Starting the server

You can install and start Manticore easily in Ubuntu, Centos, Debian, Windows and MacOS or use Manticore as a docker container.

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Ubuntu
Debian
Centos
Windows
MacOS
Docker

📋

wget https://repo.manticoresearch.com/manticore-repo.noarch.deb
sudo dpkg -i manticore-repo.noarch.deb
sudo apt update
sudo apt install manticore manticore-columnar-lib
sudo systemctl start manticore

wget https://repo.manticoresearch.com/manticore-repo.noarch.deb
sudo dpkg -i manticore-repo.noarch.deb
sudo apt update
sudo apt install manticore manticore-columnar-lib
sudo systemctl start manticore

sudo yum install https://repo.manticoresearch.com/manticore-repo.noarch.rpm
sudo yum install manticore manticore-columnar-lib
sudo systemctl start manticore

Download Windows archive from https://manticoresearch.com/install/
Extract all from the archive to C:\Manticore

C:\Manticore\bin\searchd --install --config C:\Manticore\sphinx.conf.in --servicename Manticore

Start Manticore from the Services snap-in of the Microsoft Management Console

brew install manticoresearch
brew services start manticoresearch

docker pull manticoresearch/manticore
docker run -e EXTRA=1 --name manticore -p9306:9306 -p9308:9308 -p9312:9312 -d manticoresearch/manticore

For persisting your data directory read how to use Manticore docker in production

By default Manticore is waiting for your connections on:

port 9306 for MySQL clients
port 9308 for HTTP/HTTPS connections
port 9312 for connections from other Manticore nodes and clients based on Manticore binary API

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SQL
HTTP
PHP
Python
Javascript
Java

📋

mysql -h0 -P9306

HTTP is a stateless protocol so it doesn't require any special connection phase:

curl -s "http://localhost:9308/search"

// https://github.com/manticoresoftware/manticoresearch-php
require_once __DIR__ . '/vendor/autoload.php';
$config = ['host'=>'127.0.0.1','port'=>9308];
$client = new \Manticoresearch\Client($config);

// https://github.com/manticoresoftware/manticoresearch-python
import manticoresearch
config = manticoresearch.Configuration(
    host = "http://127.0.0.1:9308"
)
client =  manticoresearch.ApiClient(config)
indexApi = manticoresearch.IndexApi(client)
searchApi = manticoresearch.SearchApi(client)
utilsApi = manticoresearch.UtilsApi(client)

// https://github.com/manticoresoftware/manticoresearch-javascript
var Manticoresearch = require('manticoresearch');
var client= new Manticoresearch.ApiClient()
client.basePath="http://127.0.0.1:9308";
indexApi = new Manticoresearch.IndexApi(client);
searchApi = new Manticoresearch.SearchApi(client);
utilsApi = new Manticoresearch.UtilsApi(client);

// https://github.com/manticoresoftware/manticoresearch-java
import com.manticoresearch.client.*;
import com.manticoresearch.client.model.*;
import com.manticoresearch.client.api.*;
...
ApiClient client = Configuration.getDefaultApiClient();
client.setBasePath("http://127.0.0.1:9308");
...
IndexApi indexApi = new IndexApi(client);
SearchApi searchApi = new UtilsApi(client);
UtilsApi utilsApi = new UtilsApi(client);

Let's now create a table called "products" with 2 fields:

title - full-text field which will contain our product's title
price - of type "float"

Note that it is possible to omit creating a table with an explicit create statement. For more information, see Auto schema.

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SQL
HTTP
PHP
Python
Javascript
Java

📋

create table products(title text, price float) morphology='stem_en';

POST /cli -d "create table products(title text, price float) morphology='stem_en'"

$index = new \Manticoresearch\Index($client);
$index->setName('products');
$index->create([
    'title'=>['type'=>'text'],
    'price'=>['type'=>'float'],
],['morphology' => 'stem_en']);

utilsApi.sql('create table products(title text, price float) morphology=\'stem_en\'')

res = await utilsApi.sql('create table products(title text, price float) morphology=\'stem_en\'');

utilsApi.sql("create table products(title text, price float) morphology='stem_en'");

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Response

Query OK, 0 rows affected (0.02 sec)

Let's now add few documents to the table:

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SQL
JSON
PHP
Python
Javascript
Java

📋

insert into products(title,price) values ('Crossbody Bag with Tassel', 19.85), ('microfiber sheet set', 19.99), ('Pet Hair Remover Glove', 7.99);

"id":0 or no id forces automatic ID generation.

