parquet-format
evernote-ai-chatbot
| parquet-format | evernote-ai-chatbot | |
|---|---|---|
| 4 | 4 | |
| 1,655 | 14 | |
| 1.8% | - | |
| 7.2 | 5.5 | |
| 4 days ago | 11 months ago | |
| Thrift | Python | |
| Apache License 2.0 | - |
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parquet-format
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Summing columns in remote Parquet files using DuckDB
Right, there's all sorts of metadata and often stats included in any parquet file: https://github.com/apache/parquet-format#file-format
The offsets of said metadata are well-defined (i.e. in the footer) so for S3 / blob storage so long as you can efficiently request a range of bytes you can pull the metadata without having to read all the data.
- FLaNK Stack for 4th of July
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I have question related to Parquet files and AWS Glue
As i read here https://github.com/apache/parquet-format/blob/master/LogicalTypes.md , they are store in Integer formats and these integers represent the number of days (for Date) or number of milliseconds, microseconds or nanoseconds (for DateTime) since 1970-01-01. This works as expected with the parquet file that written by our ETL tool from internal database --> S3, all Data/DateTime columns are Integers, means that in Glue Job, i have to convert these Integers back to Date/Datetime value to do some transformation on them. But when parquet files are written by Spark, they are Date/DateTime (or TimeStamp to be more concise) format not Integers (i checked by read these files again in other Glue Job) and that make me confused.
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Parquet: More than just “Turbo CSV”
Date is confusing with a timezone (UTC or otherwise) and the doco makes no such suggestion.
The Parquet datatypes documentation is pretty clear that there is a flag isAdjustedToUTC to define if the timestamp should be interpreted as having Instant semantics or Local semantics.
https://github.com/apache/parquet-format/blob/master/Logical...
Still no option to include a TZ offset in the data (so the same datum can be interpreted with both Local and Instant semantics) but not bad really.
evernote-ai-chatbot
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