HBASE-19450 Addendum Limit logging of chore execution time at INFO to once per 5 minutes.

* Ensure MovingAverage related classes are IA.Private
* Move trace logging into MovingAverage class

Signed-off-by: Duo Zhang <zhangduo@apache.org>
This commit is contained in:
Sean Busbey 2019-11-15 20:34:54 -06:00
parent e69431ae8c
commit baf8849050
8 changed files with 51 additions and 36 deletions

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@ -81,7 +81,9 @@ public abstract class ScheduledChore implements Runnable {
*/
private final Stoppable stopper;
private final MovingAverage<Void> timeMeasurement = new WindowMovingAverage();
private final MovingAverage<Void> timeMeasurement;
private static final long FIVE_MINUTES_IN_NANOS = TimeUnit.MINUTES.toNanos(5L);
private long lastLog = System.nanoTime();
interface ChoreServicer {
/**
@ -122,11 +124,7 @@ public abstract class ScheduledChore implements Runnable {
@InterfaceAudience.Private
@VisibleForTesting
protected ScheduledChore() {
this.name = null;
this.stopper = null;
this.period = 0;
this.initialDelay = DEFAULT_INITIAL_DELAY;
this.timeUnit = DEFAULT_TIME_UNIT;
this("TestChore", null, 0, DEFAULT_INITIAL_DELAY, DEFAULT_TIME_UNIT);
}
/**
@ -167,6 +165,7 @@ public abstract class ScheduledChore implements Runnable {
this.period = period;
this.initialDelay = initialDelay < 0 ? 0 : initialDelay;
this.timeUnit = unit;
this.timeMeasurement = new WindowMovingAverage(name);
}
/**
@ -191,8 +190,11 @@ public abstract class ScheduledChore implements Runnable {
chore();
return null;
});
LOG.info(String.format("%s average execution time: %.2f ns.", getName(),
timeMeasurement.getAverageTime()));
if (LOG.isInfoEnabled() && (System.nanoTime() - lastLog > FIVE_MINUTES_IN_NANOS)) {
LOG.info("{} average execution time: {} ns.", getName(),
(long)(timeMeasurement.getAverageTime()));
lastLog = System.nanoTime();
}
}
} catch (Throwable t) {
if (LOG.isErrorEnabled()) LOG.error("Caught error", t);

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@ -24,26 +24,26 @@ import org.apache.yetus.audience.InterfaceAudience;
* EMA is similar to {@link WeightedMovingAverage} in weighted, but the weighting factor decrease
* exponentially. It brings benefits that it is more sensitive, and can see the trends easily.
*/
@InterfaceAudience.Public
@InterfaceAudience.Private
public class ExponentialMovingAverage extends WindowMovingAverage {
private double alpha;
private double previousAverage;
private double currentAverage;
public ExponentialMovingAverage() {
this(DEFAULT_SIZE);
public ExponentialMovingAverage(String label) {
this(label, DEFAULT_SIZE);
}
public ExponentialMovingAverage(double alpha) {
this(DEFAULT_SIZE, alpha);
public ExponentialMovingAverage(String label, double alpha) {
this(label, DEFAULT_SIZE, alpha);
}
public ExponentialMovingAverage(int size) {
this(size, (double) 2 / (1 + size));
public ExponentialMovingAverage(String label, int size) {
this(label, size, (double) 2 / (1 + size));
}
public ExponentialMovingAverage(int size, double alpha) {
super(size);
public ExponentialMovingAverage(String label, int size, double alpha) {
super(label, size);
this.previousAverage = -1.0;
this.currentAverage = 0.0;
this.alpha = alpha;

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@ -29,10 +29,16 @@ import org.slf4j.LoggerFactory;
* <br>
* In different situation, different {@link MovingAverage} algorithm can be used based on needs.
*/
@InterfaceAudience.Public
@InterfaceAudience.Private
public abstract class MovingAverage<T> {
private final static Logger LOG = LoggerFactory.getLogger(MovingAverage.class);
protected final String label;
protected MovingAverage(String label) {
this.label = label;
}
/**
* Mark start time of an execution.
* @return time in ns.
@ -57,12 +63,12 @@ public abstract class MovingAverage<T> {
*/
public T measure(TimeMeasurable<T> measurable) {
long startTime = start();
LOG.debug("Start to measure at: {} ns.", startTime);
LOG.trace("{} - start to measure at: {} ns.", label, startTime);
// Here may throw exceptions which should be taken care by caller, not here.
// If exception occurs, this time wouldn't count.
T result = measurable.measure();
long elapsed = stop(startTime);
LOG.debug("Elapse: {} ns.", elapsed);
LOG.trace("{} - elapse: {} ns.", label, elapsed);
updateMostRecentTime(elapsed);
return result;
}

