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Define Data Stores

Google Cloud Storage Bucket

Atlas Data Federation supports Google Cloud Storage buckets as federated database instance stores. You must define mappings in your federated database instance to your Cloud Storage bucket to run queries against your data.

Note

We refer to objects as files and delimiter-separated prefixes as directories in this page. However, these object storage services aren't actually file systems and don't have the same behaviors in all cases as files on a hard drive.

Configuration File Format

To define a federated database instance store with Google Cloud, you can specify the configuration parameters in JSON format. The configuration contains the Google Cloud data store and maps it to virtual collections that you can query.

The JSON configuration for data in Google Cloud uses the following fields:

1{
2  "stores" : [
3    {
4      "name" : "<string>",
5      "provider" : "<string>",
6      "region" : "<string>",
7      "bucket" : "<string>",
8      "prefix": "<string>",
9      "delimiter": "<string>"
10    }
11  ],
12  "databases" : [
13    {
14      "name" : "<string>",
15      "collections" : [
16	{
17	  "name" : "<string>",
18	  "dataSources" : [
19	    {
20	      "storeName" : "<string>",
21	      "path" : "<string>",
22	      "defaultFormat" : "<string>",
23	      "provenanceFieldName": "<string>",
24	      "omitAttributes": <boolean>
25	    }
26	  ]
27	}
28      ],
29      "maxWildcardCollections" : <integer>,
30      "views" : [ 
31	{
32	  "name" : "<string>", 
33	  "source" : "<string>", 
34	  "pipeline" : "<string>" 
35	}
36      ] 
37    }
38  ]
39}
40

The JSON configuration for Google Cloud contains two top-level objects: stores and databases

stores

The stores object defines each data store associated with the federated database instance. The federated database instance store captures files in Google Cloud. Data Federation can only access data stores defined in the stores object.

The stores object contains the following fields:

1"stores" : [
2  {
3    "name" : "<string>",
4    "provider" : "<string>",
5    "region" : "<string>",
6    "bucket" : "<string>",
7    "prefix": "<string>",
8    "delimiter": "<string>"
9  }
10]

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:

  • Files in a Google Cloud Storage bucket

  • Documents in an Atlas cluster

  • Files stored at publicly accessible URLs

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

Name of the cloud provider where the data is stored. The value must be gcs for a Google Cloud Storage bucket.

stores.[n].region

string

Required

Name of the Google Cloud region in which the Google Cloud Storage bucket is hosted. For a list of valid region names, see Google Cloud Platform (GCP).

stores.[n].bucket

string

Required

Name of the Google Cloud Storage bucket. Must exactly match the name of a Google Cloud Storage bucket that Atlas Data Federation must access.

stores.[n].prefix

string

Optional

Prefix Atlas Data Federation applies when searching for files in the Google Cloud Storage bucket. For example, consider a Google Cloud Storage bucket metrics with the following structure:

metrics
|--hardware
|--software
  |--computed

The federated database instance store prepends the value of prefix to databases.[n].collections.[n].dataSources.[n].path to create the full path for files to ingest. Setting prefix to /software restricts any databases objects using the federated database instance to only subpaths of /software.

Defaults to the root of the Google Cloud Storage bucket, retrieving all files.

stores.[n].delimiter

string

Optional

Delimiter that separates databases.[n].collections.[n].dataSources.[n].path segments in the federated database instance store. Atlas Data Federation uses the delimiter to efficiently traverse Google Cloud Storage buckets with a simulated hierarchical directory structure.

databases

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

The databases object contains the following fields:

1"databases" : [
2  {
3    "name" : "<string>",
4    "collections" : [
5      {
6	"name" : "<string>",
7	"dataSources" : [
8	  {
9	    "storeName" : "<string>",
10	    "path" : "<string>",
11	    "defaultFormat" : "<string>",
12	    "provenanceFieldName": "<string>",
13	    "omitAttributes": <boolean>
14	  }
15	]
16      }
17    ],
18    "maxWildcardCollections" : <integer>,
19    "views" : [ 
20      {
21	"name" : "<string>", 
22	"source" : "<string>", 
23	"pipeline" : "<string>" 
24      }
25    ] 
26  }
27]

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.

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.

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 from file paths by specifying * for the collection name and the collectionName() function in the path field. See Generate Dynamic Collection Names from File Path for examples.

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].path

string

Required

Controls how Atlas Data Federation searches for and parses files in the databases.[n].collections.[n].dataSources.[n].storeName before mapping them to the <collection>. federated database instance prepends the stores.[n].prefix to the path to build the full path to search within. Specify / to capture all files and folders from the prefix path.

