spark streaming kafka OffsetOutOfRangeException 异常分析与解决

spark streaming kafka OffsetOutOfRangeException 异常分析与解决

自从把spark 从1.3升级到1.6之后，kafka Streaming相关问题频出。最近又遇到了一个。

job中使用Kafka DirectStream 读取topic中数据，然后做处理。其中有个测试job，停止了几天，再次启动时爆出了kafka.common.OffsetOutOfRangeException。下文记录下异常分析与解决过程。

异常分析

从字面意思上，说是kafka topic的offset越界异常；在job中使用的是Kafka DirectStream，每成功处理一批数据，就把对应的offset更新到zookeeper中；和数组越界异常一样，offset越界应该分为头越界和尾越界，如下图所示。



头部越界： zookeeper中保存的offset在topic中仍然存在的最老message的offset之前时(zk_offset < earliest_offset)；

尾部越界： zookeeper中保存的offset在topic中最新message的offset之后时(zk_offset > last_offset)

因为代码中采用了之前文章的方法，因此不可能是尾部越界，因此猜测是头部越界。

是什么导致头部越界呢？

考虑到kafka broker配置中修改了message的保持时间为24小时：

log.retention.hours=24(The minimum age of a log file to be eligible for deletion)

因此，应该是kafka 中未被消费的数据被broker清除了，使得zk中的offset落在仍存在的最老message offset的左侧，本来合法的offset变得不非法了。

验证猜测

改kafka broker 的retention time 为2分钟

配置文件

kafka/config/server.properties

log.retention.hours=168 -> log.retention.minutes=2

修改完成后重启kafka。

使用zk shell 命令得到解析器所保存的zk_offset

停止spark streaming kafka DirectStream job

发送数据到kafka topic，等待一段时间（超过两分钟）

启动streaming job，复现该异常。

通过异常验证可以导致异常的原因为：kafka broker因为log.retention.hours的配置，导致topic中有些数据被清除，而在retention时间范围内streaming job都没有把将要被清除的message消费掉，因此zk中offset落在了earliest_offset的左侧，引发异常。

解决方法

首先想到的方法就是 streaming job要及时消费掉topic中的数据，消费延迟不得大于log.retention.time的配置。

但是更好的办法是在遇到该问题时，依然能让job正常运行，因此就需要在发现

zk_offset<earliest_offset

时矫正zk_offset为合法值。

同样使用Spark Streaming ‘numRecords must not be negative’问题解决，解决思路的方法。

代码：

package com.frey.v1.utils.kafka;

import com.google.common.collect.Lists;
import com.google.common.collect.Maps;
import kafka.api.PartitionOffsetRequestInfo;
import kafka.cluster.Broker;
import kafka.common.TopicAndPartition;
import kafka.javaapi.*;
import kafka.javaapi.consumer.SimpleConsumer;

import java.util.Date;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

/**
* KafkaOffsetTool
*
* @author Shuai YUAN
* @date 2016/4/11
*/
public class KafkaOffsetTool {

private static KafkaOffsetTool instance;
final int TIMEOUT = 100000;
final int BUFFERSIZE = 64 * 1024;

private KafkaOffsetTool() {
}

public static synchronized KafkaOffsetTool getInstance() {
if (instance == null) {
instance = new KafkaOffsetTool();
}
return instance;
}

public Map<TopicAndPartition, Long> getLastOffset(String brokerList, List<String> topics,
String groupId) {

Map<TopicAndPartition, Long> topicAndPartitionLongMap = Maps.newHashMap();

Map<TopicAndPartition, Broker> topicAndPartitionBrokerMap =
KafkaOffsetTool.getInstance().findLeader(brokerList, topics);

for (Map.Entry<TopicAndPartition, Broker> topicAndPartitionBrokerEntry : topicAndPartitionBrokerMap
.entrySet()) {
// get leader broker
Broker leaderBroker = topicAndPartitionBrokerEntry.getValue();

