TraceAnalyzeHandler.java
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package com.yoho.trace.online.handler;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
import com.yoho.trace.anaylzer.model.*;
import org.apache.commons.collections.CollectionUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Durability;
import org.apache.hadoop.hbase.client.HTable;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.Optional;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.Function2;
import org.apache.spark.api.java.function.Function3;
import org.apache.spark.api.java.function.PairFlatMapFunction;
import org.apache.spark.api.java.function.VoidFunction;
import org.apache.spark.streaming.Durations;
import org.apache.spark.streaming.State;
import org.apache.spark.streaming.StateSpec;
import org.apache.spark.streaming.api.java.JavaDStream;
import org.apache.spark.streaming.api.java.JavaMapWithStateDStream;
import org.apache.spark.streaming.api.java.JavaPairDStream;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.alibaba.fastjson.JSONObject;
import com.clearspring.analytics.util.Lists;
import com.yoho.trace.anaylzer.ApiStatisticsAnalyzer;
import com.yoho.trace.sleuth.Span;
import com.yoho.trace.sleuth.Spans;
import com.yoho.trace.store.ApiStatisticsResultStore;
import com.yoho.trace.store.HBasePool;
import scala.Tuple2;
/**
* Created by markeloff on 2017/7/26.
*/
public class TraceAnalyzeHandler implements TraceHandler, Serializable {
private ApiStatisticsAnalyzer analyzer;
private static Logger logger = LoggerFactory.getLogger(TraceAnalyzeHandler.class);
public TraceAnalyzeHandler() {
analyzer = new ApiStatisticsAnalyzer(false);
}
private static final int interval = 3000; //3s
@Override
public void handle(final JavaDStream<Spans> kafkaMsgDStream) {
// key 为 traceid， value 为 每个 span
JavaPairDStream<String, SpanInfo> spanPairDStream = kafkaMsgDStream.mapPartitionsToPair(new PairFlatMapFunction<Iterator<Spans>, String, SpanInfo>() {
@Override
public Iterator<Tuple2<String, SpanInfo>> call(Iterator<Spans> spansIterator) throws Exception {
long enter = System.currentTimeMillis();
List<Tuple2<String, SpanInfo>> spanInfoList = new ArrayList<>(500);
while (spansIterator.hasNext()) {
Spans spans = spansIterator.next();
spans.getHost();
List<Span> list = spans.getSpans();
Iterator<Span> itor = list.iterator();
while (itor.hasNext()) {
Span span = itor.next();
String logEvent = "none";
if (CollectionUtils.isNotEmpty(span.logs())) {
logEvent = span.logs().get(0).getEvent();
}
SpanInfo spanInfo = new SpanInfo();
spanInfo.setName(span.getName());
spanInfo.setBegin(span.getBegin());
spanInfo.setEnd(span.getEnd());
spanInfo.setDuration(span.getEnd() - span.getBegin());
spanInfo.setTraceid(Span.idToHex(span.getTraceId()));
spanInfo.setSpanid(Span.idToHex(span.getSpanId()));
if (span.getParents().size() > 0) {
spanInfo.setParent(Span.idToHex(span.getParents().get(span.getParents().size() - 1)));
}
spanInfo.setService(spans.getHost().getServiceName());
spanInfo.setEndpoint(logEvent);
spanInfo.setIp(spans.getHost().getAddress());
spanInfo.setReceive(spans.getReceive());
if(span.tags()!=null){
spanInfo.setHttpHost(span.tags().get("http.host"));
