Himanshu Gupta created SPARK-20457:
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Summary: Spark CSV is not able to Override Schema while reading
data
Key: SPARK-20457
URL: https://issues.apache.org/jira/browse/SPARK-20457
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.1.0
Reporter: Himanshu Gupta
I have a CSV file, test.csv:
{code:csv}
col
1
2
3
4
{code}
When I read it using Spark, it gets the schema of data correct:
{code:java}
val df = spark.read.option("header", "true").option("inferSchema",
"true").csv("test.csv")
df.printSchema
root
|-- col: integer (nullable = true)
{code}
But when I override the `schema` of CSV file and make `inferSchema` false, then
SparkSession is picking up custom schema partially.
{code:java}
val df = spark.read.option("header", "true").option("inferSchema",
"false").schema(StructType(List(StructField("custom", StringType,
false)))).csv("test.csv")
df.printSchema
root
|-- custom: string (nullable = true)
{code}
I mean only column name (`custom`) and DataType (`StringType`) are getting
picked up. But, `nullable` part is being ignored, as it is still coming
`nullable = true`, which is incorrect.
I am not able to understand this behavior.
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