Data Typesedit

Warning

This functionality is experimental and may be changed or removed completely in a future release. Elastic will take a best effort approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.

Most of Elasticsearch data types are available in Elasticsearch SQL, as indicated below:

Elasticsearch type SQL type SQL precision

Core types

null

null

0

boolean

boolean

1

byte

tinyint

3

short

smallint

5

integer

integer

10

long

bigint

19

double

double

15

float

real

7

half_float

float

16

scaled_float

float

19

keyword

varchar

based on ignore_above

text

varchar

2,147,483,647

binary

varbinary

2,147,483,647

date

timestamp

24

Complex types

object

struct

0

nested

struct

0

Unsupported types

types not mentioned above

unsupported

0

Obviously, not all types in Elasticsearch have an equivalent in SQL and vice-versa hence why, Elasticsearch SQL uses the data type particularities of the former over the latter as ultimately Elasticsearch is the backing store.

SQL and multi-fieldsedit

A core concept in Elasticsearch is that of an analyzed field, that is a full-text value that is interpreted in order to be effectively indexed. These fields are of type text and are not used for sorting or aggregations as their actual value depends on the analyzer used hence why Elasticsearch also offers the keyword type for storing the exact value.

In most case, and the default actually, is to use both types when for strings which Elasticsearch supports through multi fields, that is the ability to index the same string in multiple ways; for example index it both as text for search but also as keyword for sorting and aggregations.

As SQL requires exact values, when encountering a text field Elasticsearch SQL will search for an exact multi-field that it can use for comparisons, sorting and aggregations. To do that, it will search for the first keyword that it can find that is not normalized and use that as the original field exact value.

Consider the following string mapping:

{
    "first_name" : {
        "type" : "text",
        "fields" : {
            "raw" : {
                "type" : "keyword"
            }
        }
    }
}

The following SQL query:

SELECT first_name FROM index WHERE first_name = 'John'

is identical to:

SELECT first_name FROM index WHERE first_name.raw = 'John'

as Elasticsearch SQL automatically picks up the raw multi-field from raw for exact matching.