Query DSL
ZomboDB supports a few different ways to generate Elasticsearch-compatible queries. You can use ZomboDB's Query Language, directly generate Elasticsearch QueryDSL in JSON form, or use ZomboDB's SQL builder API which closely mirrors Elasticsearch's QueryDSL.
Wherever ZomboDB wants to you specify a query, which is typically SELECT statements and aggregate functions, you can
interchangeably use any of the below query forms.
To use a SELECT statement as an example, lets suppose we want to select all the rows that contain the terms "cats and
dogs" regardless of field. The basic query template looks like:
SELECT * FROM table WHERE table ==> <cats and dogs query here>
Note that regardless of the way you query, know that essentially you're generating Elasticsearch QueryDSL in JSON.
ZomboDB tries to abstract this fact away by using a custom Postgres type called zdbquery that can be cast to/from
text, json, and jsonb. As such, the right-hand-side of ZomboDB's ==> operator is of type zdbquery.
The goal of this document is not to teach the ins-and-outs of Elasticsearch's query capabilities. It is recommented you reference its documentation when the information here is not sufficient. Where approrpiate, links to specific Elasticsearch Query DSL clauses are provided below.
That said, lets discuss how to write our example query using ZomboDB's supported query forms.
ZQL: ZomboDB Query Language
ZQL is a plain-text query language specific to ZomboDB and some of it's advanced features. You can simply specify free-form, unqualified words and "quoted phrases" and ZomboDB figures out the matching documents.\ Additionally, it supports a fairly sophisticated boolean syntax that includes field qualification, proximity, ranges, wildcards, etc.
Using zql, searching for "cats and dogs" could be any of the following:
SELECT * FROM table WHERE table ==> 'cats dogs';
SELECT * FROM table WHERE table ==> 'cats AND dogs';
To show what's happening behind the scenes, ZomboDB is actually generating Elasticsearch QueryDSL JSON for the above queries, but against a specific field:
select zdb.dump_query('main_ft', 'fulltext:(cats dogs)');
dump_query
------------------------------
{ +
"bool": { +
"must": [ +
{ +
"match": { +
"fulltext": { +
"query": "cats",+
"boost": 1.0 +
} +
} +
}, +
{ +
"match": { +
"fulltext": { +
"query": "dogs",+
"boost": 1.0 +
} +
} +
} +
] +
} +
}
Direct JSON
While the above ZQL is easy for humans to read and type, it doesn't expose every feature of Elasticsearch's QueryDSL.\ Enter direct json.
SELECT * FROM table WHERE table ==> '{"bool":{"must":[{"term":{"zdb_all":{"value":"cats"}}},{"term":{"zdb_all":{"value":"dogs"}}}]}}';
You have the full gamut of the Elasticsearch QueryDSL available to you with this form. This is likely best used when you're programatically generating queries.
Note that the field
zdb_allis ZomboDB's version of Elasticsearch's "_all" field, exceptzdb_allis enabled for all versions of Elasticsearch. It is also configured as the default search field for every ZomboDB index, which is why it wasn't specified in the Query String Syntax examples, but is here.
SQL Builder API
ZomboDB also exposes nearly all of Elasticsearch's QueryDSL queries as SQL functions, located in a schema named dsl.
These functions all return a zdbquery, and can be composed together to build complex queries. The primary advantages
of this API are that these functions are syntax- and type-checked by Postgres, so you'll catch malformed queries sooner.
In general, each function models its corresponding Elasticsearch query exactly. Default values are used for arguments in all places where Elasticsearch provides defaults for properties, and arguments are required where Elasticsearch requires the corresponding property. Postgres VARIADIC function arguments are used in most cases where Elasticsearch expects an array of queries or values.
They're designed to be used with defaults in the common cases, and then otherwise should be used using Postgres' "named arguments" function call syntax to improve readability.
All of the functions are briefly described below, but here's some examples for our "cats and dogs" queries, plus a few more examples.
