[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[SparkQA]

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https://github.com/apache/spark/pull/8597#issuecomment-138449666
  
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 * This patch **passes all tests**.
 * This patch merges cleanly.
 * This patch adds no public classes.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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https://github.com/apache/spark/pull/8597#issuecomment-138456626
  
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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[SparkQA]

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https://github.com/apache/spark/pull/8597#issuecomment-138456494
  
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 * This patch **passes all tests**.
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 * This patch adds no public classes.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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https://github.com/apache/spark/pull/8597#issuecomment-138451412
  
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 * This patch **passes all tests**.
 * This patch merges cleanly.
 * This patch adds no public classes.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[asfgit]

Github user asfgit closed the pull request at:

https://github.com/apache/spark/pull/8597


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[marmbrus]

Github user marmbrus commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-138700566
  
Thanks, merging to master.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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https://github.com/apache/spark/pull/8597#issuecomment-138606799
  
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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38934979
  
--- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JacksonParser.scala
 ---
@@ -81,9 +81,27 @@ private[sql] object JacksonParser {
   case (VALUE_NUMBER_INT | VALUE_NUMBER_FLOAT, FloatType) =>
 parser.getFloatValue
 
+  case (VALUE_STRING, FloatType) =>
+// Special case handling for NaN and Infinity.
+val value = parser.getText
+if (value.equals("NaN") || value.equals("Infinity") || 
value.equals("-Infinity")) {
+  value.toFloat
+} else {
+  sys.error(s"Cannot parse $value as FloatType.")
+}
+
   case (VALUE_NUMBER_INT | VALUE_NUMBER_FLOAT, DoubleType) =>
 parser.getDoubleValue
 
+  case (VALUE_STRING, DoubleType) =>
+// Special case handling for NaN and Infinity.
+val value = parser.getText
+if (value.equals("NaN") || value.equals("Infinity") || 
value.equals("-Infinity")) {
--- End diff --

Same as above.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38934997
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/ParquetHadoopFsRelationSuite.scala
 ---
@@ -32,6 +32,13 @@ class ParquetHadoopFsRelationSuite extends 
HadoopFsRelationTest {
 
   override val dataSourceName: String = "parquet"
 
+  // Parquet does not play well with NullType.
+  override protected def supportsDataType(dataType: DataType): Boolean = 
dataType match {
+case a: NullType => false
+case c: CalendarIntervalType => false
--- End diff --

Nit: In this case we can just write `case _: CalendarIntervalType =>`.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38934989
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/JsonHadoopFsRelationSuite.scala
 ---
@@ -28,6 +28,14 @@ import org.apache.spark.sql.types._
 class JsonHadoopFsRelationSuite extends HadoopFsRelationTest {
   override val dataSourceName: String = "json"
 
+  // JSON does not write data of NullType and does not play well with 
BinaryType.
+  override protected def supportsDataType(dataType: DataType): Boolean = 
dataType match {
+case a: NullType => false
+case b: BinaryType => false
--- End diff --

But we do handle `BinaryType` [in `JacksonGenerator`] [1]. Does this mean 
we can save a DataFrame containing `BinaryType` field(s) to JSON files via 
`df.toJSON.saveAsTextFile(...)`, but can't read it back with `JSONRelation`?

[1]: 
https://github.com/apache/spark/pull/8597/files#diff-0f04c36e499d4dcf6931fbd62b3aa012R101


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[yhuai]

Github user yhuai commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38941415
  
--- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JacksonParser.scala
 ---
@@ -81,9 +81,27 @@ private[sql] object JacksonParser {
   case (VALUE_NUMBER_INT | VALUE_NUMBER_FLOAT, FloatType) =>
 parser.getFloatValue
 
+  case (VALUE_STRING, FloatType) =>
+// Special case handling for NaN and Infinity.
+val value = parser.getText
+if (value.equals("NaN") || value.equals("Infinity") || 
value.equals("-Infinity")) {
--- End diff --

oh, originally I tried scala and it only recognizes these three forms. Just 
tried Python and it can recognize `nan`. I will make it case insensitive.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[AmplabJenkins]

Github user AmplabJenkins commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-138606827
  
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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[SparkQA]

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https://github.com/apache/spark/pull/8597#issuecomment-138609207
  
  [Test build #42136 has 
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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-138591417
  
A few minor issues. Otherwise LGTM.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38934988
  
--- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JacksonParser.scala
 ---
@@ -81,9 +81,27 @@ private[sql] object JacksonParser {
   case (VALUE_NUMBER_INT | VALUE_NUMBER_FLOAT, FloatType) =>
 parser.getFloatValue
 
+  case (VALUE_STRING, FloatType) =>
+// Special case handling for NaN and Infinity.
+val value = parser.getText
+if (value.equals("NaN") || value.equals("Infinity") || 
value.equals("-Infinity")) {
--- End diff --

Not sure about this, but should we make these comparisons case insensitive?


