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Atlas Data Federation supports Atlas clusters as federated database instance stores. You must define mappings in your federated database instance to your Atlas cluster to run queries against your data.

Important

Information in your storage configuration is visible internally at MongoDB and stored as operational data to monitor and improve the performance of Atlas Data Federation. So, we recommend that you do not use PII in your configurations.

To define a federated database instance store for an Atlas cluster, you can specify the following JSON configuration parameters in your Federated Database Instance Configuration File. The configuration contains the Atlas cluster and maps it to virtual collections that you can query.

The following JSON configuration shows the format of the stores and databases configuration fields, which you must set in your Federated Database Instance configuration file to define an Atlas cluster as a federated database instance store:

1{
2 "stores" : [
3 {
4 "name" : "<string>",
5 "provider": "<string>",
6 "clusterName": "<string>",
7 "projectId": "<string>",
8 "readPreference": {
9 "mode": "<string>",
10 "tagSets": [
11 [{"name": "<string>", "value": "<string>"},...],
12 ...
13 ],
14 "maxStalenessSeconds": <int>
15 }
16 }
17 ],
18 "databases" : [
19 {
20 "name" : "<string>",
21 "collections" : [
22 {
23 "name" : "<string>",
24 "dataSources" : [
25 {
26 "storeName" : "<string>",
27 "database" : "<string>",
28 "databaseRegex": "<string>",
29 "collection" : "<string>",
30 "collectionRegex" : "<string>",
31 "provenanceFieldName": "<string>"
32 }
33 ]
34 }
35 ],
36 "views" : [
37 {
38 "name" : "<string>",
39 "source" : "<string>",
40 "pipeline" : "<string>"
41 }
42 ]
43 }
44 ]
45}

The JSON configuration for an Atlas cluster contains two top-level objects: stores and databases

The stores object defines each data store associated with the federated database instance. This store captures documents in the Atlas cluster. Federated Database Instances can only access data stores defined in the stores object.

1"stores" : [
2 {
3 "name" : "<string>",
4 "provider" : "<string>",
5 "clusterName" : "<string>",
6 "projectId": "<string>"
7 "readPreference": {
8 "mode": "<string>",
9 "tagSets": [
10 [{"name": "<string>", "value": "<string>"},...],
11 ...
12 ],
13 "maxStalenessSeconds": <int>
14 },
15 "readConcern": {
16 "level": "<string>"
17 }
18 }
19]

The following table describes the fields in the stores object:

Field
Type
Necessity
Description
stores

array

required

Array of objects where each object represents a data store to associate with the federated database instance. The federated database instance store captures documents in the Atlas cluster. Atlas Data Federation can only access data stores defined in the stores object.

stores.[n].name

string

required

Name of the federated database instance store. The databases.[n].collections.[n].dataSources.[n].storeName field references this value as part of mapping configuration.

stores.[n].provider

string

required

Defines where the data is stored. Value must be atlas for a collection in an Atlas cluster.

stores.[n].clusterName

string

required

Name of the Atlas cluster on which the store is based. The cluster must exist in the same project as your federated database instance. The source field on the data partition is the name of the Atlas cluster.

stores.[n].projectId

string

required

Unique identifier of the project that contains the Atlas cluster on which the store is based.

stores.[n].readPreference

boolean

optional

Cluster read preference, which describes how to route read requests to the cluster.

For example:

The following readPreference setting specifies secondary mode and ANALYTICS nodeType.

{
...
"stores": [
{
"provider": "atlas",
"clusterName": <CLUSTER_NAME>,
"name": <STORE_NAME>,
"projectId": <PROJECT_ID>,
"readPreference": {
"mode": "secondary",
"tagSets": [
[
{
"name": "nodeType",
"value": "ANALYTICS"
}
],
...
]
}
}
]
}
stores.[n].readPreference.mode

string

optional

Read preference mode that specifies which replica set member to route the read requests to. Value can be one of the following:

  • primary - to route all read requests to the replica set primary

  • primaryPreferred - to route all read requests the replica set primary and to secondary members only if primary is unavailable

  • secondary - to route all read requests to the secondary members of the replica set

  • secondaryPreferred - to route all read requests to the secondary members of the replica set and the primary on sharded clusters only if secondary members are unavailable

  • nearest - to route all read requests to random eligible replica set member, irrespective of whether that member is a primary or secondary

If omitted, defaults to local.

stores.[n].readPreference.tagSets

array

optional

Arrays of tag sets or tag specification documents that contain name and value pairs for the replica set member. If specified, Atlas Data Federation routes read requests to replica set member or members that are associated with the specified tags. To learn more, Read Preference Tag Sets.

