MongoDB-CDC

Overview

The MongoDB CDC connector allows for reading snapshot data and incremental data from MongoDB. This document describes how to setup the MongoDB CDC connector to run SQL queries against MongoDB.

Supported Version

Dependencies

In order to setup the MongoDB CDC connector, the following table provides dependency information for both projects using a build automation tool (such as Maven or SBT) and SQL Client with SQL JAR bundles.

Maven dependency

<dependency>
    <groupId>org.apache.inlong</groupId>
    <artifactId>sort-connector-mongodb-cdc</artifactId>
    <version>1.8.0</version>
</dependency>

Setup MongoDB

Availability

• MongoDB version

  MongoDB version >\= 3.6 We use change streams feature (new in version 3.6) to capture change data.

• Cluster Deployment

  replica sets or sharded clusters is required.

• Storage Engine

  WiredTiger storage engine is required.

• Replica set protocol version

  Replica set protocol version 1 (pv1) is required. Starting in version 4.0, MongoDB only supports pv1. pv1 is the default for all new replica sets created with MongoDB 3.2 or later.

• Privileges

  changeStream and read privileges are required by MongoDB Kafka Connector.

  You can use the following example for simple authorization. For more detailed authorization, please refer to MongoDB Database User Roles.

  use admin;
  db.createUser({
    user: "flinkuser",
    pwd: "flinkpw",
    roles: [
      { role: "read", db: "admin" }, // read role includes changeStream privilege 
      { role: "readAnyDatabase", db: "admin" } // for snapshot reading
    ]
  });

How to create a MongoDB Extract Node

Usage for SQL API

The example below shows how to create an MongoDB Extract Node with Flink SQL :

-- Set checkpoint every 3000 milliseconds                       
Flink SQL> SET 'execution.checkpointing.interval' = '3s';   
-- Create a MySQL table 'mongodb_extract_node' in Flink SQL
Flink SQL> CREATE TABLE mongodb_extract_node (
  _id STRING, // must be declared
  name STRING,
  weight DECIMAL(10,3),
  tags ARRAY<STRING>, -- array
  price ROW<amount DECIMAL(10,2), currency STRING>, -- embedded document
  suppliers ARRAY<ROW<name STRING, address STRING>>, -- embedded documents
  PRIMARY KEY(_id) NOT ENFORCED
) WITH (
  'connector' = 'mongodb-cdc-inlong',
  'hosts' = 'localhost:27017,localhost:27018,localhost:27019',
  'username' = 'flinkuser',
  'password' = 'flinkpw',
  'database' = 'inventory',
  'collection' = 'mongodb_extract_node'
);
-- Read snapshot and binlogs from mongodb_extract_node
Flink SQL> SELECT * FROM mongodb_extract_node;

Note

MongoDB’s change event record doesn’t have update before message. So, we can only convert it to Flink’s UPSERT changelog stream. An upsert stream requires a unique key, so we must declare _id as primary key. We can’t declare other column as primary key, becauce delete operation do not contain’s the key and value besides _id and sharding key.

Usage for InLong Dashboard

TODO: It will be supported in the future.

Usage for InLong Manager Client

TODO: It will be supported in the future.

MongoDB Extract Node Options

Available Metadata

The following format metadata can be exposed as read-only (VIRTUAL) columns in a table definition.

The extended CREATE TABLE example demonstrates the syntax for exposing these metadata fields:

CREATE TABLE `mysql_extract_node` (
    db_name STRING METADATA FROM 'database_name' VIRTUAL,
    collection_name STRING METADATA  FROM 'collection_name' VIRTUAL,
    operation_ts TIMESTAMP_LTZ(3) METADATA FROM 'op_ts' VIRTUAL,
    _id STRING, // must be declared
    name STRING,
    weight DECIMAL(10,3),
    tags ARRAY<STRING>, -- array
    price ROW<amount DECIMAL(10,2), currency STRING>, -- embedded document
    suppliers ARRAY<ROW<name STRING, address STRING>>, -- embedded documents
    PRIMARY KEY(_id) NOT ENFORCED
) WITH (
      'connector' = 'mongodb-cdc-inlong', 
      'hostname' = 'YourHostname',
      'username' = 'YourUsername',
      'password' = 'YourPassword',
      'database' = 'YourDatabase',
      'collection' = 'YourTable' 
);

Data Type Mapping