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[yhuai]

Github user yhuai commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38940788
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/hadoopFsRelationSuites.scala
 ---
@@ -98,6 +100,80 @@ abstract class HadoopFsRelationTest extends QueryTest 
with SQLTestUtils with Tes
 }
   }
 
+  test("test all data types") {
+withTempPath { file =>
+  // Create the schema.
+  val struct =
+StructType(
+  StructField("f1", FloatType, true) ::
+StructField("f2", ArrayType(BooleanType), true) :: Nil)
+  // TODO: add CalendarIntervalType to here once we can save it out.
+  val dataTypes =
+Seq(
+  StringType, BinaryType, NullType, BooleanType,
+  ByteType, ShortType, IntegerType, LongType,
+  FloatType, DoubleType, DecimalType(25, 5), DecimalType(6, 5),
+  DateType, TimestampType,
+  ArrayType(IntegerType), MapType(StringType, LongType), struct,
+  new MyDenseVectorUDT())
+  val fields = dataTypes.zipWithIndex.map { case (dataType, index) =>
+StructField(s"col$index", dataType, nullable = true)
+  }
+  val schema = StructType(fields)
+
+  // Generate data at the driver side. We need to materialize the data 
first and then
+  // create RDD.
+  val maybeDataGenerator =
+RandomDataGenerator.forType(
+  dataType = schema,
+  nullable = true,
+  seed = Some(System.nanoTime()))
+  val dataGenerator =
+maybeDataGenerator
+  .getOrElse(fail(s"Failed to create data generator for schema 
$schema"))
+  val data = (1 to 10).map { i =>
+dataGenerator.apply() match {
+  case row: Row => row
+  case _ => Row.fromSeq(Seq.fill(schema.length)(null))
--- End diff --

I set the entire struct type to be nullable at line 129. So, generator will 
return null values at here. We can make it explicit at here.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[SparkQA]

Github user SparkQA commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-138647445
  
  [Test build #42136 has 
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 for   PR 8597 at commit 
[`bda8c77`](https://github.com/apache/spark/commit/bda8c779dc24fd1919f87e77b4bb8283c44216ea).
 * This patch **passes all tests**.
 * This patch merges cleanly.
 * This patch adds no public classes.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[cloud-fan]

Github user cloud-fan commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-138437490
  
LGTM


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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https://github.com/apache/spark/pull/8597#issuecomment-138435910
  
  [Test build #42119 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/42119/consoleFull)
 for   PR 8597 at commit 
[`7df91d6`](https://github.com/apache/spark/commit/7df91d6585fd3845b357c4b58bfe099a74097c47).


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[AmplabJenkins]

Github user AmplabJenkins commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-138435444
  
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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[AmplabJenkins]

Github user AmplabJenkins commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-138435437
  
 Merged build triggered.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[yhuai]

Github user yhuai commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38890662
  
--- Diff: 
sql/catalyst/src/test/scala/org/apache/spark/sql/RandomDataGenerator.scala ---
@@ -159,6 +177,27 @@ object RandomDataGenerator {
   None
 }
   }
+  case udt: UserDefinedType[_] => {
+val maybeSqlTypeGenerator = forType(udt.sqlType, nullable, seed)
+// Because random data generator at here returns scala value, we 
need to
+// convert it to catalyst value to call udt's deserialize.
+val toCatalystType = 
CatalystTypeConverters.createToCatalystConverter(udt.sqlType)
+
+if (maybeSqlTypeGenerator.isDefined) {
+  val sqlTypeGenerator = maybeSqlTypeGenerator.get
+  val generator = () => {
+val generatedScalaValue = sqlTypeGenerator.apply()
+if (generatedScalaValue == null) {
+  null
+} else {
+  udt.deserialize(toCatalystType(generatedScalaValue))
+}
+  }
+  Some(generator)
+} else {
+  None
+}
+  }
--- End diff --

@JoshRosen Can you take a look at my change to `RandomDataGenerator`?


