Configuring Transformation Stage
In the Transformation stage, the legacy code and the business logic are transformed to the preferred target. Double-click the Transformation stage to access the configuration page.
In this Topic:
Overview
In this section, you can customize the Transformation stage’s name and give a suitable description as required. By default, Transformation is provided as the Name field. Provide a relevant name and description that helps you to understand the purpose and scope of the Transformation stage.
Transform
The transformation stage ensures seamless transformation and operationalization of large-scale legacy workloads to the modern cloud platform. There are two ways to transform legacy EDW workloads:
- Core Engine: To seamlessly transform your legacy EDW workloads to modern cloud platform using LeapLogic’s intelligent grammar engine. (LeapLogic’s intelligent grammar engine seamlessly transforms your legacy EDW workloads to modern cloud platform) It supports end-to-end transformation, including core business logic to target-native equivalents. Once transformed, the target compatible packaged code can be orchestrated and executed as production-ready jobs in the target environment. Additionally, this stage provides a notebook-based inline editor for query optimization. Here, you can configure the transformation stage to transform your workloads to the target of your choice. It includes specifying the source, target, input, and output types for transformation. In an integrated pipeline (Migration stage and Transformation stage), the output of the DML scripts, source type, and the metadata details of the Migration stage are automatically mapped to the Transformation stage. LeapLogic provides the provision to transform workloads from:
- LeapLogic Express: To transform your legacy EDW workloads using a pre-trained computational algorithm. It is equipped with pre-trained models and patterns, which facilitate efficient workload conversion.
The table below lists the EDW sources along with the input types and supported targets for workload transformation.
|
Source |
Input Type |
Target |
|
Teradata |
SQL/BTQ/Procedure |
Hive |
|
Spark |
|
Amazon Redshift |
|
Azure Synapse |
|
Databricks Lakehouse |
|
Databricks Notebook |
|
Google BigQuery |
|
Snowflake |
|
AWS Glue |
|
KSH |
Spark |
|
Google BigQuery |
|
Amazon Redshift |
|
Hive |
|
MLOAD |
Databricks Notebook |
|
TPT |
AWS Glue Jobs
Spark
Databricks
|
|
Triggers |
Databricks Notebook |
|
Analytics queries |
Kyvos semantic cube |
|
Netezza |
SQL/Procedure |
Spark |
|
Amazon Redshift |
|
Azure Synapse |
|
Databricks Lakehouse |
|
Databricks Notebook |
|
Snowflake |
|
SQL Scripting (Databricks) |
|
Hive |
|
KSH |
Hive |
|
Spark |
|
Oracle |
SQL/Procedure |
Spark |
|
Amazon Redshift |
|
Azure Synapse |
|
Databricks Lakehouse |
|
Databricks Notebook |
|
GCP PostgreSQL |
|
Google BigQuery |
|
Snowflake |
|
Hive |
|
Amazon Aurora |
|
SQL Scripting (Databricks) |
|
SQL Server |
SQL/Procedure |
Spark |
|
Amazon Redshift |
|
Aurora PostgresSQL |
|
Databricks Lakehouse |
|
Databricks Notebook |
|
Snowflake |
|
SQL Scripting (Databricks) |
|
Hive |
|
Vertica |
SQL/Procedure |
Spark |
|
Hive |
|
KSH/BASH/SH |
Spark |
|
SQL/Procedure |
Databricks Lakehouse |
|
DB2 |
SQL/Procedure |
AWS Glue Job (Delta and Iceberg) |
|
Amazon Redshift |
|
Sybase |
SQL |
Databricks Lakehouse |
|
Dremio |
SQL |
Athena |
|
Greenplum |
SQL/Procedure |
Spark |
|
Hive |
|
Snowflake |
DML/DDL |
Databricks Notebook |
|
JavaScript Procedures |
Databricks Notebook |
|
Generic ANSI SQL |
SQL/Procedure |
Amazon Redshift |
|
Databricks Lakehouse |
|
Snowflake |
|
Spark |
|
PostgreSQL |
SQL/Procedure |
Databricks Notebook |
|
Redshift |
SQL/Procedure |
Databricks Notebook |
|
EDW Unity Catalog |
|
Databricks Lakehouse |
To view the Transformation Stage report, visit Transformation Report.
Output
The output of this transformation is HQL/Spark SQL, Java/Python/Scala code, or cloud compatible scripts such as SnowSQL. A detailed report is generated as output and required queries can be edited through an online notebook-based code editor.
You can configure the output of this transformation for navigation to a further stage. By default, the output configuration is set to Stop if the transformation is not 100%, or that can be configured to Continue, Error, and Pause as required.
Next:
Configuring Validation Stage
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