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README.md |
Data Connectors
This document describes the current specification of the new _data connectors_s feature of graphql-engine
, which is under active development.
The data connectors feature allows graphql-engine
to delegate the execution of operations to external web services called agents. Such agents provide access to a data set, allowing graphql-engine
to query that data set over a web API.
This document specifies (1) the web API that must be presented by agents, and (2) the precise behaviour of agents for specific reference data sets.
For further reference, the directory in which this document resides contains some implementations of different agents:
- Reference Implementation - A reference implementation in TypeScript that serves some static in-memory data
Stability
This specification is complete with regards to the current implementation, but should be considered unstable until the Data Connectors feature is officially released and explicitly marked as a non-experimental feature.
Setting up Data Connector agents with graphql-engine
In order to run one of the example agents, follow the steps in its respective README document.
Once an agent is running, import the following metadata into graphql-engine
:
POST /v1/metadata
{
"type": "replace_metadata",
"args": {
"metadata": {
"version": 3,
"backend_configs": {
"dataconnector": {
"reference": {
"uri": "http://localhost:8100/"
}
}
},
"sources": [
{
"name": "chinook",
"kind": "reference",
"tables": [
{
"table": "Album",
"object_relationships": [
{
"name": "Artist",
"using": {
"manual_configuration": {
"remote_table": "Artist",
"column_mapping": {
"ArtistId": "ArtistId"
}
}
}
}
]
},
{
"table": "Artist",
"array_relationships": [
{
"name": "Album",
"using": {
"manual_configuration": {
"remote_table": "Album",
"column_mapping": {
"ArtistId": "ArtistId"
}
}
}
}
]
}
],
"configuration": {
"tables": [ "Artist", "Album" ]
}
}
]
}
}
}
The backend_configs.dataconnector
section lets you set the URIs for as many agents as you'd like. In this case, we've defined one called "reference". When you create a source, the kind
of the source should be set to the name you gave the agent in the backend_configs.dataconnector
section (in this case, "reference").
The configuration
property under the source can contain an 'arbitrary' JSON object, and this JSON will be sent to the agent on every request via the X-Hasura-DataConnector-Config
header. The example here is configuration that the reference agent uses. The JSON object must conform to the schema specified by the agent from its /capabilities
endpoint.
The name
property under the source will be sent to the agent on every request via the X-Hasura-DataConnector-SourceName
header. This name uniquely identifies a source within an instance of HGE.
The albums
and artists
tables should now be available in the GraphiQL console. You should be able to issue queries via the web service. For example:
query {
artists {
name
albums {
title
}
}
}
Implementing Data Connector agents
This section is a guide to implementing Data Connector agents for graphql-engine
. You may find it useful to consult the code examples for reference.
The entry point to the reference agent application is a Fastify HTTP server. Raw data is loaded from JSON files on disk, and the server provides the following endpoints:
GET /capabilities
, which returns the capabilities of the agent and a schema that describes the type of the configuration expected to be sent on theX-Hasura-DataConnector-Config
headerGET /schema
, which returns information about the provided data schema, its tables and their columnsPOST /query
, which receives a query structure to be executed, encoded as the JSON request body, and returns JSON conforming to the schema described by the/schema
endpoint, and contining the requested fields.GET /health
, which can be used to either check if the agent is running, or if a particular data source is healthy
The /schema
and /query
endpoints require the request to have the X-Hasura-DataConnector-Config
header set. That header contains configuration information that agent can use to configure itself. For example, the header could contain a connection string to the database, if the agent requires a connection string to know how to connect to a specific database. The header must be a JSON object, but the specific properties that are required are up to the agent to define.
The /schema
and /query
endpoints also require the request to have the X-Hasura-DataConnector-SourceName
header set. This header contains the name of the data source configured in HGE that will be querying the agent. This can be used by the agent to maintain things like connection pools and configuration maps on a per-source basis.
We'll look at the implementation of each of the endpoints in turn.
Capabilities and configuration schema
The GET /capabilities
endpoint is used by graphql-engine
to discover the capabilities supported by the agent, and so that it can know the correct shape of configuration data that needs to be collected from the user and sent to the agent in the X-Hasura-DataConnector-Config
header. It should return a JSON object similar to the following:
{
"capabilities": {
"relationships": {}
},
"configSchemas": {
"configSchema": {
"type": "object",
"nullable": false,
"properties": {
"tables": { "$ref": "#/otherSchemas/Tables" }
}
},
"otherSchemas": {
"Tables": {
"description": "List of tables to make available in the schema and for querying",
"type": "array",
"items": { "$ref": "#/otherSchemas/TableName" },
"nullable": true
},
"TableName": {
"nullable": false,
"type": "string"
}
}
}
}
The capabilities
section describes the capabilities of the service. Specifically, the service is capable of serving queries which involve relationships.
