Support Scala 2.13 / Spark 3.2; drop Scala 2.11 / Spark 2 support (#564)

Author: srowen

.github/workflows/test_spark_2_java_8.yml …hub/workflows/test_spark_3_2_java_11.yml.github/workflows/test_spark_2_java_8.yml renamed to .github/workflows/test_spark_3_2_java_11.yml .github/workflows/test_spark_2_java_8.yml renamed to .github/workflows/test_spark_3_2_java_11.yml

@@ -1,4 +1,4 @@
-name: Spark 2 / Java 8
+name: Spark 3.2 / Java 11 / Scala 2.13
 on:
   push:
     branches: [master]
@@ -12,6 +12,6 @@ jobs:
       - name: Set up Java, SBT
         uses: olafurpg/setup-scala@v11
         with:
-          java-version: 'adopt@1.8'
+          java-version: 'adopt@1.11'
       - name: Build and test
-        run: sbt -Dspark.testVersion=2.4.8 ++2.11.12 clean scalastyle test:scalastyle mimaReportBinaryIssues test
+        run: sbt -Dspark.testVersion=3.2.0 ++2.13.5 clean test

…ithub/workflows/test_spark_3_java_11.yml .github/workflows/test_spark_3_java_8.yml.github/workflows/test_spark_3_java_11.yml renamed to .github/workflows/test_spark_3_java_8.yml .github/workflows/test_spark_3_java_11.yml renamed to .github/workflows/test_spark_3_java_8.yml

@@ -1,4 +1,4 @@
-name: Spark 3 / Java 11
+name: Spark 3 / Java 8 / Scala 2.12
 on:
   push:
     branches: [master]
@@ -12,8 +12,8 @@ jobs:
       - name: Set up Java, SBT
         uses: olafurpg/setup-scala@v11
         with:
-          java-version: 'adopt@1.11'
+          java-version: 'adopt@1.8'
       - name: Build and test
-        run: sbt -Dspark.testVersion=3.1.2 ++2.12.10 clean scalastyle test:scalastyle mimaReportBinaryIssues coverage test coverageReport
+        run: sbt -Dspark.testVersion=3.0.3 ++2.12.10 clean scalastyle test:scalastyle mimaReportBinaryIssues coverage test coverageReport
       - name: Check code coverage
-        run: bash <(curl -s https://codecov.io/bash)
+        run: bash <(curl -s https://codecov.io/bash)

README.md

@@ -7,7 +7,7 @@ The structure and test tools are mostly copied from [CSV Data Source for Spark](
 
 - This package supports to process format-free XML files in a distributed way, unlike JSON datasource in Spark restricts in-line JSON format.
 
-- Compatible with Spark 2.4.x and 3.x, with Scala 2.12. Scala 2.11 support with Spark 2.4.x is deprecated.
+- Compatible with Spark 3.0 and later with Scala 2.12, and also Spark 3.2 and later with Scala 2.12 or 2.13. Scala 2.11 and Spark 2 support ended with version 0.13.0.
 
 ## Linking
 
@@ -16,15 +16,15 @@ You can link against this library in your program at the following coordinates:
 ```
 groupId: com.databricks
 artifactId: spark-xml_2.12
-version: 0.13.0
+version: 0.14.0
 ```
 
 ## Using with Spark shell
 
 This package can be added to Spark using the `--packages` command line option. For example, to include it when starting the spark shell:
 
 ```
-$SPARK_HOME/bin/spark-shell --packages com.databricks:spark-xml_2.12:0.13.0
+$SPARK_HOME/bin/spark-shell --packages com.databricks:spark-xml_2.12:0.14.0
 ```
 
 ## Features
@@ -399,7 +399,7 @@ Automatically infer schema (data types)
 ```R
 library(SparkR)
 
-sparkR.session("local[4]", sparkPackages = c("com.databricks:spark-xml_2.12:0.13.0"))
+sparkR.session("local[4]", sparkPackages = c("com.databricks:spark-xml_2.12:0.14.0"))
 
 df <- read.df("books.xml", source = "xml", rowTag = "book")
 
@@ -411,7 +411,7 @@ You can manually specify schema:
 ```R
 library(SparkR)
 
