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new 308996b [SPARK-26716][SPARK-26765][FOLLOWUP][SQL] Clean up schema
validation methods and override toString method in Avro
308996b is described below
commit 308996bc72c95582577843d22fcca5f1051d242a
Author: Gengliang Wang <gengliang.w...@databricks.com>
AuthorDate: Thu Jan 31 15:44:44 2019 +0800
[SPARK-26716][SPARK-26765][FOLLOWUP][SQL] Clean up schema validation
methods and override toString method in Avro
## What changes were proposed in this pull request?
In #23639, the API `supportDataType` is refactored. We should also remove
the method `verifyWriteSchema` and `verifyReadSchema` in `DataSourceUtils`.
Since the error message use `FileFormat.toString` to specify the data
source naming, this PR also overriding the `toString` method in
`AvroFileFormat`.
## How was this patch tested?
Unit test.
Closes #23699 from gengliangwang/SPARK-26716-followup.
Authored-by: Gengliang Wang <gengliang.w...@databricks.com>
Signed-off-by: Wenchen Fan <wenc...@databricks.com>
---
.../org/apache/spark/sql/avro/AvroFileFormat.scala | 2 ++
.../scala/org/apache/spark/sql/avro/AvroSuite.scala | 2 +-
.../spark/sql/execution/datasources/DataSource.scala | 2 +-
.../sql/execution/datasources/DataSourceUtils.scala | 17 +----------------
.../sql/execution/datasources/FileFormatWriter.scala | 2 +-
5 files changed, 6 insertions(+), 19 deletions(-)
diff --git
a/external/avro/src/main/scala/org/apache/spark/sql/avro/AvroFileFormat.scala
b/external/avro/src/main/scala/org/apache/spark/sql/avro/AvroFileFormat.scala
index 7391665..c2a7f31 100755
---
a/external/avro/src/main/scala/org/apache/spark/sql/avro/AvroFileFormat.scala
+++
b/external/avro/src/main/scala/org/apache/spark/sql/avro/AvroFileFormat.scala
@@ -124,6 +124,8 @@ private[avro] class AvroFileFormat extends FileFormat
override def shortName(): String = "avro"
+ override def toString(): String = "Avro"
+
override def isSplitable(
sparkSession: SparkSession,
options: Map[String, String],
diff --git
a/external/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
b/external/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
index d803537..81a5cb7 100644
--- a/external/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
+++ b/external/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
@@ -896,7 +896,7 @@ class AvroSuite extends QueryTest with SharedSQLContext
with SQLTestUtils {
sql("select
testType()").write.format("avro").mode("overwrite").save(tempDir)
}.getMessage
assert(msg.toLowerCase(Locale.ROOT)
- .contains(s"data source does not support calendarinterval data type."))
+ .contains(s"avro data source does not support calendarinterval data
type."))
}
}
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
index d48261e..db81fbd 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
@@ -412,7 +412,7 @@ case class DataSource(
hs.partitionSchema.map(_.name),
"in the partition schema",
equality)
- DataSourceUtils.verifyReadSchema(hs.fileFormat, hs.dataSchema)
+ DataSourceUtils.verifySchema(hs.fileFormat, hs.dataSchema)
case _ =>
SchemaUtils.checkColumnNameDuplication(
relation.schema.map(_.name),
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala
index a32a940..74eae94 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSourceUtils.scala
@@ -24,26 +24,11 @@ import org.apache.spark.sql.types._
object DataSourceUtils {
-
- /**
- * Verify if the schema is supported in datasource in write path.
- */
- def verifyWriteSchema(format: FileFormat, schema: StructType): Unit = {
- verifySchema(format, schema, isReadPath = false)
- }
-
- /**
- * Verify if the schema is supported in datasource in read path.
- */
- def verifyReadSchema(format: FileFormat, schema: StructType): Unit = {
- verifySchema(format, schema, isReadPath = true)
- }
-
/**
* Verify if the schema is supported in datasource. This verification should
be done
* in a driver side.
*/
- private def verifySchema(format: FileFormat, schema: StructType, isReadPath:
Boolean): Unit = {
+ def verifySchema(format: FileFormat, schema: StructType): Unit = {
schema.foreach { field =>
if (!format.supportDataType(field.dataType)) {
throw new AnalysisException(
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatWriter.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatWriter.scala
index 91e92d8..2232da4 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatWriter.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatWriter.scala
@@ -98,7 +98,7 @@ object FileFormatWriter extends Logging {
val caseInsensitiveOptions = CaseInsensitiveMap(options)
val dataSchema = dataColumns.toStructType
- DataSourceUtils.verifyWriteSchema(fileFormat, dataSchema)
+ DataSourceUtils.verifySchema(fileFormat, dataSchema)
// Note: prepareWrite has side effect. It sets "job".
val outputWriterFactory =
fileFormat.prepareWrite(sparkSession, job, caseInsensitiveOptions,
dataSchema)
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