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[HUDI-4629] Create hive table from existing hoodie table failed when the table schema is not defined #6409

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[HUDI-4629] Create hive table from existing hoodie table failed when the table schema is not defined #6409

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12 changes: 11 additions & 1 deletion ...park-common/src/main/scala/org/apache/spark/sql/catalyst/catalog/HoodieCatalogTable.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -129,7 +129,17 @@ class HoodieCatalogTable(val spark: SparkSession, var table: CatalogTable) exten
/**
* Table schema
*/
lazy val tableSchema: StructType = table.schema
lazy val tableSchema: StructType = if (table.schema.nonEmpty) {
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@YannByron YannByron Sep 19, 2022

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I prefer to call loadTableSchemaByMetaClient directly without having to decide if table.schema is empty.
Parsing the metadata on spark does not need to depend on the meta from metastore.

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@dongkelun dongkelun Sep 21, 2022

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@YannByron The table.schema is not obtained from the hive metastore, but is specified by the user. Only when the user does not specify a schema, we can parse and obtain the schema from the file through the method loadTableSchemaByMetaClient

table.schema
} else {
val schemaFromMetaOpt = loadTableSchemaByMetaClient()
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@xushiyan xushiyan Aug 25, 2022

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this already handled in parseSchemaAndConfigs() , isn't it?

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@xushiyan xushiyan Aug 25, 2022

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@jinxing64 can you also have a look pls? given this is based on your previous change

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@dongkelun dongkelun Sep 1, 2022

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this already handled in parseSchemaAndConfigs() , isn't it?
yes

if (schemaFromMetaOpt.nonEmpty) {
schemaFromMetaOpt.get
} else {
throw new AnalysisException(
s"Missing schema fields when applying CREATE TABLE clause for $catalogTableName")
}
}

/**
* The schema without hoodie meta fields
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