-sparkR.session("local[4]", sparkPackages = c("com.databricks:spark-xml_2.12:0.13.0"))
+sparkR.session("local[4]", sparkPackages = c("com.databricks:spark-xml_2.12:0.14.0"))
 customSchema <- structType(
   structField("_id", "string"),
   structField("author", "string"),

build.sbt

@@ -1,16 +1,16 @@
 name := "spark-xml"
 
-version := "0.13.0"
+version := "0.14.0"
 
 organization := "com.databricks"
 
 scalaVersion := "2.12.10"
 
-crossScalaVersions := Seq("2.11.12", "2.12.10")
+crossScalaVersions := Seq("2.12.10", "2.13.5")
 
 scalacOptions := Seq("-unchecked", "-deprecation")
 
-val sparkVersion = sys.props.get("spark.testVersion").getOrElse("2.4.8")
+val sparkVersion = sys.props.get("spark.testVersion").getOrElse("3.2.0")
 
 // To avoid packaging it, it's Provided below
 autoScalaLibrary := false

src/main/scala/com/databricks/spark/xml/XmlDataToCatalyst.scala

@@ -57,4 +57,7 @@ case class XmlDataToCatalyst(
     case _: StructType => Seq(StringType)
     case ArrayType(_: StructType, _) => Seq(ArrayType(StringType))
   }
+
+  // Overrides, in Spark 3.2.0+
+  protected def withNewChildInternal(newChild: Expression): XmlDataToCatalyst = copy(newChild)
 }

src/main/scala/com/databricks/spark/xml/parsers/StaxXmlGenerator.scala

@@ -66,7 +66,7 @@ private[xml] object StaxXmlGenerator {
           writer.writeAttribute(name.substring(options.attributePrefix.length), v.toString)
 
         // For ArrayType, we just need to write each as XML element.
-        case (ArrayType(ty, _), v: Seq[_]) =>
+        case (ArrayType(ty, _), v: scala.collection.Seq[_]) =>
           v.foreach { e =>
             writeChildElement(name, ty, e)
           }
@@ -101,7 +101,7 @@ private[xml] object StaxXmlGenerator {
       // this case only can happen when we convert a normal [[DataFrame]] to XML file.
       // When [[ArrayType]] has [[ArrayType]] as elements, it is confusing what is element name
       // for XML file. Now, it is "item" but this might have to be according the parent field name.
-      case (ArrayType(ty, _), v: Seq[_]) =>
+      case (ArrayType(ty, _), v: scala.collection.Seq[_]) =>
         v.foreach { e =>
           writeChild("item", ty, e)
         }

src/test/scala/com/databricks/spark/xml/XmlSuite.scala

@@ -890,17 +890,17 @@ final class XmlSuite extends AnyFunSuite with BeforeAndAfterAll {
     val resultsOne = spark.read
       .option("treatEmptyValuesAsNulls", "true")
       .xml(resDir + "gps-empty-field.xml")
-    assert(resultsOne.selectExpr("extensions.TrackPointExtension").head.getStruct(0) !== null)
+    assert(resultsOne.selectExpr("extensions.TrackPointExtension").head().getStruct(0) !== null)
     assert(resultsOne.selectExpr("extensions.TrackPointExtension")
-      .head.getStruct(0)(0) === null)
+      .head().getStruct(0)(0) === null)
     // Is the behavior below consistent? see line above.
-    assert(resultsOne.selectExpr("extensions.TrackPointExtension.hr").head.getStruct(0) === null)
+    assert(resultsOne.selectExpr("extensions.TrackPointExtension.hr").head().getStruct(0) === null)
     assert(resultsOne.collect().length === 2)
 
     val resultsTwo = spark.read
       .option("nullValue", "2013-01-24T06:18:43Z")
       .xml(resDir + "gps-empty-field.xml")
-    assert(resultsTwo.selectExpr("time").head.getStruct(0) === null)
+    assert(resultsTwo.selectExpr("time").head().getStruct(0) === null)
     assert(resultsTwo.collect().length === 2)
   }