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MoritzS
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Feb 12, 2026
| They can be used to import information from different data systems into CedarDB. | ||
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| {{<callout type="info">}} | ||
| While interactive querying of Parquet files is also possible, CedarDB is optimized for it's own storage engine. |
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| While interactive querying of Parquet files is also possible, CedarDB is optimized for it's own storage engine. | |
| While interactive querying of Parquet files is also possible, CedarDB is optimized for its own storage engine. |
| ## Examples | ||
| Read a parquet file | ||
| ```sql | ||
| SELECT * FROM 'test.parquet'; |
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Can you also show the non-shortened syntax with parquet_view?
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| ## Creating a Table from parquet | ||
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| Either you can load parquet data directly into a table: |
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| Either you can load parquet data directly into a table: | |
| You can either load parquet data directly into a table: |
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| CedarDB's parquet scan is optimized for full parquet file imports. | ||
| The scan is fully multi-threaded and only reads the columns that are queried by the user. | ||
| We do not yet push-down filters into the parquet rowgroups to prune based on parquet statistics and metadata. |
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I would phrase this more positively for us, something like this:
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| We do not yet push-down filters into the parquet rowgroups to prune based on parquet statistics and metadata. | |
| Evaluating filter predicates is most efficient in CedarDB's native data format. |
And then you could add a "Not yet supported" thing in the "Enhanced Features" table below saying "Using Parquet statistics for better filtering" or something in that direction
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