SimpleConsumer simpleConsumer = new SimpleConsumer(leaderBroker.host(), leaderBroker.port(),
TIMEOUT, BUFFERSIZE, groupId);

long readOffset = getTopicAndPartitionLastOffset(simpleConsumer,
topicAndPartitionBrokerEntry.getKey(), groupId);

topicAndPartitionLongMap.put(topicAndPartitionBrokerEntry.getKey(), readOffset);

}

return topicAndPartitionLongMap;

}

/**
*
* @param brokerList
* @param topics
* @param groupId
* @return
*/
public Map<TopicAndPartition, Long> getEarliestOffset(String brokerList, List<String> topics,
String groupId) {

Map<TopicAndPartition, Long> topicAndPartitionLongMap = Maps.newHashMap();

Map<TopicAndPartition, Broker> topicAndPartitionBrokerMap =
KafkaOffsetTool.getInstance().findLeader(brokerList, topics);

for (Map.Entry<TopicAndPartition, Broker> topicAndPartitionBrokerEntry : topicAndPartitionBrokerMap
.entrySet()) {
// get leader broker
Broker leaderBroker = topicAndPartitionBrokerEntry.getValue();

SimpleConsumer simpleConsumer = new SimpleConsumer(leaderBroker.host(), leaderBroker.port(),
TIMEOUT, BUFFERSIZE, groupId);

long readOffset = getTopicAndPartitionEarliestOffset(simpleConsumer,
topicAndPartitionBrokerEntry.getKey(), groupId);

topicAndPartitionLongMap.put(topicAndPartitionBrokerEntry.getKey(), readOffset);

}

return topicAndPartitionLongMap;

}

/**
* 得到所有的 TopicAndPartition
*
* @param brokerList
* @param topics
* @return topicAndPartitions
*/
private Map<TopicAndPartition, Broker> findLeader(String brokerList, List<String> topics) {
// get broker's url array
String[] brokerUrlArray = getBorkerUrlFromBrokerList(brokerList);
// get broker's port map
Map<String, Integer> brokerPortMap = getPortFromBrokerList(brokerList);

// create array list of TopicAndPartition
Map<TopicAndPartition, Broker> topicAndPartitionBrokerMap = Maps.newHashMap();

for (String broker : brokerUrlArray) {

SimpleConsumer consumer = null;
try {
// new instance of simple Consumer
consumer = new SimpleConsumer(broker, brokerPortMap.get(broker), TIMEOUT, BUFFERSIZE,
"leaderLookup" + new Date().getTime());

TopicMetadataRequest req = new TopicMetadataRequest(topics);

TopicMetadataResponse resp = consumer.send(req);

List<TopicMetadata> metaData = resp.topicsMetadata();

for (TopicMetadata item : metaData) {
for (PartitionMetadata part : item.partitionsMetadata()) {
TopicAndPartition topicAndPartition =
new TopicAndPartition(item.topic(), part.partitionId());
topicAndPartitionBrokerMap.put(topicAndPartition, part.leader());
}
}
} catch (Exception e) {
e.printStackTrace();
} finally {
if (consumer != null)
consumer.close();
}
}
return topicAndPartitionBrokerMap;
}

/**
* get last offset
* @param consumer
* @param topicAndPartition
* @param clientName
* @return
*/
private long getTopicAndPartitionLastOffset(SimpleConsumer consumer,
TopicAndPartition topicAndPartition, String clientName) {
Map<TopicAndPartition, PartitionOffsetRequestInfo> requestInfo =
new HashMap<TopicAndPartition, PartitionOffsetRequestInfo>();

requestInfo.put(topicAndPartition, new PartitionOffsetRequestInfo(
kafka.api.OffsetRequest.LatestTime(), 1));

OffsetRequest request = new OffsetRequest(
requestInfo, kafka.api.OffsetRequest.CurrentVersion(),
clientName);

OffsetResponse response = consumer.getOffsetsBefore(request);

if (response.hasError()) {
System.out
.println("Error fetching data Offset Data the Broker. Reason: "
+ response.errorCode(topicAndPartition.topic(), topicAndPartition.partition()));
return 0;
}
long[] offsets = response.offsets(topicAndPartition.topic(), topicAndPartition.partition());
return offsets[0];
}

