Github user maropu commented on a diff in the pull request:

    https://github.com/apache/spark/pull/20929#discussion_r186584474
  
    --- Diff: 
sql/catalyst/src/main/scala/org/apache/spark/sql/types/TypePlaceholder.scala ---
    @@ -0,0 +1,23 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.sql.types
    +
    +/**
    + * An internal type that is a not yet available and will be replaced by an 
actual type later.
    + */
    +case object TypePlaceholder extends StringType
    --- End diff --
    
    In the first attempt, I used the new type instead of `NullType` because 
some `Sink`s (`FileStreamSink`) could not handle `NullType`;
    ```
    // parquet
    java.lang.RuntimeException: Unsupported data type NullType.
            at scala.sys.package$.error(package.scala:27)
            at 
org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport.org$apache$spark$sql$execution$datasources$parquet$ParquetWriteSupport$$makeWriter(ParquetWriteSupport.scala:206)
            at 
org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport$$anonfun$init$2.apply(ParquetWriteSupport.scala:93)
            at 
org.apache.spark.sql.execution.datasources.parquet.ParquetWriteSupport$$anonfun$init$2.apply(ParquetWriteSupport.scala:93)
            at 
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    // orc
    java.lang.IllegalArgumentException: Can't parse category at 
'struct<c0:bigint,c1:null^,c2:array<null>>'
            at 
org.apache.orc.TypeDescription.parseCategory(TypeDescription.java:223)
            at 
org.apache.orc.TypeDescription.parseType(TypeDescription.java:332)
            at 
org.apache.orc.TypeDescription.parseStruct(TypeDescription.java:327)
            at 
org.apache.orc.TypeDescription.parseType(TypeDescription.java:385)
            at 
org.apache.orc.TypeDescription.fromString(TypeDescription.java:406)
    
    // csv
    java.lang.UnsupportedOperationException: CSV data source does not support 
null data type.
            at 
org.apache.spark.sql.execution.datasources.csv.CSVUtils$.org$apache$spark$sql$execution$datasources$csv$CSVUtils$$verifyType$1(CSVUtils.scala:130)
            at 
org.apache.spark.sql.execution.datasources.csv.CSVUtils$$anonfun$verifySchema$1.apply(CSVUtils.scala:134)
            at 
org.apache.spark.sql.execution.datasources.csv.CSVUtils$$anonfun$verifySchema$1.apply(CSVUtils.scala:134)
            at scala.collection.Iterator$class.foreach(Iterator.scala:893)
    
    ```
    So, in the previous fix, I tried to add `PlaceholderType` inherited from 
`StringType` and this type could be correctly handled in all the `Sink`, but 
too tricky. 
    
    In the suggested, `NullType, ArrayType(NullType), etc should be dropped` 
means that we need to handle an inferred schema as follows? e.g.,
    ```
    Inferred schema: "StructType<IntegerType, NullType, ArrayType(NullType)>" 
-> Schema used in FileStreamSource: "StructType<IntegerType>"
    ```
    Is this right?


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