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Try them now for free →Migrating data from NetSuite to Databricks using CData SSIS Components.
Easily push NetSuite data to Databricks using the CData SSIS Tasks for NetSuite 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 NetSuite data to Databricks using the CData SSIS Components for NetSuite 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.
About NetSuite Data Integration
CData provides the easiest way to access and integrate live data from Oracle NetSuite. Customers use CData connectivity to:
- Access all editions of NetSuite, including Standard, CRM, and OneWorld.
- Connect with all versions of the SuiteTalk API (SOAP-based) and SuiteQL, which functions like SQL, enabling easier data querying and manipulation.
- Access predefined and custom reports through support for Saved Searches.
- Securely authenticate with Token-based and OAuth 2.0, ensuring compatibility and security for all use cases.
- Use SQL stored procedures to perform functional actions like uploading or downloading files, attaching or detaching records or relationships, retrieving roles, getting extra table or column info, getting job results, and more.
Customers use CData solutions to access live NetSuite data from their preferred analytics tools, Power BI and Excel. They also use CData's solutions to integrate their NetSuite data into comprehensive databases and data warehouse using CData Sync directly or leveraging CData's compatibility with other applications like Azure Data Factory. CData also helps Oracle NetSuite customers easily write apps that can pull data from and push data to NetSuite, allowing organizations to integrate data from other sources with NetSuite.
For more information about our Oracle NetSuite solutions, read our blog: Drivers in Focus Part 2: Replicating and Consolidating ... NetSuite Accounting Data.
Getting Started
Prerequisites
- Visual Studio 2022
- SQL Server Integration Services Projects extension for Visual Studio 2022
- CData SSIS Components for Databricks
- CData SSIS Components for NetSuite
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 NetSuite Source control and a CData Databricks Destination control to the data flow task.
Configure the NetSuite source
Follow the steps below to specify properties required to connect to NetSuite.
-
Double-click the CData NetSuite Source to open the source component editor and add a new connection.
-
In the CData NetSuite Connection Manager, configure the connection properties, then test and save the connection.
The User and Password properties, under the Authentication section, must be set to valid NetSuite user credentials. In addition, the AccountId must be set to the ID of a company account that can be used by the specified User. The RoleId can be optionally specified to log in the user with limited permissions.
See the "Getting Started" chapter of the help documentation for more information on connecting to NetSuite.
-
After saving the connection, select "Table or view" and select the table or view to export into Databricks, then close the CData NetSuite Source Editor.
Configure the Databricks destination
With the NetSuite 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.