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Kafka C++客户端库librdkafka笔记

日期：2018-05-02点击：599收藏

1. 前言

librdkafka提供的异步的生产接口，异步的消费接口和同步的消息接口，没有同步的生产接口。

2. 缩略语

缩略语	缩略语全称	示例或说明
rd	Rapid Development	rd.h
rk	RdKafka
toppar	Topic Partition	struct rd_kafka_toppar_t { };
rep	Reply，	struct rd_kafka_t { rd_kafka_q_t *rk_rep };
msgq	Message Queue	struct rd_kafka_msgq_t { };
rkb	RdKafka Broker	Kafka代理
rko	RdKafka Operation	Kafka操作
rkm	RdKafka Message	Kafka消息
payload		存在Kafka上的消息（或叫Log)

3. 配置和主题

3.1. 配置和主题结构

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3.1.1. Conf

配置接口，配置分两种：全局的和主题的。

3.1.2. ConfImpl

配置的实现。

3.1.3. Topic

主题接口。

3.1.4. TopicImpl

主题的实现。

4. 线程

RdKafka编程涉及到三类线程：

1) 应用线程，业务代码的实现

2) Kafka Broker线程rd_kafka_broker_thread_main，负责与Broker通讯，多个

3) Kafka Handler线程rd_kafka_thread_main，每创建一个consumer或producer即会创建一个Handler线程。

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5. 消费者

5.1. 消费者结构

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5.1.1. Handle

定义了poll等接口，它的实现者为HandleImpl。

5.1.2. HandleImpl

实现了消费者和生产者均使用的poll等，其中poll的作用为：

1) 为生产者回调消息发送结果；

2) 为生产者和消费者回调事件。

class Handle {

/**

* @brief Polls the provided kafka handle for events.

* Events will trigger application provided callbacks to be called.

* The \p timeout_ms argument specifies the maximum amount of time

* (in milliseconds) that the call will block waiting for events.

* For non-blocking calls, provide 0 as \p timeout_ms.

* To wait indefinately for events, provide -1.

* Events:

* - delivery report callbacks (if an RdKafka::DeliveryCb is configured) [producer]

* - event callbacks (if an RdKafka::EventCb is configured) [producer & consumer]

* @remark An application should make sure to call poll() at regular

* intervals to serve any queued callbacks waiting to be called.

* @warning This method MUST NOT be used with the RdKafka::KafkaConsumer,

* use its RdKafka::KafkaConsumer::consume() instead.

* @returns the number of events served.

virtual int poll(int timeout_ms) = 0;

};

5.1.3. ConsumeCb

只针对消费者的Callback。

5.1.4. RebalanceCb

只针对消费者的Callback。

5.1.5. EventCb

消费者和生产者均可设置EventCb，如：_global_conf->set("event_cb", &_event_cb, errmsg);。

/**

* @brief Event callback class

* Events are a generic interface for propagating errors, statistics, logs, etc

* from librdkafka to the application.

* @sa RdKafka::Event

class RD_EXPORT EventCb {

public:

/**

* @brief Event callback

* @sa RdKafka::Event

virtual void event_cb (Event &event) = 0;

virtual ~EventCb() { }

};

/**

* @brief Event object class as passed to the EventCb callback.

class RD_EXPORT Event {

public:

/** @brief Event type */

enum Type {

EVENT_ERROR, /**< Event is an error condition */

EVENT_STATS, /**< Event is a statistics JSON document */

EVENT_LOG, /**< Event is a log message */

EVENT_THROTTLE /**< Event is a throttle level signaling from the broker */

};

5.1.6. Consumer

简单消息者，一般不使用，而是使用KafkaConsumer。

5.1.7. KafkaConsumer

消费者和生产者均采用多重继承方式，其中KafkaConsumer为消费者接口，KafkaConsumerImpl为消费者实现。

5.1.8. KafkaConsumerImpl

KafkaConsumerImpl为消费者实现。

5.1.9. rd_kafka_message_t

消息结构。

5.1.10. rd_kafka_msg_s

消息结构，但消息数据实际存储在rd_kafka_message_t，结构大致如下：

struct rd_kafka_msg_s

{

rd_kafka_message_t rkm_rkmessage;

struct

{

rd_kafka_msg_s* tqe_next;

rd_kafka_msg_s** tqe_prev;

int64_t rkm_timestamp;

rd_kafka_timestamp_type_t rkm_tstype;

}rkm_link;

};

5.1.11. rd_kafka_msgq_t

存储消息的消息队列，生产者生产的消息并不直接socket发送到brokers，而是放入了这个队列，结构大致如下：

struct rd_kafka_msgq_t

{

struct

{

rd_kafka_msg_s* tqh_first; // 队首

rd_kafka_msg_s* tqh_last; // 队尾

};

// 消息个数

rd_atomic32_t rkmq_msg_cnt;

// 所有消息加起来的字节数

rd_atomic64_t rkmq_msg_bytes;

};

5.1.12. rd_kafka_toppar_t

Topic-Partition队列，很复杂的一个结构，部分内容如下：

// Topic + Partition combination

typedef struct rd_kafka_toppar_s

{

struct

{

rd_kafka_toppar_s* tqe_next;

rd_kafka_toppar_s** tqe_prev;

}rktp_rklink;

struct

{

rd_kafka_toppar_s* tqe_next;

rd_kafka_toppar_s** tqe_prev;

}rktp_rkblink;

struct

{

rd_kafka_toppar_s* cqe_next;

rd_kafka_toppar_s* cqe_prev;

