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Posted to commits@hbase.apache.org by ec...@apache.org on 2016/01/19 21:24:24 UTC
[2/2] hbase git commit: HBASE-14058 Stabilizing default heap memory
tuner
HBASE-14058 Stabilizing default heap memory tuner
Signed-off-by: Elliott Clark <ec...@apache.org>
Project: http://git-wip-us.apache.org/repos/asf/hbase/repo
Commit: http://git-wip-us.apache.org/repos/asf/hbase/commit/e738e69f
Tree: http://git-wip-us.apache.org/repos/asf/hbase/tree/e738e69f
Diff: http://git-wip-us.apache.org/repos/asf/hbase/diff/e738e69f
Branch: refs/heads/branch-1.2
Commit: e738e69f8cc59581a454207483aca42e7f314396
Parents: 4fb7bab
Author: abhilak <ab...@gmail.com>
Authored: Wed Jul 22 11:30:18 2015 -0700
Committer: Elliott Clark <ec...@apache.org>
Committed: Tue Jan 19 12:23:52 2016 -0800
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.../regionserver/DefaultHeapMemoryTuner.java | 93 +++++++++++++-------
1 file changed, 63 insertions(+), 30 deletions(-)
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http://git-wip-us.apache.org/repos/asf/hbase/blob/e738e69f/hbase-server/src/main/java/org/apache/hadoop/hbase/regionserver/DefaultHeapMemoryTuner.java
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diff --git a/hbase-server/src/main/java/org/apache/hadoop/hbase/regionserver/DefaultHeapMemoryTuner.java b/hbase-server/src/main/java/org/apache/hadoop/hbase/regionserver/DefaultHeapMemoryTuner.java
index 62db9e2..b6e81dd 100644
--- a/hbase-server/src/main/java/org/apache/hadoop/hbase/regionserver/DefaultHeapMemoryTuner.java
+++ b/hbase-server/src/main/java/org/apache/hadoop/hbase/regionserver/DefaultHeapMemoryTuner.java
@@ -48,20 +48,24 @@ import org.apache.hadoop.hbase.util.RollingStatCalculator;
* same amount. If none of them is sufficient we do statistical analysis on number of cache misses
* and flushes to determine tuner direction. Based on these statistics we decide the tuner
* direction. If we are not confident about which step direction to take we do nothing and wait for
- * next iteration. On expectation we will be tuning for at least 22% tuner calls. The number of
+ * next iteration. On expectation we will be tuning for at least 10% tuner calls. The number of
* past periods to consider for statistics calculation can be specified in config by
* <i>hbase.regionserver.heapmemory.autotuner.lookup.periods</i>. Also these many initial calls to
* tuner will be ignored (cache is warming up and we leave the system to reach steady state).
* After the tuner takes a step, in next call we insure that last call was indeed helpful and did
* not do us any harm. If not then we revert the previous step. The step size is dynamic and it
- * changes based on current and previous tuning direction. When last tuner step was NEUTRAL
- * and current tuning step is not NEUTRAL then we assume we are restarting the tuning process and
- * step size is changed to maximum allowed size which can be specified in config by
- * <i>hbase.regionserver.heapmemory.autotuner.step.max</i>. If we are reverting the previous step
- * then we decrease step size to half. This decrease is similar to binary search where we try to
- * reach the most desired value. The minimum step size can be specified in config by
- * <i>hbase.regionserver.heapmemory.autotuner.step.min</i>. In other cases we leave step size
- * unchanged.
+ * changes based on current and past few tuning directions and their step sizes. We maintain a
+ * parameter <i>decayingAvgTunerStepSize</i> which is sum of past tuner steps with
+ * sign(positive for increase in memstore and negative for increase in block cache). But rather
+ * than simple sum it is calculated by giving more priority to the recent tuning steps.
+ * When last few tuner steps were NETURAL then we assume we are restarting the tuning process and
+ * step size is updated to maximum allowed size which can be specified in config by
+ * <i>hbase.regionserver.heapmemory.autotuner.step.max</i>. If in a particular tuning operation
+ * the step direction is opposite to what indicated by <i>decayingTunerStepSizeSum</i>
+ * we decrease the step size by half. Step size does not change in other tuning operations.
+ * When step size gets below a certain threshold then the following tuner operations are
+ * considered to be neutral. The minimum step size can be specified in config by
+ * <i>hbase.regionserver.heapmemory.autotuner.step.min</i>.