SELECT * FROM table WHERE table ==> dsl.and('cats', 'dogs');
SELECT * FROM table WHERE table ==> dsl.and(dsl.term('zdb_all', 'cats'), dsl.term('zdb_all', 'dogs'));
Behind the scenes, ZomboDB is just generating the QueryDSL JSON for you:
SELECT dsl.and('cats', 'dogs')::json;
must
-----------------------------------------------------------------------------------------
{"bool":{"must":[{"query_string":{"query":"cats"}},{"query_string":{"query":"dogs"}}]}}
SELECT dsl.and(dsl.term('zdb_all', 'cats'), dsl.term('zdb_all', 'dogs'))::json;
must
-------------------------------------------------------------------------------------------------
{"bool":{"must":[{"term":{"zdb_all":{"value":"cats"}}},{"term":{"zdb_all":{"value":"dogs"}}}]}}
Lets say you want to find all rows that contain cats with an age greater than 3 years. This example shows, with the
range() function, using Postgres "named arugments" function call syntax so that you can specifiy only the bounds of
the range you need. We're also mix-and-matching between the plain text Query String Syntax ('cats') and the builder
API (must() and range()):
SELECT * FROM table WHERE table ==> dsl.and('cats', dsl.range(field=>'age', gt=>3));
Which rewrites to:
SELECT dsl.and('cats', dsl.range(field=>'age', gt=>3))::json;
must
------------------------------------------------------------------------------------
{"bool":{"must":[{"query_string":{"query":"cats"}},{"range":{"age":{"gt":"3"}}}]}}
One of the more powerful benefits of the Builder API is that it allows you to generate Postgres prepared statements for your text-search queries. For example:
PREPARE example AS SELECT * FROM table WHERE table ==> dsl.and($1, dsl.range(field=>'age', gt=>$2));
Now we can execute that query using a different search term and age range:
EXECUTE example('cats', 3);
EXECUTE example('dogs', 7);
EXECUTE example('elephants', 23);
Using prepared statements is extremely important to avoid SQL-injection attacks. ZomboDB makes this possible for your Elasticsearch QueryDSL query clauses too. Any argument to any of the functions can become a prepared statement arugment that you can change at EXECUTE time.
Query-time configuration
dsl.row_estimate()
FUNCTION dsl.row_estimate(
row_estimate bigint,
query zdbquery
) RETURNS zdbquery
Similar to zdb.default_row_estimate,
but applies (and is actual) only during the query.
Sorting and Limiting Results
ZomboDB allows you to limit the number of rows returned, and their sort order, similar to the SQL LIMIT and ORDER BY
clauses, except they're specified as part of the Elasticsearch query, and the sorting/limiting happens within
Elasticsearch. In general, this is significantly faster than having Postgres do it.
The following functions are designed to wrap the query you want to execute, on the outer levels. For example, to return only 10 rows:
SELECT * FROM table WHERE table ==> dsl.limit(10, dsl.term('title', 'cat'));
Or to return 10 rows sorted by id:
SELECT * FROM table WHERE table ==> dsl.sort('id', 'asc', dsl.limit(10, dsl.term('title', 'cat')));
Sort and Limit Functions
dsl.limit()
FUNCTION dsl.limit(
limit bigint,
query zdbquery
) RETURNS zdbquery
Limits the number of rows returned to the specified limit limit. If the query doesn't otherwise contain a dsl.sort()
(see below), then the results returned are first sorted by _score in descending order. This ensures that ZomboDB
returns the top scoring documents.
dsl.offset()
FUNCTION dsl.offset(
offset bigint,
query zdbquery
) RETURNS zdbquery
Similar to the SQL OFFSET clause, allows you to start returning results from a point other than the start.
dsl.sort()
FUNCTION dsl.sort(
sort_field text,
sort_direction dsl.es_sort_directions, -- one of 'asc' or 'desc'
query zdbquery
) RETURNS zdbquery
Sort the results returned from Elasticsearch by an arbitrary field.
