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  • Data Integration Connectors
  • All Products

Table of Contents

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  1. Preface
  2. Introduction to Databricks Delta Connector
  3. Connections for Databricks Delta
  4. Mappings for Databricks Delta
  5. Migrating a mapping
  6. Databricks Delta SQL ELT optimization
  7. Data type reference

Databricks Delta Connector

Databricks Delta Connector

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Mappings in advanced mode example

Mappings in advanced mode example

You work for a retail company that offers more than 50,000 products and the stores are distributed across the globe. The company ingests a large amount of customer engagement details from the transactional CRM system into Amazon S3.
The sales team wants to improve customer engagement and satisfaction at every touch point. To create a seamless customer experience and deliver personalized service across the various outlets, the retail company plans to load the data that is stored in the Amazon S3 bucket to Databricks Delta.
You can create a mapping that runs on an
advanced cluster
 to achieve faster performance when you read data from the Amazon S3 bucket and write data to the Databricks Delta target.
You can choose to add transformations to process the raw data that you read from the Amazon S3 bucket and then write the curated data to Databricks Delta.
The following example illustrates how to create a mapping in advanced mode to read from an Amazon S3 source and write to Databricks Delta target:
  1. In
    Data Integration
    , click
    New
    Mappings
    Mapping
    .
  2. In the Mapping Designer, click
    Switch to Advanced
    .
    The Mapping Designer updates the mapping canvas to display the transformations and functions that are available in advanced mode.
  3. Enter a name, location, and description for the mapping.
  4. Add a Source transformation, and specify a name and description in the general properties.
  5. On the
    Source
     tab, perform the following steps to read data from the Amazon S3 source:
    1. In the
      Connection
       field, select the Amazon S3 V2 connection.
    2. In the
      Source Type
       field, select single object as the source type.
    3. In the
      Object
       field, select the parquet file object that contains the customer details.
    4. In the
      Advanced Properties
       section, specify the required parameters.
  6. On the
    Expression
     tab, define an expression to change the file name port of the customer parquet file to uppercase based on your business requirement before you write data to the Databricks Delta target.
  7. Add a Target transformation, and specify a name and description in the general properties.
  8. On the
    Target
     tab, specify the details to write data to Databricks Delta:
    1. In the
      Connection
       field, select the Databricks Delta target connection.
    2. In the
      Target Type
       field, select single object.
    3. In the
      Object
       field, select the Databricks Delta object to which you want to write the curated customer engagement data.
    4. In the
      Operation
       field, select the insert operation.
    5. In the
      Advanced Properties
       section, specify the required advanced target properties.
  9. Click
    Save
    Run
     to validate the mapping.
    In Monitor, you can monitor the status of the logs after you run the task.
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