//标记span是否是是异常span
if(StringUtils.isNotBlank(span.tags().get("error"))){
spanInfo.setErrorCount(1);
}
String lc = span.tags().get("lc");
String httpUrl = span.tags().get("http.url");
if("redis".equals(lc)){
spanInfo.setSpanType(SpanType.REDIS);
}else if("mysql".equals(lc)){
spanInfo.setSpanType(SpanType.MYSQL);
}else if(StringUtils.isNoneBlank(httpUrl)){
spanInfo.setSpanType(SpanType.RESTTEMPLATE);
}else if(StringUtils.equals(spanInfo.getTraceid(),spanInfo.getSpanid())){
spanInfo.setSpanType(SpanType.HTTP);
}else{
spanInfo.setSpanType(SpanType.OTHER);
}
}
spanInfoList.add(new Tuple2<>(spanInfo.getTraceid(), spanInfo));
}
}
logger.info("kafkaMsgDStream.mapPartitionsToPair elapse {}, size {} ", System.currentTimeMillis() - enter, spanInfoList.size());
return spanInfoList.iterator();
}
});
//把 span 按照 traceid 进行分组， 并过滤 120s 以前的 trace，不进行分析
JavaPairDStream<String, Iterable<SpanInfo>> tracePairDStream = spanPairDStream.groupByKey().filter(new Function<Tuple2<String, Iterable<SpanInfo>>, Boolean>() {
@Override
public Boolean call(Tuple2<String, Iterable<SpanInfo>> v1) throws Exception {
Iterator<SpanInfo> itr = v1._2().iterator();
long current = System.currentTimeMillis();
if (itr.hasNext()) {
SpanInfo span = itr.next();
//过滤过早的调用信息，不进行分析
if (current - span.getEnd() >= 120000) {
logger.info("filter early trace , don't anaylze it, trace id {}", v1._1());
return false;
}
}
return true;
}
});
//返回的 dstream （mapWithStateDStream）中，是立即进行处理的， state 中保存的是 上个周期的最后3秒和本周期的最后3秒
JavaMapWithStateDStream mapWithStateDStream = tracePairDStream.mapWithState(StateSpec.function(new Function3<String, Optional<Iterable<SpanInfo>>,
State<Iterable<SpanInfo>>, Tuple2<String, Iterable<SpanInfo>>>() {
@Override
public Tuple2<String, Iterable<SpanInfo>> call(String traceId, Optional<Iterable<SpanInfo>> current, State<Iterable<SpanInfo>> state) throws Exception {
boolean isLast3sRecv = false;
List<SpanInfo> newSpanList = new ArrayList<SpanInfo>();
if (current.isPresent()) {
Iterator itor = current.get().iterator();
while (itor.hasNext()) {
SpanInfo info = (SpanInfo) itor.next();
if ((info.getReceive() - info.getEnd()) < interval) {
isLast3sRecv = true;
}
newSpanList.add(info);
}
}
// 1 只要有span出现在本批次最后3秒，全部更新的state中，不处理， return 空
if (isLast3sRecv) {
if (CollectionUtils.isNotEmpty(newSpanList)) {
logger.info("latest 3s trace in current batch, just state, trace id {}, span count {}", traceId, newSpanList.size());
state.update(newSpanList);
}
//null会被过滤掉，本批次不处理
return new Tuple2<>(traceId, null);
}
// 2 state 中有的trace，合并spanlist, 清理state， return完整的trace spanlist
if (state.exists()) {
Iterator itor = state.get().iterator();
while (itor.hasNext()) {
newSpanList.add((SpanInfo) itor.next());
}
if (!state.isTimingOut()) {
//state未超时
state.remove();
logger.info("full trace with last batch spans, trace id {}, span count {} ", traceId, newSpanList.size());
return new Tuple2<String, Iterable<SpanInfo>>(traceId, newSpanList);
} else {
//state已超时
logger.info("state is timeout, can not process, trace id {}, span count {} ", traceId, newSpanList.size());
//null会被过滤掉，不处理
return new Tuple2<>(traceId, null);
}
}
// 3 state中没有的 trace，并且不在最后3秒，return完整的trace spanlist