Because the SQL standard doesn't guarantee result ordering unless the query contains an ORDER BY clause, you should
use ORDER BY in conjunction with this function. For example:
SELECT * FROM table WHERE table ==> dsl.sort('id', 'asc', 'cats AND dogs') ORDER BY id asc;
In practice, using dsl.sort() only makes sense when combined with dsl.limit().
There's an overloaded version of dsl.sort() (described below) that allows for more complex sorting descriptors.
dsl.sd()
FUNCTION dsl.sd(
field text,
"order" dsl.es_sort_directions,
mode dsl.es_sort_modes DEFAULT NULL
) RETURNS dsl.es_sort_descriptor
dsl.sd() (which is short for "sort descriptor") allows you to contruct an object that represents sorting. It is
designed to be used as the arguments to dsl.sort_many(zdbquery, VARIADIC dsl.es_sort_descriptor[]) (defined below).
The possible values for the mode argument are min, max, sum, avg, and median. These are documented here:
https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-sort.html#\_sort_mode_option
Example:
SELECT * FROM table WHERE table ==> dsl.sort_many(dsl.match_all(), dsl.sd('field', 'asc'), dsl.sd('price', 'desc', 'avg'));
dsl.sd_nested()
FUNCTION dsl.sd_nested(
field text, "order"
dsl.es_sort_directions,
nested_path text,
nested_filter zdbquery DEFAULT NULL,
mode dsl.es_sort_modes DEFAULT NULL
) RETURNS dsl.es_sort_descriptor
dsl.sd_nested() (which is short for "nested field sort descriptor") allows you to contruct an object that represents
sorting for a nested field. It is designed to be used as an argument to
dsl.sort_many(zdbquery, VARIADIC dsl.es_sort_descriptor[]) (defined below).
The possible values for the mode argument are min, max, sum, avg, and median. These are documented here:
https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-sort.html#\_sort_mode_option
Example:
SELECT * FROM table WHERE table ==> dsl.sort_many(dsl.match_all(), dsl.sd_nested('offer.price', 'asc', 'offer', dsl.match_all(), 'avg'), dsl.sd('id', 'desc', 'avg'));
The above would first sort the results by the average value from the nested field offer.price in ascending order, and
then by id in descending order.
dsl.sort_many()
FUNCTION dsl.sort_many(
query zdbquery,
VARIADIC descriptors dsl.es_sort_descriptor[]
) RETURNS zdbquery
This is similar to the dsl.sort() function described above, however it requires the query be the first argument and
allows for a variable list of sort descriptors, that should be generated using the dsl.sd() or dsl.sd_nested()
functions.
Example:
SELECT * FROM table WHERE table ==> dsl.sort_many(dsl.match_all(), dsl.sd('field', 'asc'), dsl.sd('price', 'desc', 'avg'));
dsl.sort_direct()
FUNCTION dsl.sort_direct(
sort_json json,
query zdbquery
) RETURNS zdbquery
This function allows you to specify direct json to describe how Elasticsearch should sort the results.
In the Elasticearch _search request body, this is the top-level "sort" property
(https://www.elastic.co/guide/en/elasticsearch/reference/5.6/search-request-sort.html#nested-sorting).
Example:
SELECT * FROM table WHERE table ==> dsl.sort_direct('{
"_script" : {
"type" : "number",
"script" : {
"lang": "painless",
"source": "doc[''field_name''].value * params.factor",
"params" : {
"factor" : 1.1
}
},
"order" : "asc"
}
}', dsl.match_all());
dsl.min_score()
FUNCTION dsl.min_score(
min_score real,
query zdbquery
) RETURNS zdbquery
This allows you to specify Elastisearch's
min_score search
property to ensure documents with a score less than the specified value are excluded from the results.
SQL Builder API Functions
Simple Boolean Functions
dsl.and()
FUNCTION dsl.and(
VARIADIC queries zdbquery[]
) RETURNS zdbquery
Generates an Elasticsearch bool query where all the arguments are part of the must clause.
dsl.or()
FUNCTION dsl.or(
VARIADIC queries zdbquery[]
) RETURNS zdbquery
Generates an Elasticsearch bool query where all the arguments are part of the should clause.
dsl.not()
FUNCTION dsl.not(
VARIADIC queries zdbquery[]
) RETURNS zdbquery
Generates an Elasticsearch bool query where all the arguments are part of the must_not clause.