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[cloud-fan]

Github user cloud-fan commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38891183
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/hadoopFsRelationSuites.scala
 ---
@@ -98,6 +100,80 @@ abstract class HadoopFsRelationTest extends QueryTest 
with SQLTestUtils with Tes
 }
   }
 
+  test("test all data types") {
+withTempPath { file =>
+  // Create the schema.
+  val struct =
+StructType(
+  StructField("f1", FloatType, true) ::
+StructField("f2", ArrayType(BooleanType), true) :: Nil)
+  // TODO: add CalendarIntervalType to here once we can save it out.
+  val dataTypes =
+Seq(
+  StringType, BinaryType, NullType, BooleanType,
+  ByteType, ShortType, IntegerType, LongType,
+  FloatType, DoubleType, DecimalType(25, 5), DecimalType(6, 5),
+  DateType, TimestampType,
+  ArrayType(IntegerType), MapType(StringType, LongType), struct,
+  new MyDenseVectorUDT())
+  val fields = dataTypes.zipWithIndex.map { case (dataType, index) =>
+StructField(s"col$index", dataType, nullable = true)
+  }
+  val schema = StructType(fields)
+
+  // Generate data at the driver side. We need to materialize the data 
first and then
+  // create RDD.
+  val maybeDataGenerator =
+RandomDataGenerator.forType(
+  dataType = schema,
+  nullable = true,
+  seed = Some(System.nanoTime()))
+  val dataGenerator =
+maybeDataGenerator
+  .getOrElse(fail(s"Failed to create data generator for schema 
$schema"))
+  val data = (1 to 10).map { i =>
+dataGenerator.apply() match {
+  case row: Row => row
+  case _ => Row.fromSeq(Seq.fill(schema.length)(null))
--- End diff --

Are we handling `null` here? If it is, I think we should make it more 
explicit using `case null`.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[SparkQA]

Github user SparkQA commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-138434672
  
  [Test build #1725 has 
started](https://amplab.cs.berkeley.edu/jenkins/job/NewSparkPullRequestBuilder/1725/consoleFull)
 for   PR 8597 at commit 
[`ddc0f0d`](https://github.com/apache/spark/commit/ddc0f0d82201ad8498904bc6c17b88a1287f6dbb).


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38742310
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/SimpleTextRelation.scala 
---
@@ -112,11 +114,14 @@ class SimpleTextRelation(
 val fields = dataSchema.map(_.dataType)
 
 sparkContext.textFile(inputStatuses.map(_.getPath).mkString(",")).map 
{ record =>
-  Row(record.split(",").zip(fields).map { case (value, dataType) =>
+  Row(record.split(",", -1).zip(fields).map { case (v, dataType) =>
+val value = if (v == "") null else v
 // `Cast`ed values are always of Catalyst types (i.e. UTF8String 
instead of String, etc.)
 val catalystValue = Cast(Literal(value), dataType).eval()
 // Here we're converting Catalyst values to Scala values to test 
`needsConversion`
-CatalystTypeConverters.convertToScala(catalystValue, dataType)
+val scalaV = CatalystTypeConverters.convertToScala(catalystValue, 
dataType)
+
+scalaV
--- End diff --

Nit: Remove `scalaV`?


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38742485
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/hadoopFsRelationSuites.scala
 ---
@@ -100,6 +104,87 @@ abstract class HadoopFsRelationTest extends QueryTest 
with SQLTestUtils {
 }
   }
 
+  test("test all data types") {
+withTempDir { file =>
+  file.delete()
+
+  // Create the schema.
+  val struct =
+StructType(
+  StructField("f1", FloatType, true) ::
+StructField("f2", ArrayType(BooleanType), true) :: Nil)
+  val dataTypes =
+Seq(
+  StringType, BinaryType, NullType, BooleanType,
+  ByteType, ShortType, IntegerType, LongType,
+  FloatType, DoubleType, DecimalType(25, 5), DecimalType(6, 5),
+  DateType, TimestampType,
+  ArrayType(IntegerType), MapType(StringType, LongType), struct,
+  new MyDenseVectorUDT())
--- End diff --

`CalendarIntervalType` is not covered here. Is it intentional?


