Search - Leaf Queries

Question 1

what is

Answer 1

Leaf queries are a type of query that operate on individual fields within a document. These queries do not contain other queries within them, meaning they stand alone and match specific values, terms, text, or conditions directly on the field.

Question 2

Term

Answer 2

Designed for exact matches on values, usually on structured or keyword data.
Example: term, terms, range.

Question 3

Full-Text Queries

Answer 3

Used for analyzing text fields, performing text analysis, tokenization, and matching tokens.
match, match_phrase, multi_match.

Question 4

Span Queries

Answer 4

Specialized queries designed for exact matches with positional constraints in text
span_term, span_near, span_or, span_not

Question 5

Other Queries

Answer 5

Includes queries for handling specific types or conditions.
exists, prefix, wildcard, regexp, fuzzy.

Question 6

Term Query

Answer 6

The term query is used to find exact matches on keyword fields or fields that are not analyzed (such as IDs or tags). This query is case-sensitive and does not perform any text analysis.

{
“term”: {
“status”: “active”
}
}

Returns documents where the status field has the exact term “active”.
The term query is case-sensitive. For instance, searching for “Active” will not match “active” unless the exact casing matches in the indexed field.

Term Query with Numbers
{
“query”: {
“term”: {
“age”: 30
}
}
}

So there is no analysis of the field during search, like removal of stop words etc. Straight away sent to the search against the index without any change

Question 7

Terms Query

Answer 7

The terms query works similarly to the term query, but allows for matching any one of multiple specified values.

{
“terms”: {
“status”: [“active”, “pending”]
}
}
Returns documents where the status field is either “active” or “pending”.

Question 8

Range Query

Answer 8

The range query is used to search for values within a specific range, typically for numbers, dates, or other comparable fields.

{
“range”: {
“created_date”: {
“gte”: “2023-01-01”,
“lte”: “2023-12-31”
}
}
}

Question 9

Match Query

Answer 9

The match query is a full-text query used to search within text fields. It breaks down the search text into terms and matches them against tokens in the indexed field.

{
“match”: {
“description”: “Elasticsearch tutorial”
}
}

Matches documents where the description field contains the analyzed terms from “Elasticsearch tutorial”.

Question 10

Match Phrase Query

Answer 10

The match_phrase query looks for an exact sequence of terms in the specified order. This query is useful for phrase searches in text fields.

{
“match_phrase”: {
“description”: “Elasticsearch tutorial”
}
}

Finds documents where “Elasticsearch tutorial” appears as an exact phrase in the description field.

Question 11

Prefix Query

Answer 11

The prefix query matches documents where a field starts with a specified prefix. This is useful for autocompletion features or finding documents with similar prefixes.

{
“prefix”: {
“title”: “Elast”
}
}

Matches documents where the title field starts with “Elast”.

Question 12

Wildcard Query

Answer 12

The wildcard query enables partial and pattern-based matches within text fields. It allows the use of * to match any sequence of characters and ? to match a single character.

{
“wildcard”: {
“title”: “elastic*”
}
}

Matches documents where the title field starts with “elastic” followed by any sequence of characters.

Question 13

Regexp Query

Answer 13

The regexp query allows for complex regular expression matching within fields. It’s more flexible but slower than wildcard queries.

{
“regexp”: {
“title”: “elastic.*search”
}
}

Finds documents where the title field matches the pattern “elastic.*search” (like “elasticsearch”).

Question 14

Fuzzy Query

Answer 14

The fuzzy query performs approximate matching using a specified level of “fuzziness,” which allows for minor variations like typos or spelling errors.

{
“fuzzy”: {
“title”: {
“value”: “Elastsearch”,
“fuzziness”: “AUTO”
}
}
}
Finds documents with terms similar to “Elastsearch”, accounting for spelling variations (like “Elasticsearch”).

Question 15

Exists Query

Answer 15

The exists query is used to find documents where a specific field is present (non-null).

{
“exists”: {
“field”: “description”
}
}
Returns documents where the description field exists.

Question 16

Span Queries

Answer 16

Span queries allow for matching terms with specific positional constraints. They’re especially useful for precise text searches, such as finding words within a certain distance from each other.

{
“span_near”: {
“clauses”: [
{ “span_term”: { “description”: “Elasticsearch” } },
{ “span_term”: { “description”: “tutorial” } }
],
“slop”: 1,
“in_order”: true
}
}

Matches documents where “Elasticsearch” and “tutorial” appear in the description field within one position of each other, in the specified order.