For example, consider a Google Cloud Storage bucket named metrics with the following structure:

metrics
|--hardware
|--software
  |--computed

A path of / directs Atlas Data Federation to search all files and folders in the metrics bucket.

A path of /hardware directs Atlas Data Federation to search only that path for files to ingest.

If the stores.[n].prefix is software, Atlas Data Federation searches for files only in the path /software/computed.

Appending the * wildcard character to the path directs Atlas Data Federation to include all files and folders from that point in the path. For example, /software/computed* would match files like /software/computed-detailed, /software/computedArchive, and /software/computed/errors.

databases.[n].collections.[n].dataSources.[n].path supports additional syntax for parsing filenames, including:

  • Generating document fields from filenames.

  • Using regular expressions to control field generation.

  • Setting boundaries for bucketing filenames by timestamp.

See Define Path for S3 Data for more information.

When specifying the path:

  • Specify the data type for the partition attribute.

  • Ensure that the partition attribute type matches the data type to parse.

  • Use the delimiter specified in delimiter.

When specifying attributes of the same type, do any of the following:

  • Add a constant separator between the attributes.

  • Use regular expressions to describe the search pattern. To learn more, see Unsupported Parsing Functions.

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

string

Optional

Default format that Data Federation assumes if it encounters a file without an extension while searching the databases.[n].collections.[n].dataSources.[n].storeName.

The following values are valid for the defaultFormat field:

.json, .json.gz, .bson, .bson.gz, .avro, .avro.gz, .orc, .tsv, .tsv.gz, .csv, .csv.gz, .parquet

If your file format is CSV or TSV, you must include a header row in your data. See CSV and TSV for more information.

If omitted, Data Federation attempts to detect the file type by processing a few bytes of the file.

See also: Supported Data Formats

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

string

Optional

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

region

Google Cloud region (stores.[n].region)

bucket

Name of the Google Cloud Storage bucket (stores.[n].bucket)

key

Path (databases.[n].collections.[n].dataSources.[n].path) to the document

lastModified

Date and time the document was last modified.

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

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

boolean

Optional

Flag that specifies whether to omit the attributes (key and value pairs) that Atlas Data Federation adds to documents in the collection. You can specify one of the following values:

  • false - to add the attributes

  • true - to omit the attributes

If omitted, defaults to false and Atlas Data Federation adds the attributes.

For example, consider a file named /employees/949-555-0195.json for which you configure the databases.[n].collections.[n].dataSources.[n].path /employees/{phone string}. Atlas Data Federation adds the attribute phone: 949-555-0195 to documents in this file if omitAttributes is false, regardless of whether the key-value pair already exists in the document. If you set omitAttributes to true, Atlas Data Federation doesn't add the attribute to the document in the virtual collection.

Example Configuration for Google Cloud Storage Bucket

Consider a Google Cloud Storage bucket datacenter-alpha containing data collected from a datacenter:

|--metrics
  |--hardware

The /metrics/hardware path stores JSON files with metrics derived from the datacenter hardware, where each filename is the UNIX timestamp in milliseconds of the 24 hour period covered by that file:

/hardware/1564671291998.json

The following configuration:

  • Defines a federated database instance store on the datacenter-alpha Google Cloud Storage bucket in the us-central1 Google Cloud region. The federated database instance store is specifically restricted to include only data files in the metrics directory path. A delimiter of / is defined to simulate a file system hierarchy for ease of navigation and retrieval.

  • Maps files from the hardware directory to a MongoDB database datacenter-alpha-metrics and collection hardware. The configuration mapping includes parsing logic for capturing the timestamp implied in the filename.

{
  "stores" : [
    {
      "name" : "datacenter-alpha",
      "provider" : "gcs",
      "region" : "us-central1",
      "bucket" : "datacenter-alpha",
      "prefix": "metrics",
      "delimiter": "/"
    }
  ],
  "databases" : [
    {
      "name" : "datacenter-alpha-metrics",
      "collections" : [
        {
          "name" : "hardware",
          "dataSources" : [
            {
              "storeName" : "datacenter-alpha",
              "path" : "/hardware/{date date}"
            }
          ]
        }
      ]
    }
  ]
}

Atlas Data Federation parses the Google Cloud Storage bucket datacenter-alpha and processes all files under /metrics/hardware/. The collections object uses the path parsing syntax to map the filename to the date field, which is an ISO-8601 date, in each document. If a matching date field does not exist in a document, Atlas Data Federation adds it.

Users connected to the federated database instance can use the MongoDB Query Language and supported aggregations to analyze data in the Google Cloud Storage bucket through the datacenter-alpha-metrics.hardware collection.

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