Nth Permutation Mathematics


    1.0.0 • Public • Published


    The spleen module provides high-level abstractions for dynamic filters. This module will convert a spleen Filter into an Elasticsearch Query DSL object..



    Add spleen-elasticsearch to your package.json file's dependencies:

    $ npm install spleen-elasticsearch -S

    Then use it in your code:

    const spelastic = require('spleen-elasticsearch');
    const spleen = require('spleen');
    const filter = spleen.parse('/foo/bar eq 42 and /baz in [1,2,3] or /qux gt 0');
    const result = spelastic.convert(filter);
    // {
    //   "value": {
    //     "filter": {
    //       "bool": {
    //         "should": [
    //           {
    //             "bool": {
    //               "must": [
    //                 {
    //                   "term": { "foo.bar": 42 }
    //                 },
    //                 {
    //                   "terms": "baz": [1, 2, 3]
    //                 }
    //               ]
    //             }
    //           },
    //           {
    //             "range": {
    //               "qux": { "gt": 0 }
    //             }
    //           }
    //         ]
    //       }
    //     }
    //   }
    // }


    The spleen-elasticsearch module provides the following interface:

    • Properties

      • errors: an object that contains references to the various possible errors thrown by spleen-elasticsearch. This object has the following keys:

        • ConvertError: a general error thrown when spleen-elasticsearch is unable to convert a given Filter instance into a Query DSL object. This should generally never happen, and is here as a safeguard in the event a Filter instance is corrupted.

        • DeniedFieldError: thrown when a field is encountered that has been explicitly black-listed by the deny option.

        • InvalidTargetError: thrown if a target is encountered with an invalid format. For example, if a segment of the path contains disallowed characters.

        • NonallowedFieldError: thrown when a field is encountered that not been white-listed by the allow option.

        • RequiredFieldError: thrown when a field that has been required by the require option is not present in the given Filter.

      • Strategy: a reference to the Strategy class.

    • Methods

      • convert(filter [, strategy]): converts an instance of spleen's Filter' class into an Elasticsearch Query DSL object.


        • filter: (required) the instance of Filter to convert.

        • strategy: (optional) an instance of Strategy.

        This method returns an object with the following key:

        • fields: an array containing all of the fields (in RFC 6901 JSON pointer format) included in the filter.

        • value: a string containing the N1QL filter statement.

    Class: Strategy

    Compiles a spleen to Elasticsearch Query DSL conversion strategy, which is easily read by the convert() method.

    • new Strategy(settings)

      Creates a new instance of Strategy.


      • settings: (required) an object that controls various aspects of the conversion process. This object can have the keys:

        • allow: (optional) an array of RFC 6901 JSON pointer strings that are allowed to be in a Filter's list of targets. Any targets in a Filter instance not found in the allow or require lists will result in an error being thrown. This list functions as a white list, and can only be present if deny is absent. An empty array is the logical equivalent of the allow key being absent.

        • deny: (optional) an array of RFC 6901 JSON pointer strings that are not allowed to be in a Filter's list of targets. Any targets in a Filter instance found in this list will result in an error being thrown. This list functions as a black list, and can only be present if allow is absent.

        • discriminator: (optional) an object that configures a discriminator field, which is used for determining the Elasticsearch type to query at runtime. This feature works similarly to discriminator columns found in RDBMS table designs that utilize inheritance. If you do not wish to assign a discriminator leave this key null or undefined. This object has the following keys:

          • target: (optional) an RFC 6901 JSON pointer string that specifies a target field to use as the discriminator.

          • map: (optional) an object whose keys are possible values for the discriminator field, and the value is the name of an Elasticsearch type. The value of a discriminator must be a string or number.

        • require: (optional) an array of RFC 6901 JSON pointer strings that are required to be in a Filter's list of targets (Filter.prototype.targets). If a required target is missing, an error is thrown.

    Conversion Behavior

    A spleen filter is essentially an Boolean algebraic expression (AND, OR, NOT), and answers questions in a binary fashion — either yes or no. This contrasts with Elasticsearch's probabilistic matching, which generates a score representing the likelihood of a match. While Elasticsearch's Query DSL (EQD) provides methods for executing queries using Boolean algebra, there are some limitations.

    It is worth noting that spleen filters converted using spleen-elasticsearch are designed to answer questions about filtering in a binary fashion, and, so, none of Elasticsearch's fuzzy and probabilistic matching features. Thus, a converted spleen filter is nested in a filter, and all clauses are represented as a bool query.

