You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "DB Tsai (JIRA)" <ji...@apache.org> on 2018/09/25 18:28:02 UTC
[jira] [Updated] (SPARK-17636) Parquet filter push down doesn't
handle struct fields
[ https://issues.apache.org/jira/browse/SPARK-17636?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
DB Tsai updated SPARK-17636:
----------------------------
Fix Version/s: 2.5.0
> Parquet filter push down doesn't handle struct fields
> -----------------------------------------------------
>
> Key: SPARK-17636
> URL: https://issues.apache.org/jira/browse/SPARK-17636
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, SQL
> Affects Versions: 1.6.2, 1.6.3, 2.0.2
> Reporter: Mitesh
> Assignee: DB Tsai
> Priority: Minor
> Fix For: 2.5.0
>
>
> There's a *PushedFilters* for a simple numeric field, but not for a numeric field inside a struct. Not sure if this is a Spark limitation because of Parquet, or only a Spark limitation.
> {noformat}
> scala> hc.read.parquet("s3a://some/parquet/file").select("day_timestamp", "sale_id")
> res5: org.apache.spark.sql.DataFrame = [day_timestamp: struct<timestamp:bigint,timezone:string>, sale_id: bigint]
> scala> res5.filter("sale_id > 4").queryExecution.executedPlan
> res9: org.apache.spark.sql.execution.SparkPlan =
> Filter[23814] [args=(sale_id#86324L > 4)][outPart=UnknownPartitioning(0)][outOrder=List()]
> +- Scan ParquetRelation[day_timestamp#86302,sale_id#86324L] InputPaths: s3a://some/parquet/file, PushedFilters: [GreaterThan(sale_id,4)]
> scala> res5.filter("day_timestamp.timestamp > 4").queryExecution.executedPlan
> res10: org.apache.spark.sql.execution.SparkPlan =
> Filter[23815] [args=(day_timestamp#86302.timestamp > 4)][outPart=UnknownPartitioning(0)][outOrder=List()]
> +- Scan ParquetRelation[day_timestamp#86302,sale_id#86324L] InputPaths: s3a://some/parquet/file
> {noformat}
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org