Apache Lucene - Query Parser Syntax
This class is generated by JavaCC. The most important method is Parse String. Inherits Lucene. Inherited by Lucene. The syntax for query strings is as follows: A Query is a series of clauses. A clause may be prefixed by:. Examples of appropriately formatted queries can be found in the query syntax documentation.
Note that the format of the accepted input depends on the Locale. By default a date is converted into a search term using the deprecated DateField for compatibility reasons. To use the new DateTools to convert dates, a Lucene. Resolution has to be set. The former sets the default date resolution for all fields, whereas the latter can be used to set field specific date resolutions.
Field specific date resolutions take, if set, precedence over the default date resolution. If you use neither DateField nor DateTools in your index, you can create your own query parser that inherits QueryParser and overwrites GetRangeQuery String, String, String, bool to use a different method for date conversion.
Note that QueryParser is not thread-safe. NOTE : there is a new QueryParser in contrib, which matches the same syntax as this class, but is more modular, enabling substantial customization to how a query is created.
Definition at line of file QueryParser. Constructor with generated Token Manager. Generate ParseException. Returns the date resolution that is used by RangeQueries for the given field. Returns null, if no default or field specific date resolution has been set for the given field. Get the next Token. Get the specific Token. Command line tool to test QueryParserusing Lucene.
Usage: java Lucene.
Lucene: Indexing DateTime from Sitecore and querying date ranges
Parses a query string, returning a Lucene. Sets the default date resolution used by RangeQueries for fields for which no specific date resolutions has been set. Set to true to allow leading wildcard characters. Note that this can produce very slow queries on big indexes. Default: false.Examples of appropriately formatted queries can be found in the query syntax documentation. Note that the format of the accepted input depends on the locale. A DateTools. Resolution has to be set, if you want to use DateTools for date conversion.
Resolution or QueryParserBase. The former sets the default date resolution for all fields, whereas the latter can be used to set field specific date resolutions. Field specific date resolutions take, if set, precedence over the default date resolution. If you don't use DateTools in your index, you can create your own query parser that inherits QueryParser and overwrites QueryParserBase.
NOTE : there is a new QueryParser in contrib, which matches the same syntax as this class, but is more modular, enabling substantial customization to how a query is created. Operator The default operator for parsing queries.
Token token Current token. Token getNextToken Get the next Token. Parameters: f - the default field for query terms. NOTE: this behavior may not be suitable for all languages. Set to false if phrase queries should only be generated when surrounded by double quotes.
Default is true. All Rights Reserved. Skip navigation links. Object org. QueryBuilder org. QueryParserBase org. The most important method is QueryParserBase. The syntax for query strings is as follows: A Query is a series of clauses. This enables one to construct queries which search multiple fields.
A clause may be either: a term, indicating all the documents that contain this term; or a nested query, enclosed in parentheses. Note that QueryParser is not thread-safe. Set to true if phrase queries will be automatically generated when the analyzer returns more than one term from whitespace delimited text.
The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. But this doesn't give satisfactory results. Greater than works fine.
I am using elasticsearch v6. Please help with solution for both inclusive and exclusive of both values. Matches documents with fields that have terms within a certain range. Learn more. How to query elasticsearch for greater than and less than?
Asked 1 year, 9 months ago. Active 9 months ago.Microsoft Access Multi-Field Search Form
Viewed 22k times. I want to get values between and Rakmo Rakmo 2 2 gold badges 9 9 silver badges 31 31 bronze badges. Active Oldest Votes. Returns documents where the price value between and inclusive. Mikhail Kholodkov Mikhail Kholodkov No it doesn't for ES 6.
Take a look at example given in the link. As per your example with bool and filter you can merge gte and lte within a single price bracket, should work similar. Sign up or log in Sign up using Google. Sign up using Facebook.A Query that matches numeric values within a specified range. If your terms are instead textual, you should use TermRangeQuery. NumericRangeFilter is the filter equivalent of this query.
