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title: Mapping a GraphQL API to Your Data Sources
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# Mapping a GraphQL API to Your Data Sources

> For the full documentation index, see: https://docs.mulesoft.com/llms.txt

Connect APIkit for GraphQL to your runtime by choosing connector listeners, data fetchers, and data
loaders that match how you resolve schema fields. Pick an inbound protocol listener, then attach
fetchers for single fields and loaders when you batch per object type to avoid N+1 calls. Sections
below describe how each source fits into the GraphQL execution path in Mule.

## Select Sources

The module sources vary depending on the implementation of your GraphQL API. APIkit for GraphQL
provides two kinds of sources:

- Data Fetchers

- Data Loaders

Your selection depends on your implementation needs.

GraphQL is transport-layer agnostic, so you choose the main connector listener depending on the
protocol that you want to serve your data.

### Add a Listener

The inbound endpoint that triggers the main application flow is the connector listener specific to
the client-server protocol of your choice. GraphQL often communicates over HTTP, so APIkit
scaffolder generates an HTTP listener by default, but you can choose another source for serving your
data over a different protocol.

### Add a Data Fetcher

Data fetchers are sources of Mule flows. They fulfill the data of a single-object field in a query
result. The combination of the following key parts identify them:

- **Object type name**: One of the object types in your schema

- **Field name**: One of the fields that are part of the object type

You can add data fetchers for every object field defined on the schema, regardless of the field
type. If the Mule application does not have a data fetcher configured for a field, the parent type
populates the field value. Otherwise, the client-requested data is not fulfilled, resulting in
`null`.

### Add a Data Loader

As data fetchers, data loaders are also sources of Mule flows. They batch requests related to an
object type. Unlike data fetchers, a unique key identifies them:

- **Object type name**: One of the object types in your schema

Data loaders solve the optimization issue of the N+1 requests when implementing GraphQL APIs. This
issue occurs when N additional query statements are executed to fetch data that could have been
retrieved when performing the first query.

At run time, the module looks for a data fetcher first. If the data fetcher is not available, the
module looks for a data loader. Specifically, in case a data fetcher and a data loader exist for the
same object type, the module uses the data fetcher as the first choice for resolving a field. This
process can impact your API performance because the data fetcher keeps getting invoked N+1 times.

## Choose Operations

The module provides a set of operations that are fundamental for the correct design and execution of
a GraphQL API implementation:

- Route

- Serialize

- Serialize Batch

### Route a Query

The **Route** operation is the entry point of a GraphQL service. It parses, validates, and executes
the query by traversing the graph and calling the data fetcher and data loaders required to fulfill
the query result.

### Serialize a Data Fetcher

The **Serialize** operation occurs at the end of a flow that has a data fetcher source. The same
pair of keys that identify the data fetcher (object type name and field name) identifies it.

### Serialize Batch a Data Loader

The **Serialize Batch** operation occurs at the end of a flow that has a data loader source. The
same key that identifies the data loader (object type name) identifies it.

**Serialize** and **Serialize Batch** operations leverage the use of data sense at design time.