[jira] [Commented] (SPARK-19713) saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-19713?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15885717#comment-15885717
]
Hyukjin Kwon commented on SPARK-19713:
--
Could you update the JIRA title to be more meaningful and provide both compared
versions?
> saveAsTable
> ---
>
> Key: SPARK-19713
> URL: https://issues.apache.org/jira/browse/SPARK-19713
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Balaram R Gadiraju
>
> Hi,
> I just observed that when we use dataframe.saveAsTable("table") -- In
> oldversions
> and dataframe.write.saveAsTable("table") -- in the newer versions
> When using the method “df3.saveAsTable("brokentable")” in
> scale code. This creates a folder in hdfs and doesn’t update hive-metastore
> that it plans to create the table. So if anything goes wrong in between the
> folder still exists and hive is not aware of the folder creation. This will
> block the users from creating the table “brokentable” as the folder already
> exists, we can remove the folder using “hadoop fs –rmr
> /data/hive/databases/testdb.db/brokentable”. So below is the workaround
> which will enable to you to continue the development work.
> Current Code:
> val df3 = sqlContext.sql("select * fromtesttable")
> df3.saveAsTable("brokentable")
> THE WORKAROUND:
> By registering the DataFrame as table and then using sql command to load the
> data will resolve the issue. EX:
> val df3 = sqlContext.sql("select * from testtable").registerTempTable("df3")
> sqlContext.sql("CREATE TABLE brokentable AS SELECT * FROM df3")
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[jira] [Commented] (SPARK-19713) saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-19713?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15889114#comment-15889114
]
Hyukjin Kwon commented on SPARK-19713:
--
Hi [~balaramraju] Could you update the title?
> saveAsTable
> ---
>
> Key: SPARK-19713
> URL: https://issues.apache.org/jira/browse/SPARK-19713
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Balaram R Gadiraju
>
> Hi,
> I just observed that when we use dataframe.saveAsTable("table") -- In
> oldversions
> and dataframe.write.saveAsTable("table") -- in the newer versions
> When using the method “df3.saveAsTable("brokentable")” in
> scale code. This creates a folder in hdfs and doesn’t update hive-metastore
> that it plans to create the table. So if anything goes wrong in between the
> folder still exists and hive is not aware of the folder creation. This will
> block the users from creating the table “brokentable” as the folder already
> exists, we can remove the folder using “hadoop fs –rmr
> /data/hive/databases/testdb.db/brokentable”. So below is the workaround
> which will enable to you to continue the development work.
> Current Code:
> val df3 = sqlContext.sql("select * fromtesttable")
> df3.saveAsTable("brokentable")
> THE WORKAROUND:
> By registering the DataFrame as table and then using sql command to load the
> data will resolve the issue. EX:
> val df3 = sqlContext.sql("select * from testtable").registerTempTable("df3")
> sqlContext.sql("CREATE TABLE brokentable AS SELECT * FROM df3")
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[jira] [Commented] (SPARK-19713) saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-19713?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15895991#comment-15895991
]
Eric Maynard commented on SPARK-19713:
--
In general instead of using `DataFrameWriter.saveAsTable`, I find it's better
to create the table in advance and then insert data into it
`DataFrameWriter.insertInto`. If you use choose to use
`DataFrameWriter.saveAsTable` there is a chance of the folder being created and
the Hive table not being updated, but as a developer you can handle these
errors with `HiveContext.refreshTable` or by using `FileSystem.delete`. I think
this is not an issue.
> saveAsTable
> ---
>
> Key: SPARK-19713
> URL: https://issues.apache.org/jira/browse/SPARK-19713
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Balaram R Gadiraju
>
> Hi,
> I just observed that when we use dataframe.saveAsTable("table") -- In
> oldversions
> and dataframe.write.saveAsTable("table") -- in the newer versions
> When using the method “df3.saveAsTable("brokentable")” in
> scale code. This creates a folder in hdfs and doesn’t update hive-metastore
> that it plans to create the table. So if anything goes wrong in between the
> folder still exists and hive is not aware of the folder creation. This will
> block the users from creating the table “brokentable” as the folder already
> exists, we can remove the folder using “hadoop fs –rmr
> /data/hive/databases/testdb.db/brokentable”. So below is the workaround
> which will enable to you to continue the development work.
> Current Code:
> val df3 = sqlContext.sql("select * fromtesttable")
> df3.saveAsTable("brokentable")
> THE WORKAROUND:
> By registering the DataFrame as table and then using sql command to load the
> data will resolve the issue. EX:
> val df3 = sqlContext.sql("select * from testtable").registerTempTable("df3")
> sqlContext.sql("CREATE TABLE brokentable AS SELECT * FROM df3")
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[jira] [Commented] (SPARK-19713) saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-19713?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15928734#comment-15928734
]
Balaram R Gadiraju commented on SPARK-19713:
The issue is not only in spark, because when the folder is created and spark
ends with error. we are not able to create or drop table even in hive as hive
needs to create the folder in order to create the table.
1. Hive will not be able to create the table as the folder already exists.
2. Hive cannot drop the table because the spark has not updated HiveMetaStore
(there is not table in hive to drop)
This causes the folder to be locked until you run "hdfs dfs -rm -r
/data/hive/databases/testdb.db/brokentable"
Does everyone think this is not a issue ?
