I am using Neo4j embedded as database. I have to store thousands of articles daily and and I need to provide a search functionality where I should return the articles whose content match to the keywords entered by the users. I indexed the content of each and every article and queried on the index like below
val articles = article_content_index.query("article_content", search string)
This works fine. But, its taking lot of time when the search string contains common words like "the", "a" and etc which will be present in each and every article.
How do I solve this problem?
Probably a lucene issue.
You can configure your own analyzer which could leave off those frequent (stop-)words:
http://docs.neo4j.org/chunked/stable/indexing-create-advanced.html
http://lucene.apache.org/core/3_6_2/api/core/org/apache/lucene/analysis/Analyzer.html
http://lucene.apache.org/core/3_6_2/api/core/org/apache/lucene/analysis/standard/StandardAnalyzer.html
You might configure article_content_index as fulltext index, see http://docs.neo4j.org/chunked/stable/indexing-create-advanced.html. To switch to using fulltext index, you first have to remove the index and the first usage of IndexManager.forNodes(String, Map) needs to configure the index on creation properly.
Related
I'm using sitecore 8 and I'm looking for a way to run a full text search for all my sitecore content. I have a solution in place, but I feel there's got to be a better way to do this.
My approach:
i have a computed field that merges all text fields into a single computed field. Before I execute a search I tokenize my search text and build a ORed predicate to match on the field.
I do not like this approach because it gets really complicated if I need to boost items that match the title vs the body i.e. i loose the field level boosting.
FYI: my code is very similar to this so post.
Thanks
Sitecore already maintains a full text field, _content, that contains all the text fields. You can run your search against that. You can even create computed fields that add to _content (such as the datasource content example here).
So assuming you are building a LINQ query for your full text search, and have already filtered on templates, latest version, location, etc., adding your search terms to the query would look something like this:
var terms = SearchTerm.Split();
var currentExpression = PredicateBuilder.True<SiteSearchResultItem>();
foreach (var term in terms)
{
//Content is mapped to _content
currentExpression = PredicateBuilder.And(currentExpression, x => x.Content.Contains(term));
}
query = query.Where(currentExpression);
Typically you would want to AND search terms rather than ORing them.
You are right that field level boosting is lost in this. In the end, Lucene is not a great solution for creating a quality full-text site search. If this is an important requirement, you may want to look at Coveo or even something like a Google Site Search.
Here is my question (pardon the wordiness):
I have millions of documents and all of them are unique.
However, all documents contain a 'description' field and this field contains data that only has a few different variations in the text across all 10 million documents. This field is large-ish -400-800 words or so.
What is the most appropriate way to eliminate this repetition of data in the 'description' field?
Let me elaborate. Here is an example schema that been simplified:
Doc_id <-- this is unique
Title <-- always unique as well
Description <-- contains mostly dupe data
I search over both the title and description but only return the title itself.
I'm fairly new to Solr but have been unable to find any information on how to tackle a scenario like this. In case it matters, I'm running Solr 5 on Ubuntu.
Thanks for any help!
I will try to provide some strategies to tackle your problem.
You are saying that you search over title and description, this means you should set these fields to indexed=true in your schema.xml. Only title is returned, this means only title needs to be set to stored=true, description should be set to stored=false. See this posting for more information on stored vs. indexed: Solr index vs stored
Another useful option you could try is the field option compression. If you need to store a field, you can use gzip compression on certain fields, such as TextField and StrField, see: https://wiki.apache.org/solr/SchemaXml for more info.
Lastly, deduplication is supported in Solr, see: https://wiki.apache.org/solr/Deduplication. I did not try this feature, but from the sounds of it, you can prevent (nearly) duplicate documents to be indexed or tag duplicates. Maybe its goal "Allow for both duplicate collapsing in search results as well as deduplication on adding a document." is what you are looking for?
I have a collection of documents in MongoDb (url: String, title: String, content: String). url is a unique field and contains something like server://aaa/bbb/1.html.
I would like to index data with Lucene, not Mongo (I can change storage). I'm going to store url in Lucene's index. When user searchs something by keywords, I'll perform query with Lucene, read url field and go to Mongo to extract doc by the url. It works well.
