The built-in materializations are'view','table','incremental','materialized_view'for models as well as'test','unit','snapshot','seed', and'clone'. You can still explicitly override built-in materializations, in favor of a materialization defined in a package, by reimplementing the built-...
test_dbt_incremental: incremental # Snapshot not supported # test_dbt_snapshot_strategy_timestamp: snapshot_strategy_timestamp # test_dbt_snapshot_strategy_check_cols: snapshot_strategy_check_cols test_dbt_data_test: data_test test_dbt_schema_test: schema_test test_dbt_ephemeral_data_tests: ...
Potential footgun - If you forget to remove whitespace from the target_database config of snapshots - dbt will fail to detect that the snapshot already exist and therefor does a CTAS everytime. Expected Behavior This doesn't happen for incremental models - as in, even if we had a whitesp...
You can manage access to the datasets you're producing with dbt by using grants. To implement these permissions, define grants as resource configs on each model, seed, or snapshot. Define the default grants that apply to the entire project in your dbt_pr
run dbt snapshot command Potential next topics Let's talk for a moment about some more advanced concepts in dbt that might be of interest to you in the future. There is the concept of incremental models, which is processing only new / changed data in your warehouse without reloading everyth...
Materializationsinclude/<adapter_name>/macros/materializations/Table/view/snapshot/ workflow definitions Python classes These classes implement all the methods responsible for: Connecting to a database and issuing queries. Providing dbt with database-specific configuration information. ...
snapshot_time_data_type="DATETIME", updated_at_data_type="DATETIMEZ" ), core_types.MicrobatchExecutionDebug(msg=""), core_types.LogStartBatch(description="", batch_index=0, total_batches=0), core_types.LogBatchResult( description="", status="", batch_index=0, total_batches=0, executio...