Roundtrip null values of any type

This pull request adds functionality to spark-csv with the goal of having the ability to write null values to file and read them back out again as null. Two changes were made to enable this.

First, since the `com.databricks.spark.csv` package previously had the null string hardcoded to "`null`" when saving to a csv file, this was changed to read the null token out of the passed in parameters map, from the value for "`nullToken`", enabling writing null values as empty strings by use of this option. The default is left to "`null`" to maintain the previous behavior of the library.

Secondly, the `castTo` method from `com.databricks.spark.csv.util.TypeCast` had an impossible-to-reach case statement when the `castType` was an instance of `StringType`. As a result, it was not possible to read string values from file as null. This pull request adds a setting 'treatEmptyValuesAsNulls' that allows empty string values in fields that are marked as nullable to be read as null values, as expected. Again, the previous behavior is enabled by default, so this pull request only changes the behavior when `treatEmptyValuesAsNulls` is explicitly set to true. The appropriate changes to `CsvParser` and `CsvRelation` were made to include this new setting.

Additionally, a unit test has been added to `CsvSuite` to test the ability to round-trip (both string and non-string) null values by writing nulls and reading them back out again as nulls.

Author: Andres Perez <[email protected]>

Closes #147 from andy327/feat-set-null-tokens.

Author: andy327

build.sbt

@@ -95,6 +95,7 @@ mimaDefaultSettings ++ Seq(
     ProblemFilters.excludePackage("com.databricks.spark.csv.CsvRelation"),
     ProblemFilters.excludePackage("com.databricks.spark.csv.util.InferSchema"),
     ProblemFilters.excludePackage("com.databricks.spark.sql.readers"),
+    ProblemFilters.excludePackage("com.databricks.spark.csv.util.TypeCast"),
     // We allowed the private `CsvRelation` type to leak into the public method signature:
     ProblemFilters.exclude[IncompatibleResultTypeProblem](
       "com.databricks.spark.csv.DefaultSource.createRelation")

src/main/scala/com/databricks/spark/csv/CsvParser.scala

@@ -35,6 +35,7 @@ class CsvParser extends Serializable {
   private var parseMode: String = ParseModes.DEFAULT
   private var ignoreLeadingWhiteSpace: Boolean = false
   private var ignoreTrailingWhiteSpace: Boolean = false
+  private var treatEmptyValuesAsNulls: Boolean = false
   private var parserLib: String = ParserLibs.DEFAULT
   private var charset: String = TextFile.DEFAULT_CHARSET.name()
   private var inferSchema: Boolean = false
@@ -84,6 +85,11 @@ class CsvParser extends Serializable {
     this
   }
 
+  def withTreatEmptyValuesAsNulls(treatAsNull: Boolean): CsvParser = {
+    this.treatEmptyValuesAsNulls = treatAsNull
+    this
+  }
+
   def withParserLib(parserLib: String): CsvParser = {
     this.parserLib = parserLib
     this
@@ -114,6 +120,7 @@ class CsvParser extends Serializable {
       parserLib,
       ignoreLeadingWhiteSpace,
       ignoreTrailingWhiteSpace,
+      treatEmptyValuesAsNulls,
       schema,
       inferSchema)(sqlContext)
     sqlContext.baseRelationToDataFrame(relation)
@@ -132,6 +139,7 @@ class CsvParser extends Serializable {
       parserLib,
       ignoreLeadingWhiteSpace,
       ignoreTrailingWhiteSpace,
+      treatEmptyValuesAsNulls,
       schema,
       inferSchema)(sqlContext)
     sqlContext.baseRelationToDataFrame(relation)

src/main/scala/com/databricks/spark/csv/CsvRelation.scala

@@ -43,6 +43,7 @@ case class CsvRelation protected[spark] (
     parserLib: String,
     ignoreLeadingWhiteSpace: Boolean,
     ignoreTrailingWhiteSpace: Boolean,
+    treatEmptyValuesAsNulls: Boolean,
     userSchema: StructType = null,
     inferCsvSchema: Boolean)(@transient val sqlContext: SQLContext)
   extends BaseRelation with TableScan with InsertableRelation {
@@ -113,7 +114,8 @@ case class CsvRelation protected[spark] (
           index = 0
           while (index < schemaFields.length) {
             val field = schemaFields(index)
-            rowArray(index) = TypeCast.castTo(tokens(index), field.dataType, field.nullable)
+            rowArray(index) = TypeCast.castTo(tokens(index), field.dataType, field.nullable,
+              treatEmptyValuesAsNulls)
             index = index + 1
           }
           Some(Row.fromSeq(rowArray))

