[jira] [Resolved] (SPARK-21216) Streaming DataFrames fail to join with Hive tables

["Shixiong Zhu (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-21216?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Shixiong Zhu resolved SPARK-21216.
----------------------------------
       Resolution: Fixed
    Fix Version/s: 2.3.0

> Streaming DataFrames fail to join with Hive tables
> --------------------------------------------------
>
>                 Key: SPARK-21216
>                 URL: https://issues.apache.org/jira/browse/SPARK-21216
>             Project: Spark
>          Issue Type: Bug
>          Components: Structured Streaming
>    Affects Versions: 2.1.1
>            Reporter: Burak Yavuz
>            Assignee: Burak Yavuz
>             Fix For: 2.3.0
>
>
> The following code will throw a cryptic exception:
> {code}
> import org.apache.spark.sql.execution.streaming.MemoryStream
>     import testImplicits._
>     implicit val _sqlContext = spark.sqlContext
>     Seq((1, "one"), (2, "two"), (4, "four")).toDF("number", "word").createOrReplaceTempView("t1")
>     // Make a table and ensure it will be broadcast.
>     sql("""CREATE TABLE smallTable(word string, number int)
>           |ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe'
>           |STORED AS TEXTFILE
>         """.stripMargin)
>     sql(
>       """INSERT INTO smallTable
>         |SELECT word, number from t1
>       """.stripMargin)
>     val inputData = MemoryStream[Int]
>     val joined = inputData.toDS().toDF()
>       .join(spark.table("smallTable"), $"value" === $"number")
>     val sq = joined.writeStream
>       .format("memory")
>       .queryName("t2")
>       .start()
>     try {
>       inputData.addData(1, 2)
>       sq.processAllAvailable()
>     } finally {
>       sq.stop()
>     }
> {code}
> If someone creates a HiveSession, the planner in `IncrementalExecution` doesn't take into account the Hive scan strategies



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