You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/08/25 07:26:20 UTC

[jira] [Commented] (SPARK-17153) [Structured streams] readStream ignores partition columns

    [ https://issues.apache.org/jira/browse/SPARK-17153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15436410#comment-15436410 ] 

Apache Spark commented on SPARK-17153:
--------------------------------------

User 'viirya' has created a pull request for this issue:
https://github.com/apache/spark/pull/14803

> [Structured streams] readStream ignores partition columns
> ---------------------------------------------------------
>
>                 Key: SPARK-17153
>                 URL: https://issues.apache.org/jira/browse/SPARK-17153
>             Project: Spark
>          Issue Type: Bug
>          Components: Streaming
>    Affects Versions: 2.0.0
>            Reporter: Dmitri Carpov
>
> When parquet files are persisted using partitions, spark's `readStream` returns data with all `null`s for the partitioned columns.
> For example:
> {noformat}
> case class A(id: Int, value: Int)
> val data = spark.createDataset(Seq(
>   A(1, 1), 
>   A(2, 2), 
>   A(2, 3))
> )
> val url = "/mnt/databricks/test"
> data.write.partitionBy("id").parquet(url)
> {noformat}
> when data is read as stream:
> {noformat}
> spark.readStream.schema(spark.read.load(url).schema).parquet(url)
> {noformat}
> it reads:
> {noformat}
> id, value
> null, 1
> null, 2
> null, 3
> {noformat}
> A possible reason is `readStream` reads parquet files directly but when those are stored the columns they are partitioned by are excluded from the file itself. In the given example the parquet files contain `value` information only since `id` is partition.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org