Louis_Frolio
Databricks Employee
Databricks Employee

‎05-13-2025 12:32 PM

The error encountered, "Cannot have multiple queries named catalog.schema.destination_fact for catalog.schema.destination_fact. Additional queries on that table must be named," arises because Delta Live Tables (DLT) disallows multiple unnamed queries targeting the same table. This limitation stems from how DLT processes and manages tables within a pipeline. To resolve this, you must assign unique flow names to each apply_changes command targeting the same table.
 
The Databricks documentation and community examples mention that naming flows explicitly when using apply_changes resolves this issue. Here's how this can be implemented:

Solution: Assign Unique Flow Names

Modify the apply_changes statements to include a flow_name parameter. This parameter uniquely identifies each change flow targeting the same table.
Example:
# Apply Changes for Initial Ingestion
dlt.apply_changes(
    target=destination_fact,
    source="vw_fact",
    keys=["id"],
    sequence_by=col("inserted_timestamp"),
    stored_as_scd_type="1",
    flow_name="initial_ingestion_flow"
)

# Apply Changes for Fixing Missing Dimension 2 IDs
dlt.apply_changes(
    target=destination_fact,
    source="fix_missing_dim_2",
    keys=["id"],
    sequence_by=col("inserted_timestamp"),
    stored_as_scd_type="1",
    flow_name="missing_dim_2_fix_flow"
)
 
Explanation: By assigning flow names like "initial_ingestion_flow" and "missing_dim_2_fix_flow", you ensure that DLT can differentiate between the change flows. This approach aligns with the solution mentioned in community discussions and documentation.
 
Limitations: - You must name every change flow explicitly to avoid conflicts. - Review pipeline performance to ensure updates are applied efficiently.
 
Hope this helps, Lou.
 
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