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Posted to issues@carbondata.apache.org by GitBox <gi...@apache.org> on 2021/06/23 03:16:39 UTC
[GitHub] [carbondata] 01lin opened a new issue #4160: Why opened task less than available executors in case of insert into/load data
01lin opened a new issue #4160:
URL: https://github.com/apache/carbondata/issues/4160
In case of insert into or load data, the total number of tasks in the stage is almost equal to the number of hosts, and in general it is much smaller than the available executors. The low parallelism of the stage results in slower execution. Why must the parallelism be constrained on the distinct host? Can start more tasks to increase parallelism and improve resource utilization? Thanks
org/apache/carbondata/spark/rdd/CarbonDataRDDFactory.scala: loadDataFrame
```
/**
* Execute load process to load from input dataframe
*/
private def loadDataFrame(
sqlContext: SQLContext,
dataFrame: Option[DataFrame],
carbonLoadModel: CarbonLoadModel
): Array[(String, (LoadMetadataDetails, ExecutionErrors))] = {
try {
val rdd = dataFrame.get.rdd
// 基于getPreferredLocs获取优化位置,取distinct值:获取host list
val nodeNumOfData = rdd.partitions.flatMap[String, Array[String]] { p =>
DataLoadPartitionCoalescer.getPreferredLocs(rdd, p).map(_.host)
}.distinct.length
val nodes = DistributionUtil.ensureExecutorsByNumberAndGetNodeList(
nodeNumOfData,
sqlContext.sparkContext) // 确保executor数量要和数据的节点数一样多
val newRdd = new DataLoadCoalescedRDD[Row](sqlContext.sparkSession, rdd, nodes.toArray
.distinct)
new NewDataFrameLoaderRDD(
sqlContext.sparkSession,
new DataLoadResultImpl(),
carbonLoadModel,
newRdd
).collect()
} catch {
case ex: Exception =>
LOGGER.error("load data frame failed", ex)
throw ex
}
}
```
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[GitHub] [carbondata] QiangCai commented on issue #4160: Why opened task less than available executors in case of insert into/load data
Posted by GitBox <gi...@apache.org>.
QiangCai commented on issue #4160:
URL: https://github.com/apache/carbondata/issues/4160#issuecomment-869274861
It only works for the local_sort loading.
It can help to avoid data shuffle during executors.
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