Elasticsearch "bool" Query Support
dsl.bool()
FUNCTION dsl.bool(
VARIADIC queries dsl.esqdsl_bool_part
) RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-bool-query.html
This function represents the Elasticsearch bool query. It takes one or more "boolean part" queries, which are
generated using the SQL functions named dsl.must(), dsl.must_not(), dsl.should(), and dsl.filter().
Multiple usages of the same boolean part will be merged together automatically.
Example:
SELECT dsl.bool(
dsl.must('beer', 'wine', 'cheese'),
dsl.must_not('beer', 'wine', 'cheese'),
dsl.should('beer', 'wine', 'cheese'),
dsl.filter('beer', 'wine', 'cheese'),
dsl.must('lettuce', 'tomato', 'bread') -- we used dsl.must() above too!
);
Which ultimately generates the following Elasticsearch QueryDSL:
{
"bool": {
"filter": [
{
"query_string": {
"query": "beer"
}
},
{
"query_string": {
"query": "wine"
}
},
{
"query_string": {
"query": "cheese"
}
}
],
"must": [
{
"query_string": {
"query": "beer"
}
},
{
"query_string": {
"query": "wine"
}
},
{
"query_string": {
"query": "cheese"
}
},
{
"query_string": {
"query": "lettuce"
}
},
{
"query_string": {
"query": "tomato"
}
},
{
"query_string": {
"query": "bread"
}
}
],
"must_not": [
{
"query_string": {
"query": "beer"
}
},
{
"query_string": {
"query": "wine"
}
},
{
"query_string": {
"query": "cheese"
}
}
],
"should": [
{
"query_string": {
"query": "beer"
}
},
{
"query_string": {
"query": "wine"
}
},
{
"query_string": {
"query": "cheese"
}
}
]
}
}
dsl.must()
FUNCTION dsl.must (
VARIADIC queries zdbquery[])
RETURNS dsl.esqdsl_must
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-bool-query.html
This is the must clause of the Elasticsearch QueryDSL bool query. The queries must appear in matching documents and
will contribute to the score.
This function is designed to be used with the must argument of dsl.bool(). Its arguments can be or or more of any of
ZomboDB's dsl functions that return a type of zdbquery.
dsl.must_not()
FUNCTION dsl.must_not (
VARIADIC queries zdbquery[])
RETURNS dsl.esqdsl_must_not
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-bool-query.html
This is the must_not clause of the Elasticsearch QueryDSL bool query. The queries must not appear in the matching
documents. Clauses are executed in filter context meaning that scoring is ignored and clauses are considered for
caching. Because scoring is ignored, a score of 0 for all documents is returned.
This function is designed to be used with the must_not argument of dsl.bool(). Its arguments can be or or more of
any of ZomboDB's dsl functions that return a type of zdbquery.
dsl.should()
FUNCTION dsl.should (
VARIADIC queries zdbquery[])
RETURNS dsl.esqdsl_should
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-bool-query.html
This is the should clause of the Elasticsearch QueryDSL bool query. The queries should appear in matching documents
and will contribute to the score.
This function is designed to be used with the should argument of dsl.bool(). Its arguments can be or or more of any
of ZomboDB's dsl functions that return a type of zdbquery.
dsl.filter()
FUNCTION dsl.filter (
VARIADIC queries zdbquery[])
RETURNS dsl.esqdsl_filter
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-bool-query.html
This is the filter object of an Elasticsearch QueryDSL bool.
The clause (query) must appear in matching documents. However unlike must the score of the query will be ignored. Filter clauses are executed in filter context, meaning that scoring is ignored and clauses are considered for caching.
This function is designed to be used with the filter argument of dsl.bool(). Its arguments can be or or more of any
of ZomboDB's dsl functions that return a type of zdbquery.
