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Github user rdblue commented on the issue:
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@dongjoon-hyun, Iceberg schema evolution is based on the field IDs, not on
names. The current table schema's names are the runtime names for columns in
that table, and all reads happen by first
Github user dongjoon-hyun commented on the issue:
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Thank you, @rdblue . BTW, in general, indexing might be unsafe in Apache
Spark when Metastore Schema is different from File Schema. Does it assume
schema evolution feature in `IceBerg`?
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Github user rdblue commented on the issue:
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The approach we've taken in Iceberg is to allow `.` in names by using an
index in the top-level schema. The full path of every leaf in the schema is
produced and added to a map from the full field
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That's great!
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Github user gatorsmile commented on the issue:
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Updating `Filter` APIs sounds reasonable to me. This should be part of our
data source API v2. cc @cloud-fan @rxin @rdblue
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Can we update public `Filter` API in Spark 3.0.0? @cloud-fan and
@gatorsmile .
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Github user dbtsai commented on the issue:
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I was thinking to change the APIs in `Filter` so we can represent nested
fields easier, but also realized that it's a stable public interface.
Without changing the interface of `Filter`, we
Github user cloud-fan commented on the issue:
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I think the problem is, the current public `Filter` API uses string as the
attribute type, which is hard to represent nested fields.
Ideally we should extend the API, create a new
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@gatorsmile @cloud-fan @dongjoon-hyun @viirya
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