hadoop TypeConverter 源码
haddop TypeConverter 代码
文件路径：/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-common/src/main/java/org/apache/hadoop/mapreduce/TypeConverter.java
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.hadoop.mapreduce;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.mapred.JobPriority;
import org.apache.hadoop.mapred.TaskCompletionEvent;
import org.apache.hadoop.mapreduce.JobStatus.State;
import org.apache.hadoop.mapreduce.v2.api.records.Counter;
import org.apache.hadoop.mapreduce.v2.api.records.CounterGroup;
import org.apache.hadoop.mapreduce.v2.api.records.Counters;
import org.apache.hadoop.mapreduce.v2.api.records.JobId;
import org.apache.hadoop.mapreduce.v2.api.records.JobReport;
import org.apache.hadoop.mapreduce.v2.api.records.JobState;
import org.apache.hadoop.mapreduce.v2.api.records.Phase;
import org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptCompletionEvent;
import org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptCompletionEventStatus;
import org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId;
import org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptState;
import org.apache.hadoop.mapreduce.v2.api.records.TaskId;
import org.apache.hadoop.mapreduce.v2.api.records.TaskState;
import org.apache.hadoop.mapreduce.v2.api.records.TaskType;
import org.apache.hadoop.mapreduce.v2.util.MRApps;
import org.apache.hadoop.util.StringUtils;
import org.apache.hadoop.yarn.api.records.ApplicationId;
import org.apache.hadoop.yarn.api.records.ApplicationReport;
import org.apache.hadoop.yarn.api.records.ApplicationResourceUsageReport;
import org.apache.hadoop.yarn.api.records.FinalApplicationStatus;
import org.apache.hadoop.yarn.api.records.NodeReport;
import org.apache.hadoop.yarn.api.records.QueueACL;
import org.apache.hadoop.yarn.api.records.QueueState;
import org.apache.hadoop.yarn.api.records.QueueUserACLInfo;
import org.apache.hadoop.yarn.api.records.YarnApplicationState;
import org.apache.hadoop.yarn.exceptions.YarnRuntimeException;
import org.apache.hadoop.yarn.factories.RecordFactory;
import org.apache.hadoop.yarn.factory.providers.RecordFactoryProvider;
public class TypeConverter {
private static RecordFactory recordFactory;
static {
recordFactory = RecordFactoryProvider.getRecordFactory(null);
}
public static org.apache.hadoop.mapred.JobID fromYarn(JobId id) {
String identifier = fromClusterTimeStamp(id.getAppId().getClusterTimestamp());
return new org.apache.hadoop.mapred.JobID(identifier, id.getId());
}
//currently there is 1-1 mapping between appid and jobid
public static org.apache.hadoop.mapreduce.JobID fromYarn(ApplicationId appID) {
String identifier = fromClusterTimeStamp(appID.getClusterTimestamp());
return new org.apache.hadoop.mapred.JobID(identifier, appID.getId());
}
public static JobId toYarn(org.apache.hadoop.mapreduce.JobID id) {
JobId jobId = recordFactory.newRecordInstance(JobId.class);
jobId.setId(id.getId()); //currently there is 1-1 mapping between appid and jobid
ApplicationId appId = ApplicationId.newInstance(
toClusterTimeStamp(id.getJtIdentifier()), id.getId());
jobId.setAppId(appId);
return jobId;
}
public static int toYarnApplicationPriority(String priority) {
JobPriority jobPriority = JobPriority.valueOf(priority);
switch (jobPriority) {
case VERY_HIGH :
return 5;
case HIGH :
return 4;
case NORMAL :
return 3;
case LOW :
return 2;
case VERY_LOW :
return 1;
case DEFAULT :
return 0;
}
throw new IllegalArgumentException("Unrecognized priority: " + priority);
}
private static String fromClusterTimeStamp(long clusterTimeStamp) {
return Long.toString(clusterTimeStamp);
}
private static long toClusterTimeStamp(String identifier) {
return Long.parseLong(identifier);
}
public static org.apache.hadoop.mapreduce.TaskType fromYarn(
TaskType taskType) {
switch (taskType) {
case MAP:
return org.apache.hadoop.mapreduce.TaskType.MAP;
case REDUCE:
return org.apache.hadoop.mapreduce.TaskType.REDUCE;
default:
throw new YarnRuntimeException("Unrecognized task type: " + taskType);
