[jira] [Commented] (SPARK-21841) Spark SQL doesn't pick up column added in hive when table created with saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16147873#comment-16147873
]
Marcelo Vanzin commented on SPARK-21841:
Good to know there's a way to say "I want a proper Hive table" in 2.2, even if
the API is a little confusing for the user. Too many people just use
{{saveAsTable}} without really understanding what it means for Hive
compatibility.
It might even make more sense to not even try to save a Hive compatible table
for other formats, although that might have backwards compatibility issues.
> Spark SQL doesn't pick up column added in hive when table created with
> saveAsTable
> --
>
> Key: SPARK-21841
> URL: https://issues.apache.org/jira/browse/SPARK-21841
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.1.0, 2.2.0
>Reporter: Thomas Graves
>
> If you create a table in Spark sql but then you modify the table in hive to
> add a column, spark sql doesn't pick up the new column.
> Basic example:
> {code}
> t1 = spark.sql("select ip_address from mydb.test_table limit 1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> t1.write.saveAsTable('mydb.t1')
> In Hive:
> alter table mydb.t1 add columns (bcookie string)
> t1 = spark.table("mydb.t1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> {code}
> It looks like its because spark sql is picking up the schema from
> spark.sql.sources.schema.part.0 rather then from hive.
> Interestingly enough it appears that if you create the table differently like:
> spark.sql("create table mydb.t1 select ip_address from mydb.test_table limit
> 1")
> Run your alter table on mydb.t1
> val t1 = spark.table("mydb.t1")
> Then it works properly.
> It looks like the difference is when it doesn't work
> spark.sql.sources.provider=parquet is set.
> Its doing this from createDataSourceTable where provider is parquet.
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[jira] [Commented] (SPARK-21841) Spark SQL doesn't pick up column added in hive when table created with saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16145575#comment-16145575
]
Wenchen Fan commented on SPARK-21841:
-
yea we support the hive format since Spark 2.2. For older spark versions, you
have to use the `CREATE TABLE` statement.
> Spark SQL doesn't pick up column added in hive when table created with
> saveAsTable
> --
>
> Key: SPARK-21841
> URL: https://issues.apache.org/jira/browse/SPARK-21841
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.1.0, 2.2.0
>Reporter: Thomas Graves
>
> If you create a table in Spark sql but then you modify the table in hive to
> add a column, spark sql doesn't pick up the new column.
> Basic example:
> {code}
> t1 = spark.sql("select ip_address from mydb.test_table limit 1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> t1.write.saveAsTable('mydb.t1')
> In Hive:
> alter table mydb.t1 add columns (bcookie string)
> t1 = spark.table("mydb.t1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> {code}
> It looks like its because spark sql is picking up the schema from
> spark.sql.sources.schema.part.0 rather then from hive.
> Interestingly enough it appears that if you create the table differently like:
> spark.sql("create table mydb.t1 select ip_address from mydb.test_table limit
> 1")
> Run your alter table on mydb.t1
> val t1 = spark.table("mydb.t1")
> Then it works properly.
> It looks like the difference is when it doesn't work
> spark.sql.sources.provider=parquet is set.
> Its doing this from createDataSourceTable where provider is parquet.
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[jira] [Commented] (SPARK-21841) Spark SQL doesn't pick up column added in hive when table created with saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16145413#comment-16145413
]
Thomas Graves commented on SPARK-21841:
---
sorry for so many comments, I guess this goes back to
https://issues.apache.org/jira/browse/SPARK-19150
> Spark SQL doesn't pick up column added in hive when table created with
> saveAsTable
> --
>
> Key: SPARK-21841
> URL: https://issues.apache.org/jira/browse/SPARK-21841
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.1.0, 2.2.0
>Reporter: Thomas Graves
>
> If you create a table in Spark sql but then you modify the table in hive to
> add a column, spark sql doesn't pick up the new column.
> Basic example:
> {code}
> t1 = spark.sql("select ip_address from mydb.test_table limit 1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> t1.write.saveAsTable('mydb.t1')
> In Hive:
> alter table mydb.t1 add columns (bcookie string)
> t1 = spark.table("mydb.t1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> {code}
> It looks like its because spark sql is picking up the schema from
> spark.sql.sources.schema.part.0 rather then from hive.
> Interestingly enough it appears that if you create the table differently like:
> spark.sql("create table mydb.t1 select ip_address from mydb.test_table limit
> 1")
> Run your alter table on mydb.t1
> val t1 = spark.table("mydb.t1")
> Then it works properly.
> It looks like the difference is when it doesn't work
> spark.sql.sources.provider=parquet is set.
> Its doing this from createDataSourceTable where provider is parquet.
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[jira] [Commented] (SPARK-21841) Spark SQL doesn't pick up column added in hive when table created with saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16145399#comment-16145399
]
Thomas Graves commented on SPARK-21841:
---
Oh no I guess that is explicit check in spark 2.1:
if (source.toLowerCase == DDLUtils.HIVE_PROVIDER) {
throw new AnalysisException("Cannot create hive serde table with
saveAsTable API")
}
Perhaps this is only supported in spark 2.2?
