feat(spark): support Hive DDL / Insert operations #518
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andrew-coleman
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| ) | ||
| } | ||
| } | ||
| case WriteOp.INSERT => |
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I notice no isHive check here. Might it be possible to arrive here when isHive is not true?
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| val bytes = new PlanProtoConverter() | ||
| .toProto(substraitPlan) | ||
| .toByteArray | ||
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| // Read it back | ||
| val protoPlan = io.substrait.proto.Plan | ||
| .parseFrom(bytes) |
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It's valid but I'm wondering if there is any benefit to doing the work of de/serializing to bytes, rather than just using the protobuf object. Is it exercising anything other than protobuf's ability to de/serialize?
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In general, I put all tests through the full roundtrip lifecycle, including down to the proto bytes to ensure that all the visitors within the proto/rel converters have been implemented.
| assertResult(5)(spark.sql("select * from test").count()) | ||
| } | ||
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| test("CTAS") { |
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For the less expert amongst us, it might be clearer as:
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| test("CTAS") { | |
| test("Create table as select") { |
Add support for DdlRel and WriteRel for Hive in Spark Signed-off-by: Andrew Coleman <[email protected]>
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bestbeforetoday
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Sep 30, 2025
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Add support for DdlRel and WriteRel for Hive in Spark