logger.info("full trace in current batch, trace id {}, span count {} ", traceId, newSpanList.size());
return new Tuple2<String, Iterable<SpanInfo>>(traceId, newSpanList);
}
}).timeout(Durations.seconds(90)));
//过滤
JavaPairDStream<String, Iterable<SpanInfo>> currentTraceStream = mapWithStateDStream.filter(new Function<Tuple2<String, Iterable<SpanInfo>>, Boolean>() {
@Override
public Boolean call(Tuple2<String, Iterable<SpanInfo>> v1) throws Exception {
//本周期最后3秒收到的trace，等到下个周期再处理
if (v1._2() == null) {
logger.info("filter null trace (latest 3s will process on next batch) , trace id {}", v1._1());
return false;
}
logger.info("go to analyze current batch trace, trace id {}", v1._1());
return true;
}
}).mapPartitionsToPair(new PairFlatMapFunction<Iterator<Tuple2<String, Iterable<SpanInfo>>>, String, Iterable<SpanInfo>>() {
@Override
public Iterator<Tuple2<String, Iterable<SpanInfo>>> call(Iterator<Tuple2<String, Iterable<SpanInfo>>> tuple2Iterator) throws Exception {
return tuple2Iterator;
}
});
//mapWithStateDStream.stateSnapshots state 中 保存了 1、本批次最后3秒， 2、 上个批次最后3秒（本批次未更新的trace）
JavaPairDStream<String, Iterable<SpanInfo>> lastStateTraceStream = mapWithStateDStream.stateSnapshots()
.filter(new Function<Tuple2<String, Iterable<SpanInfo>>, Boolean>() {
@Override
public Boolean call(Tuple2<String, Iterable<SpanInfo>> v1) throws Exception {
long current = System.currentTimeMillis();
Iterator itor = v1._2().iterator();
while (itor.hasNext()) {
SpanInfo span = (SpanInfo) itor.next();
//过滤 本批次的， 只保留上个批次的
if ((current - span.getReceive()) < 60000) {
logger.info("filter latest 3s trace from state snapshot, trace id {}", v1._1());
//本批次内收到的，不处理，因为state中，1、本批次最后3秒， 2、 上个批次最后3秒（本批次未更新的trace）
return false;
}
//过滤 上个批次之前的 ， 只保留 上个批次的 ，因为 state 只在 checkpoint 的时候，才进行timeout 清理
//如果不过滤，就会有多个批次的数据， 导致重复分析
if ((current - span.getReceive()) >= 120000) {
logger.info("filter last 120s trace from state snapshot, trace id {}", v1._1());
return false;
}
}
//只保留， 60秒以上， 120秒以下的 trace信息， 即上个批次遗留下来，需要处理的trace
logger.info("go to analyze last batch trace (latest 3s on last batch), trace id {}", v1._1());
return true;
}
});
//key traceid
JavaPairDStream<String, Iterable<SpanInfo>> needAnaylzeStream = currentTraceStream.union(lastStateTraceStream);
//key minuteTime.traceMD5 value 该traceMD5的一个traceid对应的信息
JavaPairDStream<String, SortedTrace> sortSpanTrace = needAnaylzeStream.flatMapToPair(analyzer.SortSpanTreeFunc);
sortSpanTrace.cache();
JavaPairDStream<String, ApiTraceResult> apiResultTraceDStream = sortSpanTrace.mapToPair(analyzer.ConvertTraceResultFunc) ;
apiResultTraceDStream.cache();
//1处理异常调用链信息
handlerExceptionTrace(apiResultTraceDStream);
//2处理treemd5调用链总览
handlertraceApiAnalyzeMinutes(apiResultTraceDStream);
//3处理所有traceid
handlerAllTrace(apiResultTraceDStream);
//4处理span+ip的耗时分布
handlerSpanIp(sortSpanTrace);
}
private void handlerSpanIp(JavaPairDStream<String, SortedTrace> sortSpanTrace) {
// key traceMD5 + ":" + spanName + ":" + minuteStart + ":" + ip
JavaPairDStream<String, SpanIpResult> stringSpanInfoJavaPairDStream = sortSpanTrace.mapPartitionsToPair(
new PairFlatMapFunction<Iterator<Tuple2<String, SortedTrace>>, String, SpanIpResult>() {
