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https://issues.apache.org/jira/browse/HIVE-2907?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Phabricator updated HIVE-2907:
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Attachment: HIVE-2907.D2505.7.patch
mousom updated the revision "HIVE-2907 [jira] Hive error when dropping a table
with large number of partitions".
Reviewers: JIRA, kevinwilfong
REVISION DETAIL
https://reviews.facebook.net/D2505
AFFECTED FILES
conf/hive-default.xml.template
metastore/src/test/org/apache/hadoop/hive/metastore/TestHiveMetaStore.java
metastore/src/java/org/apache/hadoop/hive/metastore/HiveAlterHandler.java
metastore/src/java/org/apache/hadoop/hive/metastore/ObjectStore.java
common/src/java/org/apache/hadoop/hive/conf/HiveConf.java
ql/src/test/results/clientnegative/drop_table_failure3.q.out
ql/src/test/results/clientpositive/drop_table2.q.out
ql/src/test/queries/clientnegative/drop_table_failure3.q
ql/src/test/queries/clientpositive/drop_table2.q
ql/src/java/org/apache/hadoop/hive/ql/exec/DDLTask.java
> Hive error when dropping a table with large number of partitions
> ----------------------------------------------------------------
>
> Key: HIVE-2907
> URL: https://issues.apache.org/jira/browse/HIVE-2907
> Project: Hive
> Issue Type: Bug
> Components: Metastore
> Affects Versions: 0.9.0
> Environment: General. Hive Metastore bug.
> Reporter: Mousom Dhar Gupta
> Assignee: Mousom Dhar Gupta
> Priority: Minor
> Fix For: 0.9.0
>
> Attachments: HIVE-2907.1.patch.txt, HIVE-2907.2.patch.txt,
> HIVE-2907.3.patch.txt, HIVE-2907.D2505.1.patch, HIVE-2907.D2505.2.patch,
> HIVE-2907.D2505.3.patch, HIVE-2907.D2505.4.patch, HIVE-2907.D2505.5.patch,
> HIVE-2907.D2505.6.patch, HIVE-2907.D2505.7.patch
>
> Original Estimate: 10h
> Remaining Estimate: 10h
>
> Running into an "Out Of Memory" error when trying to drop a table with 128K
> partitions.
> The methods dropTable in
> metastore/src/java/org/apache/hadoop/hive/metastore/ObjectStore.java
> and dropTable in ql/src/java/org/apache/hadoop/hive/ql/exec/DDLTask.java
> encounter out of memory errors
> when dropping tables with lots of partitions because they try to load the
> metadata for every partition into memory.
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