The configSchema
property contains an OpenAPI 3 Schema object that represents the schema of the configuration object. It can use references ($ref
) to refer to other schemas defined in the otherSchemas
object by name.
graphql-engine
will use the configSchema
OpenAPI 3 Schema to validate the user's configuration JSON before putting it into the X-Hasura-DataConnector-Config
header.
Schema and capabilities
The GET /schema
endpoint is called whenever the metadata is (re)loaded by graphql-engine
. It returns the following JSON object:
{
"tables": [
{
"name": "Artist",
"primary_key": ["ArtistId"],
"description": "Collection of artists of music",
"columns": [
{
"name": "ArtistId",
"type": "number",
"nullable": false,
"description": "Artist primary key identifier"
},
{
"name": "Name",
"type": "string",
"nullable": true,
"description": "The name of the artist"
}
]
},
{
"name": "Album",
"primary_key": ["AlbumId"],
"description": "Collection of music albums created by artists",
"columns": [
{
"name": "AlbumId",
"type": "number",
"nullable": false,
"description": "Album primary key identifier"
},
{
"name": "Title",
"type": "string",
"nullable": false,
"description": "The title of the album"
},
{
"name": "ArtistId",
"type": "number",
"nullable": false,
"description": "The ID of the artist that created this album"
}
]
}
]
}
The tables
section describes the two available tables, as well as their columns, including types and nullability information.
Notice that the names of tables and columns are used in the metadata document to describe tracked tables and relationships.
Type definitions
The SchemaResponse
TypeScript type from the reference implementation describes the valid response body for the GET /schema
endpoint.
Responding to queries
The POST /query
endpoint is invoked when the user requests data from graphql-engine
which is resolved by the service.
The service logs queries from the request body in the console. Here is a simple example based on a GraphQL query which fetches all artist data:
query {
Artist {
ArtistId
Name
}
}
and here is the resulting query request payload:
{
"table": "Artist",
"table_relationships": [],
"query": {
"where": {
"expressions": [],
"type": "and"
},
"order_by": [],
"limit": null,
"offset": null,
"fields": {
"ArtistId": {
"type": "column",
"column": "ArtistId"
},
"Name": {
"type": "column",
"column": "Name"
}
}
}
}
The implementation of the service is responsible for intepreting this data structure and producing a JSON response body which is compatible with both the query and the schema.
Let's break down the request:
- The
table
field tells us which table to fetch the data from, namely theArtist
table. - The
table_relationships
field that lists any relationships used to join between tables in the query. This query does not use any relationships, so this is just an empty list here. - The
query
field contains further information about how to query the specified table:- The
where
field tells us that there is currently no (interesting) predicate being applied to the rows of the data set (just an empty conjunction, which ought to return every row). - The
order_by
field tells us that there is no particular ordering to use, and that we can return data in its natural order. - The
limit
andoffset
fields tell us that there is no pagination required. - The
fields
field tells us that we ought to return two fields per row (ArtistId
andName
), and that these fields should be fetched from the columns with the same names.
- The
Response Body Structure
The response body for a call to POST /query
should always consist of a JSON array of JSON objects. Each of those JSON objects should contain all of the same keys as the fields
property of the request body, even if the values of the corresponding fields may be null
.
In the case of fields appearing with type relationship
, this property should apply recursively: such fields should appear in the response body as a nested array/object of record(s) (depending on whether the relationship is an object or array relationship), each with the appropriate fields described by the relationship field's query
property.
Pagination
If the GraphQL query contains pagination information, then the limit
and offset
fields may be set to integer values, indicating the number of rows to return, and the index of the first row to return, respectively.
Filters
The where
field contains a recursive expression data structure which should be interpreted as a predicate in the context of each record.
Each node of this recursive expression structure is tagged with a type
property, which indicates the type of that node, and the node will contain one or more additional fields depending on that type. The valid expression types are enumerated below, along with these additional fields:
type | Additional fields | Description |
---|---|---|
and |
expressions |
A conjunction of several subexpressions |
or |
expressions |
A disjunction of several subexpressions |
not |
expression |
The negation of a single subexpression |
binary_op |
operator , column , value |
Test the specified column against a single value using a particular binary comparison operator |
binary_arr_op |
operator , column , values |
Test the specified column against an array of values using a particular binary comparison operator |
unary_op |
operator , column |
Test the specified column against a particular unary comparison operator |
The available binary comparison operators that can be used against a single value in binary_op
are:
Binary comparison operator | Description |
---|---|
less_than |
The < operator |
less_than_or_equal |
The <= operator |
greater_than |
The > operator |
greater_than_or_equal |
The >= operator |
equal |
The = operator |
The available binary comparison operators that can be used against an array of values in binary_arr_op
are:
Binary array comparison operator | Description |
---|---|
in |
The SQL IN operator (ie. the column must be any of the array of specified values) |
The available unary comparison operators that can be used against a column:
Unary comparison operator | Description |
---|---|
is_null |
Tests if a column is null |
Values (as used in value
in binary_op
and the values
array in binary_arr_op
) are specified as either a literal value, or a reference to another column, which could potentially be in another related table in the same query. The value object is tagged with a type
property and has different fields based on the type.