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38742967
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/hadoopFsRelationSuites.scala
 ---
@@ -100,6 +104,87 @@ abstract class HadoopFsRelationTest extends QueryTest 
with SQLTestUtils {
 }
   }
 
+  test("test all data types") {
+withTempDir { file =>
+  file.delete()
+
+  // Create the schema.
+  val struct =
+StructType(
+  StructField("f1", FloatType, true) ::
+StructField("f2", ArrayType(BooleanType), true) :: Nil)
+  val dataTypes =
+Seq(
+  StringType, BinaryType, NullType, BooleanType,
+  ByteType, ShortType, IntegerType, LongType,
+  FloatType, DoubleType, DecimalType(25, 5), DecimalType(6, 5),
+  DateType, TimestampType,
+  ArrayType(IntegerType), MapType(StringType, LongType), struct,
+  new MyDenseVectorUDT())
+  val fields = dataTypes.zipWithIndex.map { case (dataType, index) =>
+StructField(s"col$index", dataType, true)
+  }
+  val schema = StructType(fields)
+
+  // Create a RDD for the schema
+  val rdd =
+sqlContext.sparkContext.parallelize((1 to 100), 10).flatMap { i =>
+  val row1 = Row(
+s"str${i}: test save.",
+s"binary${i}: test save.".getBytes("UTF-8"),
+null,
+i % 2 == 0,
+i.toByte,
+i.toShort,
+i,
+Long.MaxValue - i.toLong,
+(i + 0.25).toFloat,
+(i + 0.75),
+BigDecimal(Long.MaxValue.toString + ".12345"),
+new java.math.BigDecimal(s"${i % 9 + 1}" + ".23456"),
+new Date(i),
+new Timestamp(i),
+(1 to i).toSeq,
+(0 to i).map(j => s"map_key_$j" -> (Long.MaxValue - j)).toMap,
+Row((i - 0.25).toFloat, Seq(true, false, null)),
+new MyDenseVector(Array(1.1, 2.1, 3.1)))
+  val row2 = Row.fromSeq(Seq.fill(dataTypes.length)(null))
+  row1 :: row2 :: Nil
+}
+  val df = sqlContext.createDataFrame(rdd, schema)
+
+  // All columns that have supported data types of this source.
+  val supportedColumns = schema.fields.filter { field =>
+supportsDataType(field.dataType)
+  }.map { field =>
+field.name
+  }
--- End diff --

Nit: Can be simplified a little bit:

```scala
val supportedColumns = schema.collect {
  case StructField(name, dataType) if supportsDataType(dataType) => name
}
```


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38742692
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/hadoopFsRelationSuites.scala
 ---
@@ -100,6 +104,87 @@ abstract class HadoopFsRelationTest extends QueryTest 
with SQLTestUtils {
 }
   }
 
+  test("test all data types") {
+withTempDir { file =>
+  file.delete()
+
+  // Create the schema.
+  val struct =
+StructType(
+  StructField("f1", FloatType, true) ::
+StructField("f2", ArrayType(BooleanType), true) :: Nil)
+  val dataTypes =
+Seq(
+  StringType, BinaryType, NullType, BooleanType,
+  ByteType, ShortType, IntegerType, LongType,
+  FloatType, DoubleType, DecimalType(25, 5), DecimalType(6, 5),
+  DateType, TimestampType,
+  ArrayType(IntegerType), MapType(StringType, LongType), struct,
+  new MyDenseVectorUDT())
+  val fields = dataTypes.zipWithIndex.map { case (dataType, index) =>
+StructField(s"col$index", dataType, true)
+  }
+  val schema = StructType(fields)
+
+  // Create a RDD for the schema
+  val rdd =
+sqlContext.sparkContext.parallelize((1 to 100), 10).flatMap { i =>
+  val row1 = Row(
+s"str${i}: test save.",
+s"binary${i}: test save.".getBytes("UTF-8"),
+null,
+i % 2 == 0,
+i.toByte,
+i.toShort,
+i,
+Long.MaxValue - i.toLong,
+(i + 0.25).toFloat,
+(i + 0.75),
--- End diff --

Nit: `075D` or add the `toDouble` call to make it explicit.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38742782
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/hadoopFsRelationSuites.scala
 ---
@@ -100,6 +104,87 @@ abstract class HadoopFsRelationTest extends QueryTest 
with SQLTestUtils {
 }
   }
 
