本文整理汇总了Java中org.apache.hadoop.util.Progress类的典型用法代码示例。如果您正苦于以下问题：Java Progress类的具体用法？Java Progress怎么用？Java Progress使用的例子？那么, 这里精选的类代码示例或许可以为您提供帮助。
Progress类属于org.apache.hadoop.util包，在下文中一共展示了Progress类的6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: merge
import org.apache.hadoop.util.Progress; //导入依赖的package包/类
public static <K extends Object, V extends Object>
RawKeyValueIterator merge(Configuration conf, FileSystem fs,
Class<K> keyClass, Class<V> valueClass,
CompressionCodec codec,
Path[] inputs, boolean deleteInputs,
int mergeFactor, Path tmpDir,
RawComparator<K> comparator, Progressable reporter,
Counters.Counter readsCounter,
Counters.Counter writesCounter,
Progress mergePhase)
throws IOException {
return
new MergeQueue<K, V>(conf, fs, inputs, deleteInputs, codec, comparator,
reporter, null,
TaskType.REDUCE).merge(keyClass, valueClass,
mergeFactor, tmpDir,
readsCounter, writesCounter,
mergePhase);
}
示例2: merge
import org.apache.hadoop.util.Progress; //导入依赖的package包/类
public static <K extends Object, V extends Object>
RawKeyValueIterator merge(Configuration conf, FileSystem fs,
Class<K> keyClass, Class<V> valueClass,
CompressionCodec codec,
List<Segment<K, V>> segments,
int mergeFactor, Path tmpDir,
RawComparator<K> comparator, Progressable reporter,
boolean sortSegments,
Counters.Counter readsCounter,
Counters.Counter writesCounter,
Progress mergePhase,
TaskType taskType)
throws IOException {
return new MergeQueue<K, V>(conf, fs, segments, comparator, reporter,
sortSegments, codec,
taskType).merge(keyClass, valueClass,
mergeFactor, tmpDir,
readsCounter, writesCounter,
mergePhase);
}
示例3: merge
import org.apache.hadoop.util.Progress; //导入依赖的package包/类
public static <K extends Object, V extends Object>
RawKeyValueIterator merge(Configuration conf, FileSystem fs,
Class<K> keyClass, Class<V> valueClass,
CompressionCodec codec,
Path[] inputs, boolean deleteInputs,
int mergeFactor, Path tmpDir,
RawComparator<K> comparator, Progressable reporter,
Counters.Counter readsCounter,
Counters.Counter writesCounter,
Progress mergePhase)
throws IOException {
return
new MergeQueue<K, V>(conf, fs, inputs, deleteInputs, codec, comparator,
reporter, null).merge(keyClass, valueClass,
mergeFactor, tmpDir,
readsCounter, writesCounter,
mergePhase);
}
示例4: merge
import org.apache.hadoop.util.Progress; //导入依赖的package包/类
public static <K extends Object, V extends Object>
RawKeyValueIterator merge(Configuration conf, FileSystem fs,
Class<K> keyClass, Class<V> valueClass,
List<Segment<K, V>> segments,
int mergeFactor, Path tmpDir,
RawComparator<K> comparator, Progressable reporter,
boolean sortSegments,
Counters.Counter readsCounter,
Counters.Counter writesCounter,
Progress mergePhase)
throws IOException {
return new MergeQueue<K, V>(conf, fs, segments, comparator, reporter,
sortSegments,
TaskType.REDUCE).merge(keyClass, valueClass,
mergeFactor, tmpDir,
readsCounter, writesCounter,
mergePhase);
}
示例5: Context
import org.apache.hadoop.util.Progress; //导入依赖的package包/类
public Context(org.apache.hadoop.mapreduce.TaskAttemptID reduceId,
JobConf jobConf, FileSystem localFS,
TaskUmbilicalProtocol umbilical,
LocalDirAllocator localDirAllocator,
Reporter reporter, CompressionCodec codec,
Class<? extends Reducer> combinerClass,
CombineOutputCollector<K,V> combineCollector,
Counters.Counter spilledRecordsCounter,
Counters.Counter reduceCombineInputCounter,
Counters.Counter shuffledMapsCounter,
Counters.Counter reduceShuffleBytes,
Counters.Counter failedShuffleCounter,
Counters.Counter mergedMapOutputsCounter,
TaskStatus status, Progress copyPhase, Progress mergePhase,
Task reduceTask, MapOutputFile mapOutputFile,
Map<TaskAttemptID, MapOutputFile> localMapFiles) {
this.reduceId = reduceId;
this.jobConf = jobConf;
this.localFS = localFS;
this. umbilical = umbilical;
this.localDirAllocator = localDirAllocator;
this.reporter = reporter;
this.codec = codec;
this.combinerClass = combinerClass;
this.combineCollector = combineCollector;
this.spilledRecordsCounter = spilledRecordsCounter;
this.reduceCombineInputCounter = reduceCombineInputCounter;
this.shuffledMapsCounter = shuffledMapsCounter;
this.reduceShuffleBytes = reduceShuffleBytes;
this.failedShuffleCounter = failedShuffleCounter;
this.mergedMapOutputsCounter = mergedMapOutputsCounter;
this.status = status;
this.copyPhase = copyPhase;
this.mergePhase = mergePhase;
this.reduceTask = reduceTask;
this.mapOutputFile = mapOutputFile;
this.localMapFiles = localMapFiles;
}
示例6: ShuffleSchedulerImpl
import org.apache.hadoop.util.Progress; //导入依赖的package包/类
public ShuffleSchedulerImpl(JobConf job, TaskStatus status,
TaskAttemptID reduceId,
ExceptionReporter reporter,
Progress progress,
Counters.Counter shuffledMapsCounter,
Counters.Counter reduceShuffleBytes,
Counters.Counter failedShuffleCounter) {
totalMaps = job.getNumMapTasks();
abortFailureLimit = Math.max(30, totalMaps / 10);
copyTimeTracker = new CopyTimeTracker();
remainingMaps = totalMaps;
finishedMaps = new boolean[remainingMaps];
this.reporter = reporter;
this.status = status;
this.reduceId = reduceId;
this.progress = progress;
this.shuffledMapsCounter = shuffledMapsCounter;
this.reduceShuffleBytes = reduceShuffleBytes;
this.failedShuffleCounter = failedShuffleCounter;
this.startTime = Time.monotonicNow();
lastProgressTime = startTime;
referee.start();
this.maxFailedUniqueFetches = Math.min(totalMaps, 5);
this.maxFetchFailuresBeforeReporting = job.getInt(
MRJobConfig.SHUFFLE_FETCH_FAILURES, REPORT_FAILURE_LIMIT);
this.reportReadErrorImmediately = job.getBoolean(
MRJobConfig.SHUFFLE_NOTIFY_READERROR, true);
this.maxDelay = job.getLong(MRJobConfig.MAX_SHUFFLE_FETCH_RETRY_DELAY,
MRJobConfig.DEFAULT_MAX_SHUFFLE_FETCH_RETRY_DELAY);
this.maxHostFailures = job.getInt(
MRJobConfig.MAX_SHUFFLE_FETCH_HOST_FAILURES,
MRJobConfig.DEFAULT_MAX_SHUFFLE_FETCH_HOST_FAILURES);
}