/**
* get earliest offset
* @param consumer
* @param topicAndPartition
* @param clientName
* @return
*/
private long getTopicAndPartitionEarliestOffset(SimpleConsumer consumer,
TopicAndPartition topicAndPartition, String clientName) {
Map<TopicAndPartition, PartitionOffsetRequestInfo> requestInfo =
new HashMap<TopicAndPartition, PartitionOffsetRequestInfo>();

requestInfo.put(topicAndPartition, new PartitionOffsetRequestInfo(
kafka.api.OffsetRequest.EarliestTime(), 1));

OffsetRequest request = new OffsetRequest(
requestInfo, kafka.api.OffsetRequest.CurrentVersion(),
clientName);

OffsetResponse response = consumer.getOffsetsBefore(request);

if (response.hasError()) {
System.out
.println("Error fetching data Offset Data the Broker. Reason: "
+ response.errorCode(topicAndPartition.topic(), topicAndPartition.partition()));
return 0;
}
long[] offsets = response.offsets(topicAndPartition.topic(), topicAndPartition.partition());
return offsets[0];
}
/**
* 得到所有的broker url
*
* @param brokerlist
* @return
*/
private String[] getBorkerUrlFromBrokerList(String brokerlist) {
String[] brokers = brokerlist.split(",");
for (int i = 0; i < brokers.length; i++) {
brokers[i] = brokers[i].split(":")[0];
}
return brokers;
}

/**
* 得到broker url 与 其port 的映射关系
*
* @param brokerlist
* @return
*/
private Map<String, Integer> getPortFromBrokerList(String brokerlist) {
Map<String, Integer> map = new HashMap<String, Integer>();
String[] brokers = brokerlist.split(",");
for (String item : brokers) {
String[] itemArr = item.split(":");
if (itemArr.length > 1) {
map.put(itemArr[0], Integer.parseInt(itemArr[1]));
}
}
return map;
}

public static void main(String[] args) {
List<String> topics = Lists.newArrayList();
topics.add("bsa_sys_tmp");
//    topics.add("bugfix");
Map<TopicAndPartition, Long> topicAndPartitionLongMap =
KafkaOffsetTool.getInstance().getEarliestOffset("bsa142:9092,bsa143:9092", topics,
"com.nsfocus.bsa.setl");

for (Map.Entry<TopicAndPartition, Long> entry : topicAndPartitionLongMap.entrySet()) {
System.out.println(entry.getKey().topic() + "-"+ entry.getKey().partition() + ":" + entry.getValue());
}
}
}

矫正offset核心代码：

/** 以下 矫正 offset */

// lastest offsets
Map<TopicAndPartition, Long> lastestTopicAndPartitionLongMap =
KafkaOffsetTool.getInstance().getLastOffset(kafkaParams.get("metadata.broker.list"),
Lists.newArrayList(topicsSet), kafkaParams.get(Constants.KAFKA_CONSUMER_GROUP_ID));

// earliest offsets
Map<TopicAndPartition, Long> earliestTopicAndPartitionLongMap =
KafkaOffsetTool.getInstance().getEarliestOffset(kafkaParams.get("metadata.broker.list"),
Lists.newArrayList(topicsSet), kafkaParams.get(Constants.KAFKA_CONSUMER_GROUP_ID));

for (Map.Entry<TopicAndPartition, Long> topicAndPartitionLongEntry : fromOffsets.entrySet()) {

long zkOffset = topicAndPartitionLongEntry.getValue();
long lastestOffset = lastestTopicAndPartitionLongMap.get(topicAndPartitionLongEntry.getKey());
long earliestOffset = earliestTopicAndPartitionLongMap.get(topicAndPartitionLongEntry.getKey());
// zkoffset 不在可用message offset区间内
if (zkOffset > lastestOffset || zkOffset < earliestOffset) {
// set offset = earliestOffset
logger.warn("矫正offset: " + zkOffset +" -> "+ earliestOffset);
topicAndPartitionLongEntry.setValue(earliestOffset);
}
}
/** 以上 矫正 offset */