[GitHub] [spark] sunchao commented on a change in pull request #34308: [SPARK-37035][SQL] Improve error message when use parquet vectorize reader

[GitBox <gi...@apache.org>]

sunchao commented on a change in pull request #34308:
URL: https://github.com/apache/spark/pull/34308#discussion_r744292413



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File path: sql/catalyst/src/main/scala/org/apache/spark/sql/errors/QueryExecutionErrors.scala
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@@ -593,6 +593,16 @@ object QueryExecutionErrors {
     new QueryExecutionException(message, e)
   }
 
+  def unsupportedParquetDictionaryDecodingError(
+      valueType: String,
+      dictionary: String,

Review comment:
       Yes it's a bit strange. The modules are organized as follow:
   
   - **Catalyst (sql/catalyst)** - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
   - **Execution (sql/core)** - A query planner / execution engine for translating Catalyst’s logical query plans into Spark RDDs. This component also includes a new public interface, SqlContext, that allows users to execute SQL or structured scala queries against existing RDDs and Parquet files. 
   - **Hive Metastore Support (sql/hive)** - An extension of SqlContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allows users to run queries that include Hive UDFs, UDAFs, and UDTFs.
   
   So it seems `QueryExecutionError` are more suited for `sql/core`




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