> saveAsTable
> ---
>
> Key: SPARK-19713
> URL: https://issues.apache.org/jira/browse/SPARK-19713
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Balaram R Gadiraju
>
> Hi,
> I just observed that when we use dataframe.saveAsTable("table") -- In
> oldversions
> and dataframe.write.saveAsTable("table") -- in the newer versions
> When using the method “df3.saveAsTable("brokentable")” in
> scale code. This creates a folder in hdfs and doesn’t update hive-metastore
> that it plans to create the table. So if anything goes wrong in between the
> folder still exists and hive is not aware of the folder creation. This will
> block the users from creating the table “brokentable” as the folder already
> exists, we can remove the folder using “hadoop fs –rmr
> /data/hive/databases/testdb.db/brokentable”. So below is the workaround
> which will enable to you to continue the development work.
> Current Code:
> val df3 = sqlContext.sql("select * fromtesttable")
> df3.saveAsTable("brokentable")
> THE WORKAROUND:
> By registering the DataFrame as table and then using sql command to load the
> data will resolve the issue. EX:
> val df3 = sqlContext.sql("select * from testtable").registerTempTable("df3")
> sqlContext.sql("CREATE TABLE brokentable AS SELECT * FROM df3")
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[jira] [Commented] (SPARK-19713) saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-19713?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15928737#comment-15928737
]
Balaram R Gadiraju commented on SPARK-19713:
@Hyukjin Kwon : please suggest what you think the title should be
> saveAsTable
> ---
>
> Key: SPARK-19713
> URL: https://issues.apache.org/jira/browse/SPARK-19713
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Balaram R Gadiraju
>
> Hi,
> I just observed that when we use dataframe.saveAsTable("table") -- In
> oldversions
> and dataframe.write.saveAsTable("table") -- in the newer versions
> When using the method “df3.saveAsTable("brokentable")” in
> scale code. This creates a folder in hdfs and doesn’t update hive-metastore
> that it plans to create the table. So if anything goes wrong in between the
> folder still exists and hive is not aware of the folder creation. This will
> block the users from creating the table “brokentable” as the folder already
> exists, we can remove the folder using “hadoop fs –rmr
> /data/hive/databases/testdb.db/brokentable”. So below is the workaround
> which will enable to you to continue the development work.
> Current Code:
> val df3 = sqlContext.sql("select * fromtesttable")
> df3.saveAsTable("brokentable")
> THE WORKAROUND:
> By registering the DataFrame as table and then using sql command to load the
> data will resolve the issue. EX:
> val df3 = sqlContext.sql("select * from testtable").registerTempTable("df3")
> sqlContext.sql("CREATE TABLE brokentable AS SELECT * FROM df3")
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[jira] [Commented] (SPARK-19713) saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-19713?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15928778#comment-15928778
]
Eric Maynard commented on SPARK-19713:
--
Not really relevant here, but to address:
>2. Hive cannot drop the table because the spark has not updated HiveMetaStore
The canonical solution to this is to run `MSCK REPAIR TABLE myTable;` in Hive.
> saveAsTable
> ---
>
> Key: SPARK-19713
> URL: https://issues.apache.org/jira/browse/SPARK-19713
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Balaram R Gadiraju
>
> Hi,
> I just observed that when we use dataframe.saveAsTable("table") -- In
> oldversions
> and dataframe.write.saveAsTable("table") -- in the newer versions
> When using the method “df3.saveAsTable("brokentable")” in
> scale code. This creates a folder in hdfs and doesn’t update hive-metastore
> that it plans to create the table. So if anything goes wrong in between the
> folder still exists and hive is not aware of the folder creation. This will
> block the users from creating the table “brokentable” as the folder already
> exists, we can remove the folder using “hadoop fs –rmr
> /data/hive/databases/testdb.db/brokentable”. So below is the workaround
> which will enable to you to continue the development work.
> Current Code:
> val df3 = sqlContext.sql("select * fromtesttable")
> df3.saveAsTable("brokentable")
> THE WORKAROUND:
> By registering the DataFrame as table and then using sql command to load the
> data will resolve the issue. EX:
> val df3 = sqlContext.sql("select * from testtable").registerTempTable("df3")
> sqlContext.sql("CREATE TABLE brokentable AS SELECT * FROM df3")
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[jira] [Commented] (SPARK-19713) saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-19713?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15928802#comment-15928802
]
Hyukjin Kwon commented on SPARK-19713:
--
> please suggest what you think the title should be
Describe the problem you met in a one line. The title, {{saveAsTable}} is not
helpful. Imagine you manage JIRAs and see a JIRA, for example, {{cache}}.
Likewise, saveAsTable what? the title is obviously not complete and does
not describe the problem.
Check other JIRAs
https://issues.apache.org/jira/browse/SPARK-19713?jql=text%20~%20%22saveAsTable%22
> saveAsTable
> ---
>
> Key: SPARK-19713
> URL: https://issues.apache.org/jira/browse/SPARK-19713
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Balaram R Gadiraju
>
> Hi,
> I just observed that when we use dataframe.saveAsTable("table") -- In
> oldversions
> and dataframe.write.saveAsTable("table") -- in the newer versions
> When using the method “df3.saveAsTable("brokentable")” in
> scale code. This creates a folder in hdfs and doesn’t update hive-metastore
> that it plans to create the table. So if anything goes wrong in between the
> folder still exists and hive is not aware of the folder creation. This will
> block the users from creating the table “brokentable” as the folder already
> exists, we can remove the folder using “hadoop fs –rmr
> /data/hive/databases/testdb.db/brokentable”. So below is the workaround
> which will enable to you to continue the development work.
> Current Code:
> val df3 = sqlContext.sql("select * fromtesttable")
> df3.saveAsTable("brokentable")
> THE WORKAROUND:
> By registering the DataFrame as table and then using sql command to load the
> data will resolve the issue. EX:
> val df3 = sqlContext.sql("select * from testtable").registerTempTable("df3")
> sqlContext.sql("CREATE TABLE brokentable AS SELECT * FROM df3")
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