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@ -23,12 +23,13 @@ import org.apache.yetus.audience.InterfaceAudience;
/**
* SMA measure the overall average execution time of a specific method.
*/
@InterfaceAudience.Public
@InterfaceAudience.Private
public class SimpleMovingAverage extends MovingAverage {
private double averageTime = 0.0;
protected long count = 0;
public SimpleMovingAverage() {
public SimpleMovingAverage(String label) {
super(label);
this.averageTime = 0.0;
this.count = 0;
}

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@ -24,7 +24,7 @@ import org.apache.yetus.audience.InterfaceAudience;
* Methods that implement this interface can be measured elapsed time.
* It works together with {@link MovingAverage} to take effect.
*/
@InterfaceAudience.Public
@InterfaceAudience.Private
public interface TimeMeasurable<T> {
/**

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@ -24,17 +24,17 @@ import org.apache.yetus.audience.InterfaceAudience;
* Different from SMA {@link SimpleMovingAverage}, WeightedMovingAverage gives each data different
* weight. And it is based on {@link WindowMovingAverage}, such that it only focus on the last N.
*/
@InterfaceAudience.Public
@InterfaceAudience.Private
public class WeightedMovingAverage extends WindowMovingAverage {
private int[] coefficient;
private int denominator;
public WeightedMovingAverage() {
this(DEFAULT_SIZE);
public WeightedMovingAverage(String label) {
this(label, DEFAULT_SIZE);
}
public WeightedMovingAverage(int size) {
super(size);
public WeightedMovingAverage(String label, int size) {
super(label, size);
int length = getNumberOfStatistics();
denominator = length * (length + 1) / 2;
coefficient = new int[length];

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@ -24,7 +24,7 @@ import org.apache.yetus.audience.InterfaceAudience;
* Instead of calculate a whole time average, this class focus on the last N.
* The last N is stored in a circle array.
*/
@InterfaceAudience.Public
@InterfaceAudience.Private
public class WindowMovingAverage extends MovingAverage {
protected final static int DEFAULT_SIZE = 5;
@ -35,11 +35,12 @@ public class WindowMovingAverage extends MovingAverage {
// If it travels a round.
protected boolean oneRound;
public WindowMovingAverage() {
this(DEFAULT_SIZE);
public WindowMovingAverage(String label) {
this(label, DEFAULT_SIZE);
}
public WindowMovingAverage(int size) {
public WindowMovingAverage(String label, int size) {
super(label);
this.lastN = new long[size <= 0 ? DEFAULT_SIZE : size];
this.mostRecent = -1;
this.oneRound = false;

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@ -22,8 +22,10 @@ import org.apache.hadoop.hbase.HBaseClassTestRule;
import org.apache.hadoop.hbase.testclassification.SmallTests;
import org.junit.Assert;
import org.junit.ClassRule;
import org.junit.Rule;
import org.junit.Test;
import org.junit.experimental.categories.Category;
import org.junit.rules.TestName;
@Category(SmallTests.class)
public class TestMovingAverage {
@ -32,12 +34,15 @@ public class TestMovingAverage {
public static final HBaseClassTestRule CLASS_RULE =
HBaseClassTestRule.forClass(TestMovingAverage.class);
@Rule
public TestName name = new TestName();
private long[] data = {1, 12, 13, 24, 25, 26, 37, 38, 39, 40};
private double delta = 0.1;
@Test
public void testSimpleMovingAverage() throws Exception {
MovingAverage<?> algorithm = new SimpleMovingAverage();
MovingAverage<?> algorithm = new SimpleMovingAverage(name.getMethodName());
int index = 0;
// [1, 12, 13, 24]
int bound = 4;
@ -67,7 +72,7 @@ public class TestMovingAverage {
@Test
public void testWindowMovingAverage() throws Exception {
// Default size is 5.
MovingAverage<?> algorithm = new WindowMovingAverage();
MovingAverage<?> algorithm = new WindowMovingAverage(name.getMethodName());
int index = 0;
// [1, 12, 13, 24]
int bound = 4;
@ -97,7 +102,7 @@ public class TestMovingAverage {
@Test
public void testWeightedMovingAverage() throws Exception {
// Default size is 5.
MovingAverage<?> algorithm = new WeightedMovingAverage();
MovingAverage<?> algorithm = new WeightedMovingAverage(name.getMethodName());
int index = 0;
// [1, 12, 13, 24]
int bound = 4;
@ -127,7 +132,7 @@ public class TestMovingAverage {
@Test
public void testExponentialMovingAverage() throws Exception {
// [1, 12, 13, 24, 25, 26, 37, 38, 39, 40]
MovingAverage<?> algorithm = new ExponentialMovingAverage();
MovingAverage<?> algorithm = new ExponentialMovingAverage(name.getMethodName());
int index = 0;
int bound = 5;
for (; index < bound; index++) {