FAQ

Guidance for Oracle as a source

Driver

Option 1

• Download ojdbc8.jar from Oracle: Visit the official Oracle website to acquire the ojdbc8.jar JAR file. This file is crucial for establishing connectivity between Databricks and Oracle databases.

• Install the JAR file on Databricks: Upon completing the download, install the JAR file onto your Databricks cluster. Refer to this page For comprehensive instructions on uploading a JAR file, Python egg, or Python wheel to your Databricks workspace.

Option 2

• Install ojdbc8 library from Maven: Follow this guide to install the Maven library on a cluster. Refer to this document for obtaining the Maven coordinates.

This installation is a necessary step to enable seamless comparison between Oracle and Databricks, ensuring that the required Oracle JDBC functionality is readily available within the Databricks environment.

Commonly Used Custom Transformations

source_type	data_type	source_transformation	target_transformation	source_value_example	target_value_example	comments
Oracle	number(10,5)	"trim(to_char(coalesce(col_name,0.0), ’99990.99999’))"	"cast(coalesce(col_name,0.0) as decimal(10,5))"	1.00	1.00000	this can be used for any precision and scale by adjusting accordingly in the transformation
Snowflake	array	"array_to_string(array_compact(col_name),’,’)"	"concat_ws(’,’, col_name)"	[1,undefined,2]	[1,2]	in case of removing "undefined" during migration(converts sparse array to dense array)
Snowflake	array	"array_to_string(array_sort(array_compact(col_name), true, true),’,’)"	"concat_ws(’,’, col_name)"	[2,undefined,1]	[1,2]	in case of removing "undefined" during migration and want to sort the array
Snowflake	timestamp_ntz	"date_part(epoch_second,col_name)"	"unix_timestamp(col_name)"	2020-01-01 00:00:00.000	2020-01-01 00:00:00.000	convert timestamp_ntz to epoch for getting a match between Snowflake and data bricks