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From "Michael Armbrust (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-17153) [Structured streams] readStream ignores partition columns
Date Mon, 26 Sep 2016 20:08:20 GMT

     [ https://issues.apache.org/jira/browse/SPARK-17153?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Michael Armbrust resolved SPARK-17153.
--------------------------------------
       Resolution: Fixed
    Fix Version/s: 2.1.0

Issue resolved by pull request 14803
[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
>             Fix For: 2.1.0
>
>
> 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.



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