Migrating data from RabbitMQ to Databricks using CData SSIS Components.
Databricks is a unified data analytics platform that allows organizations to easily process, analyze, and visualize large amounts of data. It combines data engineering, data science, and machine learning capabilities in a single platform, making it easier for teams to collaborate and derive insights from their data.
The CData SSIS Components enhance SQL Server Integration Services by enabling users to easily import and export data from various sources and destinations.
In this article, we explore the data type mapping considerations when exporting to Databricks and walk through how to migrate RabbitMQ data to Databricks using the CData SSIS Components for RabbitMQ and Databricks.
Data Type Mapping
| Databricks Schema | CData Schema |
|---|---|
|
int, integer, int32 |
int |
|
smallint, short, int16 |
smallint |
|
double, float, real |
float |
|
date |
date |
|
datetime, timestamp |
datetime |
|
time, timespan |
time |
|
string, varchar |
If length > 4000: nvarchar(max), Otherwise: nvarchar(length) |
|
long, int64, bigint |
bigint |
|
boolean, bool |
tinyint |
|
decimal, numeric |
decimal |
|
uuid |
nvarchar(length) |
|
binary, varbinary, longvarbinary |
binary(1000) or varbinary(max) after SQL Server 2000 |
Special Considerations
- String/VARCHAR: String columns from Databricks can map to different data types depending on the length of the column. If the column length exceeds 4000, then the column is mapped to nvarchar (max). Otherwise, the column is mapped to nvarchar (length).
- DECIMAL Databricks supports DECIMAL types up to 38 digits of precision, but any source column beyond that can cause load errors.
Prerequisites
- Visual Studio 2022
- SQL Server Integration Services Projects extension for Visual Studio 2022
- CData SSIS Components for Databricks
- CData SSIS Components for RabbitMQ
Create the project and add components
-
Open Visual Studio and create a new Integration Services Project.
- Add a new Data Flow Task to the Control Flow screen and open the Data Flow Task.
-
Add a CData RabbitMQ Source control and a CData Databricks Destination control to the data flow task.
Configure the RabbitMQ source
Follow the steps below to specify properties required to connect to RabbitMQ.
-
Double-click the CData RabbitMQ Source to open the source component editor and add a new connection.
-
In the CData RabbitMQ Connection Manager, configure the connection properties, then test and save the connection.
About RabbitMQ Management HTTP API
RabbitMQ is an open-source message broker that supports multiple messaging protocols. The RabbitMQ Management HTTP API provides HTTP-based access to management and monitoring data for a RabbitMQ server. The API exposes information about virtual hosts, exchanges, queues, bindings, connections, channels, consumers, users, permissions, policies, and cluster-wide statistics.
The Management plugin must be enabled on the RabbitMQ server for the HTTP API to be available. By default, the management interface listens on port 15672.
Using Basic Authentication
RabbitMQ Management HTTP API uses HTTP Basic authentication. You must supply the username and password of a RabbitMQ management user.
To enable access to the management API:
- Ensure the RabbitMQ Management plugin is enabled on your server (rabbitmq-plugins enable rabbitmq_management).
- Use an existing management user or create one with the appropriate management tag (management, policymaker, monitoring, or administrator).
- Note the full base URL of your RabbitMQ Management HTTP API (e.g., http://localhost:15672).
After configuring your RabbitMQ server, set the following connection properties to connect:
- AuthScheme: Set this to Basic.
- URL: Set this to the base URL of your RabbitMQ Management HTTP API (e.g., http://localhost:15672).
- User: Set this to your RabbitMQ management username (e.g., guest).
- Password: Set this to your RabbitMQ management password.
Example connection string:
Profile=C:\profiles\RabbitMQ.apip;AuthScheme=Basic;URL=http://localhost:15672;User=guest;Password=guest;
Available Tables
The RabbitMQ profile provides access to the following tables:
- Overview - Cluster-wide statistics and information about the RabbitMQ node
- Nodes - Information about individual nodes in the RabbitMQ cluster
- NodeMemory - Detailed memory usage breakdown for a specific cluster node
- Connections - List of all open AMQP connections to the broker
- Channels - List of all open AMQP channels across all connections
- Consumers - List of all consumers registered across all queues
- Exchanges - List of exchanges declared across all virtual hosts
- Queues - List of queues declared across all virtual hosts
- Bindings - List of all bindings between exchanges and queues
- VirtualHosts - List of virtual hosts configured on the broker
- VhostPermissions - User permissions within a specific virtual host
- Users - List of all RabbitMQ users
- Permissions - Permission records for all users across all virtual hosts
- TopicPermissions - Topic-level permission records for all users
- Policies - List of policies applied to queues and exchanges in virtual hosts
- OperatorPolicies - List of operator policies applied to queues in virtual hosts
- Parameters - List of component parameters (e.g., federation, shovel) per virtual host
- GlobalParameters - List of global parameters that apply across all virtual hosts
- VhostLimits - Resource limits configured for specific virtual hosts
- UserLimits - Resource limits configured for specific users
- FeatureFlags - List of feature flags and their enabled/disabled state on the node
- DeprecatedFeatures - List of deprecated features and their usage state
- AuthAttempts - Authentication attempt statistics for the node
- ClusterName - The name of the RabbitMQ cluster
- WhoAmI - Information about the currently authenticated management user
- ExchangeBindingsSource - Bindings for which a specific exchange is the source
- ExchangeBindingsDestination - Bindings for which a specific exchange is the destination
- QueueBindings - Bindings for a specific queue within a virtual host
-
After saving the connection, select "Table or view" and select the table or view to export into Databricks, then close the CData RabbitMQ Source Editor.
Configure the Databricks destination
With the RabbitMQ Source configured, we can configure the Databricks connection and map the columns.
-
Double-click the CData Databricks Destination to open the destination component editor and add a new connection.
-
In the CData Databricks Connection Manager, configure the connection properties, then test and save the connection. To connect to a Databricks cluster, set the properties as described below.
Note: The needed values can be found in your Databricks instance by navigating to Clusters, selecting the desired cluster, and selecting the JDBC/ODBC tab under Advanced Options.
- Server: Set to the Server Hostname of your Databricks cluster.
- HTTPPath: Set to the HTTP Path of your Databricks cluster.
- Token: Set to your personal access token (this value can be obtained by navigating to the User Settings page of your Databricks instance and selecting the Access Tokens tab).
Other helpful connection properties
- QueryPassthrough: When this is set to True, queries are passed through directly to Databricks.
- ConvertDateTimetoGMT: When this is set to True, the components will convert date-time values to GMT, instead of the local time of the machine.
- UseUploadApi: Setting this property to true will improve performance if there is a large amount of data in a Bulk INSERT operation.
- UseCloudFetch: This option specifies whether to use CloudFetch to improve query efficiency when the table contains over one million entries.
-
After saving the connection, select a table in the Use a Table menu and in the Action menu, select Insert.
-
On the Column Mappings tab, configure the mappings from the input columns to the destination columns.
Run the project
You can now run the project. After the SSIS Task has finished executing, data from your SQL table will be exported to the chosen table.