[jira] [Comment Edited] (SPARK-20236) Overwrite a partitioned data source table should only overwrite related partitions

["Anand Kannachikandy (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-20236?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17491265#comment-17491265 ] 

Anand Kannachikandy edited comment on SPARK-20236 at 2/12/22, 5:48 AM:
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[~cloud_fan]  Have anyone tested this in HDP Clusters, I'm getting the same issue  as [~doriwal] , its works well in my local machine, but when I run this HDP cluster, the folder doesn't have any partitions created at all, all I can see is a _SUCCESS file created in the path; and If set this to static the partition folders are getting created.

 

I'm running my code on spark 2.3.0 version and hip version 2.6.5

 

my sample code looks like below 

 
{code:java}
 dF
  .write
  .mode("overwrite")
  .partitionBy("Year","Month")
  .parquet(<Parquet-Path>) {code}
 

Appreciate your inputs


was (Author: JIRAUSER285114):
[~cloud_fan]  Have anyone tested this in HDP Clusters, I'm getting the same issue  as [~doriwal] , its works well in my local machine, but when I run this HDP cluster, the folder doesn't have any partitions created at all, all I can see is a _SUCCESS file created in the path; and If set this to static the partition folders are getting created.

 

I'm running my code on spark 2.3.0 version and hip version 2.6.5

 

my sample code looks like below 

 
{code:java}
// dF
  .write
  .mode("overwrite")
  .partitionBy("Year","Month")
  .parquet(<Parquet-Path>) {code}
 

Appreciate your inputs

> Overwrite a partitioned data source table should only overwrite related partitions
> ----------------------------------------------------------------------------------
>
>                 Key: SPARK-20236
>                 URL: https://issues.apache.org/jira/browse/SPARK-20236
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.2.0
>            Reporter: Wenchen Fan
>            Assignee: Wenchen Fan
>            Priority: Major
>              Labels: releasenotes
>             Fix For: 2.3.0
>
>
> When we overwrite a partitioned data source table, currently Spark will truncate the entire table to write new data, or truncate a bunch of partitions according to the given static partitions.
> For example, {{INSERT OVERWRITE tbl ...}} will truncate the entire table, {{INSERT OVERWRITE tbl PARTITION (a=1, b)}} will truncate all the partitions that starts with {{a=1}}.
> This behavior is kind of reasonable as we can know which partitions will be overwritten before runtime. However, hive has a different behavior that it only overwrites related partitions, e.g. {{INSERT OVERWRITE tbl SELECT 1,2,3}} will only overwrite partition {{a=2, b=3}}, assuming {{tbl}} has only one data column and is partitioned by {{a}} and {{b}}.
> It seems better if we can follow hive's behavior.



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