Migrating data from Vercel to Databricks using CData SSIS Components.

Cameron Leblanc
Cameron Leblanc
Senior Technology Evangelist
Easily push Vercel data to Databricks using the CData SSIS Tasks for Vercel and Databricks.

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 Vercel data to Databricks using the CData SSIS Components for Vercel 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

Create the project and add components

  1. Open Visual Studio and create a new Integration Services Project.
  2. Add a new Data Flow Task to the Control Flow screen and open the Data Flow Task.
  3. Add a CData Vercel Source control and a CData Databricks Destination control to the data flow task.

Configure the Vercel source

Follow the steps below to specify properties required to connect to Vercel.

  1. Double-click the CData Vercel Source to open the source component editor and add a new connection.
  2. In the CData Vercel Connection Manager, configure the connection properties, then test and save the connection.

    Using API Key Authentication

    Vercel uses Bearer token authentication. You can use either a personal access token or an OAuth access token as the API key.

    To obtain a personal access token:

    1. Log into your Vercel account at https://vercel.com/
    2. Navigate to Account Settings > Tokens.
    3. Click Create Token, enter a name and expiration, and click Create.
    4. Copy the generated token (it will only be shown once).

    After obtaining your token, set the following connection properties:

    • AuthScheme: Set this to APIKey.
    • APIKey: Set this to your Vercel personal access token or OAuth access token.

    Example Connection String

    Profile=C:\profiles\Vercel.apip;AuthScheme=APIKey;APIKey=your_access_token;

    Working with Teams

    Many Vercel resources are scoped to a team. To scope all requests to a specific team, set the TeamId connection property to your team's ID. You can find your team ID by querying the Teams table or from the Vercel dashboard. Alternatively, you can specify TeamId in your SQL queries using the WHERE clause where supported.

    Connecting to Vercel

    Once the authentication is configured, you can connect to Vercel and query data from any of the available tables such as Projects, Deployments, Teams, and Domains.

  3. After saving the connection, select "Table or view" and select the table or view to export into Databricks, then close the CData Vercel Source Editor.

Configure the Databricks destination

With the Vercel Source configured, we can configure the Databricks connection and map the columns.

  1. Double-click the CData Databricks Destination to open the destination component editor and add a new connection.
  2. 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.
  3. After saving the connection, select a table in the Use a Table menu and in the Action menu, select Insert.
  4. 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.

Ready to get started?

Connect to live data from Vercel with the API Driver

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