POST /insert
{
  "index":"products",
  "doc":
  {
    "title" : "Crossbody Bag with Tassel",
    "price" : 19.85
  }
}


POST /insert
{
  "index":"products",
  "doc":
  {
    "title" : "microfiber sheet set",
    "price" : 19.99
  }
}

POST /insert
{
  "index":"products",
  "doc":
  {
    "title" : "Pet Hair Remover Glove",
    "price" : 7.99
  }
}

$index->addDocuments([
        ['title' => 'Crossbody Bag with Tassel', 'price' => 19.85],
        ['title' => 'microfiber sheet set', 'price' => 19.99],
        ['title' => 'Pet Hair Remover Glove', 'price' => 7.99]
]);

indexApi.insert({"index" : "test", "doc" : {"title" : "Crossbody Bag with Tassel", "price" : 19.85}})
indexApi.insert({"index" : "test", "doc" : {"title" : "microfiber sheet set", "price" : 19.99}})
indexApi.insert({"index" : "test", "doc" : {"title" : "Pet Hair Remover Glove", "price" : 7.99}})

res = await indexApi.insert({"index" : "test", "doc" : {"title" : "Crossbody Bag with Tassel", "price" : 19.85}});
res = await indexApi.insert({"index" : "test", "doc" : {"title" : "microfiber sheet set", "price" : 19.99}});
res = await indexApi.insert({"index" : "test", doc" : {"title" : "Pet Hair Remover Glove", "price" : 7.99}});

InsertDocumentRequest newdoc = new InsertDocumentRequest();
HashMap<String,Object> doc = new HashMap<String,Object>(){{
    put("title","Crossbody Bag with Tassel");
    put("price",19.85);
}};
newdoc.index("products").setDoc(doc);
sqlresult = indexApi.insert(newdoc);

newdoc = new InsertDocumentRequest();
doc = new HashMap<String,Object>(){{
    put("title","microfiber sheet set");
    put("price",19.99);
}};
newdoc.index("products").setDoc(doc);
sqlresult = indexApi.insert(newdoc);

newdoc = new InsertDocumentRequest();
doc = new HashMap<String,Object>(){{
    put("title","Pet Hair Remover Glove");
    put("price",7.99);
 }};
newdoc.index("products").setDoc(doc);
indexApi.insert(newdoc);

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Response

Query OK, 3 rows affected (0.01 sec)

Let's find one of the documents. The query we will use is 'remove hair'. As you can see it finds document with title 'Pet Hair Remover Glove' and highlights 'Hair remover' in it even though the query has "remove", not "remover". This is because when we created the table we turned on using English stemming (morphology "stem_en").

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SQL
JSON
PHP
Python
javascript
Java

📋

select id, highlight(), price from products where match('remove hair');

POST /search
{
  "index": "products",
  "query": { "match": { "title": "remove hair" } },
  "highlight":
  {
    "fields": ["title"]
  }
}

$result = $index->search('@title remove hair')->highlight(['title'])->get();
foreach($result as $doc)
{
    echo "Doc ID: ".$doc->getId()."\n";
    echo "Doc Score: ".$doc->getScore()."\n";
    echo "Document fields:\n";
    print_r($doc->getData());
    echo "Highlights: \n";
    print_r($doc->getHighlight());
}

searchApi.search({"index":"myindex","query":{"query_string":"@title remove hair"},"highlight":{"fields":["title"]}})

res = await searchApi.search({"index":"myindex","query":{"query_string":"@title remove hair"}"highlight":{"fields":["title"]}});


query = new HashMap<String,Object>();
query.put("query_string","@title remove hair");
searchRequest = new SearchRequest();
searchRequest.setIndex("forum");
searchRequest.setQuery(query);
HashMap<String,Object> highlight = new HashMap<String,Object>(){{
    put("fields",new String[] {"title"});

}};
searchRequest.setHighlight(highlight);
searchResponse = searchApi.search(searchRequest);

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Response

+---------------------+-------------------------------+----------+
| id                  | highlight()                   | price    |
+---------------------+-------------------------------+----------+
| 1513686608316989452 | Pet <strong>Hair Remover</strong> Glove | 7.990000 |
+---------------------+-------------------------------+----------+
1 row in set (0.00 sec)

