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Github user maropu commented on the issue:
https://github.com/apache/spark/pull/21389
I checked manually and I noticed some incorrect behaviour changes (detailed
below). So, I'll update in following prs. Sorry to bother you.
- CSV
`// Struct`
`// Write Path`
Seq((1, "Tesla")).toDF("a", "b").selectExpr("struct(a, b)").write.csv(dir)
`master and this pr has the same behaviour`
`-- master`
java.lang.UnsupportedOperationException: CSV data source does not support
struct data type.
at
org.apache.spark.sql.execution.datasources.csv.CSVUtils$.org$apache$spark$sql$execution$datasources$csv$CSVUtils$$verifyType$1(CSVUtils.scala:132)
`-- thir pr`
java.lang.UnsupportedOperationException: CSV data source does not support
struct data type.
at
org.apache.spark.sql.execution.datasources.DataSourceUtils$.throwUnsupportedException$1(DataSourceUtils.scala:40)
`// Read Path`
val schema = StructType.fromDDL("a struct")
spark.range(1).write.mode("overwrite").csv(dir)
spark.read.schema(schema).csv(dir).collect()
`master and this pr has the same behaviour`
`-- master`
java.lang.UnsupportedOperationException: CSV data source does not support
struct data type.
at
org.apache.spark.sql.execution.datasources.csv.CSVUtils$.org$apache$spark$sql$execution$datasources$csv$CSVUtils$$verifyType$1(CSVUtils.scala:132)
`-- this pr`
java.lang.UnsupportedOperationException: CSV data source does not support
struct data type.
at
org.apache.spark.sql.execution.datasources.DataSourceUtils$.throwUnsupportedException$1(DataSourceUtils.scala:40)
`// Map`
`// Write Path`
Seq((1, Map("Tesla" -> 3))).toDF("id", "cars").write.csv(dir)
`master and this pr has the same behaviour`
`-- master`
java.lang.UnsupportedOperationException: CSV data source does not support
map data type.
at
org.apache.spark.sql.execution.datasources.csv.CSVUtils$.org$apache$spark$sql$execution$datasources$csv$CSVUtils$$verifyType$1(CSVUtils.scala:132)
`-- thir pr`
java.lang.UnsupportedOperationException: CSV data source does not support
map data type.
at
org.apache.spark.sql.execution.datasources.DataSourceUtils$.throwUnsupportedException$1(DataSourceUtils.scala:40)
`// Read Path`
val schema = StructType.fromDDL("a map")
spark.range(1).write.mode("overwrite").csv(dir)
spark.read.schema(schema).csv(dir).collect()
`master and this pr has the same behaviour`
`- master`
java.lang.UnsupportedOperationException: CSV data source does not support
map data type.
at
org.apache.spark.sql.execution.datasources.csv.CSVUtils$.org$apache$spark$sql$execution$datasources$csv$CSVUtils$$verifyType$1(CSVUtils.scala:132)
`- this pr`
java.lang.UnsupportedOperationException: CSV data source does not support
map data type.
at
org.apache.spark.sql.execution.datasources.DataSourceUtils$.throwUnsupportedException$1(DataSourceUtils.scala:40)
`// Array`
`// Write Path`
Seq((1, Array("Tesla", "Chevy", "Ford"))).toDF("id",
"brands").write.csv(dir)
`master and this pr has the same behaviour`
`-- master`
java.lang.UnsupportedOperationException: CSV data source does not support
array data type.
at
org.apache.spark.sql.execution.datasources.csv.CSVUtils$.org$apache$spark$sql$execution$datasources$csv$CSVUtils$$verifyType$1(CSVUtils.scala:132)
`-- thir pr`
java.lang.UnsupportedOperationException: CSV data source does not support
array data type.
at
org.apache.spark.sql.execution.datasources.DataSourceUtils$.throwUnsupportedException$1(DataSourceUtils.scala:40)
`// Read Path`
val schema = StructType.fromDDL("a array")
spark.range(1).write.mode("overwrite").csv(dir)
spark.read.schema(schema).csv(dir).collect()
`master and this pr has the same behaviour`
`--master`
java.lang.UnsupportedOperationException: CSV data source does not support
array data type.
at
org.apache.spark.sql.execution.datasources.csv.CSVUtils$.org$apache$spark$sql$execution$datasources$csv$CSVUtils$$verifyType$1(CSVUtils.scala:132)
`-- this pr`
java.lang.UnsupportedOperationException: CSV data source does not support
array data type.
at
org.apache.spark.sql.execution.datasources.DataSourceUtils$.throwUnsupportedException$1(DataSourceUtils.scala:40)
`// Interval`
`// Write Path`
sql("select interval 1 days").write.csv(dir)
`master and this pr has the same behaviour`
`-- master`
org.apache.spark.sql.AnalysisException: Cannot save interval data type into
external storage.;
at
org.apache.spark.sql.execution.datasources.DataSource.planForWriting(DataSource.scala:511)
`-- thir pr`
org.apache.spark.sql.AnalysisException: Cannot save interval data type into
external storage.;
at
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Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/21389 @maropu Just want to double check whether all the data types are not supported before this PR? Have you ran these test cases without the code changes? After this PR, the error messages are more readable and captured earlier? --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark issue #21389: [SPARK-24204][SQL] Verify a schema in Json/Orc/ParquetFi...
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[GitHub] spark issue #21389: [SPARK-24204][SQL] Verify a schema in Json/Orc/ParquetFi...
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[GitHub] spark issue #21389: [SPARK-24204][SQL] Verify a schema in Json/Orc/ParquetFi...
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