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https://issues.apache.org/jira/browse/SPARK-20236?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16619236#comment-16619236
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Deepanker edited comment on SPARK-20236 at 9/19/18 3:03 PM:
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Hi Wenchen Fan,
Tested this even further and found out that it works for managed tables as
well. But not for tables created via saveAsTable API of spark which is a bit
surprising because saveAsTable also creates a managed table only.
As a test i did the following:
saveAsTable(x) [Stored as ORC ] [Partitioned by arbitrary column] [Doesn't work
for this]
Create Table like x [Using Beeline CLI] [Same properties as above table] [Works
for this]
Create external Table like x [Using Beeline CLI] [Same properties as above
table] [Works for this]
Is this the expected behaviour? I am using Spark 2.2 and Hive 1.1
If/When find time can you also confirm my hypothesis for the difference between
two Jira in my previous post?
was (Author: deepanker):
Hi Wenchen Fan,
Tested this even further and found out that it works for managed tables as
well. But not for tables created via saveAsTable API of spark.
As a test i did the following:
saveAsTable [Stored as ORC ] [Partitioned by arbitrary column] [Doesn't work
for this]
Create Table like x [Using Beeline CLI] [Same properties as above table] [Works
for this]
Create external Table like x [Using Beeline CLI] [Same properties as above
table] [Works for this]
Is this the expected behaviour? I am using Spark 2.2 and Hive 1.1
If/When find time can you also confirm my hypothesis for the difference between
two Jira in my previous post?
> 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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