{
  "took": 0,
  "timed_out": false,
  "hits": {
    "total": 1,
    "hits": [
      {
        "_id": "1513686608316989452",
        "_score": 1680,
        "_source": {
          "price": 7.99,
          "title": "Pet Hair Remover Glove"
        },
        "highlight": {
          "title": [
            "Pet <strong>Hair Remover</strong> Glove"
          ]
        }
      }
    ]
  }
}

Doc ID: 1513686608316989452
Doc Score: 1680
Document fields:
Array
(
    [price] => 7.99
    [title] => Pet Hair Remover Glove
)
Highlights:
Array
(
    [title] => Array
        (
            [0] => Pet <strong>Hair Remover</strong> Glove
        )
)

`

{'hits': {'hits': [{u'_id': u'1513686608316989452',
                    u'_score': 1680,
                    u'_source': {u'title': u'Pet Hair Remover Glove', u'price':7.99},
                    u'highlight':{u'title':[u'Pet <strong>Hair Remover</strong> Glove']}}}],
          'total': 1},
 'profile': None,
 'timed_out': False,
 'took': 0}

{"hits": {"hits": [{"_id": "1513686608316989452",
                    "_score": 1680,
                    "_source": {"title": "Pet Hair Remover Glove", "price":7.99},
                    "highlight":{"title":["Pet <strong>Hair Remover</strong> Glove"]}}],
          "total": 1},
 "profile": None,
 "timed_out": False,
 "took": 0}

class SearchResponse {
    took: 84
    timedOut: false
    hits: class SearchResponseHits {
        total: 1
        maxScore: null
        hits: [{_id=1513686608316989452, _score=1, _source={price=7.99, title=Pet Hair Remover Glove}, highlight={title=[Pet <strong>Hair Remover</strong> Glove]}}]
        aggregations: null
    }
    profile: null
}

Let's assume we now want to update the document - change the price to 18.5. This can be done by filtering by any field, but normally you know the document id and update something based on that.

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SQL
JSON
PHP
Python
javascript
Java

📋

update products set price=18.5 where id = 1513686608316989452;

POST /update
{
  "index": "products",
  "id": 1513686608316989452,
  "doc":
  {
    "price": 18.5
  }
}

$doc = [
    'body' => [
        'index' => 'products',
        'id' => 2,
        'doc' => [
            'price' => 18.5
        ]
    ]
];

$response = $client->update($doc);

indexApi = api = manticoresearch.IndexApi(client)
indexApi.update({"index" : "products", "id" : 1513686608316989452, "doc" : {"price":18.5}})

res = await indexApi.update({"index" : "products", "id" : 1513686608316989452, "doc" : {"price":18.5}});

UpdateDocumentRequest updateRequest = new UpdateDocumentRequest();
doc = new HashMap<String,Object >(){{
    put("price",18.5);
}};
updateRequest.index("products").id(1513686608316989452L).setDoc(doc);
indexApi.update(updateRequest);

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Response

Query OK, 1 row affected (0.00 sec)

Let's now delete all documents with price lower than 10.

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SQL
JSON
PHP
Python
javascript
Java

📋

delete from products where price < 10;

POST /delete
{
  "index": "products",
  "query":
  {
    "range":
    {
      "price":
      {
        "lte": 10
      }
    }
  }
}

$result = $index->deleteDocuments(new \Manticoresearch\Query\Range('price',['lte'=>10]));

indexApi.delete({"index" : "products", "query": {"range":{"price":{"lte":10}}}})

res = await indexApi.delete({"index" : "products", "query": {"range":{"price":{"lte":10}}}});

DeleteDocumentRequest deleteRequest = new DeleteDocumentRequest();
query = new HashMap<String,Object>();
query.put("range",new HashMap<String,Object>(){{
    put("range",new HashMap<String,Object>(){{
        put("lte",10);
    }});
}});
deleteRequest.index("products").setQuery(query);
indexApi.delete(deleteRequest);

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Response

Query OK, 1 row affected (0.00 sec)

{
  "_index": "products",
  "deleted": 1
}

Array
(
    [_index] => products
    [deleted] => 1
)

Quick start guide

Install and start Manticore

Connect to Manticore

Create a table

Add documents

Search

Update

Delete