The performance of NumericRangeQuery is much better than the corresponding TermRangeQuery because the number of terms that must be searched is usually far fewer, thanks to trie indexing, described below. You can optionally specify a precisionStep when creating this query. This is necessary if you've changed this configuration from its default 4 during indexing. Lower values consume more disk space but speed up searching. Suitable values are between 1 and 8.
See below for details. This query defaults to MultiTermQuery. We have developed an extension to Apache Lucene that stores the numerical values in a special string-encoded format with variable precision all numerical values like doubles, longs, floats, and ints are converted to lexicographic sortable string representations and stored with different precisions for a more detailed description of how the values are stored, see NumericUtils.
A range is then divided recursively into multiple intervals for searching: The center of the range is searched only with the lowest possible precision in the triewhile the boundaries are matched more exactly.
This reduces the number of terms dramatically. For the variant that stores long values in 8 different precisions each reduced by 8 bits that uses a lowest precision of 1 byte, the index contains only a maximum of distinct values in the lowest precision.
In practice, we have seen up to terms in most cases index withmetadata records and a uniform value distribution. You can choose any precisionStep when encoding values.
Lower step values mean more precisions and so more terms in index and index gets larger. On the other hand, if the precisionStep is smaller, the maximum number of terms to match reduces, which optimizes query speed. The formula to calculate the maximum number of terms that will be visited while executing the query is:.
But the faster search speed is reduced by more seeking in the term enum of the index. Because of this, the ideal precisionStep value can only be found out by testing. Important: You can index with a lower precision step value and test search speed using a multiple of the original step value. Good values for precisionStep are depending on usage and data type: The default for all data types is 4which is used, when no precisionStep is given. Ideal value in most cases for 64 bit data types long, double is 6 or 8.
Ideal value in most cases for 32 bit data types int, float is 4. For low cardinality fields larger precision steps are good. But it can be used to produce fields, that are solely used for sorting in this case simply use Integer.
Using IntFieldLongFieldFloatField or DoubleField for sorting is ideal, because building the field cache is much faster than with text-only numbers.Lucene has a custom query syntax for querying its indexes. Here are some query examples demonstrating the query syntax. Search for either the phrase "foo bar" in the title field AND the phrase "quick fox" in the body field, or the word "fox" in the title field.
Note that for proximity searches, exact matches are proximity zero, and word transpositions bar foo are proximity 1.
Whilst both queries are effectively equivalent with respect to the documents that are returned, the proximity query assigns a higher score to documents for which the terms foo and bar are closer together. Range Queries allow one to match documents whose field s values are between the lower and upper bound specified by the Range Query.
Range Queries can be inclusive or exclusive of the upper and lower bounds. Sorting is done lexicographically. Solr's built-in field types are very convenient for performing range queries on numbers without requiring padding.
The higher the boost factor, the more relevant the term will be, and therefore the higher the corresponding document scores. A typical boosting technique is assigning higher boosts to title matches than to body content matches:. Lucene queries can also be constructed programmatically. This can be really handy at times. Besides, there are some queries which are not possible to construct by parsing. These classes are part of the org. Lucene Query Syntax Lucene has a custom query syntax for querying its indexes.
Keyword matching Search for word "foo" in the title field. Proximity matching Lucene supports finding words are a within a specific distance away. Search for "foo bar" within 4 words from each other. The trade-off, is that the proximity query is slower to perform and requires more CPU. Solr DisMax and eDisMax query parsers can add phrase proximity matches to a user query.
Range searches Range Queries allow one to match documents whose field s values are between the lower and upper bound specified by the Range Query. Parsing Queries Queries can be parsed by constructing a QueryParser object and invoking the parse method.
Available query objects as of 3. MUST ; bq. About Me Siblings SolrTutorial.A DateFilter does not cache, so each search re-enumerates the terms in the range.
