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- Merge Statement for SCD Type 2 11924
- This is a practical, step-by-step guide to using DuckDB's MERGE statement (introduced in v1.4.0) to perform upserts and build Slowly Changing Dimension Type 2 (SCD Type 2) tables . Type 2 SCDs let you keep full historical versions of record
...R BY duck_id, begin_date DESC; -- Only current records SELECT * FROM master_ducks WHERE is_current = true; -- Only expired historical records SELECT * FROM master_ducks WHERE is_current = false ORDER BY duck_id, begin_date DESC; Step 6: Examine a Single Du...d the post update insert statement, we can see the individual rows for Quackers . To view the original row of data that is historical: SELECT * FROM master_ducks WHERE duck_name = 'Quackers' AND is_current = false; Returns: record_id duck_id duck_name bree...The end date is NOT NULL, it has the date when this duck's data was updated. The is_current is false indicating this is a historical record. The field that will change is location , it is currently Pond A and will be updated to Pond B . To view the curren... - https://man.mtool.work/duckdb/2.0/guides/sql_features/merge.html
- Iceberg Extension 8092
- The iceberg extension implements support for the Apache Iceberg open table format . There are two ways to work with Iceberg in DuckDB: Individual tables are read directly from storage, by pointing at a table's metadata. This requires no cat
...a version-hint.text file or with non-standard metadata file names, see Selecting Metadata Versions . Time Travel To read a historical snapshot of a table, pass either snapshot_from_id or snapshot_from_timestamp (the two are mutually exclusive). Use iceberg... - https://man.mtool.work/duckdb/2.0/core_extensions/iceberg/overview.html
- Jupyter Notebooks 7850
- DuckDB's Python client can be used directly in Jupyter notebooks with no additional configuration, as the first section shows. Additional libraries can simplify SQL query development; the rest of this guide uses the JupySQL package. See oth
...extension allows Parquet and CSV files to be queried remotely over http. These examples query a Parquet file that contains historical taxi data from NYC. Using the Parquet format allows DuckDB to only pull the rows and columns into memory that are needed r... - https://man.mtool.work/duckdb/2.0/guides/python/jupyter.html
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