pushcart 1.7.3

Metadata transformations for Spark

pushcart

Helps with moving potatoes, bricks and data around.

Pushcart is a metadata-based solution accelerator running on top of Spark. It also provides a set of ready-made functionalities for data transformations which might otherwise take a lot of code to put together using only pyspark.sql.functions.

Who is this for

• Data engineers writing pure Spark code
• Data engineers working with Databricks Delta Live Tables

How does the metadata look like?

Useful for transforming data from bronze to silver, a metadata specification looks as such:

column_order	source_column_name	source_column_type	dest_column_name	dest_column_type	transform_function	default_value	validation_rule	validation_action
0	id	string	Id	int			Id IS NOT NULL	DROP
1	first_name	string
2	surname	string
3			Name	string	"F.concat_ws(' ', F.col('first_name'), F.col('surname'))",F.lit('John Doe')
4	dob	string	DateOfBirth	date	"F.to_date(F.col('dob'), 'yyyy-MM-dd')"
5	record_ts	string	RecordDateTime	timestamp	"F.to_timestamp(F.col('record_ts'), 'yyyy-MM-dd HH:mm:ss')"		RecordDateTime IS NOT NULL	DROP