Sameer Agarwal created SPARK-20590:
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Summary: Map default input data source formats to inlined classes
Key: SPARK-20590
URL: https://issues.apache.org/jira/browse/SPARK-20590
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.2.0
Reporter: Sameer Agarwal
One of the common usability problems around reading data in spark (particularly
CSV) is that there can often be a conflict between different readers in the
classpath.
As an example, if someone launches a 2.x spark shell with the spark-csv package
in the classpath, Spark currently fails in an extremely unfriendly way
{code}
./bin/spark-shell --packages com.databricks:spark-csv_2.11:1.5.0
scala> val df = spark.read.csv("/foo/bar.csv")
java.lang.RuntimeException: Multiple sources found for csv
(org.apache.spark.sql.execution.datasources.csv.CSVFileFormat,
com.databricks.spark.csv.DefaultSource15), please specify the fully qualified
class name.
at scala.sys.package$.error(package.scala:27)
at
org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:574)
at
org.apache.spark.sql.execution.datasources.DataSource.providingClass$lzycompute(DataSource.scala:85)
at
org.apache.spark.sql.execution.datasources.DataSource.providingClass(DataSource.scala:85)
at
org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:295)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:178)
at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:533)
at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:412)
... 48 elided
{code}
This JIRA proposes a simple way of fixing this error by always mapping default
input data source formats to inlined classes (that exist in Spark).
{code}
./bin/spark-shell --packages com.databricks:spark-csv_2.11:1.5.0
scala> val df = spark.read.csv("/foo/bar.csv")
df: org.apache.spark.sql.DataFrame = [_c0: string]
{code}
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