IMPORTANT: Atlas Data Federation doesn't support tagSets for sharded clusters.

stores.[n].readPreference.maxStalenessSeconds

string

optional

Maximum replication lag, or "staleness", for reads from secondaries. To learn more about maxStalenessSeconds, see Read Preference maxStalenessSeconds.

stores.[n].readConcern

string

optional

Consistency and isolation properties of the data read from an Atlas cluster. To learn more, see Read Concern. The value for the level of consistency and availability can be one of the following:

  • local - to return data from an instance with no guarantee that the data has been written to a majority of the replica set members. To learn more, see Read Concern "local".

  • available - to return data from an instance with no guarantee that the data has been written to a majority of the replica set members. This can return orphaned documents when reading from a sharded collection. To learn more, see Read Concern "available".

  • majority - to return data that has been acknowledged by a majority of the nodes on the Atlas cluster. To learn more, see Read Concern "majority".

  • linearizable - to return data that reflects all successful majority-acknowledged writes that completed prior to the start of the read operation. To learn more, see Read Concern "linearizable".

  • snapshot - to return majority-committed data as it appears across shards from a specific single point in time in the recent past. To learn more, see Read Concern "snapshot".

The databases object defines the mapping between each federated database instance store defined in stores and MongoDB collections in the databases.

1"databases" : [
2 {
3 "name" : "<string>",
4 "collections" : [
5 {
6 "name" : "<string>",
7 "dataSources" : [
8 {
9 "storeName" : "<string>",
10 "database" : "<string>",
11 "databaseRegex": "<string>",
12 "collection" : "<string>",
13 "collectionRegex" : "<string>",
14 "provenanceFieldName": "<string>"
15 }
16 ]
17 }
18 ]
19 }
20]

The following table describes the fields in the databases object:

Field
Type
Necessity
Description
databases

array

required

Array of objects where each object represents a database, its collections, and, optionally, any views on the collections. Each database can have multiple collections and views objects.

databases.[n].name

string

required

Name of the database to which Atlas Data Federation maps the data contained in the data store. You can generate databases dynamically by specifying * for the database name. Dynamically generated databases:

  • Can exist alongside explicitly defined databases. However, Atlas Data Federation won't dynamically generate databases with names that conflict with explicitly defined databases in the storage configuration.

  • Can only be from a single Atlas cluster. Atlas Data Federation won't dynamically generate databases from multiple Atlas clusters or other data stores.

databases.[n].collections

array

required

Array of objects where each object represents a collection and data sources that map to a stores federated database instance store. For dynamically generated databases, you can define only one wildcard (*) collection object in the storage configuration.

databases.[n].collections.[n].name

string

required

Name of the collection to which Atlas Data Federation maps the data contained in each databases.[n].collections.[n].dataSources.[n].storeName. Each object in the array represents the mapping between the collection and an object in the stores array.

You can generate collection names dynamically by specifying * for the collection name and omitting the collection field. To dynamically generate wildcard (*) collections for dynamically generated wilcard (*) databases, specify the databases.[n].collections.[n].dataSources.[n].storeName option and omit the databases.[n].collections.[n].dataSources.[n].database option. Note that for dynamically generated databases, you can define only one wildcard (*) collection object in the storage configuration.

For wildcard (*) collections, you can also define regex patterns using databases.[n].collections.[n].dataSources.[n].collectionRegex field to filter the collections only.

databases.[n].collections.[n].dataSources

array

required

Array of objects where each object represents a stores federated database instance store to map with the collection.

databases.[n].collections.[n].dataSources.[n].storeName

string

required

Name of a federated database instance store to map to the <collection>. Must match the name of an object in the stores array.

databases.[n].collections.[n].dataSources.[n].database

string

required

Name of the database on the Atlas cluster that contains the collection. You must omit this setting to:

  • Create a wildcard (*) collection for a wilcard (*) database.