}
}
public static TaskType
toYarn(org.apache.hadoop.mapreduce.TaskType taskType) {
switch (taskType) {
case MAP:
return TaskType.MAP;
case REDUCE:
return TaskType.REDUCE;
default:
throw new YarnRuntimeException("Unrecognized task type: " + taskType);
}
}
public static org.apache.hadoop.mapred.TaskID fromYarn(TaskId id) {
return new org.apache.hadoop.mapred.TaskID(fromYarn(id.getJobId()),
fromYarn(id.getTaskType()), id.getId());
}
public static TaskId toYarn(org.apache.hadoop.mapreduce.TaskID id) {
TaskId taskId = recordFactory.newRecordInstance(TaskId.class);
taskId.setId(id.getId());
taskId.setTaskType(toYarn(id.getTaskType()));
taskId.setJobId(toYarn(id.getJobID()));
return taskId;
}
public static TaskAttemptState toYarn(
org.apache.hadoop.mapred.TaskStatus.State state) {
switch (state) {
case COMMIT_PENDING:
return TaskAttemptState.COMMIT_PENDING;
case FAILED:
case FAILED_UNCLEAN:
return TaskAttemptState.FAILED;
case KILLED:
case KILLED_UNCLEAN:
return TaskAttemptState.KILLED;
case RUNNING:
return TaskAttemptState.RUNNING;
case SUCCEEDED:
return TaskAttemptState.SUCCEEDED;
case UNASSIGNED:
return TaskAttemptState.STARTING;
default:
throw new YarnRuntimeException("Unrecognized State: " + state);
}
}
public static Phase toYarn(org.apache.hadoop.mapred.TaskStatus.Phase phase) {
switch (phase) {
case STARTING:
return Phase.STARTING;
case MAP:
return Phase.MAP;
case SHUFFLE:
return Phase.SHUFFLE;
case SORT:
return Phase.SORT;
case REDUCE:
return Phase.REDUCE;
case CLEANUP:
return Phase.CLEANUP;
default:
break;
}
throw new YarnRuntimeException("Unrecognized Phase: " + phase);
}
public static TaskCompletionEvent[] fromYarn(
TaskAttemptCompletionEvent[] newEvents) {
TaskCompletionEvent[] oldEvents =
new TaskCompletionEvent[newEvents.length];
int i = 0;
for (TaskAttemptCompletionEvent newEvent
: newEvents) {
oldEvents[i++] = fromYarn(newEvent);
}
return oldEvents;
}
public static TaskCompletionEvent fromYarn(
TaskAttemptCompletionEvent newEvent) {
return new TaskCompletionEvent(newEvent.getEventId(),
fromYarn(newEvent.getAttemptId()), newEvent.getAttemptId().getId(),
newEvent.getAttemptId().getTaskId().getTaskType().equals(TaskType.MAP),
fromYarn(newEvent.getStatus()),
newEvent.getMapOutputServerAddress());
}
public static TaskCompletionEvent.Status fromYarn(
TaskAttemptCompletionEventStatus newStatus) {
switch (newStatus) {
case FAILED:
return TaskCompletionEvent.Status.FAILED;
case KILLED:
return TaskCompletionEvent.Status.KILLED;
case OBSOLETE:
return TaskCompletionEvent.Status.OBSOLETE;
case SUCCEEDED:
return TaskCompletionEvent.Status.SUCCEEDED;
case TIPFAILED:
return TaskCompletionEvent.Status.TIPFAILED;
}
throw new YarnRuntimeException("Unrecognized status: " + newStatus);
}
public static org.apache.hadoop.mapred.TaskAttemptID fromYarn(
TaskAttemptId id) {
return new org.apache.hadoop.mapred.TaskAttemptID(fromYarn(id.getTaskId()),
id.getId());
}
public static TaskAttemptId toYarn(
org.apache.hadoop.mapred.TaskAttemptID id) {
TaskAttemptId taskAttemptId = recordFactory.newRecordInstance(TaskAttemptId.class);
taskAttemptId.setTaskId(toYarn(id.getTaskID()));
taskAttemptId.setId(id.getId());
return taskAttemptId;
}
public static TaskAttemptId toYarn(
org.apache.hadoop.mapreduce.TaskAttemptID id) {
TaskAttemptId taskAttemptId = recordFactory.newRecordInstance(TaskAttemptId.class);
taskAttemptId.setTaskId(toYarn(id.getTaskID()));
taskAttemptId.setId(id.getId());
return taskAttemptId;
}
public static org.apache.hadoop.mapreduce.Counters fromYarn(
Counters yCntrs) {
if (yCntrs == null) {
return null;
}
org.apache.hadoop.mapreduce.Counters counters =
new org.apache.hadoop.mapreduce.Counters();
for (CounterGroup yGrp : yCntrs.getAllCounterGroups().values()) {
counters.addGroup(yGrp.getName(), yGrp.getDisplayName());
for (Counter yCntr : yGrp.getAllCounters().values()) {
org.apache.hadoop.mapreduce.Counter c =
counters.findCounter(yGrp.getName(),
yCntr.getName());
// if c can be found, or it will be skipped.