Elasticsearch Query DSL Support
dsl.boosting()
FUNCTION dsl.boosting (
positive zdbquery,
negative zdbquery,
negative_boost real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-boosting-query.html
The boosting query can be used to effectively demote results that match a given query. Unlike the "NOT" clause in bool query, this still selects documents that contain undesirable terms, but reduces their overall score.
dsl.common()
FUNCTION dsl.common (
field text,
query text,
boost real DEFAULT NULL,
cutoff_frequency real DEFAULT NULL,
analyzer text DEFAULT NULL,
minimum_should_match integer DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-common-terms-query.html
The common terms query is a modern alternative to stopwords which improves the precision and recall of search results (by taking stopwords into account), without sacrificing performance.
dsl.constant_score()
FUNCTION dsl.constant_score (
boost real,
query zdbquery)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-constant-score-query.html
A query that wraps another query and simply returns a constant score equal to the query boost for every document in the filter. Maps to Lucene ConstantScoreQuery.
dsl.datetime_range()
FUNCTION dsl.datetime_range (
field text,
lt timestamp with time zone DEFAULT NULL,
gt timestamp with time zone DEFAULT NULL,
lte timestamp with time zone DEFAULT NULL,
gte timestamp with time zone DEFAULT NULL,
boost real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-range-query.html
Matches documents with fields that have terms within a certain range. This form is for timestamp values.
ZomboDB will automatically convert the specified time to UTC (to be compatible with Elasticsearch) however, if you
don't specify the time zone the timestamp represents then Postgres will first assume it belongs to whatever time zone
the server is running in (via the TimeZone GUC). Read here for more about how Postgres handles time zones:
https://www.postgresql.org/docs/11/datatype-datetime.html#DATATYPE-TIMEZONES
dsl.dis_max()
FUNCTION dsl.dis_max (
queries zdbquery[],
boost real DEFAULT NULL,
tie_breaker real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-dis-max-query.html
A query that generates the union of documents produced by its subqueries, and that scores each document with the maximum score for that document as produced by any subquery, plus a tie breaking increment for any additional matching subqueries.
dsl.field_exists()
FUNCTION dsl.field_exists (
field text)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-exists-query.html
Returns documents that have at least one non-null value in the specified field
dsl.field_missing()
FUNCTION dsl.field_missing (
field text)
RETURNS zdbquery
The inverse of dsl.field_exists(). Returns documents that have no value in the specified field
dsl.fuzzy()
FUNCTION dsl.fuzzy (
field text,
value text,
boost real DEFAULT NULL,
fuzziness integer DEFAULT NULL,
prefix_length integer DEFAULT NULL,
max_expansions integer DEFAULT NULL,
transpositions boolean DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-fuzzy-query.html
The fuzzy query uses similarity based on Levenshtein edit distance.
dsl.match()
FUNCTION dsl.match (
field text,
query text,
boost real DEFAULT NULL,
analyzer text DEFAULT NULL,
minimum_should_match integer DEFAULT NULL,
lenient boolean DEFAULT NULL,
fuzziness integer DEFAULT NULL,
fuzzy_rewrite text DEFAULT NULL,
fuzzy_transpositions boolean DEFAULT NULL,
prefix_length integer DEFAULT NULL,
cutoff_frequency real DEFAULT NULL,
auto_generate_synonyms_phrase_query boolean DEFAULT NULL,
zero_terms_query zerotermsquery DEFAULT NULL,
operator operator DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-match-query.html
match queries accept text/numerics/dates, analyzes them, and constructs a query.
