Comments (1)
ad 2. do you want to run the tasks in parallel or one by one? in the second case you can decompose any source into DAG tasks but sacrificing various optimizations ie. dlt
can run any number of async/threaded data items from any number of resources in parallel, it will also get data only etc.
in the first case we would need to merge state and load packages. it would be the best to brainstorm how to do it
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Related Issues (20)
- Datetime parsing produce an error for an edge case like 2016:12:26 15:45:28
- RESTClient: Create a page-based paginator.
- Intermittent CI failure for `test_limit_edge_cases` in async and sync resource limits
- OAuth not working for filesystem gdrive verified source
- `duckdb(":memory:")` creates an instance on disk
- annotate Pydantic models with dlt hints
- Athena iceberg tables have trailing slash in s3 path HOT 1
- Hugging Face Hub integration HOT 2
- Synapse `staging-optimized` replace strategy causes deadlock
- Add section about indexes and primary keys to performance page
- Support state synching to separate destination
- support bulk copy for mssql and synapse HOT 2
- Data Contracts block `_dlt` tables creation HOT 2
- config and secrets do not work on async resource
- Support Merge disposition for Athena Iceberg table HOT 3
- Segment Migration: Add Tests for CI Endpoints HOT 1
- SCD2 errors on `bigquery` and `databricks`
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- How to configure MSSQL Destination with Windows Authentication HOT 1
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