diff options
| -rw-r--r-- | core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala | 53 | ||||
| -rw-r--r-- | docs/configuration.md | 9 |
2 files changed, 47 insertions, 15 deletions
diff --git a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala index 8010dd9008..775141775e 100644 --- a/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala +++ b/core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala @@ -132,27 +132,47 @@ class HadoopRDD[K, V]( // used to build JobTracker ID private val createTime = new Date() + private val shouldCloneJobConf = sc.conf.get("spark.hadoop.cloneConf", "false").toBoolean + // Returns a JobConf that will be used on slaves to obtain input splits for Hadoop reads. protected def getJobConf(): JobConf = { val conf: Configuration = broadcastedConf.value.value - if (conf.isInstanceOf[JobConf]) { - // A user-broadcasted JobConf was provided to the HadoopRDD, so always use it. - conf.asInstanceOf[JobConf] - } else if (HadoopRDD.containsCachedMetadata(jobConfCacheKey)) { - // getJobConf() has been called previously, so there is already a local cache of the JobConf - // needed by this RDD. - HadoopRDD.getCachedMetadata(jobConfCacheKey).asInstanceOf[JobConf] - } else { - // Create a JobConf that will be cached and used across this RDD's getJobConf() calls in the - // local process. The local cache is accessed through HadoopRDD.putCachedMetadata(). - // The caching helps minimize GC, since a JobConf can contain ~10KB of temporary objects. - // Synchronize to prevent ConcurrentModificationException (Spark-1097, Hadoop-10456). + if (shouldCloneJobConf) { + // Hadoop Configuration objects are not thread-safe, which may lead to various problems if + // one job modifies a configuration while another reads it (SPARK-2546). This problem occurs + // somewhat rarely because most jobs treat the configuration as though it's immutable. One + // solution, implemented here, is to clone the Configuration object. Unfortunately, this + // clone can be very expensive. To avoid unexpected performance regressions for workloads and + // Hadoop versions that do not suffer from these thread-safety issues, this cloning is + // disabled by default. HadoopRDD.CONFIGURATION_INSTANTIATION_LOCK.synchronized { + logDebug("Cloning Hadoop Configuration") val newJobConf = new JobConf(conf) - initLocalJobConfFuncOpt.map(f => f(newJobConf)) - HadoopRDD.putCachedMetadata(jobConfCacheKey, newJobConf) + if (!conf.isInstanceOf[JobConf]) { + initLocalJobConfFuncOpt.map(f => f(newJobConf)) + } newJobConf } + } else { + if (conf.isInstanceOf[JobConf]) { + logDebug("Re-using user-broadcasted JobConf") + conf.asInstanceOf[JobConf] + } else if (HadoopRDD.containsCachedMetadata(jobConfCacheKey)) { + logDebug("Re-using cached JobConf") + HadoopRDD.getCachedMetadata(jobConfCacheKey).asInstanceOf[JobConf] + } else { + // Create a JobConf that will be cached and used across this RDD's getJobConf() calls in the + // local process. The local cache is accessed through HadoopRDD.putCachedMetadata(). + // The caching helps minimize GC, since a JobConf can contain ~10KB of temporary objects. + // Synchronize to prevent ConcurrentModificationException (SPARK-1097, HADOOP-10456). + HadoopRDD.CONFIGURATION_INSTANTIATION_LOCK.synchronized { + logDebug("Creating new JobConf and caching it for later re-use") + val newJobConf = new JobConf(conf) + initLocalJobConfFuncOpt.map(f => f(newJobConf)) + HadoopRDD.putCachedMetadata(jobConfCacheKey, newJobConf) + newJobConf + } + } } } @@ -276,7 +296,10 @@ class HadoopRDD[K, V]( } private[spark] object HadoopRDD extends Logging { - /** Constructing Configuration objects is not threadsafe, use this lock to serialize. */ + /** + * Configuration's constructor is not threadsafe (see SPARK-1097 and HADOOP-10456). + * Therefore, we synchronize on this lock before calling new JobConf() or new Configuration(). + */ val CONFIGURATION_INSTANTIATION_LOCK = new Object() /** diff --git a/docs/configuration.md b/docs/configuration.md index f0204c640b..96fa1377ec 100644 --- a/docs/configuration.md +++ b/docs/configuration.md @@ -620,6 +620,15 @@ Apart from these, the following properties are also available, and may be useful previous versions of Spark. Simply use Hadoop's FileSystem API to delete output directories by hand.</td> </tr> <tr> + <td><code>spark.hadoop.cloneConf</code></td> + <td>false</td> + <td>If set to true, clones a new Hadoop <code>Configuration</code> object for each task. This + option should be enabled to work around <code>Configuration</code> thread-safety issues (see + <a href="https://issues.apache.org/jira/browse/SPARK-2546">SPARK-2546</a> for more details). + This is disabled by default in order to avoid unexpected performance regressions for jobs that + are not affected by these issues.</td> +</tr> +<tr> <td><code>spark.executor.heartbeatInterval</code></td> <td>10000</td> <td>Interval (milliseconds) between each executor's heartbeats to the driver. Heartbeats let |