on the Solr Wiki.
classPhoto < ActiveRecord::Basesearchabledotext:descriptionstring:caption,:default_boost=>1.5time:created_atinteger:photo_container_idendendclassPhotoContainer < ActiveRecord::Basesearchabledotext:namejoin(:description,:target=>Photo,:type=>:text,:join=>{:from=>:photo_container_id,:to=>:id})join(:caption,:target=>Photo,:type=>:string,:join=>{:from=>:photo_container_id,:to=>:id})join(:photos_created,:target=>Photo,:type=>:time,:join=>{:from=>:photo_container_id,:to=>:id},:as=>'created_at_d')endendPhotoContainer.searchdowith(:caption,'blah')with(:photos_created).between(Date.new(2011,3,1)..Date.new(2011,4,1))fulltext("keywords",:fields=>[:name,:description])end# ...orPhotoContainer.searchdowith(:caption,'blah')with(:photos_created).between(Date.new(2011,3,1)..Date.new(2011,4,1))anydofulltext("keyword1",:fields=>:name)fulltext("keyword2",:fields=>:description)# will be joined from the Photo modelendendclassTweet < ActiveRecord::Basesearchabledotext:keywordsinteger:profile_idendendclassRss < ActiveRecord::Basesearchabledotext:keywordsinteger:profile_idendendclassProfile < ActiveRecord::Basesearchabledotext:namejoin(:keywords,:prefix=>"tweet",:target=>Tweet,:type=>:text,:join=>{:from=>:profile_id,:to=>:id})join(:keywords,:prefix=>"rss",:target=>Rss,:type=>:text,:join=>{:from=>:profile_id,:to=>:id})endendProfile.searchdoanydofulltext("keyword1 keyword2",:fields=>[:tweet_keywords])dominimum_match1endfulltext("keyword3",:fields=>[:rss_keywords])endend# ...produces:# sort: "score desc", fl: "* score", start: 0, rows: 20,# fq: ["type:Profile"],# q: (_query_:"{!join from=profile_ids_i to=id_i v=$qTweet91755700}" OR _query_:"{!join from=profile_ids_i to=id_i v=$qRss91753840}"),# qTweet91755700: _query_:"{!field f=type}Tweet"+_query_:"{!edismax qf='keywords_text' mm='1'}keyword1 keyword2",# qRss91753840: _query_:"{!field f=type}Rss"+_query_:"{!edismax qf='keywords_text'}keyword3"SolrCloud only
If you use the compositeId router (the default), you can send documents with a prefix in
the document ID which will be used to calculate the hash Solr uses to determine the shard a
document is sent to for indexing. The prefix can be anything you’d like it to be (it doesn’t
have to be the shard name, for example), but it must be consistent so Solr behaves
consistently.
For example, if you want to co-locate documents for a customer, you could use the customer
name or ID as the prefix. If your customer is IBM, for example, with a document with the
ID 12345, you would insert the prefix into the document id field: IBM!12345.
The exclamation mark (!) is critical here, as it distinguishes the prefix used to determine
which shard to direct the document to.
classPost < ActiveRecord::Basesearchabledoid_prefix"IBM!"# ...endendThe compositeId router supports prefixes containing up to 2 levels of routing. For
example: a prefix routing first by region, then by customer: USA!IBM!12345
classPost < ActiveRecord::Basesearchabledoid_prefix"USA!IBM!"# ...endendUsage with Joins
This feature is also useful with joins, which require joined collections to
be single-sharded. For example, if you have Blog and Post models and want
to join fields from Posts when searching Blogs, you need these two collections
to stay on the same shard. In this case the configuration would be:
classBlog < ActiveRecord::Basehas_many:postssearchabledoid_prefix"BLOGDATA!"# ...endendclassPost < ActiveRecord::Basebelongs_to:blogsearchabledoid_prefix"BLOGDATA!"# ...endendAs a result, all Blogs and Posts will be stored on a single shard. But
since other Blogs will generate other prefixes Solr will distribute them
evenly across the available shards.
If you have large collections that you want to use joins with and still want to
utilize sharding instead of storing everything on a single shard, it's also
possible to only ensure a single Blog and its associated Posts stored on
a signle shard, while the whole collections could still be distributed across
multiple shards. The thing is that Solr can do distributed joins across
multiple shards, but the records that have to be joined should be stored on
a single shard. To achieve this your configuration would look like this:
classBlog < ActiveRecord::Basehas_many:postssearchabledoid_prefixdo"BLOGDATA#{self.id}!"end# ...endendclassPost < ActiveRecord::Basebelongs_to:blogsearchabledoid_prefixdo"BLOGDATA#{self.blog_id}!"end# ...endendThis way a single Blog and its Ports have the same ID prefix and will go
to a single Shard.