*/
@InterfaceAudience.Private
class DefaultHeapMemoryTuner implements HeapMemoryTuner {
@@ -74,9 +78,9 @@ class DefaultHeapMemoryTuner implements HeapMemoryTuner {
public static final String NUM_PERIODS_TO_IGNORE =
"hbase.regionserver.heapmemory.autotuner.ignored.periods";
// Maximum step size that the tuner can take
- public static final float DEFAULT_MAX_STEP_VALUE = 0.08f; // 8%
+ public static final float DEFAULT_MAX_STEP_VALUE = 0.04f; // 4%
// Minimum step size that the tuner can take
- public static final float DEFAULT_MIN_STEP_VALUE = 0.005f; // 0.5%
+ public static final float DEFAULT_MIN_STEP_VALUE = 0.00125f; // 0.125%
// If current block cache size or memstore size in use is below this level relative to memory
// provided to it then corresponding component will be considered to have sufficient memory
public static final float DEFAULT_SUFFICIENT_MEMORY_LEVEL_VALUE = 0.5f; // 50%
@@ -85,6 +89,9 @@ class DefaultHeapMemoryTuner implements HeapMemoryTuner {
public static final int DEFAULT_LOOKUP_PERIODS = 60;
public static final int DEFAULT_NUM_PERIODS_IGNORED = 60;
private static final TunerResult NO_OP_TUNER_RESULT = new TunerResult(false);
+ // If deviation of tuner step size gets below this value then it means past few periods were
+ // NEUTRAL(given that last tuner period was also NEUTRAL).
+ private static final double TUNER_STEP_EPS = 1e-6;
private Log LOG = LogFactory.getLog(DefaultHeapMemoryTuner.class);
private TunerResult TUNER_RESULT = new TunerResult(true);
@@ -106,9 +113,14 @@ class DefaultHeapMemoryTuner implements HeapMemoryTuner {
private RollingStatCalculator rollingStatsForCacheMisses;
private RollingStatCalculator rollingStatsForFlushes;
private RollingStatCalculator rollingStatsForEvictions;
+ private RollingStatCalculator rollingStatsForTunerSteps;
// Set step size to max value for tuning, this step size will adjust dynamically while tuning
private float step = DEFAULT_MAX_STEP_VALUE;
private StepDirection prevTuneDirection = StepDirection.NEUTRAL;
+ //positive means memstore's size was increased
+ //It is not just arithmetic sum of past tuner periods. More priority is given to recent
+ //tuning steps.
+ private double decayingTunerStepSizeSum = 0;
@Override
public TunerResult tune(TunerContext context) {
@@ -124,6 +136,7 @@ class DefaultHeapMemoryTuner implements HeapMemoryTuner {
if (ignoreInitialPeriods < numPeriodsToIgnore) {
// Ignoring the first few tuner periods
ignoreInitialPeriods++;
+ rollingStatsForTunerSteps.insertDataValue(0);
return NO_OP_TUNER_RESULT;
}
String tunerLog = "";
@@ -190,30 +203,33 @@ class DefaultHeapMemoryTuner implements HeapMemoryTuner {
}
// If we are not reverting. We try to tune memory sizes by looking at cache misses / flushes.
if (!isReverting){
- // mean +- deviation/2 is considered to be normal
+ // mean +- deviation*0.8 is considered to be normal
// below it its consider low and above it is considered high.
// We can safely assume that the number cache misses, flushes are normally distributed over
// past periods and hence on all the above mentioned classes (normal, high and low)
- // are equally likely with 33% probability each. Hence there is very good probability that
- // we will not always fall in default step.
+ // are likely to occur with probability 56%, 22%, 22% respectively. Hence there is at
+ // least ~10% probability that we will not fall in NEUTRAL step.
+ // This optimization solution is feedback based and we revert when we
+ // dont find our steps helpful. Hence we want to do tuning only when we have clear
+ // indications because too many unnecessary tuning may affect the performance of cluster.
