[jira] [Created] (SPARK-19575) Reading from or writing to a hive serde table with a non pre-existing location should succeed

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

Song Jun created SPARK-19575:
--------------------------------

             Summary: Reading from or writing to a hive serde table with a non pre-existing location should succeed
                 Key: SPARK-19575
                 URL: https://issues.apache.org/jira/browse/SPARK-19575
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 2.2.0
            Reporter: Song Jun


currently when we select from a hive serde table which has a non pre-existing location will throw an exception:

```
Input path does not exist: file:/tmp/spark-37caa4e6-5a6a-4361-a905-06cc56afb274
org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: file:/tmp/spark-37caa4e6-5a6a-4361-a905-06cc56afb274
        at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:285)
        at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:228)
        at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:313)
        at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:194)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
        at scala.Option.getOrElse(Option.scala:121)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
        at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
        at scala.Option.getOrElse(Option.scala:121)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
        at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
        at scala.Option.getOrElse(Option.scala:121)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
        at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
        at scala.Option.getOrElse(Option.scala:121)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
        at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
        at scala.Option.getOrElse(Option.scala:121)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
        at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
        at scala.Option.getOrElse(Option.scala:121)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:2080)
        at org.apache.spark.rdd.RDD.count(RDD.scala:1157)
        at org.apache.spark.sql.QueryTest$.checkAnswer(QueryTest.scala:258)
```

this is a folllowup work from SPARK-19329 which has unify the action when we reading from or writing to a datasource table with a non pre-existing locaiton, so here we should also unify the hive serde tables



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