NOTE: Solr developers also recommend adjusting replication factor so every shard node contains replicas of all shards in the cluster. If you have 4 shards on separate nodes each of these nodes should have 4 replicas (one replica of each shard).
More information and usage examples could be found here: https://lucene.apache.org/solr/guide/6_6/shards-and-indexing-data-in-solrcloud.html
Highlighting allows you to display snippets of the part of the document that matched the query.
The fields you wish to highlight must be stored.
classPost < ActiveRecord::Basesearchabledo# ...text:body,:stored=>trueendendHighlighting matches on the body field, for instance, can be achieved
like:
search=Post.searchdofulltext"pizza"dohighlight:bodyendend# Will output something similar to:# Post #1# I really love *pizza*# *Pizza* is my favorite thing# Post #2# Pepperoni *pizza* is delicioussearch.hits.eachdo |hit|
puts"Post ##{hit.primary_key}"hit.highlights(:body).eachdo |highlight|
puts" " + highlight.format{ |word| "*#{word}*"}endendSolr can return some statistics on indexed numeric fields. Fetching statistics
for average_rating:
search=Post.searchdostats:average_ratingendputs"Minimum average rating: #{search.stats(:average_rating).min}"puts"Maximum average rating: #{search.stats(:average_rating).max}"search=Post.searchdostats:average_rating,:blog_idendIt's possible to facet field stats on another field:
search=Post.searchdostats:average_ratingdofacet:featuredendendsearch.stats(:average_rating).facet(:featured).rows.eachdo |row|
puts"Minimum average rating for featured=#{row.value}: #{row.min}"endTake care when requesting facets on a stats field, since all facet results are returned by Solr!
search=Post.searchdostats:average_ratingdojson_facet:featuredendendsearch.json_facet_stats(:featured).rows.eachdo |row|
puts"Minimum average rating for featured=#{row.value}: #{row.min}"endsearch=Post.searchdostats:average_ratingdofacet:featuredendstats:blog_iddofacet:average_ratingendendFunctions in Solr make it possible to dynamically compute values for each document. This gives you more flexability and you don't have to only deal with static values. For more details, please read Fuction Query documentation.
Sunspot supports functions in two ways:
- You can use functions to dynamically count boosting for field:
#Posts with pizza, scored higher (square promotion field) if is_promotedPost.searchdofulltext'pizza'doboost(function{sqrt(:promotion)}){with(:is_promoted,true)}end# adds boost query (bq parameter)boost(0.5)dowith(:is_promoted,true)end# adds a boost function (bf parameter)boost(function{sqrt(:promotion)})# adds a multiplicative boost function (boost parameter)boost_multiplicative(function{sqrt(:promotion)})end- You're able to use functions for ordering (see examples for order_by_function)
Atomic Updates is a feature in Solr 4.0 that allows you to update on a field level rather than on a document level. This means that you can update individual fields without having to send the entire document to Solr with the un-updated fields values. For more details, please read Atomic Update documentation.
All fields of the model must be stored, otherwise non-stored values will be lost after an update.
classPost < ActiveRecord::Basesearchabledo# all fields storedtext:body,:stored=>truestring:title,:stored=>trueendendpost1=Post.create#...post2=Post.create#...# atomic update on class levelPost.atomic_updatepost1.id=>{title: 'A New Title'},post2.id=>{body: 'A New Body'}# atomic update on instance levelpost1.atomic_updatebody: 'A New Body',title: 'Another New Title'If you are using Composite ID you should pass instance as key, not id.
Post.atomic_updatepost1=>{title: 'A New Title'},post2=>{body: 'A New Body'}It's required only for atomic updates on class level.
Sunspot can extract related items using more_like_this. When searching for similar items, you can pass a block with the following options:
- fields :field_1[, :field_2, ...]
- minimum_term_frequency ##
- minimum_document_frequency ##
- minimum_word_length ##
- maximum_word_length ##
- maximum_query_terms ##
- boost_by_relevance true/false
classPost < ActiveRecord::Basesearchabledo# The :more_like_this option must be set to truetext:body,:more_like_this=>trueendendpost=Post.firstresults=Sunspot.more_like_this(post)dofields:bodyminimum_term_frequency5endTo use more_like_this you need to have the MoreLikeThis handler enabled in solrconfig.xml.
Example handler will look like this:
<requestHandler class="solr.MoreLikeThisHandler" name="/mlt">
<lst name="defaults">
<str name="mlt.mintf">1</str>
<str name="mlt.mindf">2</str>
</lst>
</requestHandler>
Solr supports spellchecking of search results against a dictionary. Sunspot supports turning on the spellchecker via the query DSL and parsing the response. Read the solr docs for more information on how this all works inside Solr.
