本文整理汇总了Java中org.apache.hadoop.vaidya.statistics.job.JobStatisticsInterface.MapTaskKeys类的典型用法代码示例。如果您正苦于以下问题：Java MapTaskKeys类的具体用法？Java MapTaskKeys怎么用？Java MapTaskKeys使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
MapTaskKeys类属于org.apache.hadoop.vaidya.statistics.job.JobStatisticsInterface包，在下文中一共展示了MapTaskKeys类的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: evaluate
import org.apache.hadoop.vaidya.statistics.job.JobStatisticsInterface.MapTaskKeys; //导入依赖的package包/类
@Override
public double evaluate(JobStatistics job) {
/*
* Set the this._job
*/
this._job = job;
/*
* Read the Normalization Factor
*/
double normF = getInputElementDoubleValue("NormalizationFactor", 3.0);
/*
* Get the sorted map task list by number MapTaskKeys.OUTPUT_BYTES
*/
List<MapTaskStatistics> smTaskList = job.getMapTaskList(MapTaskKeys.FILE_BYTES_WRITTEN, KeyDataType.LONG);
int size = smTaskList.size();
long numLocalBytesWrittenByMaps = 0;
for (int i=0; i<size; i++) {
numLocalBytesWrittenByMaps += smTaskList.get(i).getLongValue(MapTaskKeys.FILE_BYTES_WRITTEN);
}
this._numLocalBytesWrittenByMaps = numLocalBytesWrittenByMaps;
/*
* Map only job vs. map reduce job
* For MapReduce job MAP_OUTPUT_BYTES are normally written by maps on local disk, so they are subtracted
* from the localBytesWrittenByMaps.
*/
if (job.getLongValue(JobKeys.TOTAL_REDUCES) > 0) {
this._impact = (this._numLocalBytesWrittenByMaps - job.getLongValue(JobKeys.MAP_OUTPUT_BYTES))/job.getLongValue(JobKeys.MAP_OUTPUT_BYTES);
} else {
this._impact = this._numLocalBytesWrittenByMaps/job.getLongValue(JobKeys.MAP_OUTPUT_BYTES);
}
if (this._impact > normF) {
this._impact = 1.0;
} else {
this._impact = this._impact/normF;
}
return this._impact;
}
示例2: evaluate
import org.apache.hadoop.vaidya.statistics.job.JobStatisticsInterface.MapTaskKeys; //导入依赖的package包/类
@Override
public double evaluate(JobStatistics job) {
/*
* Set the this._job
*/
this._job = job;
/*
* Read the Normalization Factor
*/
double normF = getInputElementDoubleValue("NormalizationFactor", 3.0);
/*
* Get the sorted reduce task list by number MapTaskKeys.OUTPUT_BYTES
*/
List<MapTaskStatistics> srTaskList = job.getMapTaskList(MapTaskKeys.LOCAL_BYTES_WRITTEN, KeyDataType.LONG);
int size = srTaskList.size();
long numLocalBytesWrittenByMaps = 0;
for (int i=0; i<size; i++) {
numLocalBytesWrittenByMaps += srTaskList.get(i).getLongValue(MapTaskKeys.LOCAL_BYTES_WRITTEN);
}
this._numLocalBytesWrittenByMaps = numLocalBytesWrittenByMaps;
/*
* Map only job vs. map reduce job
*/
if (job.getLongValue(JobKeys.TOTAL_REDUCES) > 0) {
this._impact = (this._numLocalBytesWrittenByMaps - job.getLongValue(JobKeys.MAP_OUTPUT_BYTES))/job.getLongValue(JobKeys.MAP_OUTPUT_BYTES);
} else {
this._impact = this._numLocalBytesWrittenByMaps/job.getLongValue(JobKeys.MAP_OUTPUT_BYTES);
}
if (this._impact > normF) {
this._impact = 1.0;
} else {
this._impact = this._impact/normF;
}
return this._impact;
}