[jira] [Updated] (SPARK-21287) Cannot use Int.MIN_VALUE as Spark SQL fetchsize

2019-10-24 Thread Dongjoon Hyun (Jira) 


 [ 
https://issues.apache.org/jira/browse/SPARK-21287?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Dongjoon Hyun updated SPARK-21287:
--
Affects Version/s: 3.0.0
   2.2.3
   2.3.4
   2.4.4

> Cannot use Int.MIN_VALUE as Spark SQL fetchsize
> ---
>
> Key: SPARK-21287
> URL: https://issues.apache.org/jira/browse/SPARK-21287
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.1.1, 2.2.3, 2.3.4, 2.4.4, 3.0.0
>Reporter: Maciej Bryński
>Priority: Major
>
> MySQL JDBC driver gives possibility to not store ResultSet in memory.
> We can do this by setting fetchSize to Int.MIN_VALUE.
> Unfortunately this configuration isn't correct in Spark.
> {code}
> java.lang.IllegalArgumentException: requirement failed: Invalid value 
> `-2147483648` for parameter `fetchsize`. The minimum value is 0. When the 
> value is 0, the JDBC driver ignores the value and does the estimates.
>   at scala.Predef$.require(Predef.scala:224)
>   at 
> org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.(JDBCOptions.scala:105)
>   at 
> org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.(JDBCOptions.scala:34)
>   at 
> org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:32)
>   at 
> org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:330)
>   at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152)
>   at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:125)
>   at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:166)
>   at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:206)
>   at sun.reflect.GeneratedMethodAccessor46.invoke(Unknown Source)
>   at 
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>   at java.lang.reflect.Method.invoke(Method.java:498)
>   at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
>   at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
>   at py4j.Gateway.invoke(Gateway.java:280)
>   at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
>   at py4j.commands.CallCommand.execute(CallCommand.java:79)
>   at py4j.GatewayConnection.run(GatewayConnection.java:214)
>   at java.lang.Thread.run(Thread.java:748)
> {code}
> https://dev.mysql.com/doc/connector-j/5.1/en/connector-j-reference-implementation-notes.html



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[jira] [Updated] (SPARK-21287) Cannot use Int.MIN_VALUE as Spark SQL fetchsize

2017-07-03 Thread JIRA 

 [ 
https://issues.apache.org/jira/browse/SPARK-21287?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Maciej Bryński updated SPARK-21287:
---
Description: 
MySQL JDBC driver gives possibility to not store ResultSet in memory.
We can do this by setting fetchSize to Int.MIN_VALUE.
Unfortunately this configuration isn't correct in Spark.
{code}
java.lang.IllegalArgumentException: requirement failed: Invalid value 
`-2147483648` for parameter `fetchsize`. The minimum value is 0. When the value 
is 0, the JDBC driver ignores the value and does the estimates.
at scala.Predef$.require(Predef.scala:224)
at 
org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.(JDBCOptions.scala:105)
at 
org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.(JDBCOptions.scala:34)
at 
org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:32)
at 
org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:330)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:125)
at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:166)
at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:206)
at sun.reflect.GeneratedMethodAccessor46.invoke(Unknown Source)
at 
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:748)
{code}

https://dev.mysql.com/doc/connector-j/5.1/en/connector-j-reference-implementation-notes.html

  was:
MySQL JDBC driver gives possibility to not store ResultSet in memory.
We can do this by setting fetchSize to Int.MIN_VALUE.
Unfortunately this configuration isn't correct in Spark.
{code}
java.lang.IllegalArgumentException: requirement failed: Invalid value 
`-2147483648` for parameter `fetchsize`. The minimum value is 0. When the value 
is 0, the JDBC driver ignores the value and does the estimates.
at scala.Predef$.require(Predef.scala:224)
at 
org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.(JDBCOptions.scala:105)
at 
org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.(JDBCOptions.scala:34)
at 
org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:32)
at 
org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:330)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:125)
at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:166)
at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:206)
at sun.reflect.GeneratedMethodAccessor46.invoke(Unknown Source)
at 
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:748)
{code}


> Cannot use Int.MIN_VALUE as Spark SQL fetchsize
> ---
>
> Key: SPARK-21287
> URL: https://issues.apache.org/jira/browse/SPARK-21287
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.1.1
>Reporter: Maciej Bryński
>
> MySQL JDBC driver gives possibility to not store ResultSet in memory.
> We can do this by setting fetchSize to Int.MIN_VALUE.
> Unfortunately this configuration isn't correct in Spark.
> {code}
> java.lang.IllegalArgumentException: requirement failed: Invalid value 
> `-2147483648` for parameter `fetchsize`. The minimum value is 0. When the 
> value is 0, the JDBC driver ignores the value and does the estimates.
>   at scala.Predef$.require(Predef.scala:224)
>   at 
> org.apache.spark.sql.execution.datasources.

[jira] [Updated] (SPARK-21287) Cannot use Int.MIN_VALUE as Spark SQL fetchsize

2017-07-03 Thread JIRA 

 [ 
https://issues.apache.org/jira/browse/SPARK-21287?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Maciej Bryński updated SPARK-21287:
---
Summary: Cannot use Int.MIN_VALUE as Spark SQL fetchsize  (was: Cannot use 
Iint.MIN_VALUE as Spark SQL fetchsize)

> Cannot use Int.MIN_VALUE as Spark SQL fetchsize
> ---
>
> Key: SPARK-21287
> URL: https://issues.apache.org/jira/browse/SPARK-21287
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.1.1
>Reporter: Maciej Bryński
>
> MySQL JDBC driver gives possibility to not store ResultSet in memory.
> We can do this by setting fetchSize to Int.MIN_VALUE.
> Unfortunately this configuration isn't correct in Spark.
> {code}
> java.lang.IllegalArgumentException: requirement failed: Invalid value 
> `-2147483648` for parameter `fetchsize`. The minimum value is 0. When the 
> value is 0, the JDBC driver ignores the value and does the estimates.
>   at scala.Predef$.require(Predef.scala:224)
>   at 
> org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.(JDBCOptions.scala:105)
>   at 
> org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.(JDBCOptions.scala:34)
>   at 
> org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:32)
>   at 
> org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:330)
>   at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152)
>   at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:125)
>   at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:166)
>   at org.apache.spark.sql.DataFrameReader.jdbc(DataFrameReader.scala:206)
>   at sun.reflect.GeneratedMethodAccessor46.invoke(Unknown Source)
>   at 
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>   at java.lang.reflect.Method.invoke(Method.java:498)
>   at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
>   at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
>   at py4j.Gateway.invoke(Gateway.java:280)
>   at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
>   at py4j.commands.CallCommand.execute(CallCommand.java:79)
>   at py4j.GatewayConnection.run(GatewayConnection.java:214)
>   at java.lang.Thread.run(Thread.java:748)
> {code}



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