Solr's default spellchecking engine expects to use a dictionary
comprised of values from an indexed field. This tends to work better
than a static dictionary file, since it includes proper nouns in your
index. The default in sunspot's solrconfig.xml is textSpell (note
that buildOnCommit isn't recommended in production):
<lst name="spellchecker">
<str name="name">default</str>
<!-- change field to textSpell and use copyField in schema.xml
to spellcheck multiple fields -->
<str name="field">textSpell</str>
<str name="buildOnCommit">true</str>
</lst>
Define the textSpell field in your schema.xml.
<field name="textSpell" stored="false" type="textSpell" multiValued="true" indexed="true"/>
To get some data into your spellchecking field, you can use copyField in schema.xml:
<copyField source="*_text" dest="textSpell" />
<copyField source="*_s" dest="textSpell" />
copyField works before any analyzers you have set up on the source
fields. You can add your own analyzer by customizing the textSpell field type in schema.xml:
<fieldType name="textSpell" class="solr.TextField" positionIncrementGap="100" omitNorms="true">
<analyzer>
<tokenizer class="solr.StandardTokenizerFactory"/>
<filter class="solr.StandardFilterFactory"/>
<filter class="solr.LowerCaseFilterFactory"/>
</analyzer>
</fieldType>
It's dangerous to add too much to this analyzer chain. It runs before words are inserted into the spellcheck dictionary, which means the suggestions that come back from solr are post-analyzer. With the default above, that means all spelling suggestions will be lower-case.
Once you have solr configured, you can turn it on for a given query using the query DSL (see spellcheck_spec.rb for more examples):
search = Sunspot.search(Post) do
keywords 'Cofee'
spellcheck :count => 3
end
Access the suggestions via the spellcheck_suggestions or
spellcheck_suggestion_for (for just the top one) methods:
search.spellcheck_suggestion_for('cofee') # => 'coffee'
search.spellcheck_suggestions # => [{word: 'coffee', freq: 10}, {word: 'toffee', freq: 1}]
If you've turned on collation, you can also get that result:
search = Sunspot.search(Post) do
keywords 'Cofee market'
spellcheck :count => 3
end
search.spellcheck_collation # => 'coffee market'
TODO
To specify that a field should be boosted in relation to other fields for all queries, you can specify the boost at index time:
classPost < ActiveRecord::Basesearchabledotext:title,:boost=>5.0text:bodyendendStored fields keep an original (untokenized/unanalyzed) version of their contents in Solr.
Stored fields allow data to be retrieved without also hitting the underlying database (usually an SQL server). They are also required for highlighting and more like this queries.
Stored fields come at some performance cost in the Solr index, so use them wisely.
classPost < ActiveRecord::Basesearchabledotext:body,:stored=>trueendend# Retrieving stored contents without hitting the databasePost.search.hits.eachdo |hit|
putshit.stored(:body)endPlease note that when you have stored fields declared, they are all going to be retrieved from Solr every time, even if you don't really need them. You can reduce returned stored dataset by using field lists, or you can skip all of them entirely:
Post.searchdowithout_stored_fieldsendSunspot simply stores the type and primary key of objects in Solr. When results are retrieved, those primary keys are used to load the actual object (usually from an SQL database).
# Using #results pulls in the records from the object-relational# mapper (e.g., ActiveRecord + a SQL server)Post.search.results.eachdo |result|
putsresult.bodyendTo access information about the results without querying the underlying
database, use hits:
# Using #hits gives back all information requested from Solr, but does# not load the object from the object-relational mapperPost.search.hits.eachdo |hit|
putshit.stored(:body)endIf you need both the result (ORM-loaded object) and Hit (e.g., for
faceting, highlighting, etc...), you can use the convenience method
each_hit_with_result:
Post.search.each_hit_with_resultdo |hit,result|
# ...endIf you are using Rails, objects are automatically indexed to Solr as a
part of the save callbacks.
There are a number of ways to index manually within Ruby:
# On a class itselfPerson.reindexSunspot.commit# or commit(true) for a soft commit (Solr4)# On mixed objectsSunspot.index[post1,item2]Sunspot.indexperson3Sunspot.commit# or commit(true) for a soft commit (Solr4)# With autocommitSunspot.index![post1,item2,person3]If you make a change to the object's "schema" (code in the searchable block),
you must reindex all objects so the changes are reflected in Solr:
bundle exec rake sunspot:reindex
# or, to be specific to a certain model with a certain batch size:
bundle exec rake sunspot:reindex[500,Post] # some shells will require escaping [ with \[ and ] with \]# to skip the prompt asking you if you want to proceed with the reindexing:
bundle exec rake sunspot:reindex[,,true] # some shells will require escaping [ with \[ and ] with \]TODO
The default Sunspot Session is not thread-safe. If used in a multi-threaded environment (such as sidekiq), you should configure Sunspot to use the ThreadLocalSessionProxy:
Sunspot.session=Sunspot::SessionProxy::ThreadLocalSessionProxy.newWithin a Rails app, to ensure your config/sunspot.yml settings are properly setup in this session you can use Sunspot::Rails.build_session to mirror the normal Sunspot setup process:
session=Sunspot::Rails.build_sessionSunspot::Rails::Configuration.newSunspot.session=sessionTo add or modify parameters sent to Solr, use adjust_solr_params:
Post.searchdoadjust_solr_paramsdo |params|
params[:q] += " AND something_s:more"endendIf you want to do eager loading on your sunspot search all you have to do is add this:
Sunspot.searchPostdodata_accessor_for(Post).include=[:comment]endThis is as long as you have the relationship in the model as a has_many etc.