> Spark SQL doesn't pick up column added in hive when table created with
> saveAsTable
> --
>
> Key: SPARK-21841
> URL: https://issues.apache.org/jira/browse/SPARK-21841
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.1.0, 2.2.0
>Reporter: Thomas Graves
>
> If you create a table in Spark sql but then you modify the table in hive to
> add a column, spark sql doesn't pick up the new column.
> Basic example:
> {code}
> t1 = spark.sql("select ip_address from mydb.test_table limit 1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> t1.write.saveAsTable('mydb.t1')
> In Hive:
> alter table mydb.t1 add columns (bcookie string)
> t1 = spark.table("mydb.t1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> {code}
> It looks like its because spark sql is picking up the schema from
> spark.sql.sources.schema.part.0 rather then from hive.
> Interestingly enough it appears that if you create the table differently like:
> spark.sql("create table mydb.t1 select ip_address from mydb.test_table limit
> 1")
> Run your alter table on mydb.t1
> val t1 = spark.table("mydb.t1")
> Then it works properly.
> It looks like the difference is when it doesn't work
> spark.sql.sources.provider=parquet is set.
> Its doing this from createDataSourceTable where provider is parquet.
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[jira] [Commented] (SPARK-21841) Spark SQL doesn't pick up column added in hive when table created with saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16145396#comment-16145396
]
Thomas Graves commented on SPARK-21841:
---
Unfortunately that isn't working for me, but might be something with our hive
version as its a bit non-standard:
scala> t1.write.format("hive").saveAsTable("mydb.t62")
org.apache.spark.sql.AnalysisException: Cannot create hive serde table with
saveAsTable API;
at org.apache.spark.sql.DataFrameWriter.saveAsTable(DataFrameWriter.scala:363)
at org.apache.spark.sql.DataFrameWriter.saveAsTable(DataFrameWriter.scala:358)
... 48 elided
> Spark SQL doesn't pick up column added in hive when table created with
> saveAsTable
> --
>
> Key: SPARK-21841
> URL: https://issues.apache.org/jira/browse/SPARK-21841
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.1.0, 2.2.0
>Reporter: Thomas Graves
>
> If you create a table in Spark sql but then you modify the table in hive to
> add a column, spark sql doesn't pick up the new column.
> Basic example:
> {code}
> t1 = spark.sql("select ip_address from mydb.test_table limit 1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> t1.write.saveAsTable('mydb.t1')
> In Hive:
> alter table mydb.t1 add columns (bcookie string)
> t1 = spark.table("mydb.t1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> {code}
> It looks like its because spark sql is picking up the schema from
> spark.sql.sources.schema.part.0 rather then from hive.
> Interestingly enough it appears that if you create the table differently like:
> spark.sql("create table mydb.t1 select ip_address from mydb.test_table limit
> 1")
> Run your alter table on mydb.t1
> val t1 = spark.table("mydb.t1")
> Then it works properly.
> It looks like the difference is when it doesn't work
> spark.sql.sources.provider=parquet is set.
> Its doing this from createDataSourceTable where provider is parquet.
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[jira] [Commented] (SPARK-21841) Spark SQL doesn't pick up column added in hive when table created with saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16145392#comment-16145392
]
Thomas Graves commented on SPARK-21841:
---
I'll try that out.
Honestly I didn't even know you could specify "hive" as a format. I actually
tried to look at the docs for something like that but didn't see anything about
it. Perhaps we need some better docs there or perhaps I just missed it.
> Spark SQL doesn't pick up column added in hive when table created with
> saveAsTable
> --
>
> Key: SPARK-21841
> URL: https://issues.apache.org/jira/browse/SPARK-21841
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.1.0, 2.2.0
>Reporter: Thomas Graves
>
> If you create a table in Spark sql but then you modify the table in hive to
> add a column, spark sql doesn't pick up the new column.
> Basic example:
> {code}
> t1 = spark.sql("select ip_address from mydb.test_table limit 1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> t1.write.saveAsTable('mydb.t1')
> In Hive:
> alter table mydb.t1 add columns (bcookie string)
> t1 = spark.table("mydb.t1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> {code}
> It looks like its because spark sql is picking up the schema from
> spark.sql.sources.schema.part.0 rather then from hive.
> Interestingly enough it appears that if you create the table differently like:
> spark.sql("create table mydb.t1 select ip_address from mydb.test_table limit
> 1")
> Run your alter table on mydb.t1
> val t1 = spark.table("mydb.t1")
> Then it works properly.
> It looks like the difference is when it doesn't work
> spark.sql.sources.provider=parquet is set.
> Its doing this from createDataSourceTable where provider is parquet.
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[jira] [Commented] (SPARK-21841) Spark SQL doesn't pick up column added in hive when table created with saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16145325#comment-16145325
]
Wenchen Fan commented on SPARK-21841:
-
This is above the data source layer. When you create a data source table, i.e.
{{t1.write.saveAsTable('mydb.t1')}} , spark will keep the table schema in table
properties and ignore schema updates from hive. When you create a hive serde
table, i.e., {{t1.write.format("hive").saveAsTable('mydb.t1')}} , then it can
work as you expect, because hive serde table will always respect table schema
from hive metastore.
