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/*
* Copyright (C) 2012-2015 DataStax Inc.
*
* Licensed 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 com.datastax.driver.core;
import com.datastax.driver.core.exceptions.*;
import com.datastax.driver.$internal.com.google.common.collect.ImmutableSet;
import com.datastax.driver.$internal.com.google.common.util.concurrent.Futures;
import com.datastax.driver.$internal.com.google.common.util.concurrent.ListenableFuture;
import com.datastax.driver.$internal.com.google.common.util.concurrent.SettableFuture;
import org.HdrHistogram.Histogram;
import org.HdrHistogram.Recorder;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.Set;
import java.util.concurrent.*;
import static com.datastax.driver.$internal.com.google.common.base.Preconditions.checkArgument;
import static java.util.concurrent.TimeUnit.*;
/**
* A {@link LatencyTracker} that records query latencies over a sliding time interval, and exposes an API to retrieve
* the latency at a given percentile.
*
* Percentiles may be computed separately for different categories of requests; this is implementation-dependent and
* determined by {@link #computeKey(Host, Statement, Exception)}.
*
* This class is used by percentile-aware components such as
* {@link QueryLogger.Builder#withDynamicThreshold(PercentileTracker, double)} QueryLogger} and
* {@link com.datastax.driver.core.policies.PercentileSpeculativeExecutionPolicy}.
*
* It uses HdrHistogram to record latencies:
* for each category, there is a "live" histogram where current latencies are recorded, and a "cached", read-only
* histogram that is used when clients call {@link #getLatencyAtPercentile(Host, Statement, Exception, double)}. Each
* time the cached histogram becomes older than the interval, the two histograms are switched. Statistics will not be
* available during the first interval at cluster startup, since we don't have a cached histogram yet.
*/
public abstract class PercentileTracker implements LatencyTracker {
private static final Logger logger = LoggerFactory.getLogger(PercentileTracker.class);
private final long highestTrackableLatencyMillis;
private final int numberOfSignificantValueDigits;
private final int minRecordedValues;
private final long intervalMs;
// The "live" recorders: this is where we store the latencies received from the cluster
private final ConcurrentMap recorders;
// The cached histograms, corresponding to the previous interval. This is where we get the percentiles from when the
// user requests them. Each histogram is valid for a given duration, when it gets stale we request a new one from
// the corresponding recorder.
private final ConcurrentMap cachedHistograms;
/**
* Builds a new instance.
*
* @see Builder
*/
protected PercentileTracker(long highestTrackableLatencyMillis,
int numberOfSignificantValueDigits,
int minRecordedValues,
long intervalMs) {
this.highestTrackableLatencyMillis = highestTrackableLatencyMillis;
this.numberOfSignificantValueDigits = numberOfSignificantValueDigits;
this.minRecordedValues = minRecordedValues;
this.intervalMs = intervalMs;
this.recorders = new ConcurrentHashMap();
this.cachedHistograms = new ConcurrentHashMap();
}
/**
* Computes a key used to categorize measurements. Measurements with the same key will be recorded in the same
* histogram.
*
* It's recommended to keep the number of distinct keys low, in order to limit the memory footprint of the
* histograms.
*
* @param host the host that was queried.
* @param statement the statement that was executed.
* @param exception if the query failed, the corresponding exception.
* @return the key.
*/
protected abstract Object computeKey(Host host, Statement statement, Exception exception);
@Override
public void update(Host host, Statement statement, Exception exception, long newLatencyNanos) {
if (!include(host, statement, exception))
return;
long latencyMs = NANOSECONDS.toMillis(newLatencyNanos);
try {
Recorder recorder = getRecorder(host, statement, exception);
if (recorder != null)
recorder.recordValue(latencyMs);
} catch (ArrayIndexOutOfBoundsException e) {
logger.warn("Got request with latency of {} ms, which exceeds the configured maximum trackable value {}",
latencyMs, highestTrackableLatencyMillis);
}
}
/**
* Returns the request latency at a given percentile.
*
* @param host the host (if this is relevant in the way percentiles are categorized).
* @param statement the statement (if this is relevant in the way percentiles are categorized).
* @param exception the exception (if this is relevant in the way percentiles are categorized).
* @param percentile the percentile (for example, {@code 99.0} for the 99th percentile).
* @return the latency (in milliseconds) at the given percentile, or a negative value if it's not available yet.
* @see #computeKey(Host, Statement, Exception)
*/
public long getLatencyAtPercentile(Host host, Statement statement, Exception exception, double percentile) {
checkArgument(percentile >= 0.0 && percentile < 100,
"percentile must be between 0.0 and 100 (was %s)", percentile);
Histogram histogram = getLastIntervalHistogram(host, statement, exception);
if (histogram == null || histogram.getTotalCount() < minRecordedValues)
return -1;
return histogram.getValueAtPercentile(percentile);
}
private Recorder getRecorder(Host host, Statement statement, Exception exception) {
Object key = computeKey(host, statement, exception);
if (key == null)
return null;
Recorder recorder = recorders.get(key);
if (recorder == null) {
recorder = new Recorder(highestTrackableLatencyMillis, numberOfSignificantValueDigits);
Recorder old = recorders.putIfAbsent(key, recorder);
if (old != null) {
// We got beaten at creating the recorder, use the actual instance and discard ours
recorder = old;
} else {
// Also set an empty cache entry to remember the time we started recording:
cachedHistograms.putIfAbsent(key, CachedHistogram.empty());
}
}
return recorder;
}
/**
* @return null if no histogram is available yet (no entries recorded, or not for long enough)
*/
private Histogram getLastIntervalHistogram(Host host, Statement statement, Exception exception) {
Object key = computeKey(host, statement, exception);
if (key == null)
return null;
try {
while (true) {
CachedHistogram entry = cachedHistograms.get(key);
if (entry == null)
return null;
long age = System.currentTimeMillis() - entry.timestamp;
if (age < intervalMs) { // current histogram is recent enough
return entry.histogram.get();
} else { // need to refresh
Recorder recorder = recorders.get(key);
// intervalMs should be much larger than the time it takes to replace a histogram, so this future should never block
Histogram staleHistogram = entry.histogram.get(0, MILLISECONDS);
SettableFuture future = SettableFuture.create();
CachedHistogram newEntry = new CachedHistogram(future);
if (cachedHistograms.replace(key, entry, newEntry)) {
// Only get the new histogram if we successfully replaced the cache entry.
