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https://issues.apache.org/jira/browse/SPARK-10848?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15001685#comment-15001685
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Xin Wu commented on SPARK-10848:
--------------------------------
One case I found where there is inconsistency between using asNullable and not
using asNullable.
That is
{code}
val dfDFfromFile =
sqlContext.read.schema(mySchema).json("/home/xwu0226/spark-tables/Orders.json")
dfDFfromFile1.filter("CustomerID is null").show
+-------+----------+
|OrderID|CustomerID|
+-------+----------+
+-------+----------+
{code}
When asNullable is used to set the DataFrame schema to nullable on all fields,
you will see the result in above case as following:
{code}
+-------+----------+
|OrderID|CustomerID|
+-------+----------+
| 2 + null |
+-------+----------+
{code}
I guess in this case, the user may expect to see the latter result.
> Applied JSON Schema Works for json RDD but not when loading json file
> ---------------------------------------------------------------------
>
> Key: SPARK-10848
> URL: https://issues.apache.org/jira/browse/SPARK-10848
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.5.0
> Reporter: Miklos Christine
> Priority: Minor
>
> Using a defined schema to load a json rdd works as expected. Loading the json
> records from a file does not apply the supplied schema. Mainly the nullable
> field isn't applied correctly. Loading from a file uses nullable=true on all
> fields regardless of applied schema.
> Code to reproduce:
> {code}
> import org.apache.spark.sql.types._
> val jsonRdd = sc.parallelize(List(
> """{"OrderID": 1, "CustomerID":452 , "OrderDate": "2015-05-16",
> "ProductCode": "WQT648", "Qty": 5}""",
> """{"OrderID": 2, "CustomerID":16 , "OrderDate": "2015-07-11",
> "ProductCode": "LG4-Z5", "Qty": 10, "Discount":0.25,
> "expressDelivery":true}"""))
> val mySchema = StructType(Array(
> StructField(name="OrderID" , dataType=LongType, nullable=false),
> StructField("CustomerID", IntegerType, false),
> StructField("OrderDate", DateType, false),
> StructField("ProductCode", StringType, false),
> StructField("Qty", IntegerType, false),
> StructField("Discount", FloatType, true),
> StructField("expressDelivery", BooleanType, true)
> ))
> val myDF = sqlContext.read.schema(mySchema).json(jsonRdd)
> val schema1 = myDF.printSchema
> val dfDFfromFile = sqlContext.read.schema(mySchema).json("Orders.json")
> val schema2 = dfDFfromFile.printSchema
> {code}
> Orders.json
> {code}
> {"OrderID": 1, "CustomerID":452 , "OrderDate": "2015-05-16", "ProductCode":
> "WQT648", "Qty": 5}
> {"OrderID": 2, "CustomerID":16 , "OrderDate": "2015-07-11", "ProductCode":
> "LG4-Z5", "Qty": 10, "Discount":0.25, "expressDelivery":true}
> {code}
> The behavior should be consistent.
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