+  test("test all data types") {
+withTempDir { file =>
+  file.delete()
+
+  // Create the schema.
+  val struct =
+StructType(
+  StructField("f1", FloatType, true) ::
+StructField("f2", ArrayType(BooleanType), true) :: Nil)
+  val dataTypes =
+Seq(
+  StringType, BinaryType, NullType, BooleanType,
+  ByteType, ShortType, IntegerType, LongType,
+  FloatType, DoubleType, DecimalType(25, 5), DecimalType(6, 5),
+  DateType, TimestampType,
+  ArrayType(IntegerType), MapType(StringType, LongType), struct,
+  new MyDenseVectorUDT())
+  val fields = dataTypes.zipWithIndex.map { case (dataType, index) =>
+StructField(s"col$index", dataType, true)
+  }
+  val schema = StructType(fields)
+
+  // Create a RDD for the schema
+  val rdd =
+sqlContext.sparkContext.parallelize((1 to 100), 10).flatMap { i =>
+  val row1 = Row(
+s"str${i}: test save.",
+s"binary${i}: test save.".getBytes("UTF-8"),
+null,
+i % 2 == 0,
+i.toByte,
+i.toShort,
+i,
+Long.MaxValue - i.toLong,
+(i + 0.25).toFloat,
+(i + 0.75),
+BigDecimal(Long.MaxValue.toString + ".12345"),
+new java.math.BigDecimal(s"${i % 9 + 1}" + ".23456"),
+new Date(i),
+new Timestamp(i),
+(1 to i).toSeq,
+(0 to i).map(j => s"map_key_$j" -> (Long.MaxValue - j)).toMap,
+Row((i - 0.25).toFloat, Seq(true, false, null)),
+new MyDenseVector(Array(1.1, 2.1, 3.1)))
+  val row2 = Row.fromSeq(Seq.fill(dataTypes.length)(null))
+  row1 :: row2 :: Nil
+}
--- End diff --

Seems that `RandomDataGenerator` helps here?


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38742367
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/hadoopFsRelationSuites.scala
 ---
@@ -100,6 +104,87 @@ abstract class HadoopFsRelationTest extends QueryTest 
with SQLTestUtils {
 }
   }
 
+  test("test all data types") {
+withTempDir { file =>
+  file.delete()
--- End diff --

You can use `withTempPath` here.  It provides a temporary path without 
creating the directory, so that you don't need the `delete()` call.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[liancheng]

Github user liancheng commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-137714184
  
Generally looks good except for a few minor issues.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[yhuai]

Github user yhuai commented on a diff in the pull request:

https://github.com/apache/spark/pull/8597#discussion_r38769233
  
--- Diff: 
sql/hive/src/test/scala/org/apache/spark/sql/sources/hadoopFsRelationSuites.scala
 ---
@@ -100,6 +104,87 @@ abstract class HadoopFsRelationTest extends QueryTest 
with SQLTestUtils {
 }
   }
 
+  test("test all data types") {
+withTempDir { file =>
+  file.delete()
+
+  // Create the schema.
+  val struct =
+StructType(
+  StructField("f1", FloatType, true) ::
+StructField("f2", ArrayType(BooleanType), true) :: Nil)
+  val dataTypes =
+Seq(
+  StringType, BinaryType, NullType, BooleanType,
+  ByteType, ShortType, IntegerType, LongType,
+  FloatType, DoubleType, DecimalType(25, 5), DecimalType(6, 5),
+  DateType, TimestampType,
+  ArrayType(IntegerType), MapType(StringType, LongType), struct,
+  new MyDenseVectorUDT())
--- End diff --

I do not think we can save it to any data source right now.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[AmplabJenkins]

Github user AmplabJenkins commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-137847555
  
 Merged build triggered.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[SparkQA]

Github user SparkQA commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-137848585
  
  [Test build #42018 has 
finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/42018/console)
 for   PR 8597 at commit 
[`5436236`](https://github.com/apache/spark/commit/54362366042f07e04c030923d308976c0f49eb42).
 * This patch **fails Scala style tests**.
 * This patch merges cleanly.
 * This patch adds no public classes.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[AmplabJenkins]

Github user AmplabJenkins commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-137848592
  
Test FAILed.
Refer to this link for build results (access rights to CI server needed): 
https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/42018/
Test FAILed.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[AmplabJenkins]

Github user AmplabJenkins commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-137848590
  
Merged build finished. Test FAILed.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

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  * `class DCT(JavaTransformer, HasInputCol, HasOutputCol):`
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 * This patch **passes all tests**.
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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[AmplabJenkins]

Github user AmplabJenkins commented on the pull request:

https://github.com/apache/spark/pull/8597#issuecomment-137636846
  
Merged build started.


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[GitHub] spark pull request: [SPARK-10441][SQL] Save data correctly to json...

[yhuai]

GitHub user yhuai opened a pull request:

https://github.com/apache/spark/pull/8597

[SPARK-10441][SQL] Save data correctly to json.

https://issues.apache.org/jira/browse/SPARK-10441

You can merge this pull request into a Git repository by running:

$ git pull https://github.com/yhuai/spark timestampJson

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/spark/pull/8597.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

This closes #8597


commit bd9898ad7e4da1050efb6691737164e05f70a14c
Author: Yin Huai 
Date:   2015-09-04T03:08:50Z

Save data correctly to json.




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