Enum zerotermsquery available values: none, all
dsl.match_all()
FUNCTION dsl.match_all (
boost real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-match-all-query.html
The most simple query, which matches all documents, giving them all a _score of 1.0.
dsl.match_none()
FUNCTION dsl.match_none ()
RETURNS zdbquery
The inverse of dsl.match_all(). Matches no documents.
dsl.match_phrase()
FUNCTION dsl.match_phrase (
field text,
query text,
boost real DEFAULT NULL,
slop integer DEFAULT NULL,
analyzer text DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-match-query-phrase.html
The match_phrase query analyzes the text and creates a phrase query out of the analyzed text.
dsl.match_phrase_prefix()
FUNCTION dsl.match_phrase_prefix (
field text,
query text,
boost real DEFAULT NULL,
slop integer DEFAULT NULL,
analyzer text DEFAULT NULL,
max_expansions integer DEFAULT NULL)
RETURNS zdbquery
ds.match_phrase_prefix() is the same as dsl.match_phrase(), except that it allows for prefix matches on the last
term in the text.
dsl.more_like_this()
FUNCTION dsl.more_like_this (
"like" text,
fields text[] DEFAULT NULL,
stop_words text[] DEFAULT ARRAY[...],
boost real DEFAULT NULL,
unlike text DEFAULT NULL,
analyzer text DEFAULT NULL,
minimum_should_match integer DEFAULT NULL,
boost_terms real DEFAULT NULL,
include boolean DEFAULT NULL,
min_term_freq integer DEFAULT NULL,
max_query_terms integer DEFAULT NULL,
min_doc_freq integer DEFAULT NULL,
max_doc_freq integer DEFAULT NULL,
min_word_length integer DEFAULT NULL,
max_word_length integer DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-mlt-query.html
The More Like This Query finds documents that are "like" a given set of documents. In order to do so, MLT selects a set of representative terms of these input documents, forms a query using these terms, executes the query and returns the results.
This form takes a single blob of text as the source document.
dsl.more_like_this()
FUNCTION dsl.more_like_this (
"like" text[],
fields text[] DEFAULT NULL,
stop_words text[] DEFAULT ARRAY[...],
boost real DEFAULT NULL,
unlike text DEFAULT NULL,
analyzer text DEFAULT NULL,
minimum_should_match integer DEFAULT NULL,
boost_terms real DEFAULT NULL,
include boolean DEFAULT NULL,
min_term_freq integer DEFAULT NULL,
max_query_terms integer DEFAULT NULL,
min_doc_freq integer DEFAULT NULL,
max_doc_freq integer DEFAULT NULL,
min_word_length integer DEFAULT NULL,
max_word_length integer DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-mlt-query.html
The More Like This Query finds documents that are "like" a given set of documents. In order to do so, MLT selects a set of representative terms of these input documents, forms a query using these terms, executes the query and returns the results.
This form takes multiple snippets of text as the source documents.
dsl.multi_match()
FUNCTION dsl.multi_match (
fields text[],
query text,
boost real DEFAULT NULL,
analyzer text DEFAULT NULL,
minimum_should_match integer DEFAULT NULL,
lenient boolean DEFAULT NULL,
fuzziness integer DEFAULT NULL,
fuzzy_rewrite text DEFAULT NULL,
fuzzy_transpositions boolean DEFAULT NULL,
prefix_length integer DEFAULT NULL,
cutoff_frequency real DEFAULT NULL,
auto_generate_synonyms_phrase_query boolean DEFAULT NULL,
zero_terms_query zerotermsquery DEFAULT NULL,
operator operator DEFAULT NULL,
match_type matchtype DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-multi-match-query.html
The multi_match query builds on the match query to allow multi-field queries.
Enum zerotermsquery available values: none, all
dsl.query_string()
FUNCTION dsl.query_string(
query text,
default_field text DEFAULT NULL,
allow_leading_wildcard boolean DEFAULT NULL,
analyze_wildcard boolean DEFAULT NULL,
analyzer text DEFAULT NULL,
auto_generate_synonyms_phrase_query boolean DEFAULT NULL,
boost real DEFAULT NULL,
default_operator querystringdefaultoperator DEFAULT NULL,
enable_position_increments boolean DEFAULT NULL,
fields text[] DEFAULT NULL,
fuzziness integer DEFAULT NULL,
fuzzy_max_expansions bigint DEFAULT NULL,
fuzzy_transpositions boolean DEFAULT NULL,
fuzzy_prefix_length bigint DEFAULT NULL,
lenient boolean DEFAULT NULL,
max_determinized_states bigint DEFAULT NULL,
minimum_should_match integer DEFAULT NULL,
quote_analyzer text DEFAULT NULL,
phrase_slop bigint DEFAULT NULL,
quote_field_suffix text DEFAULT NULL,
time_zone text DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-query-string-query.html
A query that uses a query parser in order to parse its content. The query_string query parses the input and splits text around operators. Each textual part is analyzed independently of each other.