@Override
public Iterator<Tuple2<String, SpanIpResult>> call(Iterator<Tuple2<String, SortedTrace>> tuple2List)
throws Exception {
if (null == tuple2List) {
return null;
}
List<Tuple2<String, SpanIpResult>> resultList = Lists.newArrayList();
while (tuple2List.hasNext()) {
Tuple2<String, SortedTrace> tuple2 = tuple2List.next();
String minuteStart = StringUtils.split(tuple2._1, '.')[0];
String traceMD5 = StringUtils.split(tuple2._1, '.')[1];
SortedTrace sortTrace = tuple2._2;
List<SpanInfo> sortSpanList = sortTrace.getSortSpanList();
for (SpanInfo spanInfo : sortSpanList) {
String ip = "";
// 只有root和resttemplate才会生成ip
if (spanInfo.getTraceid().equals(spanInfo.getSpanid())) {
ip = spanInfo.getIp();
} else {
if (StringUtils.isNotBlank(spanInfo.getHttpHost())) {
ip = spanInfo.getHttpHost();
}
}
if (StringUtils.isBlank(ip)) {
continue;
}
SpanIpResult spanIpResult = new SpanIpResult();
String spanName = spanInfo.getName();
long duration = spanInfo.getEnd() - spanInfo.getBegin();
spanIpResult.setAvgDuration(duration);
spanIpResult.setIp(ip);
spanIpResult.setTimes(1);
String key = traceMD5 + ":" + spanName + ":" + minuteStart + ":" + ip;
Tuple2<String, SpanIpResult> resultTuple2 = new Tuple2<>(key, spanIpResult);
resultList.add(resultTuple2);
}
}
return resultList.iterator();
}
});
JavaPairDStream<String, SpanIpResult> stringSpanIpResultJavaPairDStream = stringSpanInfoJavaPairDStream.reduceByKey(new Function2<SpanIpResult, SpanIpResult, SpanIpResult>() {
@Override
public SpanIpResult call(SpanIpResult v1, SpanIpResult v2) throws Exception {
SpanIpResult result = new SpanIpResult();
result.setIp(v1.getIp());
result.setTimes(v1.getTimes() + v2.getTimes());
result.setAvgDuration((v1.getAvgDuration() * v1.getTimes() + v2.getAvgDuration() * v2.getTimes()) / result.getTimes());
return result;
}
});
stringSpanIpResultJavaPairDStream.foreachRDD(new VoidFunction<JavaPairRDD<String, SpanIpResult>>() {
@Override
public void call(JavaPairRDD<String, SpanIpResult> stringSpanIpResultJavaPairRDD) throws Exception {
stringSpanIpResultJavaPairRDD.foreachPartition(new VoidFunction<Iterator<Tuple2<String, SpanIpResult>>>() {
@Override
public void call(Iterator<Tuple2<String, SpanIpResult>> tuple2Iterator) throws Exception {
HTable resultTable = null;
try {
if (resultTable == null) {
resultTable = (HTable) HBasePool.getConnection().getTable(TableName.valueOf("span_ip"));
}
if(tuple2Iterator == null){
return;
}
List<Put> putList = new ArrayList<>();
while(tuple2Iterator.hasNext()){
Tuple2<String, SpanIpResult> next = tuple2Iterator.next();
String key = next._1;
SpanIpResult spanIpResult = next._2;
Put put = new Put(Bytes.toBytes(key));
//其实不推荐关闭WAL，不过关了的确可以提升性能...因为HBase在写数据前会先写WAL，以保证在异常情况下，HBase可以按照WAL的记录来恢复还未持久化的数据。
put.setDurability(Durability.SKIP_WAL);
put.addColumn(Bytes.toBytes("data"), Bytes.toBytes("avg_duration"), Bytes.toBytes(spanIpResult.getAvgDuration()));
put.addColumn(Bytes.toBytes("data"), Bytes.toBytes("times"), Bytes.toBytes(spanIpResult.getTimes()));
put.addColumn(Bytes.toBytes("data"), Bytes.toBytes("ip"), Bytes.toBytes(spanIpResult.getIp()));
putList.add(put);
}
resultTable.put(putList);
} catch (Exception e) {
