gfwleak/galaxy-tsg-olap-generate-baseline
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修改滤波器参数

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This commit is contained in:
yinjiangyi
2021-08-04 15:57:12 +08:00
parent d562d3db99
commit d60d5f5e43
4 changed files with 9 additions and 13 deletions
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2
src/main/java/cn/mesalab/config/ApplicationConfig.java
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@@ -44,7 +44,7 @@ public class ApplicationConfig {
public static final String HBASE_ZOOKEEPER_CLIENT_PORT= ConfigUtils.getStringProperty("hbase.zookeeper.client.port"); public static final String HBASE_ZOOKEEPER_CLIENT_PORT= ConfigUtils.getStringProperty("hbase.zookeeper.client.port");
public static final Double BASELINE_KALMAN_Q = ConfigUtils.getDoubleProperty("baseline.kalman.q"); public static final Double BASELINE_KALMAN_P = ConfigUtils.getDoubleProperty("baseline.kalman.p");
public static final Double BASELINE_KALMAN_R = ConfigUtils.getDoubleProperty("baseline.kalman.r"); public static final Double BASELINE_KALMAN_R = ConfigUtils.getDoubleProperty("baseline.kalman.r");
public static final Integer LOG_WRITE_COUNT = ConfigUtils.getIntProperty("log.write.count"); public static final Integer LOG_WRITE_COUNT = ConfigUtils.getIntProperty("log.write.count");

2
src/main/java/cn/mesalab/service/BaselineGeneration.java
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@@ -121,7 +121,7 @@ public class BaselineGeneration {
// 获取IP列表 // 获取IP列表
List<String> destinationIps = DruidData.getServerIpList(allFromDruid); List<String> destinationIps = DruidData.getServerIpList(allFromDruid);
ThreadFactory generationThreadFactory = new ThreadFactoryBuilder() ThreadFactory generationThreadFactory = new ThreadFactoryBuilder()
.setNameFormat("baseline-load-data-%d").build(); .setNameFormat("baseline-generate-%d").build();
ThreadPoolExecutor generationExecutor = new ThreadPoolExecutor( ThreadPoolExecutor generationExecutor = new ThreadPoolExecutor(
threadNum, threadNum, 0L, threadNum, threadNum, 0L,
TimeUnit.MILLISECONDS, new LinkedBlockingQueue<>(1024), generationThreadFactory, TimeUnit.MILLISECONDS, new LinkedBlockingQueue<>(1024), generationThreadFactory,

14
src/main/java/cn/mesalab/service/algorithm/KalmanFilter.java
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@@ -20,7 +20,6 @@ public class KalmanFilter {
private double mdelt; private double mdelt;
private double Gauss; private double Gauss;
private double kalmanGain; private double kalmanGain;
private final static double Q = ApplicationConfig.BASELINE_KALMAN_Q;
private final static double R = ApplicationConfig.BASELINE_KALMAN_R; private final static double R = ApplicationConfig.BASELINE_KALMAN_R;
public KalmanFilter() { public KalmanFilter() {
@@ -28,9 +27,7 @@ public class KalmanFilter {
} }
public void initial(){ public void initial(){
// TODO 调整 pdelt = ApplicationConfig.BASELINE_KALMAN_P;
pdelt = 1;
mdelt = 1;
} }
private ArrayList<Integer> smoothSeries; private ArrayList<Integer> smoothSeries;
@@ -40,20 +37,18 @@ public class KalmanFilter {
//第一个估计值 //第一个估计值
predict = oldValue; predict = oldValue;
current = value; current = value;
//高斯噪声方差
Gauss = Math.sqrt(pdelt * pdelt + mdelt * mdelt) + Q;
//估计方差 //估计方差
kalmanGain = Math.sqrt((Gauss * Gauss)/(Gauss * Gauss + pdelt * pdelt)) + R; kalmanGain = pdelt/(pdelt + R);
//估计值 //估计值
estimate = (int) (kalmanGain * (current - predict) + predict); estimate = (int) (kalmanGain * (current - predict) + predict);
//新的估计方差 //新的估计方差
mdelt = Math.sqrt((1-kalmanGain) * Gauss * Gauss); mdelt = (1-kalmanGain) * pdelt ;
return estimate; return estimate;
} }
public void forcast(List<Integer> historicalSeries, Integer length){ public void forcast(List<Integer> historicalSeries, Integer length){
// 滤波
int oldvalue = (historicalSeries.stream().mapToInt(Integer::intValue).sum())/historicalSeries.size(); int oldvalue = (historicalSeries.stream().mapToInt(Integer::intValue).sum())/historicalSeries.size();
smoothSeries = new ArrayList<Integer>(); smoothSeries = new ArrayList<Integer>();
for(int i = 0; i < historicalSeries.size(); i++){ for(int i = 0; i < historicalSeries.size(); i++){
@@ -62,6 +57,7 @@ public class KalmanFilter {
smoothSeries.add(oldvalue); smoothSeries.add(oldvalue);
} }
// 平均
forecastSeries = new ArrayList<>(); forecastSeries = new ArrayList<>();
Integer partitonNum = historicalSeries.size()/length; Integer partitonNum = historicalSeries.size()/length;
for(int i = 0; i<length; i++){ for(int i = 0; i<length; i++){

4
src/main/resources/application.properties
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@@ -49,8 +49,8 @@ baseline.historical.ratio.threshold=0.1
baseline.historical.sparse.fill.percentile=0.95 baseline.historical.sparse.fill.percentile=0.95
baseline.rational.percentile=0.95 baseline.rational.percentile=0.95
#Kalman Filter #Kalman Filter
baseline.kalman.q=0.000001 baseline.kalman.p=0.000001
baseline.kalman.r=0.002 baseline.kalman.r=4
# 每更新1000个记录打印log # 每更新1000个记录打印log