diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JacksonGenerator.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JacksonGenerator.scala index 99ac7730bd1c97d5a7c542cfe76b414996fa730e..330ba907b2ef9274ab9c2de7c273076f26e8fca3 100644 --- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JacksonGenerator.scala +++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JacksonGenerator.scala @@ -95,7 +95,7 @@ private[sql] object JacksonGenerator { case (FloatType, v: Float) => gen.writeNumber(v) case (DoubleType, v: Double) => gen.writeNumber(v) case (LongType, v: Long) => gen.writeNumber(v) - case (DecimalType(), v: java.math.BigDecimal) => gen.writeNumber(v) + case (DecimalType(), v: Decimal) => gen.writeNumber(v.toJavaBigDecimal) case (ByteType, v: Byte) => gen.writeNumber(v.toInt) case (BinaryType, v: Array[Byte]) => gen.writeBinary(v) case (BooleanType, v: Boolean) => gen.writeBoolean(v) diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/sources/JsonHadoopFsRelationSuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/sources/JsonHadoopFsRelationSuite.scala index ed6d512ab36fe63f414b0f6ab243dca9ce20fdef..8ca3a17085194f6f81d3372f61f78769c36401f3 100644 --- a/sql/hive/src/test/scala/org/apache/spark/sql/sources/JsonHadoopFsRelationSuite.scala +++ b/sql/hive/src/test/scala/org/apache/spark/sql/sources/JsonHadoopFsRelationSuite.scala @@ -17,6 +17,8 @@ package org.apache.spark.sql.sources +import java.math.BigDecimal + import org.apache.hadoop.fs.Path import org.apache.spark.deploy.SparkHadoopUtil @@ -75,4 +77,29 @@ class JsonHadoopFsRelationSuite extends HadoopFsRelationTest { ) } } + + test("SPARK-10196: save decimal type to JSON") { + withTempDir { file => + file.delete() + + val schema = + new StructType() + .add("decimal", DecimalType(7, 2)) + + val data = + Row(new BigDecimal("10.02")) :: + Row(new BigDecimal("20000.99")) :: + Row(new BigDecimal("10000")) :: Nil + val df = createDataFrame(sparkContext.parallelize(data), schema) + + // Write the data out. + df.write.format(dataSourceName).save(file.getCanonicalPath) + + // Read it back and check the result. + checkAnswer( + read.format(dataSourceName).schema(schema).load(file.getCanonicalPath), + df + ) + } + } }