GitHub user scwf opened a pull request:
https://github.com/apache/spark/pull/1385
Optimize SparkContext.hadoopFile api
1 use SparkContext.hadoopRDD() instead of instantiate HadoopRDD directly in
SparkContext.hadoopFile.
SparkContext.hadoopRDD() Add necessary security credentials to the
JobConf before broadcasting it.
2 broadcast jobConf in HadoopRDD, not Configuration. this will resolve the
dead lock issue----
now HadoopRDD broadcast Configuration and in each task (compute method) to
get jobConf
then the lock of
conf.synchronized {
val newJobConf = new JobConf(conf)
initLocalJobConfFuncOpt.map(f => f(newJobConf))
HadoopRDD.putCachedMetadata(jobConfCacheKey, newJobConf)
newJobConf
}
will conflict with hadoop version fix Hadoop-10456:
hadoop-common-project/hadoop-common/src/main/java/org/apache/hadoop/conf/Configuration.java
synchronized(Configuration.class) {
REGISTRY.put(this, null);
}
we can reproduce the bug like this:
hadoop version 2.4.1
spark master branch
hql("SELECT t1.a, t1.b, t1.c FROM table_A t1 JOIN table_A t2 ON (t1.a =
t2.a)")
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/scwf/spark kasi
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/1385.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #1385
----
commit c691f3d1cdb770aaafbb025a52c49233cb13c9f7
Author: w00228970 <[email protected]>
Date: 2014-07-12T07:59:04Z
use SparkContext.hadoopRDD() instead of instantiate HadoopRDD directly in
SparkContext.hadoopFile
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