Connectors#
Connectors are the source of all data for queries in Trino. Even if your data source doesn’t have underlying tables backing it, as long as you adapt your data source to the API expected by Trino, you can write queries against this data.
ConnectorFactory#
Instances of your connector are created by a ConnectorFactory
instance which
is created when Trino calls getConnectorFactory()
on the plugin. The
connector factory is a simple interface responsible for providing the connector
name and creating an instance of a Connector
object. A basic connector
implementation that only supports reading, but not writing data, should return
instances of the following services:
Configuration#
The create()
method of the connector factory receives a config
map,
containing all properties from the catalog properties file. It can be used
to configure the connector, but because all the values are strings, they
might require additional processing if they represent other data types.
It also doesn’t validate if all the provided properties are known. This
can lead to the connector behaving differently than expected when a
connector ignores a property due to the user making a mistake in
typing the name of the property.
To make the configuration more robust, define a Configuration class. This class describes all the available properties, their types, and additional validation rules.
import io.airlift.configuration.Config;
import io.airlift.configuration.ConfigDescription;
import io.airlift.configuration.ConfigSecuritySensitive;
import io.airlift.units.Duration;
import io.airlift.units.MaxDuration;
import io.airlift.units.MinDuration;
import javax.validation.constraints.NotNull;
public class ExampleConfig
{
private String secret;
private Duration timeout = Duration.succinctDuration(10, TimeUnit.SECONDS);
public String getSecret()
{
return secret;
}
@Config("secret")
@ConfigDescription("Secret required to access the data source")
@ConfigSecuritySensitive
public ExampleConfig setSecret(String secret)
{
this.secret = secret;
return this;
}
@NotNull
@MaxDuration("10m")
@MinDuration("1ms")
public Duration getTimeout()
{
return timeout;
}
@Config("timeout")
public ExampleConfig setTimeout(Duration timeout)
{
this.timeout = timeout;
return this;
}
}
The preceding example defines two configuration properties and makes the connector more robust by:
defining all supported properties, which allows detecting spelling mistakes in the configuration on server startup
defining a default timeout value, to prevent connections getting stuck indefinitely
preventing invalid timeout values, like 0 ms, that would make all requests fail
parsing timeout values in different units, detecting invalid values
preventing logging the secret value in plain text
The configuration class needs to be bound in a Guice module:
import com.google.inject.Binder;
import com.google.inject.Module;
import static io.airlift.configuration.ConfigBinder.configBinder;
public class ExampleModule
implements Module
{
public ExampleModule()
{
}
@Override
public void configure(Binder binder)
{
configBinder(binder).bindConfig(ExampleConfig.class);
}
}
And then the module needs to be initialized in the connector factory, when creating a new instance of the connector:
@Override
public Connector create(String connectorName, Map<String, String> config, ConnectorContext context)
{
requireNonNull(config, "config is null");
Bootstrap app = new Bootstrap(new ExampleModule());
Injector injector = app
.doNotInitializeLogging()
.setRequiredConfigurationProperties(config)
.initialize();
return injector.getInstance(ExampleConnector.class);
}
Note
Environment variables in the catalog properties file
(ex. secret=${ENV:SECRET}
) are resolved only when using
the io.airlift.bootstrap.Bootstrap
class to initialize the module.
See Secrets for more information.
If you end up needing to define multiple catalogs using the same connector just to change one property, consider adding support for schema and/or table properties. That would allow a more fine-grained configuration. If a connector doesn’t support managing the schema, query predicates for selected columns could be used as a way of passing the required configuration at run time.
For example, when building a connector to read commits from a Git repository, the repository URL could be a configuration property. But this would result in a catalog being able to return data only from a single repository. Alternatively, it can be a column, where every select query would require a predicate for it:
SELECT *
FROM git.default.commits
WHERE url = 'https://github.com/trinodb/trino.git'
ConnectorMetadata#
The connector metadata interface allows Trino to get a lists of schemas, tables, columns, and other metadata about a particular data source.
A basic read-only connector should implement the following methods:
listSchemaNames
listTables
streamTableColumns
getTableHandle
getTableMetadata
getColumnHandles
getColumnMetadata
If you are interested in seeing strategies for implementing more methods, look at the Example HTTP connector and the Cassandra connector. If your underlying data source supports schemas, tables, and columns, this interface should be straightforward to implement. If you are attempting to adapt something that isn’t a relational database, as the Example HTTP connector does, you may need to get creative about how you map your data source to Trino’s schema, table, and column concepts.
The connector metadata interface allows to also implement other connector features, like:
Schema management, which is creating, altering and dropping schemas, tables, table columns, views, and materialized views.
Support for table and column comments, and properties.
Schema, table and view authorization.
Executing Table functions.
Providing table statistics used by the Cost Based Optimizer (CBO) and collecting statistics during writes and when analyzing selected tables.
Data modification, which is:
inserting, updating, and deleting rows in tables,
refreshing materialized views,
truncating whole tables,
and creating tables from query results.
Role and grant management.
Pushing down:
Limit
Predicates
Projections
Sampling
Aggregations
Joins
Top N - limit with sort items
Table function invocation
Note that data modification also requires implementing a ConnectorPageSinkProvider.
ConnectorSplitManager#
The split manager partitions the data for a table into the individual chunks that Trino distributes to workers for processing. For example, the Hive connector lists the files for each Hive partition and creates one or more splits per file. For data sources that don’t have partitioned data, a good strategy here is to simply return a single split for the entire table. This is the strategy employed by the Example HTTP connector.
ConnectorRecordSetProvider#
Given a split and a list of columns, the record set provider is
responsible for delivering data to the Trino execution engine.
It creates a RecordSet
, which in turn creates a RecordCursor
that’s used by Trino to read the column values for each row.
ConnectorPageSourceProvider#
Given a split and a list of columns, the page source provider is
responsible for delivering data to the Trino execution engine.
It creates a ConnectorPageSource
, which in turn creates Page
objects
that are used by Trino to read the column values.
If not implemented, a default RecordPageSourceProvider
is used.
Given a record set provider, it returns an instance of RecordPageSource
that builds Page
objects from records in a record set.
A connector should implement a page source provider instead of a record set provider when it’s possible to create pages directly. The conversion of individual records from a record set provider into pages adds overheads during query execution.
To add support for updating and/or deleting rows in a connector, it needs
to implement a ConnectorPageSourceProvider
that returns
an UpdatablePageSource
. See Supporting DELETE and UPDATE for more.
ConnectorPageSinkProvider#
Given an insert table handle, the page sink provider is responsible for
consuming data from the Trino execution engine.
It creates a ConnectorPageSink
, which in turn accepts Page
objects
that contains the column values.
Example that shows how to iterate over the page to access single values:
@Override
public CompletableFuture<?> appendPage(Page page)
{
for (int channel = 0; channel < page.getChannelCount(); channel++) {
Block block = page.getBlock(channel);
for (int position = 0; position < page.getPositionCount(); position++) {
if (block.isNull(position)) {
// or handle this differently
continue;
}
// channel should match the column number in the table
// use it to determine the expected column type
String value = VARCHAR.getSlice(block, position).toStringUtf8();
// TODO do something with the value
}
}
return NOT_BLOCKED;
}