Github user rdblue commented on the issue:
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@stczwd, I agree with @mccheah. Tables are basically named data sets.
Whether they support batch, micro-batch streaming, or continuous streaming is
determined by checking whether they implement
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@stczwd that's my understanding yeah. Others can feel free to correct me
otherwise.
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@mccheah you mean the tables user created do not distinguish between stream
and batch, but only when they are actually read from it?
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@stczwd my understanding here is that a table isn't a streaming table or a
batch table, but rather that a table points to data that can either be scanned
in stream or in batch, and that the table
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> @stczwd, thanks for taking a look at this. What are the differences
between batch and stream DDL that you think will come up?
1. Source needs to be defined for stream table
2. Stream
Github user gatorsmile commented on the issue:
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A general question. How to use this catalog API to implement the Hive
metastore? Is it doable?
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@stczwd, thanks for taking a look at this. What are the differences between
batch and stream DDL that you think will come up?
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@rdblue Have you considered about stream table API? It may have some
differences between batch table ddl and stream table ddl.
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@felixcheung, we're waiting on more reviews and a community decision about
how to pass partition transforms.
For passing transforms, I think the most reasonable compromise is to go
with a
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where are we on this?
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@tigerquoll, the proposal isn't to make partitions part of table
configuration. It is to make the partitioning scheme part of the table
configuration. How sources choose to handle individual
Github user tigerquoll commented on the issue:
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So Kudu range partitions support arbitrary sized partition intervals, like
the example below, where the first and last range partition are six months in
size, but the middle partition is one
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Sure,
I am looking at the point of view of supporting Kudu. Check out
https://kudu.apache.org/docs/schema_design.html#partitioning for some of the
details. In particular
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> Can we support column range partition predicates please?
This has an "apply" transform for passing other functions directly through,
so that may help if you have additional transforms that
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Can we support column range partition predicates please?
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Retest this please.
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@rxin, I've updated this to use a new interface, `PartitionTransform`,
instead of `Expression`. This is used to pass well-known transformations when
creating tables, like `Filter` is used to pass a
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@cloud-fan, on the dev thread about 2.4 you talked about getting this PR
in. What do we need to do next?
I can call a vote on the SPIP if you think that's ready. I just bumped the
thread.
Github user rdblue commented on the issue:
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#21888 demonstrates how to add a `TableIdentifier` with a catalog element,
`CatalogTableIdentifier` and how to safely migrate from the old identifier to
the new one with catalog.
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@marmbrus, @cloud-fan, @gatorsmile, I've updated this PR to use reflection
to instantiate catalogs. This allows implementations to provide named catalogs
(and reuse implementations) and configure
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