Enum querystringdefaultoperator available values: and, or
dsl.nested()
FUNCTION dsl.nested (
path text,
query zdbquery,
score_mode scoremode DEFAULT 'avg'::scoremode),
ignore_unmapped boolean DEFAULT NULL
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-nested-query.html
Nested query allows to query nested objects / docs (see nested mapping). The query is executed against the nested objects / docs as if they were indexed as separate docs (they are, internally) and resulting in the root parent doc (or parent nested mapping).
Enum scoremode available values: avg, sum, min, max, none
dsl.noteq()
FUNCTION dsl.noteq (
query zdbquery)
RETURNS zdbquery
Generates a bool query where the argument is the only member of the bool query's must_not clause.
dsl.phrase()
FUNCTION dsl.phrase (
field text,
query text,
boost real DEFAULT NULL,
slop integer DEFAULT NULL,
analyzer text DEFAULT NULL)
RETURNS zdbquery
Short-hand form of dsl.match_phrase().
dsl.prefix()
FUNCTION dsl.prefix (
field text,
prefix text,
boost real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-prefix-query.html
Matches documents that have fields containing terms with a specified prefix (not analyzed).
dsl.range()
FUNCTION dsl.range (
field text,
lt numeric DEFAULT NULL,
gt numeric DEFAULT NULL,
lte numeric DEFAULT NULL,
gte numeric DEFAULT NULL,
boost real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-range-query.html
Matches documents with fields that have terms within a certain range. This form is for numeric values.
dsl.range()
FUNCTION dsl.range (
field text,
lt text DEFAULT NULL,
gt text DEFAULT NULL,
lte text DEFAULT NULL,
gte text DEFAULT NULL,
boost real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-range-query.html
Matches documents with fields that have terms within a certain range. This form is for text values.
dsl.regexp()
FUNCTION dsl.regexp (
field text,
regexp text,
boost real DEFAULT NULL,
flags regexflags[] DEFAULT NULL,
max_determinized_states integer DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-regexp-query.html
The regexp query allows you to use regular expression term queries.
Enum regexflags available values: all, complement, interval, intersection, anystring
dsl.script()
FUNCTION dsl.script (
source_code text,
params json DEFAULT NULL,
lang text DEFAULT 'painless'::text)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-script-query.html
A query allowing to define scripts as queries. They are typically used in a filter context.
dsl.span_containing()
FUNCTION dsl.span_containing (
little zdbquery,
big zdbquery)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-span-containing-query.html
Returns matches which enclose another span query.
dsl.span_first()
FUNCTION dsl.span_first (
query zdbquery,
"end" integer)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-span-first-query.html
Matches spans near the beginning of a field.
dsl.span_masking()
FUNCTION dsl.span_masking (
field text,
query zdbquery)
RETURNS zdbquery
Wrapper to allow span queries to participate in composite single-field span queries by lying about their search field.
dsl.span_multi()
FUNCTION dsl.span_multi (
query zdbquery)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-span-multi-term-query.html
Allows you to wrap a multi term query (one of dsl.wildcard(), dsl.fuzzy(), dsl.prefix(), dsl.range() or
dsl.regexp() query) as a span query, so it can be nested.
dsl.span_near()
FUNCTION dsl.span_near (
in_order boolean,
slop integer,
VARIADIC clauses zdbquery[])
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-span-near-query.html
Matches spans which are near one another. One can specify slop, the maximum number of intervening unmatched positions, as well as whether matches are required to be in-order.
