nickdelnano commented on issue #1202:
URL:
https://github.com/apache/iceberg-python/issues/1202#issuecomment-2577929467
@vikramsg i updated my comment a bit, but yes
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vikramsg commented on issue #1202:
URL:
https://github.com/apache/iceberg-python/issues/1202#issuecomment-2577900498
> These apps used to write messages to Kafka and then Flink would stream
them to our data lake, but pyiceberg is simpler, costs less and supports schema
evolution better.
emorfam commented on issue #1202:
URL:
https://github.com/apache/iceberg-python/issues/1202#issuecomment-2472881903
Currently using PyIceberg for monitoring metadata statistics of Iceberg
tables in a custom application (e.g. file count, record count, data
distribution across partitions). W
djouallah commented on issue #1202:
URL:
https://github.com/apache/iceberg-python/issues/1202#issuecomment-2440232128
I use it mainly for testing xtable conversion from iceberg to delta, it is
by the far the easiest way to generate Iceberg tables :)
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mariotaddeucci commented on issue #1202:
URL:
https://github.com/apache/iceberg-python/issues/1202#issuecomment-2412604690
Hey, actually I'm using in production for small datasets in combination with
duckdb specially to avoid small files with webscrapping.
For ingestion, reading many