}rktp_fetchlink;

struct

{

rd_kafka_toppar_s* tqe_next;

rd_kafka_toppar_s** tqe_prev;

}rktp_rktlink;

struct

{

rd_kafka_toppar_s* tqe_next;

rd_kafka_toppar_s** tqe_prev;

}rktp_cgrplink;

rd_kafka_itopic_t* rktp_rkt;

int32_t rktp_partition;

int32_t rktp_leader_id;

rd_kafka_broker_t* rktp_leader;

rd_kafka_broker_t* rktp_next_leader;

rd_refcnt_t rktp_refcnt;

rd_kafka_msgq_t rktp_msgq; // application->rdkafka queue

}rd_kafka_toppar_t;

6. 生产者

6.1. 生产者结构

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6.1.1. DeliveryReportCb

消息已经成功递送到Broker时回调，只针对生产者有效。

6.1.2. PartitionerCb

计算分区号回调函数，只针对生产者有效。

6.1.3. Producer

Producer为生产者接口，它的实现者为ProducerImpl。

6.1.4. ProduceImpl

ProducerImpl为生产者的实现。

6.2. 生产者启动过程1

启动时会创建两组线程：一组Broker线程（rd_kafka_broker_thread_main，多个），实为与Broker间的网络IO线程；一组Handler线程（rd_kafka_thread_main，单个），每调用一次RdKafka::Producer::create或rd_kafka_new即创建一Handler线程。

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Handler线程调用栈：

(gdb) t 17

[Switching to thread 17 (Thread 0x7ff7059d3700 (LWP 16765))]

#0 0x00007ff7091e6cf2 in pthread_cond_timedwait@@GLIBC_2.3.2 () from /lib64/libpthread.so.0

(gdb) bt

#0 0x00007ff7091e6cf2 in pthread_cond_timedwait@@GLIBC_2.3.2 () from /lib64/libpthread.so.0

#1 0x00000000005b4d2f in cnd_timedwait_ms (cnd=0x1517748, mtx=0x1517720, timeout_ms=898) at tinycthread.c:501

#2 0x0000000000580e16 in rd_kafka_q_serve (rkq=0x1517720, timeout_ms=898, max_cnt=0, cb_type=RD_KAFKA_Q_CB_CALLBACK, callback=0x0, opaque=0x0) at rdkafka_queue.c:440

#3 0x000000000054ee9b in rd_kafka_thread_main (arg=0x1516df0) at rdkafka.c:1227

#4 0x00000000005b4e0f in _thrd_wrapper_function (aArg=0x15179d0) at tinycthread.c:624

#5 0x00007ff7091e2e25 in start_thread () from /lib64/libpthread.so.0

#6 0x00007ff7082d135d in clone () from /lib64/libc.so.6

6.3. 生产者启动过程2

创建网络IO线程，消费者启动过程类似，只是一个调用rd_kafka_broker_producer_serve(rkb)，另一个调用rd_kafka_broker_consumer_serve(rkb)。

IO线程负责消息的收和发，发送底层调用的是sendmsg，收调用的是recvmsg（但MSVC平台调用send和recv）。

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6.4. 生产者生产过程

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生产者生产的消息并不直接socket发送到brokers，而是放入队列rd_kafka_msgq_t中。Broker线程（rd_kafka_broker_thread_main）消费这个队列。

Broker线程同时监控与Broker间的网络连接，又要监控队列中是否有数据，如何实现的？这个队列和管道绑定在一起的，绑定的是管道写端（rktp->rktp_msgq_wakeup_fd = rkb->rkb_toppar_wakeup_fd; rkb->rkb_toppar_wakeup_fd=rkb->rkb_wakeup_fd[1]）。

这样Broker线程即可同时监听网络数据和管道数据。

// int rd_kafka_msg_partitioner(rd_kafka_itopic_t *rkt, rd_kafka_msg_t *rkm,int do_lock)

(gdb) p *rkm

$7 = {rkm_rkmessage = {err = RD_KAFKA_RESP_ERR_NO_ERROR, rkt = 0x1590c10, partition = 1, payload = 0x7f48c4001260, len = 203, key = 0x7f48c400132b, key_len = 14, offset = 0,

_private = 0x0}, rkm_link = {tqe_next = 0x5b5d47554245445b, tqe_prev = 0x6361667265746e69}, rkm_flags = 196610, rkm_timestamp = 1524829399009,

rkm_tstype = RD_KAFKA_TIMESTAMP_CREATE_TIME, rkm_u = {producer = {ts_timeout = 16074575505526, ts_enq = 16074275505526}}}

(gdb) p rkm->rkm_rkmessage

$8 = {err = RD_KAFKA_RESP_ERR_NO_ERROR, rkt = 0x1590c10, partition = 1, payload = 0x7f48c4001260, len = 203, key = 0x7f48c400132b, key_len = 14, offset = 0, _private = 0x0}

(gdb) p rkm->rkm_rkmessage->payload

$9 = (void *) 0x7f48c4001260

(gdb) p (char*)rkm->rkm_rkmessage->payload

$10 = 0x7f48c4001260 "{\"p\":\"f\",\"o\":1,\"d\":\"m\",\"d\":\"m\",\"i\":\"f2\",\"ip\":\"127.0.0.1\",\"pt\":2018,\"sc\":0,\"fc\":1,\"tc\":0,\"acc\":395,\"mcc\":395,\"cd\":\"test\",\"cmd\":\"tester\",\"cf\":\"main\",\"cp\":\"1.49.16.9"...