dsl.span_not()
FUNCTION dsl.span_not (
include zdbquery,
exclude zdbquery,
pre integer DEFAULT NULL,
post integer DEFAULT NULL,
dist integer DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-span-not-query.html
Removes matches which overlap with another span query or which are within x tokens before (controlled by the parameter pre) or y tokens after (controled by the parameter post) another SpanQuery.
dsl.span_or()
FUNCTION dsl.span_or (
VARIADIC clauses zdbquery[])
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-span-or-query.html
Matches the union of its span clauses.
dsl.span_term()
FUNCTION dsl.span_term (
field text,
value text,
boost real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-span-term-query.html
Matches spans containing a term.
dsl.span_within()
FUNCTION dsl.span_within (
little zdbquery,
big zdbquery)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-span-within-query.html
Returns matches which are enclosed inside another span query.
dsl.term()
FUNCTION dsl.term (
field text,
value numeric,
boost real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-term-query.html
The term query finds documents that contain the exact term specified in the inverted index. This form is for numeric terms.
dsl.term()
FUNCTION dsl.term (
field text,
value text,
boost real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-term-query.html
The term query finds documents that contain the exact term specified in the inverted index. This form is for text terms.
dsl.terms()
FUNCTION dsl.terms (
field text,
VARIADIC "values" numeric[])
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-terms-query.html
Filters documents that have fields that match any of the provided terms (not analyzed). This form is for numeric terms.
dsl.terms()
FUNCTION dsl.terms (
field text,
VARIADIC "values" text[])
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-terms-query.html
Filters documents that have fields that match any of the provided terms (not analyzed). This form is for text terms.
dsl.terms_array()
FUNCTION dsl.terms_array (
field text,
"values" anyarray)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-terms-query.html
Filters documents that have fields that match any of the provided terms (not analyzed). This form is for an array of any kind of Postgres datatype.
dsl.terms_lookup()
FUNCTION dsl.terms_lookup (
field text,
index text,
type text,
path text,
id text)
RETURNS zdbquery
When it’s needed to specify a terms filter with a lot of terms it can be beneficial to fetch those term values from a document in an index.
dsl.wildcard()
FUNCTION dsl.wildcard (
field text,
wildcard text,
boost real DEFAULT NULL)
RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-wildcard-query.html
Matches documents that have fields matching a wildcard expression (not analyzed). Supported wildcards are *, which matches any character sequence (including the empty one), and ?, which matches any single character. Note that this query can be slow, as it needs to iterate over many terms. In order to prevent extremely slow wildcard queries, a wildcard term should not start with one of the wildcards * or ?.
Postgis Support
ZomboDB provides basic support for Postgis. It automatically maps columns of type geometry and geography to
Elasticsearch's geo_shape type, and geometry(Point, 2276) is instead indexed as an Elasticsearch geo_point.
Additionally, it exposes a few functions for querying geo_shapes and polygons and bounding boxes.
dsl.geo_shape()
FUNCTION dsl.geo_shape(
field text,
geojson_shape json,
relation geoshaperelation
) RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-geo-shape-query.html
The geoshape query uses the same grid square representation as the geoshape mapping to find documents that have a shape that intersects with the query shape. It will also use the same PrefixTree configuration as defined for the field mapping.
The query supports one way of defining the query shape: by providing a whole shape definition.
Enum geoshaperelation available values: INTERSECTS, DISJOINT, WITHIN, CONTAINS
dsl.geo_polygon()
FUNCTION dsl.geo_polygon(
field text,
VARIADIC points point[]
) RETURNS zdbquery
https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-geo-polygon-query.html
Given an array of Postgres point objects, generates an Elasticsearch geo_polygon() query
dsl.geo_bounding_box()
FUNCTION dsl.geo_bounding_box(
field text,
bounding_box box,
box_type geoboundingboxtype DEFAULT 'memory'::geoboundingboxtype
)
Given a Postgres box object, generates an Elasticsearch geo_bounding_box() query.
Enum geoboundingboxtype available values: memory, indexed