Debezium operational data store

Set of tools to materialize raw data, provided by Debezium CDC and landed with Kafka-Connect.

How to use it.

1. Generate Raw landing table.

In this package there is an operation, which helps to generate landing tables for debezium sources.

Operation create_source_table

Generates the source table in database and prints the YAML for it to the output.

Arguments:

• table_name Required Type: string. A name of a table to create.
• schema_name Optional Type: string or None. Default None. A name of a schema to create the table in. If empty, the schema would be taken from target. If the schema does not exist, the operation attempts to create it.
• role_name Optional Type: string or None. Default None. A name of a role to grant required permissions. If None -- no permissions will be grant.
• db Optional Type: string or None. Default None. A name of a database to create the table and the schema. If None -- the database from a profile is used. Taking effect only for platforms, supporting multi-database adapters.
• aliases Optional Type: Dict[string,string] or None. Default None. Default technical column aliases. Takes into the account keys row_id and loaded_at. The values are names for the related columns. If None or the keys are missed -- values are taken from vars row_id__alias and loaded_at__alias. The default values for those are rolling_row_id and snowpipe_loaded_at.
• dry_run Optional Type: boolean Default False. If it should really apply the queries to the database or just prit it.

Example:

$ dbt run-operation create_source_table \
    --args '{db: raw_layer, schema_name: kafka_connect, table_name: my_lending_table}'

2. Build model.

2.1 Use only actual data.

To stage the table with an actual state the model should be defined with the following macro:

Macro to_stg_layer

Generates the model internals to stage a source with actual states.

Arguments:

• source_ref Required Type: Source The Source definition.
• fields Required Type: List[string | Dict[string,string] | Dict[string,Dict[string,boolean]]. List of the fields not including the Primary Key field. Each field could be defined with a name (as a string), with single-key dict, containing the field name as the key and an expresssion to cast it to some type in the python format string format as the, or with dict {"is_date": true} as value.
• incremental Required Type: boolean. The value of is_incremental() macro.
• source_engine Required Type: string The type of source database engine. Currently supports only postgresql value.
• contains_prev_state Optional Type: boolean Default False. If the source contains previous values. For more information see Debezium documentation.
• aliases Optional Type: Dict[string,string] or None. Default None. Default technical column aliases. Takes into the account keys is_deleted, deleted_at, ts, row_id and loaded_at. The values are names for the related columns. If None or the keys are missed -- values are taken from vars is_deleted__alias, deleted_at__alias, ts__alias, row_id__alias and loaded_at__alias. The default values for those are is_deleted, deleted_at, ts_ms rolling_row_id and snowpipe_loaded_at.

2.2 Use historical data (Slow changing dimentions)

Supported stack

1. Supported debezium connectors:

• io.debezium.connector.postgresql.PostgresConnector

2. Supported warehouse synk connectors:

• Snowflake