Create a MongoDB Sink Connector

The MongoDB Sink managed connector exports Redpanda structured data to a MongoDB database.

Prerequisites

  • Valid credentials with the readWrite role to access the MongoDB database. For more granular access, you need to allow insert, remove and update actions for specific databases or collections.

Limitations

If you want to use the MongoDB sink connector with the MongoDB CDC handler for data sourced from MongoDB (using the MongoDB source connector), you must select STRING or BYTES as the value converter for both the source and sink connectors.

Create a MongoDB Sink connector

To create a MongoDB Sink connector:

  1. In Redpanda Cloud, click Connectors in the navigation menu, and then click Create Connector.

  2. Select Export to MongoDB Sink.

  3. On the Create Connector page, specify the following required connector configuration options:

    Property name Property key Description

    Topics to export

    topics

    A comma-separated list of the cluster topics you want to export to MongoDB.

    Topics regex

    topics.regex

    Java regular expression of topics to replicate. For example: specify .* to replicate all available topics in the cluster. Applicable only when Use regular expressions is selected.

    MongoDB Connection URL

    connection.url

    The MongoDB connection URI string to connect to your MongoDB instance or cluster. For example, mongodb://locahost/.

    MongoDB username

    connection.username

    A valid MongoDB user.

    MongoDB password

    connection.password

    The password for the account associated with the MongoDB user.

    MongoDB database name

    database

    The name of an existing MongoDB database to store output files in.

    Kafka message key format

    key.converter

    Format of the key in the Redpanda topic. Default is STRING.

    Kafka message value format

    value.converter

    Format of the value in the Redpanda topic. Default is STRING.

    Default MongoDB collection name

    collection

    (Optional). Single sink collection name to write to. If following multiple topics, then this will be the default collection to which they are mapped.

    Max Tasks

    tasks.max

    Maximum number of tasks to use for this connector. The default is 1. Each task replicates exclusive set of partitions assigned to it.

    Connector name

    name

    Globally-unique name to use for this connector.

  4. Click Next. Review the connector properties specified, then click Create.

Advanced MongoDB Sink connector configuration

In most instances, the preceding basic configuration properties are sufficient. If you require additional property settings, then specify any of the following optional advanced connector configuration properties by selecting Show advanced options on the Create Connector page:

Property name Property key Description

CDC handler

change.data.capture.handler

The CDC (change data capture) handler to use for processing. The MongoDB handler requires plain JSON or BSON format. The default is NONE.

Key projection type

key.projection.type

The type of key projection to use: either AllowList or BlockList.

Key projection list

key.projection.list

A comma-separated list of field names for key projection.

Value projection type

value.projection.type

Only use with Value projection list. The type of value projection to use: AllowList or BlockList. The default is NONE.

Value projection list

value.projection.list

A comma-separated list of field names for value projection.

Field renamer mapping

field.renamer.mapping

An inline JSON array with objects describing field name mappings. For example: [{"oldName":"key.fieldA","newName":"field1"},{"oldName":"value.xyz","newName":"abc"}].

Field used for time

timeseries.timefield

Name of the top level field used for time. Inserted documents must specify this field, and it must be of the BSON datetime type.

Field describing the series

timeseries.metafield

The name of the top-level field that contains metadata in each time series document. The metadata in the specified field should be data that is used to label a unique series of documents. The metadata should rarely, if ever, change. This field is used to group related data and may be of any BSON type, except for array. The metadata field may not be the same as the timeField or _id.

Convert the field to a BSON datetime type

timeseries.timefield.auto.convert

Converts the timeseries field to a BSON datetime type. If the value is a numeric value it will use the milliseconds from epoch. Any fractional parts are discarded. If the value is a STRING it will use the timeseries.timefield.auto.convert.date.format property to parse the date.

DateTimeFormatter pattern for the date

timeseries.timefield.auto.convert .date.format

The DateTimeFormatter pattern to use when converting string dates. Defaults to support ISO style date times. A string is expected to contain both the date and time. If the string only contains date information, then the time since epoch is taken from the start of that day. If a string representation does not contain a timezone offset, then the extracted date and time is interpreted as UTC.

Data expiry time in seconds

timeseries.expire.after.seconds

The amount of time in seconds that the data will be kept in MongoDB before being automatically deleted.

Data expiry time

timeseries.granularity

The expected interval between subsequent measurements for a time series. Possible values are "seconds", "minutes" or "hours".

Error tolerance

errors.tolerance

Error tolerance response during connector operation. Default value is none and signals that any error will result in an immediate connector task failure. Value of all changes the behavior to skip over problematic records.

Dead letter queue topic name

errors.deadletterqueue.topic.name

The name of the topic to be used as the dead letter queue (DLQ) for messages that result in an error when processed by this sink connector, its transformations, or converters. The topic name is blank by default, which means that no messages are recorded in the DLQ.

Dead letter queue topic replication factor

errors.deadletterqueue.topic .replication.factor

Replication factor used to create the dead letter queue topic when it doesn’t already exist.

Enable error context headers

errors.deadletterqueue.context .headers.enable

When true, adds a header containing error context to the messages written to the dead letter queue. To avoid clashing with headers from the original record, all error context header keys, start with __connect.errors.

Map data

Use the appropriate key or value converter (input data format) for your data as follows:

  • JSON (org.apache.kafka.connect.json.JsonConverter) when your messages are structured JSON. Select Message JSON contains schema, with the schema and payload fields.

  • AVRO (io.confluent.connect.avro.AvroConverter) when your messages contain AVRO-encoded messages, with schema stored in the Schema Registry.

  • STRING (org.apache.kafka.connect.storage.StringConverter) when your messages contain plaintext JSON.

  • BYTES (org.apache.kafka.connect.converters.ByteArrayConverter) when your messages contain BSON.

Test the connection

After the connector is created, verify that your new collections apper in your MongoDB database:

show collections

Troubleshoot

Issues are reported using a failed task error message. Select Show Logs to view error details.

Message Action

Invalid value wrong_uri for configuration connection.uri: The connection string is invalid. Connection strings must start with either 'mongodb://' or 'mongodb+srv://

Check to make sure the Connection URI is a valid MongoDB URL.

Unable to connect to the server.

Check to ensure that the Connection URI is valid and that the MongoDB server accepts connections.

Invalid user permissions authentication failed. Exception authenticating MongoCredential{mechanism=SCRAM-SHA-1, userName='user', source='admin', password=, mechanismProperties=}.

Check to ensure that you specified valid username and password credentials.

DataException: Could not convert key into a BsonDocument.

Make sure your message keys are valid JSONs or skip configuration for fields that require valid JSON keys.

DataException: Error: operationType field doc is missing.

Make sure the input record format is correct (produced by a MongoDB source connector if you use MongoDB CDC handler).

DataException: Value document is missing or CDC operation is not a string

Make sure the input record format is correct (produced by a Debezium source connector if you use Debezium CDC handler).

JsonParseException: Unrecognized token 'text': was expecting (JSON String, Number, Array, Object or token 'null', 'true' or 'false')

Make sure the input record format is JSON.

Unexpected documentKey field type, expecting a document but found BsonString…​: {…​}

Make sure the source data is in the plain JSON or BSON format (value converter STRING or BYTES).

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