Or bytetype depending on the use case
> On 23. Nov 2017, at 10:18, Herman van Hövell tot Westerflier
> <hvanhov...@databricks.com> wrote:
>
> You need to use a StringType. The CharType and VarCharType are there to
> ensure compatibility with Hive and ORC; they should not be used anywhere else.
>
>> On Thu, Nov 23, 2017 at 4:09 AM, 163 <hewenting_...@163.com> wrote:
>> Hi,
>> when I use Dataframe with table schema, It goes wrong:
>>
>> val test_schema = StructType(Array(
>> StructField("id", IntegerType, false),
>> StructField("flag", CharType(1), false),
>> StructField("time", DateType, false)));
>>
>> val df = spark.read.format("com.databricks.spark.csv")
>> .schema(test_schema)
>> .option("header", "false")
>> .option("inferSchema", "false")
>> .option("delimiter", ",")
>> .load("file:///Users/name/b")
>>
>> The log is below:
>> Exception in thread "main" scala.MatchError: CharType(1) (of class
>> org.apache.spark.sql.types.CharType)
>> at
>> org.apache.spark.sql.catalyst.encoders.RowEncoder$.org$apache$spark$sql$catalyst$encoders$RowEncoder$$serializerFor(RowEncoder.scala:73)
>> at
>> org.apache.spark.sql.catalyst.encoders.RowEncoder$$anonfun$2.apply(RowEncoder.scala:158)
>> at
>> org.apache.spark.sql.catalyst.encoders.RowEncoder$$anonfun$2.apply(RowEncoder.scala:157)
>>
>> Why? Is this a bug?
>>
>> But I found spark will translate char type to string when using create
>> table command:
>>
>> create table test(flag char(1));
>> desc test: flag string;
>>
>>
>>
>>
>> Regards
>> Wendy He
>
>
>
> --
> Herman van Hövell
> Software Engineer
> Databricks Inc.
> hvanhov...@databricks.com
> +31 6 420 590 27
> databricks.com
>
>
>
>
