I've read a lot about Lucene indexing and searching and still can't understand what Term is?What is the difference between term and fields?
A very rough analogy would be that fields are like columns in a database table, and terms are like the contents in each database column.
More specifically to Lucene:
Terms
Terms are indexed tokens. See here:
Lucene Analyzers are processing pipelines that break up text into indexed tokens, a.k.a. terms
So, for example, if you have the following sentence in a document...
"This is a list of terms"
...and you pass it through a whitespace tokenizer, this will generate the following terms:
This
is
a
list
of
terms
Terms are therefore also what you place into queries, when performing searches. See here for a definition of how they are used in the classic query parser.
Fields
A field is a section of a document.
A simple example is the title of a document versus the body (the remaining text/content) of the document. These can be defined as two separate Lucene fields within a Lucene index.
(You obviously need to be able to parse the source document so that you can separate the title from the body - otherwise you cannot populate each separate field correctly, while building your Lucene index.)
You can then place all of the title's terms into the title field; and the body's terms into the body field.
Now you can search title data separately from body data.
You can read about fields here and here. There are various different types of fields, specific to the type of data (terms) they will be holding.
Related
Will someone please explain under what circumstance I may use Field.Store.NO instead of Field.Store.YES? I am extremely new to Lucene. And I am trying to create a document. Per my basic knowledge, I am doing
doc.add(new StringField(fieldNameA,fieldValueA,Field.Store.YES));
doc.add(new TextField(fieldNameB,fieldValueB,Field.Store.YES));
There are two basic ways a document can be written into Lucene.
Indexed - The field is analyzed and indexed, and can be searched.
Stored - The field's full text is stored and will be returned with search results.
If a document is indexed but not stored, you can search for it, but it won't be returned with search results.
One reasonably common pattern is to use lucene for search, but only have an ID field being stored which can be used to retrieve the full contents of the document/record from, for instance, a SQL database, a file system, or an web resource.
You might also opt not to store a field when that field is just a search tool, but you wouldn't display it to the user, such as a soundex/metaphone, or an alternate analysis of a content field.
Use Field.Store.YES when you need a document back from Lucene document. Use NO when you just need a search from document. Here is a link explained with a scenario.
https://handyopinion.com/java-lucene-saving-fields-or-not/
I've got a basic search working, and I'm highlighting using FastVectorHighlighter. When you ask the highlighter for a "best fragment" you have a few overloads of getBestFragment(s) to choose from, documented here. I'm now using the simplest one, like this:
highlightedText = highlighter.getBestFragment(fieldQuery, searcher.getIndexReader(),
scoreDoc.doc, "description", 100)
So I'm highlighting the match from the "description" field. My query however searches another field, "notes". How do I include that in the highlighting? There is an overload that takes a Set<String> matchedFields and one String storedField, but I don't understand the docs. The doc for the method says:
it is advisable that all matchedFields share the same source as storedField or are at least a prefix of it.
What does that mean? How do I index the "notes" and "description" Strings, and what do I pass for matchedFields and storedField?
That call, I believe, is intended to highlight against multiple indexed forms of the same content. That is, if you have one stored full-text content field, but you have indexed it in a number of different ways to expand how you can search it. Perhaps you have one indexed field that uses standard analysis, another with language-specific stemming, another that uses ngrams, and another indexing metaphones.
If you want to highlight two different stored fields, two calls to getBestFragment would be called for. Or you could use a different highlighter that allows multiple stored fields to be highlighted at the same time, PostingsHighlighter, for instance.
Lets use emails for an example as a document. You have your subject, body, the person who its from and lets say we can also tag them (as gmail does)
From my understanding of QueryParser i give it ONE field and the parser type. If a user enter text the user only searches whatever i set. I notice it will look in the subject or body field if i wrote fieldName: text to search however how do i make a regular query such as "funny SO question unicorn" find result(s) with some of those strings in the subject, the others in the body? ATM because i knew it would be easy i made a field called ALL and combined all the other fields into that but i would like to know how i can do it in a proper way. Especially since my next app is text search dependent
Use MultiFieldQueryParser. You can specify list of fields to be searched using following constructor.
MultiFieldQueryParser(Version matchVersion, String[] fields, Analyzer analyzer)
This will generate a query as if you have created multiple queries on different fields. This partially addresses your problem. This, still, will not match one term matching in field1 and another matching in field2. For this, as you have rightly pointed out, you will need to combine all the fields in one single field and search in that field. Nevertheless, you will find MultiFieldQueryParser useful when query terms do not cross the field boundaries.
Consider I'm having a couple of documents indexed with Solr 4.0. Each has 2 fields - unique ID and text DATA field. DATA field contains few paragraphs of text. Who could advise me what kind of analyzers/parsers I should use and how to build statistical query to find out sorted list of most frequently used words in all DATA fields of all documents.
for the most frequent terms look into the terms- and statistical component
besides the answers mentioned here, you can use the "HighFreqTerms" class: its in the lucene-misc-4.0 jar (which is bundled with Solr).
This is a command line application which lets you see the top terms for any field either by document frequency or by total term frequency (the -t option)
Here is the usage:
java org.apache.lucene.misc.HighFreqTerms [-t] [number_terms] [field]
-t: include totalTermFreq
Here's the original patch, which is committed and in the 4.0 (trunk) and branch_3x codebases: https://issues.apache.org/jira/browse/LUCENE-2393
For ID field use analyzer based on keyword tokenizer - it will take all the content of the field as a single token.
For DATA field use language specific analyzer. Notice, that there's possibility to auto-detect the language of the text (patch).
I'm not sure, if it's possible to find the most frequent words with Solr, but if you can use Lucene itself, pay attention to this question. My own suggestion for it is to use HighFreqTerms class from Luke project.
I have a "description" field indexed in Lucene.This field contains a book's description.
How do i achieve "All of these words" functionality on this field using BooleanQuery class?
For example if a user types in "top selling book" then it should return books which have all of these words in its description.
Thanks!
There are two pieces to get this to work:
You need the incoming documents to be analysed properly, so that individual words are tokenised and indexed separately
The user query needs to be tokenised, and the tokens combined with the AND operator.
For #1, there are a number of Analyzers and Tokenizers that come with Lucene - have a look in the org.apache.lucene.analysis package. There are options for many different languages, stemming, stopwords and so on.
For #2, there are again a lot of query parsers that come with Lucene, mainly in the org.apache.lucene.queryParser packagage. MultiFieldQueryParser might be good for you: to require every term to be present, just call
QueryParser.setDefaultOperator(QueryParser.AND_OPERATOR)
Lucene in Action, although a few versions old, is still accurate and extremely useful for more information on analysis and query parsing.
I believe if you add all query parts (one per term) via
BooleanQuery.add(Query, BooleanClause.Occur)
and set that second parameter to the constant BooleanClause.Occur.MUST, then you should get what you want. The equivalent query syntax would be "+term1+term2 +term3 ...".