[jira] [Commented] (SPARK-19742) When using SparkSession to write a dataset to Hive the schema is ignored

["Song Jun (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-19742?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15885399#comment-15885399 ] 

Song Jun commented on SPARK-19742:
----------------------------------

this is expected, see the comment.

{code}
/**
   * Inserts the content of the `DataFrame` to the specified table. It requires that
   * the schema of the `DataFrame` is the same as the schema of the table.
   *
   * @note Unlike `saveAsTable`, `insertInto` ignores the column names and just uses position-based
   * resolution. For example:
   *
   * {{{
   *    scala> Seq((1, 2)).toDF("i", "j").write.mode("overwrite").saveAsTable("t1")
   *    scala> Seq((3, 4)).toDF("j", "i").write.insertInto("t1")
   *    scala> Seq((5, 6)).toDF("a", "b").write.insertInto("t1")
   *    scala> sql("select * from t1").show
   *    +---+---+
   *    |  i|  j|
   *    +---+---+
   *    |  5|  6|
   *    |  3|  4|
   *    |  1|  2|
   *    +---+---+
   * }}}
   *
   * Because it inserts data to an existing table, format or options will be ignored.
   *
   * @since 1.4.0
   */
  def insertInto(tableName: String): Unit = {
    insertInto(df.sparkSession.sessionState.sqlParser.parseTableIdentifier(tableName))
  }
{code}

> When using SparkSession to write a dataset to Hive the schema is ignored
> ------------------------------------------------------------------------
>
>                 Key: SPARK-19742
>                 URL: https://issues.apache.org/jira/browse/SPARK-19742
>             Project: Spark
>          Issue Type: Bug
>          Components: Java API
>    Affects Versions: 2.0.1
>         Environment: Running on Ubuntu with HDP 2.4.
>            Reporter: Navin Goel
>
> I am saving a Dataset that is created form reading a json and some selects and filters into a hive table. The dataset.write().insertInto function does not look at schema when writing to the table but instead writes in order to the hive table.
> The schemas for both the tables are same.
> schema printed from spark of the dataset being written:
> StructType(StructField(countrycode,StringType,true), StructField(systemflag,StringType,true), StructField(classcode,StringType,true), StructField(classname,StringType,true), StructField(rangestart,StringType,true), StructField(rangeend,StringType,true), StructField(tablename,StringType,true), StructField(last_updated_date,TimestampType,true))
> Schema of the dataset after loading the same table from Hive:
> StructType(StructField(systemflag,StringType,true), StructField(RangeEnd,StringType,true), StructField(classcode,StringType,true), StructField(classname,StringType,true), StructField(last_updated_date,TimestampType,true), StructField(countrycode,StringType,true), StructField(rangestart,StringType,true), StructField(tablename,StringType,true))



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