// This ensures that only one thread will do it.
Histogram newHistogram = recorder.getIntervalHistogram(staleHistogram);
future.set(newHistogram);
return newHistogram;
}
// If we couldn't replace the entry it means we raced, so loop to try again
}
}
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
return null;
} catch (ExecutionException e) {
throw new DriverInternalError("Unexpected error", e.getCause());
} catch (TimeoutException e) {
throw new DriverInternalError("Unexpected timeout while getting histogram", e);
}
}
/**
* A histogram and the timestamp at which it was retrieved.
* The data is only relevant for (timestamp + intervalMs); after that, the histogram is stale and we want to
* retrieve a new one.
*/
static class CachedHistogram {
final ListenableFuture histogram;
final long timestamp;
CachedHistogram(ListenableFuture histogram) {
this.histogram = histogram;
this.timestamp = System.currentTimeMillis();
}
static CachedHistogram empty() {
return new CachedHistogram(Futures.immediateFuture(null));
}
}
@Override
public void onRegister(Cluster cluster) {
// nothing by default
}
@Override
public void onUnregister(Cluster cluster) {
// nothing by default
}
/**
* Determines whether a particular measurement should be included.
*
* This is used to ignore measurements that could skew the statistics; for example, we typically want to ignore
* invalid query errors because they have a very low latency and would make a given cluster/host appear faster than
* it really is.
*
* @param host the host that was queried.
* @param statement the statement that was executed.
* @param exception if the query failed, the corresponding exception.
* @return whether the measurement should be included.
*/
protected boolean include(Host host, Statement statement, Exception exception) {
// query was successful: always consider
if (exception == null)
return true;
// filter out "fast" errors
// TODO this was copy/pasted from LatencyAwarePolicy, maybe it could be refactored as a shared method
return !EXCLUDED_EXCEPTIONS.contains(exception.getClass());
}
/**
* A set of DriverException subclasses that we should prevent from updating the host's score.
* The intent behind it is to filter out "fast" errors: when a host replies with such errors,
* it usually does so very quickly, because it did not involve any actual
* coordination work. Such errors are not good indicators of the host's responsiveness,
* and tend to make the host's score look better than it actually is.
*/
private static final Set> EXCLUDED_EXCEPTIONS = ImmutableSet.>of(
UnavailableException.class, // this is done via the snitch and is usually very fast
OverloadedException.class,
BootstrappingException.class,
UnpreparedException.class,
QueryValidationException.class // query validation also happens at early stages in the coordinator
);
/**
* Base class for {@code PercentileTracker} implementation builders.
*
* @param the type of the concrete builder implementation.
* @param the type of the object to build.
*/
public static abstract class Builder {
protected final long highestTrackableLatencyMillis;
protected int numberOfSignificantValueDigits = 3;
protected int minRecordedValues = 1000;
protected long intervalMs = MINUTES.toMillis(5);
Builder(long highestTrackableLatencyMillis) {
this.highestTrackableLatencyMillis = highestTrackableLatencyMillis;
}
protected abstract B self();
/**
* Sets the number of significant decimal digits to which histograms will maintain value
* resolution and separation. This must be an integer between 0 and 5.
*
* If not set explicitly, this value defaults to 3.
*
* See the HdrHistogram Javadocs
* for a more detailed explanation on how this parameter affects the resolution of recorded samples.
*
* @param numberOfSignificantValueDigits the new value.
* @return this builder.
*/
public B withNumberOfSignificantValueDigits(int numberOfSignificantValueDigits) {
this.numberOfSignificantValueDigits = numberOfSignificantValueDigits;
return self();
}
/**
* Sets the minimum number of values that must be recorded for a host before we consider
* the sample size significant.
*
* If this count is not reached during a given interval,
* {@link #getLatencyAtPercentile(Host, Statement, Exception, double)} will return a negative value, indicating
* that statistics are not available. In particular, this is true during the first interval.
*
* If not set explicitly, this value default to 1000.
*
* @param minRecordedValues the new value.
* @return this builder.
*/
public B withMinRecordedValues(int minRecordedValues) {
this.minRecordedValues = minRecordedValues;
return self();
}
/**
* Sets the time interval over which samples are recorded.
*
* For each host, there is a "live" histogram where current latencies are recorded, and a "cached", read-only
* histogram that is used when clients call {@link #getLatencyAtPercentile(Host, Statement, Exception, double)}.
* Each time the cached histogram becomes older than the interval, the two histograms are switched. Note that
* statistics will not be available during the first interval at cluster startup, since we don't have a cached
* histogram yet.
*
* If not set explicitly, this value defaults to 5 minutes.
*
* @param interval the new interval.
* @param unit the unit that the interval is expressed in.
* @return this builder.
*/
public B withInterval(long interval, TimeUnit unit) {
this.intervalMs = MILLISECONDS.convert(interval, unit);
return self();
}
/**
* Builds the {@code PercentileTracker} instance configured with this builder.
*
* @return the instance.
*/
public abstract T build();
}
}
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