Skip to content

[SPARK-18269][SQL] CSV datasource should read null properly when schema is lager than parsed tokens #15767

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
HyukjinKwon wants to merge 7 commits into from
Closed

[SPARK-18269][SQL] CSV datasource should read null properly when schema is lager than parsed tokens #15767

Changes from 1 commit
Commits
Show all changes
7 commits
Select commit Hold shift + click to select a range
3692099
Take the case of null into account
HyukjinKwon Nov 4, 2016
e1c58c1
minimise the change
HyukjinKwon Nov 4, 2016
4132075
Indentation
HyukjinKwon Nov 4, 2016
c0667d1
Make the condition better
HyukjinKwon Nov 5, 2016
b913eac
No extra change
HyukjinKwon Nov 5, 2016
e5146e3
address the comment for condition and exception
HyukjinKwon Nov 5, 2016
aa89171
Print field name in the exception message
HyukjinKwon Nov 6, 2016
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
Next Next commit
Indentation
  • Loading branch information
@HyukjinKwon
HyukjinKwon committed Nov 4, 2016
commit 41320754f198278535fd09e6f30f38280c0ec578
2 changes: 1 addition & 1 deletion sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -896,7 +896,7 @@ class CSVSuite extends QueryTest with SharedSQLContext with SQLTestUtils {
Seq("1").toDF().write.text(path.getAbsolutePath)
val schema = StructType(
StructField("a", IntegerType, true) ::
StructField("b", IntegerType, true) :: Nil)
StructField("b", IntegerType, true) :: Nil)
val df = spark.read
.schema(schema)
.option("header", "false")
Expand Down