Percolate index is a special index which stores queries instead of documents. It is used for prospective searches (or "search in reverse").

See section Percolate query for more details about performing a search query against a percolate index.
See section Adding rules to a percolate index to learn how to prepare an index for searching.

The schema of a percolate index is fixed and contains the following fields:

Field	Description
ID	Unsigned 64-bit integer with autoincrement functionality therefore it can be omitted when you add a PQ rule
Query	Full-text query of the rule. You can think of it as the value of a MATCH clause or JSON /search. If per field operators are used inside the query, the full text fields need to be declared in the percolate index configuration. If the stored query is supposed to do only attribute filtering (no full-text querying), the query value can be empty or simply omitted. The value of this field should correspond to the expected document schema which you specify when you create a percolate index
Filters	Filters is an optional string containing attribute filters and/or expressions the same way they are defined in the WHERE clause or JSON filtering. The value of this field should correspond to the expected document schema which you specify when you create a percolate index
Tags	Optional. Tags represent a list of string labels separated by comma that can be used for filtering/deleting PQ rules. The tags can be returned along with matching documents when you Percolate query

You don't need to worry about adding the above fields when you create a percolate index.

What you need to take care of when you add a new index is to specify the expected schema of a document which is to be checked against the rules you will add later. This is done the same way as for any other local index.

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SQL
HTTP
PHP
Python
javascript
java
CONFIG

📋

CREATE TABLE products(title text, meta json) type='pq';

POST /sql -d "mode=raw&query=CREATE TABLE products(title text, meta json) type='pq'"

$index = [
    'index' => 'products',
    'body' => [
        'columns' => [
            'title' => ['type' => 'text'],
            'meta' => ['type' => 'json']
        ],
        'settings' => [
            'type' => 'pq'
        ]
    ]
];
$client->indices()->create($index);

utilsApi.sql('mode=raw&query=CREATE TABLE products(title text, meta json) type=\'pq\'')

res = await utilsApi.sql('mode=raw&query=CREATE TABLE products(title text, meta json) type=\'pq\'');

utilsApi.sql("mode=raw&query=CREATE TABLE products(title text, meta json) type='pq'");

index products {
  type = percolate
  path = idx_pq
  rt_field = title
  rt_attr_json = meta
}

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Response

Query OK, 0 rows affected (0.00 sec)

{
"total":0,
"error":"",
"warning":""
}

Array(
    [total] => 0
    [error] => 
    [warning] =>
)

Template index is a pseudo-index since it does not store any data and does not create any files on your disk. At the same time it can have the same NLP settings as a plain or a real-time index. Template indexes can be used for few purposes:

as templates to inherit plain/real-time indexes in Plain mode just to minify Manticore configuration file
keywords generation with help of CALL KEYWORDS
highlighting of an arbitrary string using CALL SNIPPETS

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CONFIG

CONFIG

📋

index template {
  type = template
  morphology = stem_en
  wordforms = wordforms.txt
  exceptions = exceptions.txt
  stopwords = stopwords.txt
}

Percolate index

Creating a percolate index via MySQL protocol:

Creating a percolate index via JSON over HTTP:

Creating a percolate index via PHP client:

Creating a percolate index via config:

Template index

Creating a template index via a configuration file:

NLP and tokenization