之前介绍了如何在SpringBoot中集成Kafka,但是默认情况下，@KafkaListener都是一条一条消费，如果想要一次消费一个批量的话，我们都知道，在kafka原生的API可以通过poll(num)来获取一次获取num条消息：
那么使用在Springboot中使用@KafkaListener能否实现批量监听呢？
看了spring-kafka的官方文档介绍，可以知道自1.1版本之后，@KafkaListener开始支持批量消费，只需要设置batchListener参数为true
https://docs.spring.io/spring-kafka/reference/html/_reference.html
下面是我在项目中使用到的方法：
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@
Bean
public
KafkaListenerContainerFactory
<
?
>
batchFactory
(
)
{
ConcurrentKafkaListenerContainerFactory
<
Integer
,
String
>
factory
=
new
ConcurrentKafkaListenerContainerFactory
<>
(
)
;
factory
.
setConsumerFactory
(
consumerFactory
(
)
)
;
factory
.
setConcurrency
(
1
)
;
factory
.
setBatchListener
(
true
)
;
//设置为批量消费，每个批次数量在Kafka配置参数中设置ConsumerConfig.MAX_POLL_RECORDS_CONFIG
factory
.
getContainerProperties
(
)
.
setAckMode
(
AckMode
.
MANUAL_IMMEDIATE
)
;
//设置提交偏移量的方式
return
factory
;
}
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@
Bean
public
Map
<
String
,
Object
>
consumerConfigs
(
)
{
Map
<
String
,
Object
>
props
=
new
HashMap
<>
(
)
;
props
.
put
(
ConsumerConfig
.
BOOTSTRAP_SERVERS_CONFIG
,
bootstrapServers
)
;
props
.
put
(
ConsumerConfig
.
ENABLE_AUTO_COMMIT_CONFIG
,
false
)
;
props
.
put
(
ConsumerConfig
.
AUTO_COMMIT_INTERVAL_MS_CONFIG
,
"100"
)
;
props
.
put
(
ConsumerConfig
.
SESSION_TIMEOUT_MS_CONFIG
,
"15000"
)
;
props
.
put
(
ConsumerConfig
.
KEY_DESERIALIZER_CLASS_CONFIG
,
StringDeserializer
.
class
)
;
props
.
put
(
ConsumerConfig
.
VALUE_DESERIALIZER_CLASS_CONFIG
,
StringDeserializer
.
class
)
;
props
.
put
(
ConsumerConfig
.
GROUP_ID_CONFIG
,
groupId
)
;
props
.
put
(
ConsumerConfig
.
MAX_POLL_RECORDS_CONFIG
,
maxPollRecords
)
;
//每一批数量
props
.
put
(
ConsumerConfig
.
AUTO_OFFSET_RESET_CONFIG
,
autoOffsetReset
)
;
return
props
;
}
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开始监听，批量消费后采用JPA的方式批量写入数据库，这里containerFactory = “batchFactory”要指定为批量消费
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@
KafkaListener
(
topics
=
"${tgs.kafka.topics}"
,
containerFactory
=
"batchFactory"
)
public
void
listen
(
List
<
ConsumerRecord
<?
,
?>
>
records
,
Acknowledgment
ack
)
{
logger
.
info
(
"records.size: "
+
records
.
size
(
)
+
" in all"
)
;
List
<
B_ZDRYGK_ZDRYXX_FJ_HCB1
>
list
=
new
ArrayList
<
B_ZDRYGK_ZDRYXX_FJ_HCB1
>
(
)
;
ObjectMapper
mapper
=
new
ObjectMapper
(
)
;
B_ZDRYGK_ZDRYXX_FJ_HCB1
b_zdrygk_zdryxx_fj_hcb1
=
null
;
for
(
ConsumerRecord
<?
,
?>
record
:
records
)
{
try
{
b_zdrygk_zdryxx_fj_hcb1
=
mapper
.
readValue
(
record
.
value
(
)
.
toString
(
)
,
B_ZDRYGK_ZDRYXX_FJ_HCB1
.
class
)
;
}
catch
(
IOException
e
)
{
e
.
printStackTrace
(
)
;
}
if
(
null
!=
b_zdrygk_zdryxx_fj_hcb1
)
{
list
.
add
(
b_zdrygk_zdryxx_fj_hcb1
)
;
}
}
try
{
List
<
B_ZDRYGK_ZDRYXX_FJ_HCB1
>
hcb1List
=
b_ZDRYGK_ZDRYXX_FJ_HCB1Repository
.
save
(
list
)
;
b_ZDRYGK_ZDRYXX_FJ_HCB1Repository
.
flush
(
)
;
logger
.
info
(
"flush size: "
+
hcb1List
.
size
(
)
)
;
}
catch
(
Exception
e
)
{
e
.
printStackTrace
(
)
;
}
finally
{
logger
.
info
(
"start commit offset"
)
;
ack
.
acknowledge
(
)
;
//手动提交偏移量
logger
.
info
(
"stop commit offset"
)
;
}
}
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运行结果如下图,每批消费100条消息：