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From "Sean Owen (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-21287) Cannot use Int.MIN_VALUE as Spark SQL fetchsize
Date Mon, 03 Jul 2017 13:11:01 GMT

    [ https://issues.apache.org/jira/browse/SPARK-21287?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16072414#comment-16072414
] 

Sean Owen commented on SPARK-21287:
-----------------------------------

It's not supposed to do that right -- you're saying the MySQL driver doesn't quite use the
value as intended?
Hm, so any MySQL user would have the whole resultset pulled back into memory every time? that
seems like a problem, yeah, but surely MySQL has fixed this?
If not, I could see this being a big enough deal that it has to be allowed as a value even
if it is wrong.

> 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 BryƄski
>
> 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.<init>(JDBCOptions.scala:105)
> 	at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(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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