if (c != null) {
c.setValue(yCntr.getValue());
}
}
}
return counters;
}
public static Counters toYarn(org.apache.hadoop.mapred.Counters counters) {
if (counters == null) {
return null;
}
Counters yCntrs = recordFactory.newRecordInstance(Counters.class);
yCntrs.addAllCounterGroups(new HashMap<String, CounterGroup>());
for (org.apache.hadoop.mapred.Counters.Group grp : counters) {
CounterGroup yGrp = recordFactory.newRecordInstance(CounterGroup.class);
yGrp.setName(grp.getName());
yGrp.setDisplayName(grp.getDisplayName());
yGrp.addAllCounters(new HashMap<String, Counter>());
for (org.apache.hadoop.mapred.Counters.Counter cntr : grp) {
Counter yCntr = recordFactory.newRecordInstance(Counter.class);
yCntr.setName(cntr.getName());
yCntr.setDisplayName(cntr.getDisplayName());
yCntr.setValue(cntr.getValue());
yGrp.setCounter(yCntr.getName(), yCntr);
}
yCntrs.setCounterGroup(yGrp.getName(), yGrp);
}
return yCntrs;
}
public static Counters toYarn(org.apache.hadoop.mapreduce.Counters counters) {
if (counters == null) {
return null;
}
Counters yCntrs = recordFactory.newRecordInstance(Counters.class);
yCntrs.addAllCounterGroups(new HashMap<String, CounterGroup>());
for (org.apache.hadoop.mapreduce.CounterGroup grp : counters) {
CounterGroup yGrp = recordFactory.newRecordInstance(CounterGroup.class);
yGrp.setName(grp.getName());
yGrp.setDisplayName(grp.getDisplayName());
yGrp.addAllCounters(new HashMap<String, Counter>());
for (org.apache.hadoop.mapreduce.Counter cntr : grp) {
Counter yCntr = recordFactory.newRecordInstance(Counter.class);
yCntr.setName(cntr.getName());
yCntr.setDisplayName(cntr.getDisplayName());
yCntr.setValue(cntr.getValue());
yGrp.setCounter(yCntr.getName(), yCntr);
}
yCntrs.setCounterGroup(yGrp.getName(), yGrp);
}
return yCntrs;
}
public static JobStatus fromYarn(JobReport jobreport, String trackingUrl) {
JobPriority jobPriority = (jobreport.getJobPriority() == null)
? JobPriority.DEFAULT
: fromYarnPriority(jobreport.getJobPriority().getPriority());
JobStatus jobStatus = new org.apache.hadoop.mapred.JobStatus(
fromYarn(jobreport.getJobId()), jobreport.getSetupProgress(),
jobreport.getMapProgress(), jobreport.getReduceProgress(),
jobreport.getCleanupProgress(), fromYarn(jobreport.getJobState()),
jobPriority, jobreport.getUser(), jobreport.getJobName(),
jobreport.getJobFile(), trackingUrl, jobreport.isUber(),
jobreport.getHistoryFile());
jobStatus.setStartTime(jobreport.getStartTime());
jobStatus.setFinishTime(jobreport.getFinishTime());
jobStatus.setFailureInfo(jobreport.getDiagnostics());
return jobStatus;
}
private static JobPriority fromYarnPriority(int priority) {
switch (priority) {
case 5 :
return JobPriority.VERY_HIGH;
case 4 :
return JobPriority.HIGH;
case 3 :
return JobPriority.NORMAL;
case 2 :
return JobPriority.LOW;
case 1 :
return JobPriority.VERY_LOW;
case 0 :
return JobPriority.DEFAULT;
default :
break;
}
return JobPriority.UNDEFINED_PRIORITY;
}
public static org.apache.hadoop.mapreduce.JobPriority
fromYarnApplicationPriority(int priority) {
switch (priority) {
case 5 :
return org.apache.hadoop.mapreduce.JobPriority.VERY_HIGH;
case 4 :
return org.apache.hadoop.mapreduce.JobPriority.HIGH;
case 3 :
return org.apache.hadoop.mapreduce.JobPriority.NORMAL;
case 2 :
return org.apache.hadoop.mapreduce.JobPriority.LOW;
case 1 :
return org.apache.hadoop.mapreduce.JobPriority.VERY_LOW;
case 0 :
return org.apache.hadoop.mapreduce.JobPriority.DEFAULT;
default :
break;
}
return org.apache.hadoop.mapreduce.JobPriority.UNDEFINED_PRIORITY;
}
public static org.apache.hadoop.mapreduce.QueueState fromYarn(
QueueState state) {
org.apache.hadoop.mapreduce.QueueState qState =
