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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/08/25 07:26:20 UTC
[jira] [Assigned] (SPARK-17153) [Structured streams] readStream
ignores partition columns
[ https://issues.apache.org/jira/browse/SPARK-17153?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-17153:
------------------------------------
Assignee: (was: Apache Spark)
> [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.
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