if ((double)cacheMissCount < rollingStatsForCacheMisses.getMean() -
- rollingStatsForCacheMisses.getDeviation()/2.00 &&
+ rollingStatsForCacheMisses.getDeviation()*0.80 &&
(double)totalFlushCount < rollingStatsForFlushes.getMean() -
- rollingStatsForFlushes.getDeviation()/2.00) {
+ rollingStatsForFlushes.getDeviation()*0.80) {
// Everything is fine no tuning required
newTuneDirection = StepDirection.NEUTRAL;
} else if ((double)cacheMissCount > rollingStatsForCacheMisses.getMean() +
- rollingStatsForCacheMisses.getDeviation()/2.00 &&
+ rollingStatsForCacheMisses.getDeviation()*0.80 &&
(double)totalFlushCount < rollingStatsForFlushes.getMean() -
- rollingStatsForFlushes.getDeviation()/2.00) {
+ rollingStatsForFlushes.getDeviation()*0.80) {
// more misses , increasing cache size
newTuneDirection = StepDirection.INCREASE_BLOCK_CACHE_SIZE;
tunerLog +=
"Increasing block cache size as observed increase in number of cache misses.";
} else if ((double)cacheMissCount < rollingStatsForCacheMisses.getMean() -
- rollingStatsForCacheMisses.getDeviation()/2.00 &&
+ rollingStatsForCacheMisses.getDeviation()*0.80 &&
(double)totalFlushCount > rollingStatsForFlushes.getMean() +
- rollingStatsForFlushes.getDeviation()/2.00) {
+ rollingStatsForFlushes.getDeviation()*0.80) {
// more flushes , increasing memstore size
newTuneDirection = StepDirection.INCREASE_MEMSTORE_SIZE;
tunerLog += "Increasing memstore size as observed increase in number of flushes.";
@@ -228,32 +244,48 @@ class DefaultHeapMemoryTuner implements HeapMemoryTuner {
}
}
}
- // Adjusting step size for tuning to get to steady state.
+ // Adjusting step size for tuning to get to steady state or restart from steady state.
// Even if the step size was 4% and 32 GB memory size, we will be shifting 1 GB back and forth
- // per tuner operation and it can affect the performance of cluster
- if (prevTuneDirection == StepDirection.NEUTRAL && newTuneDirection != StepDirection.NEUTRAL) {
- // Restarting the tuning from steady state.
+ // per tuner operation and it can affect the performance of cluster so we keep on decreasing
+ // step size until everything settles.
+ if (prevTuneDirection == StepDirection.NEUTRAL
+ && newTuneDirection != StepDirection.NEUTRAL
+ && rollingStatsForTunerSteps.getDeviation() < TUNER_STEP_EPS) {
+ // Restarting the tuning from steady state and setting step size to maximum.
+ // The deviation cannot be that low if last period was neutral and some recent periods were
+ // not neutral.
step = maximumStepSize;
- } else if (prevTuneDirection != newTuneDirection) {
- // Decrease the step size to reach the steady state. Similar procedure as binary search.
+ } else if ((newTuneDirection == StepDirection.INCREASE_MEMSTORE_SIZE
+ && decayingTunerStepSizeSum < 0) ||
+ (newTuneDirection == StepDirection.INCREASE_BLOCK_CACHE_SIZE
+ && decayingTunerStepSizeSum > 0)) {
+ // Current step is opposite of past tuner actions so decrease the step size to reach steady
+ // state.
step = step/2.00f;
- if (step < minimumStepSize) {
- // Ensure step size does not gets too small.
- step = minimumStepSize;
- }
+ }
+ if (step < minimumStepSize) {
+ // If step size is too small then we do nothing.
+ step = 0.0f;
+ newTuneDirection = StepDirection.NEUTRAL;
}
// Increase / decrease the memstore / block cahce sizes depending on new tuner step.
switch (newTuneDirection) {
case INCREASE_BLOCK_CACHE_SIZE:
newBlockCacheSize = context.getCurBlockCacheSize() + step;
newMemstoreSize = context.getCurMemStoreSize() - step;
+ rollingStatsForTunerSteps.insertDataValue(-(int)(step*100000));
+ decayingTunerStepSizeSum = (decayingTunerStepSizeSum - step)/2.00f;
break;
case INCREASE_MEMSTORE_SIZE:
newBlockCacheSize = context.getCurBlockCacheSize() - step;
newMemstoreSize = context.getCurMemStoreSize() + step;
+ rollingStatsForTunerSteps.insertDataValue((int)(step*100000));
+ decayingTunerStepSizeSum = (decayingTunerStepSizeSum + step)/2.00f;
break;
default:
prevTuneDirection = StepDirection.NEUTRAL;
+ rollingStatsForTunerSteps.insertDataValue(0);
+ decayingTunerStepSizeSum = (decayingTunerStepSizeSum)/2.00f;
return NO_OP_TUNER_RESULT;
}
// Check we are within max/min bounds.
@@ -303,6 +335,7 @@ class DefaultHeapMemoryTuner implements HeapMemoryTuner {
this.rollingStatsForCacheMisses = new RollingStatCalculator(this.tunerLookupPeriods);
this.rollingStatsForFlushes = new RollingStatCalculator(this.tunerLookupPeriods);
this.rollingStatsForEvictions = new RollingStatCalculator(this.tunerLookupPeriods);
+ this.rollingStatsForTunerSteps = new RollingStatCalculator(this.tunerLookupPeriods);
}
private enum StepDirection{