org.apache.hadoop.mapreduce.QueueState.getState(
StringUtils.toLowerCase(state.toString()));
return qState;
}
public static int fromYarn(JobState state) {
switch (state) {
case NEW:
case INITED:
return org.apache.hadoop.mapred.JobStatus.PREP;
case RUNNING:
return org.apache.hadoop.mapred.JobStatus.RUNNING;
case KILLED:
return org.apache.hadoop.mapred.JobStatus.KILLED;
case SUCCEEDED:
return org.apache.hadoop.mapred.JobStatus.SUCCEEDED;
case FAILED:
case ERROR:
return org.apache.hadoop.mapred.JobStatus.FAILED;
}
throw new YarnRuntimeException("Unrecognized job state: " + state);
}
public static org.apache.hadoop.mapred.TIPStatus fromYarn(
TaskState state) {
switch (state) {
case NEW:
case SCHEDULED:
return org.apache.hadoop.mapred.TIPStatus.PENDING;
case RUNNING:
return org.apache.hadoop.mapred.TIPStatus.RUNNING;
case KILLED:
return org.apache.hadoop.mapred.TIPStatus.KILLED;
case SUCCEEDED:
return org.apache.hadoop.mapred.TIPStatus.COMPLETE;
case FAILED:
return org.apache.hadoop.mapred.TIPStatus.FAILED;
}
throw new YarnRuntimeException("Unrecognized task state: " + state);
}
public static TaskReport fromYarn(org.apache.hadoop.mapreduce.v2.api.records.TaskReport report) {
String[] diagnostics = null;
if (report.getDiagnosticsList() != null) {
diagnostics = new String[report.getDiagnosticsCount()];
int i = 0;
for (String cs : report.getDiagnosticsList()) {
diagnostics[i++] = cs.toString();
}
} else {
diagnostics = new String[0];
}
TaskReport rep = new TaskReport(fromYarn(report.getTaskId()),
report.getProgress(), report.getTaskState().toString(),
diagnostics, fromYarn(report.getTaskState()), report.getStartTime(), report.getFinishTime(),
fromYarn(report.getCounters()));
List<org.apache.hadoop.mapreduce.TaskAttemptID> runningAtts
= new ArrayList<org.apache.hadoop.mapreduce.TaskAttemptID>();
for (org.apache.hadoop.mapreduce.v2.api.records.TaskAttemptId id
: report.getRunningAttemptsList()) {
runningAtts.add(fromYarn(id));
}
rep.setRunningTaskAttemptIds(runningAtts);
if (report.getSuccessfulAttempt() != null) {
rep.setSuccessfulAttemptId(fromYarn(report.getSuccessfulAttempt()));
}
return rep;
}
public static List<TaskReport> fromYarn(
List<org.apache.hadoop.mapreduce.v2.api.records.TaskReport> taskReports) {
List<TaskReport> reports = new ArrayList<TaskReport>();
for (org.apache.hadoop.mapreduce.v2.api.records.TaskReport r : taskReports) {
reports.add(fromYarn(r));
}
return reports;
}
public static State fromYarn(YarnApplicationState yarnApplicationState,
FinalApplicationStatus finalApplicationStatus) {
switch (yarnApplicationState) {
case NEW:
case NEW_SAVING:
case SUBMITTED:
case ACCEPTED:
return State.PREP;
case RUNNING:
return State.RUNNING;
case FINISHED:
if (finalApplicationStatus == FinalApplicationStatus.SUCCEEDED) {
return State.SUCCEEDED;
} else if (finalApplicationStatus == FinalApplicationStatus.KILLED) {
return State.KILLED;
}
case FAILED:
return State.FAILED;
case KILLED:
return State.KILLED;
}
throw new YarnRuntimeException("Unrecognized application state: " + yarnApplicationState);
}
private static final String TT_NAME_PREFIX = "tracker_";
public static TaskTrackerInfo fromYarn(NodeReport node) {
TaskTrackerInfo taskTracker =
new TaskTrackerInfo(TT_NAME_PREFIX + node.getNodeId().toString());
return taskTracker;
}
public static TaskTrackerInfo[] fromYarnNodes(List<NodeReport> nodes) {
List<TaskTrackerInfo> taskTrackers = new ArrayList<TaskTrackerInfo>();
for (NodeReport node : nodes) {
taskTrackers.add(fromYarn(node));
}
return taskTrackers.toArray(new TaskTrackerInfo[nodes.size()]);
}
public static JobStatus fromYarn(ApplicationReport application,