logger.error(e.getMessage(),e);
} finally {
if (resultTable != null)
resultTable.close();
}
}
});
}
});
}
private void handlertraceApiAnalyzeMinutes(JavaPairDStream<String, ApiTraceResult> apiResultTraceDStream){
//根据traceMD5分组计算value
JavaPairDStream<String, ApiTraceResult> resultDStream = apiResultTraceDStream.reduceByKey(analyzer.ReduceFunc) ;
resultDStream.foreachRDD(new VoidFunction<JavaPairRDD<String, ApiTraceResult>>() {
@Override
public void call(JavaPairRDD<String, ApiTraceResult> apiResultRdd) throws Exception {
ApiStatisticsResultStore.store(apiResultRdd, "trace_api_analyze_minutes");
}
});
}
private void handlerExceptionTrace(JavaPairDStream<String, ApiTraceResult> apiResultTraceDStream){
JavaPairDStream<String, ApiTraceResult> filter = apiResultTraceDStream.filter(new Function<Tuple2<String, ApiTraceResult>, Boolean>() {
@Override
public Boolean call(Tuple2<String, ApiTraceResult> stringSortedTraceTuple2) throws Exception {
if(stringSortedTraceTuple2._2.isErrorStatus()){
if(StringUtils.isBlank(stringSortedTraceTuple2._2.getApiName()) || StringUtils.equals("http:/",stringSortedTraceTuple2._2.getApiName())){
return false;
}
return true;
}else{
return false;
}
}
});
filter.foreachRDD(new VoidFunction<JavaPairRDD<String, ApiTraceResult>>() {
@Override
public void call(JavaPairRDD<String, ApiTraceResult> stringSortedTraceJavaPairRDD) throws Exception {
stringSortedTraceJavaPairRDD.foreachPartition(new VoidFunction<Iterator<Tuple2<String, ApiTraceResult>>>() {
@Override
public void call(Iterator<Tuple2<String, ApiTraceResult>> tuple2Iterator) throws Exception {
HTable resultTable = null;
try {
if(tuple2Iterator == null){
return;
}
if (resultTable == null) {
resultTable = (HTable) HBasePool.getConnection().getTable(TableName.valueOf("exception_trace"));
}
List<Put> putList = new ArrayList<>();
while(tuple2Iterator.hasNext()){
Tuple2<String, ApiTraceResult> next = tuple2Iterator.next();
ApiTraceResult apiTraceResult = next._2;
Put put = new Put(Bytes.toBytes(apiTraceResult.getTraceStartTime()/1000 + ":" + apiTraceResult.getTraceId()));
//其实不推荐关闭WAL，不过关了的确可以提升性能...因为HBase在写数据前会先写WAL，以保证在异常情况下，HBase可以按照WAL的记录来恢复还未持久化的数据。
put.setDurability(Durability.SKIP_WAL);
// put.addColumn(Bytes.toBytes("data"), Bytes.toBytes("spans"), Bytes.toBytes(JSONObject.toJSONString(apiTraceResult.getSpans())));
// put.addColumn(Bytes.toBytes("data"), Bytes.toBytes("traceid"), Bytes.toBytes(apiTraceResult.getTraceId()));
// put.addColumn(Bytes.toBytes("data"), Bytes.toBytes("starttime"), Bytes.toBytes(apiTraceResult.getTraceStartTime()/1000));
put.addColumn(Bytes.toBytes("data"), Bytes.toBytes("api"), Bytes.toBytes(apiTraceResult.getApiName()));
Put put2 = new Put(Bytes.toBytes(apiTraceResult.getApiName() + ":" + apiTraceResult.getTraceStartTime()/1000 + ":" + apiTraceResult.getTraceId()));
//其实不推荐关闭WAL，不过关了的确可以提升性能...因为HBase在写数据前会先写WAL，以保证在异常情况下，HBase可以按照WAL的记录来恢复还未持久化的数据。
put2.setDurability(Durability.SKIP_WAL);
put2.addColumn(Bytes.toBytes("data"), Bytes.toBytes("spans"), Bytes.toBytes(JSONObject.toJSONString(apiTraceResult.getSpans())));
put2.addColumn(Bytes.toBytes("data"), Bytes.toBytes("traceid"), Bytes.toBytes(apiTraceResult.getTraceId()));