But I can't delete data from Lucene's index by url because it contains a lot of not allowed symbols. I use following settins for url field:
store = true
analyzed = false
indexed = true
(Should I index this field? What if I don't index this field? Will Lucene do a full scan? Collection can contain millions of documents)
If I want to have good performance should I create secondary index (Int or Long) and don't search by url?
I use latest versions of JVM, Lucene, Ubuntu and Mongo.
You need to properly encode your URL in a query, it should help.
E.g. in your case some.url/foo should be passed in a query as some.url%2Ffoo. You could try decoding/encoding online here - http://www.url-encode-decode.com/
For more info about escaping chars in Solr query take a look here - https://wiki.apache.org/solr/SolrQuerySyntax#NOTE:_URL_Escaping_Special_Characters
I am working on neo4j database version 2.0.I have following requirements :
Case 1. I want to fetch all records where name contains some string,for example if i am searching for Neo4j then all records having name Neo4j Data,Neo4j Database,Neo4jDatabase etc. should be returned.
Case 2. When i want to fire field less query,if a set of properties is having matching value then those records should be returned or it may also be global level instead of label level.
Case Sensitivity is also a point.
I have read multiple thing about like,index,full text search,legacy index etc.,so what will be the best fit for my case,or i have to use elastic search etc.
I am using spring-data-neo4j in my application,so provide some configuration for SDN
Annotate your name with #Indexed annotation:
#Indexed(indexName = "whateverIndexName", indexType = IndexType.FULLTEXT)
private String name;
Then query for it following way (example for method in SDN repository, you can use similar anywhere else you use cypher):
#Query("START n=node:whateverIndexName({query}) return n"
Set<Topic> findByName(#Param("query") String query);
Neo4j uses lucene as backend for indexing so the query value must be a valid lucene query, e.g. "name:neo4j" or "name:neo4j*".
There is an article that explains the confusion around various Neo4j indexes http://nigelsmall.com/neo4j/index-confusion.
I don't think you need to be using elastic search-- you can use the legacy indexes or the lucene indexes to do full text searches.
Check out Michael Hunger's blog: jexp.de/blog
thix post specifically: http://jexp.de/blog/2014/03/full-text-indexing-fts-in-neo4j-2-0/
I am using Lucene.NET and have a basic question:
Do I need to make an additional Index for Autocompletion?
I created an index based on two different tables from a database.
Here are two Docs:
stored,indexed,tokenized,termVector<URL:/Service/Zahlungsmethoden/Teilzahlung>
stored,indexed,tokenized,termVector<Website:Body:The Text of the first Page>
stored,indexed,tokenized,termVector<Website:ID:19>
stored,indexed,tokenized,termVector<Website:Title:Teilzahlung>
stored,indexed,tokenized,termVector<URL:/Service/Kundenservice/Kinderbetreeung>
stored,indexed,tokenized,termVector<Website:Body:The text of the second Page>
stored,indexed,tokenized,termVector<Website:ID:13>
stored,indexed,tokenized,termVector<Website:Title:Kinderbetreuung>
I need to create a dropdown for a search with suggestions:
eg: term "Pag" should suggest "Page"
so I assume that for every word (token) in every doc, I need a list like:
p
pa
pag
page
is this correct?
Where do I store these?
In an additional Index?
Or how would I re-arrange the existing structure of my index to hold the autocompletion-suggestions?
Thank you!
1) Like femtoRgon said above, look at the Lucene Suggest API.
2) That being said, one cheap way to perform auto-suggest is to look for all words that start with the string you've typed so far, like 'pa' returning 'pa' + 'pag' + 'page'. A wildcard query would return those results -- in Lucene query syntax, a query like 'pa*'. (You might want to restrict the suggestions to only those strings of length 2+.)
Mark Leighton Fisher has the right approach for a cheap way but performing a wildcard query just returns you the documents but not the words. It's better to look at the imlpementation of the WildcardQuery maybe. You need to use the Terms object retrieved from the IndexReader and iterate through the terms in the index.