    ANDs, ORs, and NOTs

    The EQD does not include AND, OR, or NOT operators. Instead, we are provided with must, should, and must_not. The challenge is converting spleen.Filter instance while preserving its Boolean logic. To do this, the spleen-elasticsearch module follows a few rules:

    1. The AND operator is given precedence over OR.

    2. Clauses chained together with AND are treated as a single group, with OR being the delimiter between groups.

    3. All clauses in an AND group are nested in a must.

    4. If there is more than one AND group in the filter, then all must queries are nested in a should.


    Under the hood, Elasticsearch is utilizing the Apache Lucene project to create and query indexes. Lucene does not have a concept of comparison operators. Searching Lucene indexes using different kinds of comparisons translate into different types of queries. Elasticsearch's Query DSL provides a high level abstraction of Lucene query types, and different spleen operators must be translated accordingly.

    Operator Elasticsearch Query DSL
    eq { "term": { "key": "value" } }
    neq { "bool": { "must_not": { "term": { "key": "value" } } } }
    gt { "range": { "key": { "gt": "value" } } }
    gte { "range": { "key": { "gte": "value" } } }
    lt { "range": { "key": { "lt": "value" } } }
    lte { "range": { "key": { "lte": "value" } } }
    between { "range": { "key": { "gte": "value1", "lte": "value2" } } }
    nbetween { "bool": { "must_not": { "range": { "key": { "gte": "value1", "lte": "value2" } } } } }
    in { "terms": { "key": ["value1", "value2", "valueN"] } }
    nin { "bool": { "must_not": { "terms": { "key": ["value1", "value2", "valueN"] } } } }
    like { "regex": { "key": "like value converted to regex" } }
    nlike { "bool": { "must_not": { "regex": { "key": "like value converted to regex" } } } }

    Pattern Matching Conversion to Regex

    Elasticsearch can perform pattern matching usig regular expressions. The spleen-elasticsearch module converts like patterns to regex in the following way.

    like Char Regex Operator
    * .*
    _ .{1}

    All like statements converted to regex begin with ^ and $. For example, the like pattern *Hello World_ is converted into the regex ^.*Hello World.{1}$.

    Range Comparisons

    Elasticsearch's Query DSL does not support queries where the document property is evaluated on to the right of a literal value (i.e. 42 gt /foo). In cases where gt, gte, lt, or lte comparisons are performed with the target on the right and the literal on the left, the operator used in the Elasticsearch Query DSL range query is inverted (gt is replaced with lt, gte is replaced with lte, or visa versa).

    Handling nil Literals

    When a spleen filter includes a comparison between a target and a nil literal, the exists query DSL is used. The spleen expression dialect allows for a variety of operators to be used when comparing against a nil. Different operators result in different Elasticsearch Query DSL...

    Operator Elasticsearch Query DSL
    eq nil { "bool": { "must_not": { "exists": { "field": "key" } } } }
    neq nil { "exists": { "field": "key" } }
    gt nil { "exists": { "field": "key" } }
    gte nil { "exists": { "field": "key" } }
    lt nil { "bool": { "must_not": { "exists": { "field": "key" } } } }
    lte nil { "bool": { "must_not": { "exists": { "field": "key" } } } }

    Comparing Two Properties/Literals

    Comparison between properties on a document does not exist as a first-class citizen in Elasticsearch Query DSL. However, it is possible using script queries. Thus, clauses that are a comparison between two targets will be translated to a script query.

    For example, the spleen expression...

    /foo eq /bar

    ...is translated to...

      "script": {
        "script": "doc['foo'].value == doc['bar'].value"

    Though not a typical use case, comparisons between two literal values are handled the same way.

    Mapping Considerations

    In order for spleen filters to work properly when converted into Elasticsearch's Query DSL there are a couple of things to consider when creating index mappings.

    String Properties

    Because spleen-elasticsearch uses term and terms for comparisons, Elasticsearch will attempt to make exact comparisons of values in its inverted index. Document property mappings of type text are "analyzed," and the entire value of a property may not be in the index. For example, stopwords and most punctuation will not be indexed. For this reason it is recommended that you map string values as keyword for indexes you intend to run converted spleen filters against.

    Referencing Array Values by Index

    In a future release, support for referencing array items by index will be added. In order to make this possible, you will need to create a computed property mapping using the token_count.


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