String jobFile) {
String trackingUrl = application.getTrackingUrl();
trackingUrl = trackingUrl == null ? "" : trackingUrl;
JobStatus jobStatus =
new JobStatus(
TypeConverter.fromYarn(application.getApplicationId()),
0.0f, 0.0f, 0.0f, 0.0f,
TypeConverter.fromYarn(application.getYarnApplicationState(), application.getFinalApplicationStatus()),
fromYarnApplicationPriority(
(application.getPriority() == null) ? 0 :
application.getPriority().getPriority()),
application.getUser(), application.getName(),
application.getQueue(), jobFile, trackingUrl, false
);
jobStatus.setSchedulingInfo(trackingUrl); // Set AM tracking url
jobStatus.setStartTime(application.getStartTime());
jobStatus.setFinishTime(application.getFinishTime());
jobStatus.setFailureInfo(application.getDiagnostics());
ApplicationResourceUsageReport resourceUsageReport =
application.getApplicationResourceUsageReport();
if (resourceUsageReport != null) {
jobStatus.setNeededMem(
(int)resourceUsageReport.getNeededResources().getMemorySize());
jobStatus.setNumReservedSlots(
resourceUsageReport.getNumReservedContainers());
jobStatus.setNumUsedSlots(resourceUsageReport.getNumUsedContainers());
jobStatus.setReservedMem(
(int)resourceUsageReport.getReservedResources().getMemorySize());
jobStatus.setUsedMem(
(int) resourceUsageReport.getUsedResources().getMemorySize());
}
return jobStatus;
}
public static JobStatus[] fromYarnApps(List<ApplicationReport> applications,
Configuration conf) {
List<JobStatus> jobStatuses = new ArrayList<JobStatus>();
for (ApplicationReport application : applications) {
// each applicationReport has its own jobFile
org.apache.hadoop.mapreduce.JobID jobId =
TypeConverter.fromYarn(application.getApplicationId());
jobStatuses.add(TypeConverter.fromYarn(application,
MRApps.getJobFile(conf, application.getUser(), jobId)));
}
return jobStatuses.toArray(new JobStatus[jobStatuses.size()]);
}
public static QueueInfo fromYarn(org.apache.hadoop.yarn.api.records.QueueInfo
queueInfo, Configuration conf) {
QueueInfo toReturn = new QueueInfo(queueInfo.getQueueName(), "Capacity: " +
queueInfo.getCapacity() * 100 + ", MaximumCapacity: " +
(queueInfo.getMaximumCapacity() < 0 ? "UNDEFINED" :
queueInfo.getMaximumCapacity() * 100) + ", CurrentCapacity: " +
queueInfo.getCurrentCapacity() * 100, fromYarn(queueInfo.getQueueState()),
TypeConverter.fromYarnApps(queueInfo.getApplications(), conf));
List<QueueInfo> childQueues = new ArrayList<QueueInfo>();
for(org.apache.hadoop.yarn.api.records.QueueInfo childQueue :
queueInfo.getChildQueues()) {
childQueues.add(fromYarn(childQueue, conf));
}
toReturn.setQueueChildren(childQueues);
return toReturn;
}
public static QueueInfo[] fromYarnQueueInfo(
List<org.apache.hadoop.yarn.api.records.QueueInfo> queues,
Configuration conf) {
List<QueueInfo> queueInfos = new ArrayList<QueueInfo>(queues.size());
for (org.apache.hadoop.yarn.api.records.QueueInfo queue : queues) {
queueInfos.add(TypeConverter.fromYarn(queue, conf));
}
return queueInfos.toArray(new QueueInfo[queueInfos.size()]);
}
public static QueueAclsInfo[] fromYarnQueueUserAclsInfo(
List<QueueUserACLInfo> userAcls) {
List<QueueAclsInfo> acls = new ArrayList<QueueAclsInfo>();
for (QueueUserACLInfo aclInfo : userAcls) {
List<String> operations = new ArrayList<String>();
for (QueueACL qAcl : aclInfo.getUserAcls()) {
operations.add(qAcl.toString());
}
QueueAclsInfo acl =
new QueueAclsInfo(aclInfo.getQueueName(),
operations.toArray(new String[operations.size()]));
acls.add(acl);
}
return acls.toArray(new QueueAclsInfo[acls.size()]);
}
}
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