Fix count() in avro failed when reader_types is coalescing #6225
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Signed-off-by: thirtiseven <ntlihy@gmail.com>
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build |
firestarman
reviewed
Aug 4, 2022
Signed-off-by: thirtiseven <ntlihy@gmail.com>
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Filed a follow up issue issue6226. |
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@GaryShen2008 is this for 22.08? If so, it will need to be approved and merged by Friday Aug 5. |
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spark.read.format("avro").load(data_path).count()reports error:QueryExecutionException: Expected 0 columns but read 8 from ArrayBuffer, if reader_types isCOALESCING. It is because Avro reader always specifies the schema from a file when coalescing reading, causing it to always read all columns of data.This PR use readDataSchema instead the schema from a file to quick fix this bug.
Further, we should build an evolved schema from readschema and dataSchema to do type checking and filtering, just like orc reader and parquet reader do. We also use readschema when reading files from cudf now, so it will be a bit complicated to make this change. Filed a followed issue #6226 to track it.
Fixes #6131
Signed-off-by: thirtiseven ntlihy@gmail.com