put2.addColumn(Bytes.toBytes("data"), Bytes.toBytes("starttime"), Bytes.toBytes(apiTraceResult.getTraceStartTime()/1000));
putList.add(put);
putList.add(put2);
}
resultTable.put(putList);
} catch (Exception e) {
logger.error(e.getMessage(),e);
} finally {
if (resultTable != null)
resultTable.close();
}
}
});
}
});
}
private void handlerAllTrace(JavaPairDStream<String, ApiTraceResult> apiResultTraceDStream){
apiResultTraceDStream.foreachRDD(new VoidFunction<JavaPairRDD<String, ApiTraceResult>>() {
@Override
public void call(JavaPairRDD<String, ApiTraceResult> stringSortedTraceJavaPairRDD) throws Exception {
stringSortedTraceJavaPairRDD.foreachPartition(new VoidFunction<Iterator<Tuple2<String, ApiTraceResult>>>() {
@Override
public void call(Iterator<Tuple2<String, ApiTraceResult>> tuple2Iterator) throws Exception {
HTable resultTable = null;
try {
if(tuple2Iterator == null){
return;
}
if (resultTable == null) {
resultTable = (HTable) HBasePool.getConnection().getTable(TableName.valueOf("all_trace"));
}
List<Put> putList = new ArrayList<>();
while(tuple2Iterator.hasNext()){
Tuple2<String, ApiTraceResult> next = tuple2Iterator.next();
ApiTraceResult apiTraceResult = next._2;
String[] md5Tags = StringUtils.split(apiTraceResult.getTraceMd5(), '.');
Put put1 = new Put(Bytes.toBytes( md5Tags[1] + ":" + apiTraceResult.getTraceStartTime()/1000 + ":" + apiTraceResult.getTraceId()));
//其实不推荐关闭WAL，不过关了的确可以提升性能...因为HBase在写数据前会先写WAL，以保证在异常情况下，HBase可以按照WAL的记录来恢复还未持久化的数据。
put1.setDurability(Durability.SKIP_WAL);
put1.addColumn(Bytes.toBytes("data"), Bytes.toBytes("spans"), Bytes.toBytes(JSONObject.toJSONString(apiTraceResult.getSpans())));
put1.addColumn(Bytes.toBytes("data"), Bytes.toBytes("traceid"), Bytes.toBytes(apiTraceResult.getTraceId()));
put1.addColumn(Bytes.toBytes("data"), Bytes.toBytes("starttime"), Bytes.toBytes(apiTraceResult.getTraceStartTime()/1000));
put1.addColumn(Bytes.toBytes("data"), Bytes.toBytes("traceMd5"), Bytes.toBytes(apiTraceResult.getTraceMd5()));
put1.addColumn(Bytes.toBytes("data"), Bytes.toBytes("duration"), Bytes.toBytes(apiTraceResult.getDuration()));
Put put2 = new Put(Bytes.toBytes( apiTraceResult.getApiName() + ":" + apiTraceResult.getTraceStartTime()/1000 + ":" + apiTraceResult.getTraceId()));
//其实不推荐关闭WAL，不过关了的确可以提升性能...因为HBase在写数据前会先写WAL，以保证在异常情况下，HBase可以按照WAL的记录来恢复还未持久化的数据。
put2.setDurability(Durability.SKIP_WAL);
put2.addColumn(Bytes.toBytes("data"), Bytes.toBytes("spans"), Bytes.toBytes(JSONObject.toJSONString(apiTraceResult.getSpans())));
put2.addColumn(Bytes.toBytes("data"), Bytes.toBytes("traceid"), Bytes.toBytes(apiTraceResult.getTraceId()));
put2.addColumn(Bytes.toBytes("data"), Bytes.toBytes("starttime"), Bytes.toBytes(apiTraceResult.getTraceStartTime()/1000));
put2.addColumn(Bytes.toBytes("data"), Bytes.toBytes("traceMd5"), Bytes.toBytes(apiTraceResult.getTraceMd5()));
put2.addColumn(Bytes.toBytes("data"), Bytes.toBytes("duration"), Bytes.toBytes(apiTraceResult.getDuration()));
putList.add(put1);
putList.add(put2);
}
resultTable.put(putList);
} catch (Exception e) {
logger.error(e.getMessage(),e);
} finally {
if (resultTable != null)
resultTable.close();
}
}
});
}
});
}
}