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https://issues.apache.org/jira/browse/SPARK-17573?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Jianfei Wang updated SPARK-17573:
---------------------------------
    Description: 
I find that there are many places in spark that we don't close the input/output 
Streams manually, if so ,there will  potential "OOM" errors and some other 
errors happens
such as:
{code}
 private[sql] def bytesToRow(bytes: Array[Byte], schema: StructType): Row = {
    val bis = new ByteArrayInputStream(bytes)
    val dis = new DataInputStream(bis)
    val num = SerDe.readInt(dis)
    Row.fromSeq((0 until num).map { i =>
      doConversion(SerDe.readObject(dis), schema.fields(i).dataType)
    })
  }

  private[sql] def rowToRBytes(row: Row): Array[Byte] = {
    val bos = new ByteArrayOutputStream()
    val dos = new DataOutputStream(bos)

    val cols = (0 until row.length).map(row(_).asInstanceOf[Object]).toArray
    SerDe.writeObject(dos, cols)
    bos.toByteArray()
  }
 override def deserialize(storageFormat: Array[Byte]): MaxValue = {
      val in = new ByteArrayInputStream(storageFormat)
      val stream = new DataInputStream(in)
      val isValueSet = stream.readBoolean()
      val value = stream.readInt()
      new MaxValue(value, isValueSet)
    }
{code} 

  was:
I find that there are many places in spark that we don't close the input/output 
Streams manually, if so ,there will  potential "OOM" errors and some other 
errors
such as:
{code}
 private[sql] def bytesToRow(bytes: Array[Byte], schema: StructType): Row = {
    val bis = new ByteArrayInputStream(bytes)
    val dis = new DataInputStream(bis)
    val num = SerDe.readInt(dis)
    Row.fromSeq((0 until num).map { i =>
      doConversion(SerDe.readObject(dis), schema.fields(i).dataType)
    })
  }

  private[sql] def rowToRBytes(row: Row): Array[Byte] = {
    val bos = new ByteArrayOutputStream()
    val dos = new DataOutputStream(bos)

    val cols = (0 until row.length).map(row(_).asInstanceOf[Object]).toArray
    SerDe.writeObject(dos, cols)
    bos.toByteArray()
  }
 override def deserialize(storageFormat: Array[Byte]): MaxValue = {
      val in = new ByteArrayInputStream(storageFormat)
      val stream = new DataInputStream(in)
      val isValueSet = stream.readBoolean()
      val value = stream.readInt()
      new MaxValue(value, isValueSet)
    }
{code} 


> Why don't we close the input/output Streams
> -------------------------------------------
>
>                 Key: SPARK-17573
>                 URL: https://issues.apache.org/jira/browse/SPARK-17573
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.0.0
>            Reporter: Jianfei Wang
>              Labels: performance
>
> I find that there are many places in spark that we don't close the 
> input/output Streams manually, if so ,there will  potential "OOM" errors and 
> some other errors happens
> such as:
> {code}
>  private[sql] def bytesToRow(bytes: Array[Byte], schema: StructType): Row = {
>     val bis = new ByteArrayInputStream(bytes)
>     val dis = new DataInputStream(bis)
>     val num = SerDe.readInt(dis)
>     Row.fromSeq((0 until num).map { i =>
>       doConversion(SerDe.readObject(dis), schema.fields(i).dataType)
>     })
>   }
>   private[sql] def rowToRBytes(row: Row): Array[Byte] = {
>     val bos = new ByteArrayOutputStream()
>     val dos = new DataOutputStream(bos)
>     val cols = (0 until row.length).map(row(_).asInstanceOf[Object]).toArray
>     SerDe.writeObject(dos, cols)
>     bos.toByteArray()
>   }
>  override def deserialize(storageFormat: Array[Byte]): MaxValue = {
>       val in = new ByteArrayInputStream(storageFormat)
>       val stream = new DataInputStream(in)
>       val isValueSet = stream.readBoolean()
>       val value = stream.readInt()
>       new MaxValue(value, isValueSet)
>     }
> {code} 



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