  • Glob multiple databases.

databases.[n].collections.[n].dataSources.[n].databaseRegex

string

optional

Regex pattern to use for globbing databases to combine multiple collections. If you specify this option, the federated database instance instance contains a single database with collections from multiple databases. For globbing databases, you must do the following:

Suppose you have 2 databases named foo and bar that each have a collection named Sales. You can combine the Sales collection from foo and bar using the databaseRegex option in your storage configuration:

{
"databases": [
{
"name": "Transactions",
"collections": [
{
"name": "AllSales",
"dataSources": [
{
"storeName": "atlasStore",
"databaseRegex": ".*",
"collection": "Sales"
}
]
}
]
}
]
}
For the preceding :datalakeconf-atlas:`databases` object, Atlas Data Federation
generates the following in your federated database instance:
- A virtual database named ``Transactions``.
- A virtual collection named ``AllSales`` that contains data from
the collection named ``Sales`` in all the databases whose name
match the regex pattern specified in the ``databaseRegex``
option.

If you specify this option, you must specify the name of the collection. You can't specify this option for wildcard collections.

databases.[n].collections.[n].dataSources.[n].collection

string

required

Name of the collection in the Atlas cluster on which the federated database instance store is based. You must omit this setting for:

  • Creating a wildcard (*) collection.

  • Creating wildcard collection names that match regex patterns.

  • Combining multiple collections in a database using regex patterns.

databases.[n].collections.[n].dataSources.[n].collectionRegex

string

Optional for wildcard collections Required for combining collections in a database

Regex pattern to use for creating the wildcard (*) collection or for combining mulitple collections in a database.

To use regex patterns for wildcard (*) collection names, you must do the following:

If you specify this field for generating wildcard collections, the federated database instance instance only contains collections with names that match the specified regular expression. The collections in the federated database instance storage configuration use their original names in the Atlas cluster.

To use regex patterns for combining multiple collections in a database, you must do the following:

If you specify this field for combining multiple collections, the collection in the federated database instance contains data from all the Atlas collections with names that match the specified regular expression. The collection in the federated database instance storage configuration uses the name that you specify as value for databases.[n].collections.[n].name.

To learn more about the regex syntax, see Go programming language.

databases.[n].collections.[n].dataSources.[n].provenanceFieldName

string

required

Name for the field that includes the provenance of the documents in the results. If you specify this setting in the storage configuration, Atlas Data Federation returns the following fields for each document in the result:

Field Name
Description

provider

Provider (stores.[n].provider) in the federated database instance storage configuration

clusterName

Name of the Atlas cluster (stores.[n].clusterName)

databaseName

Name of the database (databases.[n].collections.[n].dataSources.[n].database) in the Atlas cluster

collectionName

Name of the collection (databases.[n].collections.[n].name)

You can't configure this setting using the Visual Editor in the Atlas UI.

databases.[n].views

array

required

Array of objects where each object represents an aggregation pipeline on a collection. To learn more about views, see Views.

databases.[n].views.[n].name

string

required

Name of the view.

databases.[n].views.[n].source

string

required

Name of the source collection for the view. If you want to create a view with a $sql stage, you must omit this field as the SQL statement will specify the source collection.

databases.[n].views.[n].pipeline

string

required

Aggregation pipeline stage(s) to apply to the source collection. You can also create views using the $sql stage.

Consider a M10 or higher Atlas cluster named myDataCenter containing data in the metrics.hardware collection. The metrics.hardware collection contains JSON documents with metrics derived from the hardware in a datacenter. The following configuration:

  • Specifies the Atlas cluster named myDataCenter in the specified project as a federated database instance store.

  • Maps documents from the metrics.hardware collection in the Atlas cluster to the dataCenter.inventory collection in the storage configuration.

{
"stores" : [
{
"name" : "atlasClusterStore",
"provider" : "atlas",
"clusterName" : "myDataCenter",
"projectId" : "5e2211c17a3e5a48f5497de3"
}
],
"databases" : [
{
"name" : "dataCenter",
"collections" : [
{
"name" : "inventory",
"dataSources" : [
{
"storeName" : "atlasClusterStore",
"database" : "metrics",
"collection" : "hardware"
}
]
}
]
}
]
}
Atlas Data Federation maps all the documents in the ``metrics.hardware``
collection to the ``dataCenter.inventory`` collection in the storage
configuration.
Users connected to the federated database instance can use the MongoDB Query Language
and supported aggregations to analyze data in the |service| cluster
through the ``dataCenter.inventory`` collection. When you run
queries, the query first goes to Atlas Data Federation. Therefore, if you run
aggregation queries that are supported by your |service| cluster but
not by Atlas Data Federation, the queries will fail. To learn more about supported
and unsupported commands in Data Federation, see :ref:`adf-mql-support`.