type | Additional fields | Description |
---|---|---|
scalar |
value |
A scalar value to compare against |
column |
column |
A column in the current table being queried to compare against |
Columns (as used in column
fields in binary_op
, binary_arr_op
, unary_op
and in column
-typed Values) are specified as a column name
, as well as a path
to the table that contains the column. This path is an array of relationship names that starts from the table being queried (ie the table being queried by the query that this where expression is being specified in). An empty array means the column would be on the table being queried itself.
Here is a simple example, which correponds to the predicate "first_name
is John and last_name
is Smith":
{
"type": "and",
"expressions": [
{
"type": "binary_op",
"operator": "equal",
"column": {
"path": [],
"name": "first_name"
},
"value": {
"type": "scalar",
"value": "John"
}
},
{
"type": "binary_op",
"operator": "equal",
"column": {
"path": [],
"name": "last_name"
},
"value": {
"type": "scalar",
"value": "John"
}
}
]
}
Here's another example, which corresponds to the predicate "first_name
is the same as last_name
":
{
"type": "and",
"expressions": [
{
"type": "binary_op",
"operator": "equal",
"column": {
"path": [],
"name": "first_name"
},
"value": {
"type": "column",
"column": {
"path": [],
"name": "last_name"
}
}
}
]
}
Ordering
The order_by
field specifies an array of zero-or-more orderings, each of which consists of a field to order records by, and an order which is either asc
(ascending) or desc
(descending).
If there are multiple orderings specified then records should be ordered lexicographically, with earlier orderings taking precedence.
For example, to order records principally by last_name
, delegating to first_name
in the case where two last names are equal, we would use the following order_by
structure:
[
{
"field": "last_name",
"order_type": "asc"
},
{
"field": "first_name",
"order_type": "asc"
}
]
Relationships
If the call to GET /capabilities
returns a capabilities
record with a relationships
field then the query structure may include fields corresponding to relationships.
Note : if the relationships
capability is not present then graphql-engine
will not send queries to this agent involving relationships.
Relationship fields are indicated by a type
field containing the string relationship
. Such fields will also include the name of the relationship in a field called relationship
. This name refers to a relationship that is specified on the top-level query request object in the table_relationships
field.
This table_relationships
is a list of tables, and for each table, a map of relationship name to relationship information. The information is an object that has a field target_table
that specifies the name of the related table. It has a field called relationship_type
that specified either an object
(many to one) or an array
(one to many) relationship. There is also a column_mapping
field that indicates the mapping from columns in the source table to columns in the related table.
It is intended that the backend should execute the query
contained in the relationship field and return the resulting record set as the value of this field, with the additional record-level predicate that any mapped columns should be equal in the context of the current record of the current table.
An example will illustrate this. Consider the following GraphQL query:
query {
Artist {
Name
Albums {
Title
}
}
}
This will generate the following JSON query if the agent supports relationships:
{
"table": "Artist",
"table_relationships": [
{
"source_table": "Artist",
"relationships": {
"ArtistAlbums": {
"target_table": "Album",
"relationship_type": "array",
"column_mapping": {
"ArtistId": "ArtistId"
}
}
}
}
],
"query": {
"where": {
"expressions": [],
"type": "and"
},
"offset": null,
"order_by": [],
"limit": null,
"fields": {
"Albums": {
"type": "relationship",
"relationship": "ArtistAlbums",
"query": {
"where": {
"expressions": [],
"type": "and"
},
"offset": null,
"from": "albums",
"order_by": [],
"limit": null,
"fields": {
"Title": {
"type": "column",
"column": "Title"
}
}
}
},
"Name": {
"type": "column",
"column": "Name"
}
}
}
}
Note the Albums
field in particular, which traverses the Artists
-> Albums
relationship, via the ArtistAlbums
relationship:
{
"type": "relationship",
"relationship": "ArtistAlbums",
"query": {
"where": {
"expressions": [],
"type": "and"
},
"offset": null,
"from": "albums",
"order_by": [],
"limit": null,
"fields": {
"Title": {
"type": "column",
"column": "Title"
}
}
}
}
The top-level table_relationships
can be looked up by starting from the source table (in this case Artist
), locating the ArtistAlbums
relationship under that table, then extracting the relationship information. This information includes the target_table
field which indicates the table to be queried when following this relationship is the Album
table. The relationship_type
field indicates that this relationship is an array
relationship (ie. that it will return zero to many Album rows per Artist row). The column_mapping
field indicates the column mapping for this relationship, namely that the Artist's ArtistId
must equal the Album's ArtistId
.