I think the confusing part is, for `DataFrameWriter`, by default it creates
parquet data source table, while for `CREATE TABLE` statement, by default it
creates text hive serde table. This is due to some historical reasons, but we
may need to document it more explicitly.
> Spark SQL doesn't pick up column added in hive when table created with
> saveAsTable
> --
>
> Key: SPARK-21841
> URL: https://issues.apache.org/jira/browse/SPARK-21841
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.1.0, 2.2.0
>Reporter: Thomas Graves
>
> If you create a table in Spark sql but then you modify the table in hive to
> add a column, spark sql doesn't pick up the new column.
> Basic example:
> {code}
> t1 = spark.sql("select ip_address from mydb.test_table limit 1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> t1.write.saveAsTable('mydb.t1')
> In Hive:
> alter table mydb.t1 add columns (bcookie string)
> t1 = spark.table("mydb.t1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> {code}
> It looks like its because spark sql is picking up the schema from
> spark.sql.sources.schema.part.0 rather then from hive.
> Interestingly enough it appears that if you create the table differently like:
> spark.sql("create table mydb.t1 select ip_address from mydb.test_table limit
> 1")
> Run your alter table on mydb.t1
> val t1 = spark.table("mydb.t1")
> Then it works properly.
> It looks like the difference is when it doesn't work
> spark.sql.sources.provider=parquet is set.
> Its doing this from createDataSourceTable where provider is parquet.
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[jira] [Commented] (SPARK-21841) Spark SQL doesn't pick up column added in hive when table created with saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16144540#comment-16144540
]
Marcelo Vanzin commented on SPARK-21841:
"DataSource tables" (those created, in certain cases, with {{saveAsTable}}),
have pretty spotty Hive compatibility. I've run into this in a recent PR
(SPARK-21617) and [~smilegator] suggested having an explicit config added to
ensure compatibility, although I don't think anyone is working on that.
The workaround you have (using DDL SQL commands instead of doing it via Scala
code) is what we have been suggesting to people for a really long time now.
I haven't looked closely at the spec to see whether it covers this, but maybe
this could be called out explicitly in SPARK-15689, which plans to update the
DataSource APIs.
> Spark SQL doesn't pick up column added in hive when table created with
> saveAsTable
> --
>
> Key: SPARK-21841
> URL: https://issues.apache.org/jira/browse/SPARK-21841
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.1.0, 2.2.0
>Reporter: Thomas Graves
>
> If you create a table in Spark sql but then you modify the table in hive to
> add a column, spark sql doesn't pick up the new column.
> Basic example:
> {code}
> t1 = spark.sql("select ip_address from mydb.test_table limit 1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> t1.write.saveAsTable('mydb.t1')
> In Hive:
> alter table mydb.t1 add columns (bcookie string)
> t1 = spark.table("mydb.t1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> {code}
> It looks like its because spark sql is picking up the schema from
> spark.sql.sources.schema.part.0 rather then from hive.
> Interestingly enough it appears that if you create the table differently like:
> spark.sql("create table mydb.t1 select ip_address from mydb.test_table limit
> 1")
> Run your alter table on mydb.t1
> val t1 = spark.table("mydb.t1")
> Then it works properly.
> It looks like the difference is when it doesn't work
> spark.sql.sources.provider=parquet is set.
> Its doing this from createDataSourceTable where provider is parquet.
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[jira] [Commented] (SPARK-21841) Spark SQL doesn't pick up column added in hive when table created with saveAsTable
[
https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16142958#comment-16142958
]
Dongjoon Hyun commented on SPARK-21841:
---
Apache Spark 2.2 is the same. More worse, it seems to overwrite the existing
schema if Spark do `ALTER TABLE ADD COLUMNS` then. The column added by Hive is
gone away.
> Spark SQL doesn't pick up column added in hive when table created with
> saveAsTable
> --
>
> Key: SPARK-21841
> URL: https://issues.apache.org/jira/browse/SPARK-21841
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.1.0, 2.2.0
>Reporter: Thomas Graves
>
> If you create a table in Spark sql but then you modify the table in hive to
> add a column, spark sql doesn't pick up the new column.
> Basic example:
> {code}
> t1 = spark.sql("select ip_address from mydb.test_table limit 1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> t1.write.saveAsTable('mydb.t1')
> In Hive:
> alter table mydb.t1 add columns (bcookie string)
> t1 = spark.table("mydb.t1")
> t1.show()
> ++
> | ip_address|
> ++
> |1.30.25.5|
> ++
> {code}
> It looks like its because spark sql is picking up the schema from
> spark.sql.sources.schema.part.0 rather then from hive.
> Interestingly enough it appears that if you create the table differently like:
> spark.sql("create table mydb.t1 select ip_address from mydb.test_table limit
> 1")
> Run your alter table on mydb.t1
> val t1 = spark.table("mydb.t1")
> Then it works properly.
> It looks like the difference is when it doesn't work
> spark.sql.sources.provider=parquet is set.
> Its doing this from createDataSourceTable where provider is parquet.
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