Manticore Search Manual: Starting the server

Install and start Manticore

You can install and start Manticore easily on various operating systems, including Ubuntu, Centos, Debian, Windows, and MacOS. Additionally, you can also 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 the Windows archive from https://manticoresearch.com/install/
Extract all files from the archive to C:\Manticore
Run the following command to install Manticore as a service:

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

Connect to Manticore

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. You can simply send a HTTP request to the server and receive the response. To communicate with Manticore using the HTTP interface, you can use any HTTP client library in your programming language of choice to send GET or POST requests to the server and parse the JSON responses:

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);

Create a table

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)

Add documents

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

res = await indexApi.insert({"index" : "products", "doc" : {"title" : "Crossbody Bag with Tassel", "price" : 19.85}});
res = await indexApi.insert({"index" : "products", "doc" : {"title" : "microfiber sheet set", "price" : 19.99}});
res = await indexApi.insert({"index" : "products", "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)

Search

Let's find one of the documents. The query we will use is 'remove hair'. As you can see, it finds a document with the 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

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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":"products","query":{"query_string":"@title remove hair"},"highlight":{"fields":["title"]}})

res = await searchApi.search({"index":"products","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
}

Update

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)

Delete

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
)

Manticore Search server can be started in several ways, depending on how it was installed.

When Manticore Search is installed using DEB or RPM packages, the searchd process can be run and managed by the operating system's init system. Most Linux versions now use systemd, while older releases use SysV init.

To check which init system your platform uses, run the following command:

ps --no-headers -o comm 1

This will display the name of the process that is running as the init process, which can be used to determine the init system in use.

Starting and stopping using systemd

After the installation the Manticore Search service is not started automatically. To start Manticore run the following command:

sudo systemctl start manticore

To stop Manticore run the following command:

sudo systemctl stop manticore

The Manticore service is set to run at boot. You can check it by running:

sudo systemctl is-enabled manticore

If you want to disable Manticore from starting at boot time, run:

sudo systemctl disable manticore

To make Manticore start at boot, run:

sudo systemctl enable manticore

In some newer operating systems, it may fail with an error "Failed to enable unit: Unit... is transient or generated." In this case, you can remove the generator and try again. It's unlikely you need the generator ever again after Manticore is installed.

In Debian-based operating systems run:

sudo rm /lib/systemd/system-generators/manticore-generator
sudo systemctl daemon-reload

In CentOS and RHEL run:

sudo rm /usr/lib/systemd/system-generators/manticore-search-generator
sudo systemctl daemon-reload

If you still need the generator again, just install the Manticore packages again and it will recover the generator file.

searchd process logs startup information in systemd journal. If systemd logging is enabled you can view the logged information with the following command:

sudo journalctl --unit manticore

Custom startup flags using systemd

systemctl set-environment _ADDITIONAL_SEARCHD_PARAMS allows you to specify custom startup flags that the Manticore Search daemon should be started with. See full list here.

For example, to start Manticore with the debug logging level, you can run:

systemctl set-environment _ADDITIONAL_SEARCHD_PARAMS='--logdebug'
systemctl restart manticore

To undo it, run:

systemctl set-environment _ADDITIONAL_SEARCHD_PARAMS=''
systemctl restart manticore

Note, systemd environment variables get reset on server reboot.

Starting and stopping using service

Manticore can be started and stopped using service commands:

sudo service manticore start
sudo service manticore stop

To enable the sysV service at boot on RedHat systems run:

chkconfig manticore on

To enable the sysV service at boot on Debian systems (including Ubuntu) run:

update-rc.d manticore defaults

Please note that searchd is started by the init system under the manticore user and all files created by the server will be owned by this user. If searchd is started under, for example, the root user, the file permissions will be changed, which may result in issues when running searchd as a service again.

Quick start guide

Install and start Manticore

Connect to Manticore

Create a table

Add documents

Search

Update

Delete

Starting the server

Starting Manticore in Linux

Starting and stopping using systemd

Custom startup flags using systemd

Starting and stopping using service