In Manticore Search, there are two ways to manage tables:

Real-time mode requires no table definition in the configuration file. However, the data_dir directive in the searchd section is mandatory. Index files are stored inside the data_dir.

Replication is only available in this mode.

You can use SQL commands such as CREATE TABLE, ALTER TABLE and DROP TABLE to create and modify table schema, and to drop it. This mode is particularly useful for real-time and percolate tables.

Table names are converted to lowercase when created.

In this mode, you can specify the table schema in the configuration file. Manticore reads this schema on startup and creates the table if it doesn't exist yet. This mode is particularly useful for plain tables that use data from an external storage.

To drop a table, remove it from the configuration file or remove the path setting and send a HUP signal to the server or restart it.

Table names are case-sensitive in this mode.

All table types are supported in this mode.

A real-time table is a main type of table in Manticore. It lets you add, update, and delete documents, and you can see these changes right away. You can set up a real-time Table in a configuration file or use commands like CREATE, UPDATE, DELETE, or ALTER.

Internally a real-time table consists of one or more plain tables called chunks. There are two kinds of chunks:

• multiple disk chunks - these are saved on a disk and are structured like a plain table.
• single ram chunk - this is kept in memory and collects all changes.

The size of the RAM chunk is controlled by the rt_mem_limit setting. Once this limit is reached, the RAM chunk is transferred to disk as a disk chunk. If there are too many disk chunks, Manticore combines some of them to improve performance.

You can create a new real-time table in two ways: by using the CREATE TABLE command or through the _mapping endpoint of the HTTP JSON API.

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'],
]);

utilsApi.sql('CREATE TABLE forum(title text, price float)')

res = await utilsApi.sql('CREATE TABLE forum(title text, price float)');

utilsApi.sql("CREATE TABLE forum(title text, price float)");

utilsApi.Sql("CREATE TABLE forum(title text, price float)");

table products {
  type = rt
  path = tbl
  rt_field = title
  rt_attr_uint = price
  stored_fields = title
}

Query OK, 0 rows affected (0.00 sec)

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

NOTE: The _mapping API requires Manticore Buddy. If it doesn't work, make sure Buddy is installed.

"properties"
{
  "FIELD_NAME_1":
  {
    "type": "FIELD_TYPE_1"
  },
  "FIELD_NAME_2":
  {
    "type": "FIELD_TYPE_2"
  },

  ...

  "FIELD_NAME_N":
  {
    "type": "FIELD_TYPE_M"
  }
}

POST /your_table_name/_mapping -d '
{
  "test": {
    "mappings": {
      "properties": {
        "price": {
            "type": "float"
        },
        "title": {
            "type": "text"
        }
      }
    }
  }
}
'

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

CREATE TABLE table_name LIKE old_table_name [WITH DATA]

create table products LIKE old_products;

create table products LIKE old_products WITH DATA;

• Add documents.
• Update attributes and full-text fields using the Update process.
• Delete documents.
• Empty the table.
• Change the schema online with the ALTER command, as explained in Change schema online.
• Define the table in a configuration file, as detailed in Define table.
• Use the UUID feature for automatic ID provisioning.

• Ingest data using the indexer feature.
• Connect it to sources for easy indexing from external storage.
• Update the killlist_target, as it is automatically managed by the real-time table.

The following table outlines the different file extensions and their respective descriptions in a real-time table:

For more information on the structure of disk chunks, refer to the plain table files structure.

Plain table is a basic element for non-percolate searching. It can be defined only in a configuration file using the Plain mode, and is not supported in the RT mode. It is typically used in conjunction with a source to process data from the external storage and can later be attached to a real-time table.

To create a plain table, you'll need to define it in a configuration file. It's not supported by the CREATE TABLE command.

source source {
  type             = mysql
  sql_host         = localhost
  sql_user         = myuser
  sql_pass         = mypass
  sql_db           = mydb
  sql_query        = SELECT id, title, description, category_id  from mytable
  sql_attr_uint    = category_id
  sql_field_string = title
 }

table tbl {
  type   = plain
  source = source
  path   = /path/to/table
 }

• Build it from an external storage using a source and indexer
• Perform an in-place update of integer, float, string and MVA attribute
• Update it's killlist_target

• Insert additional data into the table once it has been built
• Delete data from the table
• Create, delete, or alter the table schema online
• Use UUID for automatic ID generation (data from external storage must include a unique identifier)

Numeric attributes, including MVAs, are the only elements that can be updated in a plain table. All other data in the table is immutable. If updates or new records are required, the table must be rebuilt. During the rebuilding process, the existing table remains available to serve requests, and a process called rotation is performed when the new version is ready, bringing it online and discarding the old version.

The speed at which a plain table is indexed depends on several factors, including:

• Data source retrieval speed
• Tokenization settings
• The hardware specifications (such as CPU, RAM, and disk performance)

For small data sets, the simplest option is to have a single plain table that is fully rebuilt as needed. This approach is acceptable when:

• The data in the table is not as fresh as the data in the source
• The time it takes to build the table increases as the data set grows

For larger data sets, a plain table can be used instead of a Real-Time. The main+delta scenario involves:

• Creating a smaller table for incremental indexing
• Combining the two tables using a distributed table

This approach allows for infrequent rebuilding of the larger table and more frequent processing of updates from the source. The smaller table can be rebuilt more often (e.g. every minute or even every few seconds).

However, as time goes on, the indexing duration for the smaller table will become too long, requiring a rebuild of the larger table and the emptying of the smaller one.

The main+delta schema is explained in detail in this interactive course.

The mechanism of kill list and killlist_target directive is used to ensure that documents from the current table take precedence over those from the other table.

For more information on this topic, see here.

The following table outlines the various file extensions used in a plain table and their respective descriptions: