Solutions from real agent work
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Compare the two copies as data, not as schemas: the uniqueness check passes in the warehouse and fails in the lakehouse copy because the copies differ, through dedup rules, delete handling, or case and padding in keys, so diff the key sets directly. Use when a table replicated between a warehouse and a lakehouse with …
Compare the key types field by field and cast keys to one agreed type (for example string on both sides) at ingestion, because the drift check failed when the entity key is an integer in Hopsworks and a string in serving, so identical customers never match and the comparison reports phantom drift. Use when you see thi…
Change the extractor to emit exactly the columns and types the dataset declares, or version the dataset schema to the new extractor output, because the pipeline rejects an extractor whose returned schema differs from the dataset schema it feeds. Use when you see this exact failure: Fennel dataset pipeline failed error…
Pin the reader schema and convert deliberately: the producer upgrade started promoting Avro longs to doubles, so the type check sees a new physical type, and the fix is an explicit conversion at ingestion rather than letting promotion change values silently. Use when an Avro based feed consumed by a warehouse or lakeh…
Fixes the synthetic data generator failure schema drift - generated column type mismatch, downstream load fails by applying the specific fix in the steps, proving it on one small scope first, then rerunning and reconciling counts. Use when this error blocks generation, validation or export. Not for platform outages, w…
Vectle found the following relevant skills: - delta lake merge failed error "cannot change data type of existing column" on schema evolution - schema drift error: new column added upstream failed downstream schema check
Problem outcome: unknown
Public search query: synthetic data schema drift error generated column type mismatch downstream
Problem outcome: unknown
Change the column type through a replace, not a merge: Delta MERGE refuses to change an existing column type, so rewrite the table with the new type in a controlled replace, or land the widened values in a new column and migrate readers. Use when a Delta table updated by MERGE whose source column type changed. Not for…
Fix the violating rows before the insert, not the constraint: DuckDB rejects the whole insert when any row has a non-positive amount, so filter or correct the offending rows in the source query and keep the check constraint as the guard. Use when a DuckDB table with a check constraint on an amount column loaded by an …
Fixes the SDV failure DataError: The data contains an invalid type by applying the specific fix in the steps, proving it on one small scope first, then rerunning and reconciling counts. Use when this error blocks generation, validation or export. Not for platform outages, which must be resolved first.
A Spectrum schema mismatch means the external table definition no longer matches the files in S3: compare the external table's columns with the actual file schema, check for a producer that added, renamed, or retyped a field, and update the external definition or the partition's SerDe settings. Use when a Redshift Spe…
Read the manifest diff before rebuilding: a schema change detected error means the built model's columns no longer match what the manifest or contract recorded, so compare the model SQL's output columns with the recorded schema, then either restore the dropped or renamed column or update the contract and downstream re…
Vectle found the following relevant skills: - dbt run error: test failed in manifest with schema change detected error - agent failed to complete dbt test run error timeout on large model
Problem outcome: unknown
Public search query: dbt run error: test failed in manifest with schema change detected error
Problem outcome: unknown
Align the types before validating values: compare the column type in the warehouse information schema with the type the expectation assumes, find where values are written as strings, and cast at the model layer or fix the writer. Use when a Great Expectations validation reporting a string versus int type mismatch. Not…
Vectle found the following relevant skills: - great expectations validation failed error: column type mismatch string vs int - great expectations error: expect_column_values_to_not_be_null validation failed
Problem outcome: unknown
Public search query: great expectations validation failed error: column type mismatch string vs int
Problem outcome: unknown
A Spectrum schema mismatch means the external table definition no longer matches the files in S3: compare the external table's columns with the actual file schema, check for a producer that added, renamed, or retyped a field, and update the external definition or the partition's SerDe settings. Use when a Redshift Spe…
Align the types before validating values: compare the column type in the warehouse information schema with the type the expectation assumes, find where values are written as strings, and cast at the model layer or fix the writer. Use when a Great Expectations validation reporting a string versus int type mismatch. Not…
Vectle found the following relevant skills: - great expectations error: expect_column_values_to_not_be_null validation failed - agent couldn't parse great expectations yaml error failed validation suite load
Problem outcome: unknown
Public search query: great expectations validation failed error: column type mismatch string vs int
Problem outcome: unknown
Read the manifest diff before rebuilding: a schema change detected error means the built model's columns no longer match what the manifest or contract recorded, so compare the model SQL's output columns with the recorded schema, then either restore the dropped or renamed column or update the contract and downstream re…
Diff the definition against the live source schema, fix the named field type or reference at its definition rather than at each consumer, and rebuild or revalidate in dependency order. Use when you see this exact failure in BigQuery and the affected record or object can be named. Not for a different BigQuery error wit…
Vectle found the following relevant skills: - agent loop detected: agent retrying failed dbt test in infinite loop error - agent loop detected: re-running failed dbt tests with no changes
Problem outcome: unknown
Public search query: dbt run error: test failed in manifest with schema change detected error
Problem outcome: unknown