src/main/scala/com/databricks/spark/csv/DefaultSource.scala

@@ -112,6 +112,14 @@ class DefaultSource
     } else {
       throw new Exception("Ignore white space flag can be true or false")
     }
+    val treatEmptyValuesAsNulls = parameters.getOrElse("treatEmptyValuesAsNulls", "false")
+    val treatEmptyValuesAsNullsFlag = if (treatEmptyValuesAsNulls == "false") {
+      false
+    } else if (treatEmptyValuesAsNulls == "true") {
+      true
+    } else {
+      throw new Exception("Treat empty values as null flag can be true or false")
+    }
 
     val charset = parameters.getOrElse("charset", TextFile.DEFAULT_CHARSET.name())
     // TODO validate charset?
@@ -137,6 +145,7 @@ class DefaultSource
       parserLib,
       ignoreLeadingWhiteSpaceFlag,
       ignoreTrailingWhiteSpaceFlag,
+      treatEmptyValuesAsNullsFlag,
       schema,
       inferSchemaFlag)(sqlContext)
   }

src/main/scala/com/databricks/spark/csv/package.scala

@@ -52,6 +52,7 @@ package object csv {
         parserLib = parserLib,
         ignoreLeadingWhiteSpace = ignoreLeadingWhiteSpace,
         ignoreTrailingWhiteSpace = ignoreTrailingWhiteSpace,
+        treatEmptyValuesAsNulls = false,
         inferCsvSchema = inferSchema)(sqlContext)
       sqlContext.baseRelationToDataFrame(csvRelation)
     }
@@ -76,6 +77,7 @@ package object csv {
         parserLib = parserLib,
         ignoreLeadingWhiteSpace = ignoreLeadingWhiteSpace,
         ignoreTrailingWhiteSpace = ignoreTrailingWhiteSpace,
+        treatEmptyValuesAsNulls = false,
         inferCsvSchema = inferSchema)(sqlContext)
       sqlContext.baseRelationToDataFrame(csvRelation)
     }
@@ -116,11 +118,13 @@ package object csv {
         case None => None
       }
 
+      val nullValue = parameters.getOrElse("nullValue", "null")
+
       val csvFormatBase = CSVFormat.DEFAULT
         .withDelimiter(delimiterChar)
         .withEscape(escapeChar)
         .withSkipHeaderRecord(false)
-        .withNullString("null")
+        .withNullString(nullValue)
 
       val csvFormat = quoteChar match {
         case Some(c) => csvFormatBase.withQuote(c)
@@ -139,7 +143,7 @@ package object csv {
           .withDelimiter(delimiterChar)
           .withEscape(escapeChar)
           .withSkipHeaderRecord(false)
-          .withNullString("null")
+          .withNullString(nullValue)
 
         val csvFormat = quoteChar match {
           case Some(c) => csvFormatBase.withQuote(c)

src/main/scala/com/databricks/spark/csv/util/TypeCast.scala

@@ -35,8 +35,12 @@ object TypeCast {
    * @param datum string value
    * @param castType SparkSQL type
    */
-  private[csv] def castTo(datum: String, castType: DataType, nullable: Boolean = true): Any = {
-    if (datum == "" && nullable && !castType.isInstanceOf[StringType]){
+  private[csv] def castTo(
+      datum: String,
+      castType: DataType,
+      nullable: Boolean = true,
+      treatEmptyValuesAsNulls: Boolean = false): Any = {
+    if (datum == "" && nullable && (!castType.isInstanceOf[StringType] || treatEmptyValuesAsNulls)){
       null
     } else {
       castType match {

src/test/scala/com/databricks/spark/csv/CsvSuite.scala

@@ -167,6 +167,30 @@ abstract class AbstractCsvSuite extends FunSuite with BeforeAndAfterAll {
     assert(exception.getMessage.contains("Malformed line in FAILFAST mode: 2015,Chevy,Volt"))
   }
 
+  test("DSL test roundtrip nulls") {
+    // Create temp directory
+    TestUtils.deleteRecursively(new File(tempEmptyDir))
+    new File(tempEmptyDir).mkdirs()
+    val copyFilePath = tempEmptyDir + "null-numbers.csv"
+    val agesSchema = StructType(List(StructField("name", StringType, true),
+                                     StructField("age", IntegerType, true)))
+
+    val agesRows = Seq(Row("alice", 35), Row("bob", null), Row(null, 24))
+    val agesRdd = sqlContext.sparkContext.parallelize(agesRows)
+    val agesDf = sqlContext.createDataFrame(agesRdd, agesSchema)
+
+    agesDf.saveAsCsvFile(copyFilePath, Map("header" -> "true", "nullValue" -> ""))
+
+    val agesCopy = new CsvParser()
+      .withSchema(agesSchema)
+      .withUseHeader(true)
+      .withTreatEmptyValuesAsNulls(true)
+      .withParserLib(parserLib)
+      .csvFile(sqlContext, copyFilePath)
+
+    assert(agesCopy.count == agesRows.size)
+    assert(agesCopy.collect.toSet == agesRows.toSet)
+  }
 
   test("DSL test with alternative delimiter and quote") {
     val results = new CsvParser()