Back on the relationship field inside the query, there is another query
field. This indicates the query that should be executed against the Album
table, but we must remember to enforce the additional constraint between Artist's ArtistId
and Album's ArtistId
. That is, in the context of any single outer Artist
record, we should populate the Albums
field with the array of Album records for which the ArtistId
field is equal to the outer record's ArtistId
field.
Cross-Table Filtering
It is possible to form queries that filter their results by comparing columns across tables via relationships. One way this can happen in Hasura GraphQL Engine is when configuring permissions on a table. It is possible to configure a filter on a table such that it joins to another table in order to compare some data in the filter expression.
The following metadata when used with HGE configures a Customer
and Employee
table, and sets up a select permission rule on Customer
such that only customers that live in the same country as their SupportRep Employee would be visible to users in the user
role:
POST /v1/metadata
{
"type": "replace_metadata",
"args": {
"metadata": {
"version": 3,
"backend_configs": {
"dataconnector": {
"reference": {
"uri": "http://localhost:8100/"
}
}
},
"sources": [
{
"name": "chinook",
"kind": "reference",
"tables": [
{
"table": "Customer",
"object_relationships": [
{
"name": "SupportRep",
"using": {
"manual_configuration": {
"remote_table": "Employee",
"column_mapping": {
"SupportRepId": "EmployeeId"
}
}
}
}
],
"select_permissions": [
{
"role": "user",
"permission": {
"columns": [
"CustomerId",
"FirstName",
"LastName",
"Country",
"SupportRepId"
],
"filter": {
"SupportRep": {
"Country": {
"_ceq": ["$","Country"]
}
}
}
}
}
]
},
{
"table": "Employee"
}
],
"configuration": {}
}
]
}
}
}
Given this GraphQL query (where the X-Hasura-Role
header is set to user
):
query getCustomer {
Customer {
CustomerId
FirstName
LastName
Country
SupportRepId
}
}
We would get the following query request JSON:
{
"table": "Customer",
"table_relationships": [
{
"source_table": "Customer",
"relationships": {
"SupportRep": {
"target_table": "Employee",
"relationship_type": "object",
"column_mapping": {
"SupportRepId": "EmployeeId"
}
}
}
}
],
"query": {
"fields": {
"Country": {
"type": "column",
"column": "Country"
},
"CustomerId": {
"type": "column",
"column": "CustomerId"
},
"FirstName": {
"type": "column",
"column": "FirstName"
},
"LastName": {
"type": "column",
"column": "LastName"
},
"SupportRepId": {
"type": "column",
"column": "SupportRepId"
}
},
"where": {
"type": "and",
"expressions": [
{
"type": "binary_op",
"operator": "equal",
"column": {
"path": ["SupportRep"],
"name": "Country"
},
"value": {
"type": "column",
"column": {
"path": [],
"name": "Country"
}
}
}
]
}
}
}
The key point of interest here is in the where
field where we are comparing between columns. The first column's path
is ["SupportRep"]
indicating that the Country
column specified there is on the other side of the Customer
table's SupportRep
relationship (ie. to the Employee
table). The related Employee
's Country
column is being compared with equal
to Customer
's Country
column (as indicated by the []
path). So, in order to evaluate this condition, we'd need to join the Employee
table using the column_mapping
specified in the SupportRep
relationship and if any of the related rows (in this case, only one because it is an object
relation) contain a Country
that is equal to Employee row's Country
, then the binary_op
evaluates to True and we don't filter out the row.
Type Definitions
The QueryRequest
TypeScript type in the reference implementation describes the valid request body payloads which may be passed to the POST /query
endpoint. The response body structure is captured by the QueryResponse
type.
Health endpoint
Agents must expose a /health
endpoint which must return a 204 No Content HTTP response code if the agent is up and running. This does not mean that the agent is able to connect to any data source it performs queries against, only that the agent is running and can accept requests, even if some of those requests might fail because a dependant service is unavailable.
However, this endpoint can also be used to check whether the ability of the agent to talk to a particular data source is healthy. If the endpoint is sent the X-Hasura-DataConnector-Config
and X-Hasura-DataConnector-SourceName
headers, then the agent is expected to check that it can successfully talk to whatever data source is being specified by those headers. If it can do so, then it must return a 204 No Content response code.