In fact, DateFilter by itself is practically of no use Erik Hatcher, message. The cache is keyed by IndexReader. Erik Hatcher also wrote message : One more point In many cases I would argue: all cases it doesn't make sense to Query on a Range of Dates. Querying scores items based on the frequency of terms — which is something most people don't care about when dealing with dates, particularly given the overhead involved.
For example to search for every date in the 's, search for To search for the date range Jan up to and including Jansearch for OR A similar scheme can be used for general numerical range searching. This trades off index size for search performance. This works by mapping values to be indexed to a 64 bit long value, and by indexing various length prefixes of these 64 bit values.
Order preserving mappings for dates and floating points are available. See SearchNumericalFields. When longer dates or numbers need to be indexed, for example CCYYMMDDhhmmss with hours, minutes and seconds added, consider indexing the hhmmss separately, possibly with hierarchical prefixes themselves. Evaluate Confluence today. Apache Lucene Java. Pages Blog. Space shortcuts Meeting notes.
Page tree. Browse pages. A t tachments 0 Page History. Dashboard Home Old Moin wiki. Jira links. If you have a set of canned date ranges, there are two approaches worth considering: DateFilter wrapped by a CachingWrappingFilter RangeQuery wrapped in a QueryFilter which does cache. Before caching the Field After caching the field 10 10 6 8 6. No labels. Content Tools.
Powered by Atlassian Confluence 7. DateFilter wrapped by a CachingWrappingFilter. RangeQuery wrapped in a QueryFilter which does cache.A simple query parser implemented with JavaCC. Note that JavaCC defines lots of public classes, methods and fields that do not need to be public. These clutter the documentation. Note that because JavaCC defines a class named Tokenorg. Token must always be fully qualified in source code in this package.
NOTE : org. Although Lucene provides the ability to create your own queries through its API, it also provides a rich query language through the Query Parser, a lexer which interprets a string into a Lucene Query using JavaCC. Generally, the query parser syntax may change from release to release.
This page describes the syntax as of the current release. Before choosing to use the provided Query Parser, please consider the following: If you are programmatically generating a query string and then parsing it with the query parser then you should seriously consider building your queries directly with the query API. In other words, the query parser is designed for human-entered text, not for program-generated text. Untokenized fields are best added directly to queries, and not through the query parser.
If a field's values are generated programmatically by the application, then so should query clauses for this field. An analyzer, which the query parser uses, is designed to convert human-entered text to terms. Program-generated values, like dates, keywords, etc. In a query form, fields which are general text should use the query parser. All others, such as date ranges, keywords, etc. A field with a limit set of values, that can be specified with a pull-down menu should not be added to a query string which is subsequently parsed, but rather added as a TermQuery clause.
A query is broken up into terms and operators. There are two types of terms: Single Terms and Phrases. A Single Term is a single word such as "test" or "hello". A Phrase is a group of words surrounded by double quotes such as "hello dolly". Multiple terms can be combined together with Boolean operators to form a more complex query see below. Note: The analyzer used to create the index will be used on the terms and phrases in the query string.
So it is important to choose an analyzer that will not interfere with the terms used in the query string. Lucene supports fielded data. When performing a search you can either specify a field, or use the default field.
The field names and default field is implementation specific. You can search any field by typing the field name followed by a colon ":" and then the term you are looking for. As an example, let's assume a Lucene index contains two fields, title and text and text is the default field.
Note: The field is only valid for the term that it directly precedes, so the query title:The Right Way Will only find "The" in the title field. It will find "Right" and "Way" in the default field in this case the text field. Lucene supports modifying query terms to provide a wide range of searching options. Wildcard Searches Lucene supports single and multiple character wildcard searches within single terms not within phrase queries.
To perform a single character wildcard search use the "? The single character wildcard search looks for terms that match that with the single character replaced. For example, to search for "text" or "test" you can use the search: te?