/**
* 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.yarn.server.applicationhistoryservice.metrics.timeline;
import org.apache.hadoop.metrics2.sink.timeline.MetricHostAggregate;
import org.apache.hadoop.metrics2.sink.timeline.TimelineMetric;
import org.apache.hadoop.metrics2.sink.timeline.TimelineMetrics;
import org.apache.hadoop.yarn.server.applicationhistoryservice.metrics.timeline.aggregators.TimelineClusterMetric;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
import java.util.TreeMap;
public class MetricTestHelper {
public static MetricHostAggregate createMetricHostAggregate(double max, double min, int numberOfSamples, double sum) {
MetricHostAggregate expectedAggregate = new MetricHostAggregate();
expectedAggregate.setMax(max);
expectedAggregate.setMin(min);
expectedAggregate.setNumberOfSamples(numberOfSamples);
expectedAggregate.setSum(sum);
return expectedAggregate;
}
public static TimelineMetrics prepareSingleTimelineMetric(long startTime,
String host,
String metricName,
double val) {
return prepareSingleTimelineMetric(startTime, host, null, metricName, val);
}
public static TimelineMetrics prepareSingleTimelineMetric(long startTime,
String host,
String instanceId,
String metricName,
double val) {
TimelineMetrics m = new TimelineMetrics();
m.setMetrics(Arrays.asList(
createTimelineMetric(startTime, metricName, host, null, instanceId, val)));
return m;
}
public static TimelineMetrics prepareSingleTimelineMetric(long startTime,
String host,
String appId,
String instanceId,
String metricName,
double val) {
TimelineMetrics m = new TimelineMetrics();
m.setMetrics(Arrays.asList(
createTimelineMetric(startTime, metricName, host, appId, instanceId, val)));
return m;
}
public static TimelineMetric createTimelineMetric(long startTime,
String metricName,
String host,
String appId,
String instanceId,
double val) {
TimelineMetric m = new TimelineMetric();
m.setHostName(host);
m.setAppId(appId != null ? appId : "host");
m.setInstanceId(instanceId);
m.setMetricName(metricName);
m.setStartTime(startTime);
TreeMap<Long, Double> vals = new TreeMap<Long, Double>();
vals.put(startTime + 15000l, val);
vals.put(startTime + 30000l, val);
vals.put(startTime + 45000l, val);
vals.put(startTime + 60000l, val);
m.setMetricValues(vals);
return m;
}
public static TimelineMetric createEmptyTimelineMetric(long startTime) {
TimelineMetric metric = new TimelineMetric();
metric.setMetricName("disk_used");
metric.setAppId("test_app");
metric.setInstanceId("test_instance");
metric.setHostName("test_host");
metric.setTimestamp(startTime);
return metric;
}
public static TimelineClusterMetric createEmptyTimelineClusterMetric(
String name, long startTime) {
TimelineClusterMetric metric = new TimelineClusterMetric(name,
"test_app", "instance_id", startTime, null);
return metric;
}
public static TimelineClusterMetric createEmptyTimelineClusterMetric(
long startTime) {
return createEmptyTimelineClusterMetric("disk_used", startTime);
}
}