Don Drake created SPARK-19477:
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Summary: [SQL] Datasets created from a Dataframe with extra
columns retain the extra columns
Key: SPARK-19477
URL: https://issues.apache.org/jira/browse/SPARK-19477
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.1.0
Reporter: Don Drake
In 1.6, when you created a Dataset from a Dataframe that had extra columns, the
columns not in the case class were dropped from the Dataset.
For example in 1.6, the column c4 is gone:
{code}
scala> case class F(f1: String, f2: String, f3:String)
defined class F
scala> import sqlContext.implicits._
import sqlContext.implicits._
scala> val df = Seq(("a","b","c","x"), ("d", "e", "f","y"), ("h", "i",
"j","z")).toDF("f1", "f2", "f3", "c4")
df: org.apache.spark.sql.DataFrame = [f1: string, f2: string, f3: string, c4:
string]
scala> val ds = df.as[F]
ds: org.apache.spark.sql.Dataset[F] = [f1: string, f2: string, f3: string]
scala> ds.show
+---+---+---+
| f1| f2| f3|
+---+---+---+
| a| b| c|
| d| e| f|
| h| i| j|
{code}
This seems to have changed in Spark 2.0 and also 2.1:
Spark 2.1.0:
{code}
scala> case class F(f1: String, f2: String, f3:String)
defined class F
scala> import spark.implicits._
import spark.implicits._
scala> val df = Seq(("a","b","c","x"), ("d", "e", "f","y"), ("h", "i",
"j","z")).toDF("f1", "f2", "f3", "c4")
df: org.apache.spark.sql.DataFrame = [f1: string, f2: string ... 2 more fields]
scala> val ds = df.as[F]
ds: org.apache.spark.sql.Dataset[F] = [f1: string, f2: string ... 2 more fields]
scala> ds.show
+---+---+---+---+
| f1| f2| f3| c4|
+---+---+---+---+
| a| b| c| x|
| d| e| f| y|
| h| i| j| z|
+---+---+---+---+
scala> import org.apache.spark.sql.Encoders
import org.apache.spark.sql.Encoders
scala> val fEncoder = Encoders.product[F]
fEncoder: org.apache.spark.sql.Encoder[F] = class[f1[0]: string, f2[0]: string,
f3[0]: string]
scala> fEncoder.schema == ds.schema
res2: Boolean = false
scala> ds.schema
res3: org.apache.spark.sql.types.StructType =
StructType(StructField(f1,StringType,true), StructField(f2,StringType,true),
StructField(f3,StringType,true), StructField(c4,StringType,true))
scala> fEncoder.schema
res4: org.apache.spark.sql.types.StructType =
StructType(StructField(f1,StringType,true), StructField(f2,StringType,true),
StructField(f3,StringType,true))
{code}
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