Class NumericRangeQuery<T>

A Query that matches numeric values within a specified range. To use this, you must first index the numeric values using Int32Field, SingleField, Int64Field or DoubleField (expert: NumericTokenStream). If your terms are instead textual, you should use TermRangeQuery. NumericRangeFilter is the filter equivalent of this query.

You create a new NumericRangeQuery<T> with the static factory methods, eg: 

Query q = NumericRangeQuery.NewFloatRange("weight", 0.03f, 0.10f, true, true);

matches all documents whose float valued "weight" field ranges from 0.03 to 0.10, inclusive.

The performance of NumericRangeQuery<T> 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. A good starting point to test is 4, which is the default value for all Numeric* classes. See below for details.

This query defaults to CONSTANT_SCORE_AUTO_REWRITE_DEFAULT. With precision steps of <=4, this query can be run with one of the BooleanQuery rewrite methods without changing BooleanQuery's default max clause count.

How it works

See the publication about panFMP, where this algorithm was described (referred to as TrieRangeQuery):

Schindler, U, Diepenbroek, M, 2008. Generic XML-based Framework for Metadata Portals. Computers & Geosciences 34 (12), 1947-1955. doi:10.1016/j.cageo.2008.02.023

A quote from this paper: Because Apache Lucene is a full-text search engine and not a conventional database, it cannot handle numerical ranges (e.g., field value is inside user defined bounds, even dates are numerical values). 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 trie, while 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 256 distinct values in the lowest precision. Overall, a range could consist of a theoretical maximum of 

7*255*2 + 255 = 3825
distinct terms (when there is a term for every distinct value of an 8-byte-number in the index and the range covers almost all of them; a maximum of 255 distinct values is used because it would always be possible to reduce the full 256 values to one term with degraded precision). In practice, we have seen up to 300 terms in most cases (index with 500,000 metadata records and a uniform value distribution).

Precision Step

You can choose any precisionStep when encoding values. Lower step values mean more precisions and so more terms in index (and index gets larger). The number of indexed terms per value is (those are generated by NumericTokenStream):

  indexedTermsPerValue = ceil(bitsPerValue / precisionStep)

As the lower precision terms are shared by many values, the additional terms only slightly grow the term dictionary (approx. 7% for precisionStep=4), but have a larger impact on the postings (the postings file will have more entries, as every document is linked to indexedTermsPerValue terms instead of one). The formula to estimate the growth of the term dictionary in comparison to one term per value:

  \mathrm{termDictOverhead} = \sum\limits_{i=0}^{\mathrm{indexedTermsPerValue}-1} \frac{1}{2^{\mathrm{precisionStep}\cdot i}}

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:

  \mathrm{maxQueryTerms} = \left[ \left( \mathrm{indexedTermsPerValue} - 1 \right) \cdot \left(2^\mathrm{precisionStep} - 1 \right) \cdot 2 \right] + \left( 2^\mathrm{precisionStep} - 1 \right)

For longs stored using a precision step of 4, maxQueryTerms = 15*15*2 + 15 = 465, and for a precision step of 2, maxQueryTerms = 31*3*2 + 3 = 189. 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 4, which 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. If the cardinality is < 100, it is fair to use MaxValue (see below).
  • Steps >=64 for long/double and >=32 for int/float produces one token per value in the index and querying is as slow as a conventional TermRangeQuery. But it can be used to produce fields, that are solely used for sorting (in this case simply use MaxValue as precisionStep). Using Int32Field, Int64Field, SingleField or DoubleField for sorting is ideal, because building the field cache is much faster than with text-only numbers. These fields have one term per value and therefore also work with term enumeration for building distinct lists (e.g. facets / preselected values to search for). Sorting is also possible with range query optimized fields using one of the above precisionSteps.

Comparisons of the different types of RangeQueries on an index with about 500,000 docs showed that TermRangeQuery in boolean rewrite mode (with raised BooleanQuery clause count) took about 30-40 secs to complete, TermRangeQuery in constant score filter rewrite mode took 5 secs and executing this class took <100ms to complete (on an Opteron64 machine, Java 1.5, 8 bit precision step). This query type was developed for a geographic portal, where the performance for e.g. bounding boxes or exact date/time stamps is important.

@since 2.9

Inheritance
object
Query
MultiTermQuery
NumericRangeQuery<T>
Inherited Members
Namespace: Lucene.Net.Search
Assembly: Lucene.Net.dll
Syntax
public sealed class NumericRangeQuery<T> : MultiTermQuery where T : struct, IComparable<T>
Type Parameters
Name Description
T

Properties

IncludesMax

Returns true if the upper endpoint is inclusive

Declaration
public bool IncludesMax { get; }
Property Value
Type Description
bool

IncludesMin

Returns true if the lower endpoint is inclusive

Declaration
public bool IncludesMin { get; }
Property Value
Type Description
bool

Max

Returns the upper value of this range query

Declaration
public T? Max { get; }
Property Value
Type Description
T?

Min

Returns the lower value of this range query

Declaration
public T? Min { get; }
Property Value
Type Description
T?

PrecisionStep

Returns the precision step.

Declaration
public int PrecisionStep { get; }
Property Value
Type Description
int

Methods

Equals(object)

Determines whether the specified object is equal to the current object.

Declaration
public override bool Equals(object o)
Parameters
Type Name Description
object o
Returns
Type Description
bool

true if the specified object is equal to the current object; otherwise, false.
Overrides

GetHashCode()

Serves as the default hash function.

Declaration
public override int GetHashCode()
Returns
Type Description
int

A hash code for the current object.
Overrides

GetTermsEnum(Terms, AttributeSource)

Construct the enumeration to be used, expanding the pattern term. this method should only be called if the field exists (ie, implementations can assume the field does exist). this method should not return null (should instead return EMPTY if no terms match). The TermsEnum must already be positioned to the first matching term. The given AttributeSource is passed by the MultiTermQuery.RewriteMethod to provide attributes, the rewrite method uses to inform about e.g. maximum competitive boosts. this is currently only used by TopTermsRewrite<Q>.

Declaration
protected override TermsEnum GetTermsEnum(Terms terms, AttributeSource atts)
Parameters
Type Name Description
Terms terms
AttributeSource atts
Returns
Type Description
TermsEnum
Overrides

ToString(string)

Prints a query to a string, with field assumed to be the default field and omitted.

Declaration
public override string ToString(string field)
Parameters
Type Name Description
string field
Returns
Type Description
string
Overrides