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https://issues.apache.org/jira/browse/SPARK-8008?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14567993#comment-14567993
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Reynold Xin commented on SPARK-8008:
------------------------------------
As discussed on the dev list, there's already warning to avoid high concurrency
{code}
/**
* Construct a [[DataFrame]] representing the database table accessible via
JDBC URL
* url named table. Partitions of the table will be retrieved in parallel
based on the parameters
* passed to this function.
*
* Don't create too many partitions in parallel on a large cluster; otherwise
Spark might crash
* your external database systems.
*
* @param url JDBC database url of the form `jdbc:subprotocol:subname`
* @param table Name of the table in the external database.
* @param columnName the name of a column of integral type that will be used
for partitioning.
* @param lowerBound the minimum value of `columnName` used to decide
partition stride
* @param upperBound the maximum value of `columnName` used to decide
partition stride
* @param numPartitions the number of partitions. the range
`minValue`-`maxValue` will be split
* evenly into this many partitions
* @param connectionProperties JDBC database connection arguments, a list of
arbitrary string
* tag/value. Normally at least a "user" and
"password" property
* should be included.
*
* @since 1.4.0
*/
{code}
Even with the warning, it'd be great to have some way to throttle.
> sqlContext.jdbc can kill your database due to high concurrency
> --------------------------------------------------------------
>
> Key: SPARK-8008
> URL: https://issues.apache.org/jira/browse/SPARK-8008
> Project: Spark
> Issue Type: Bug
> Reporter: Rene Treffer
>
> Spark tries to load as many partitions as possible in parallel, which can in
> turn overload the database although it would be possible to load all
> partitions given a lower concurrency.
> It would be nice to either limit the maximum concurrency or to at least warn
> about this behavior.
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