In this case you could call the Post.comment and not have any sql queries
TODO
The following FieldTypes are used in sunspot. sunspot_solr will create schema.xml file inside Project for FieldType reference.
- Boolean
- SortableFloat
- Date
- SortableInt
- String
- SortableDouble
- SortableLong
- TrieInteger
- TrieFloat
- TrieInt
- LatlonField
Configure Sunspot by creating a config/sunspot.yml file or by setting a SOLR_URL or a WEBSOLR_URL environment variable.
The defaults are as follows.
development:
solr:
hostname: localhostport: 8982log_level: INFOtest:
solr:
hostname: localhostport: 8981log_level: WARNINGYou may want to use SSL for production environments with a username and password. For example, set SOLR_URL to https://username:password@production.solr.example.com/solr.
You can examine the value of Sunspot::Rails.configuration at runtime.
sunspot_solr gem is a convenient way to start working with Solr in development.
However, it is not suitable for production use. Below are some options for deploying Solr:
- Standalone or
- Docker Solr setup (also a good alternative for development)
- Chef (can be used with solr 7 as well)
- Ansible
- Kubernetes This deploys a Zookeeper cluster so you will need to convert cores to collections in order to use it.
You can also use Docker Solr for development which, regardless of how you deploy in production, will let you match the version you have deployed in production with the version you develop against. This can simplify maintenance of your cores. See the examples directory for a suitable starting point for a core you can use.
You can run solr in a docker container with the following commands:
docker pull solr:7.7.2
docker run -p 8983:8983 solr:7.7.2 #Add -d to run it in the backgroundOr in a docker-compose environment:
solr:
image: solr:7.7.2ports:
- "8983:8983"volumes:
- ./solr/init:/docker-entrypoint-initdb.d/
- data:/opt/solr/server/solr/mycoresrestart:
unless-stoppedwhere the ./solr/init directory contains a shell script that does any initial setup like downloading and unzipping your cores.
In both cases, the solr images by default expects cores to be placed in /opt/solr/server/solr/mycores.
To run all the specs just call rake from the library root folder.
To run specs related to individual gems, consider using one of the following commands:
GEM=sunspot ci/travis.sh
GEM=sunspot_rails ci/travis.sh
GEM=sunspot_solr ci/travis.shInstall the yard and redcarpet gems:
$ gem install yard redcarpetUninstall the rdiscount gem, if installed:
$ gem uninstall rdiscountGenerate the documentation from topmost directory:
$ yardoc -o docs */lib/**/*.rb - README.md- Using Sunspot, Websolr, and Solr on Heroku (mrdanadams)
- Full Text Searching with Solr and Sunspot (Collective Idea)
- Full-text search in Rails with Sunspot (Tropical Software Observations)
- Sunspot: A Solr-Powered Search Engine for Ruby (Linux Magazine)
- Sunspot Showed Me the Light (ben koonse)
- RubyGems.org — A case study in upgrading to full-text search (Websolr)
- How to Implement Spatial Search with Sunspot and Solr (Code Quest)
- Sunspot 1.2 with Spatial Solr Plugin 2.0 (joelmats)
- rails3 + heroku + sunspot : madness (anhaminha)
- heroku + websolr + sunspot (Onemorecloud)
- How to get full text search working with Sunspot (Hobo Cookbook)
- Full text search with Sunspot in Rails (hemju)
- Using Sunspot for Free-Text Search with Redis (While I Pondered...)
- Default scope with Sunspot (Cloudspace)
- Index External Models with Sunspot/Solr (Medihack)
- Testing with Sunspot and Cucumber (Collective Idea)
- The Saga of the Switch (mrb -- includes comparison of Sunspot and Ultrasphinx)
- Conditional Indexing with Sunspot (mikepack)
- Introduction to Full Text Search for Rails Developers (Valve's)
Sunspot is distributed under the MIT License, copyright (c) 2008-2013 Mat Brown