分布式服务链路追踪系统Zipkin学习记录

Zipkin是一个分布式追踪系统。它有助于收集解决微服务架构中延迟问题所需的时序数据。它管理这些数据的收集和查找。Zipkin的设计基于 Google Dapper论文。

应用程序用于向Zipkin报告时间数据。Zipkin用户界面还提供了一个依赖关系图，显示每一个应用程序有多少跟踪请求。若是您正在解决延迟问题或错误问题，则能够根据应用程序，跟踪长度，注释或时间戳过滤或排序全部跟踪。一旦选择了一个跟踪，您能够看到每一个跨度所花费的总跟踪时间的百分比，从而能够肯定问题应用程序。

官网地址：https://zipkin.io/

github 地址 ：https://github.com/openzipkin/zipkin

为何使用Zipkin

随着业务愈来愈复杂，系统也随之进行各类拆分，特别是随着微服务架构和容器技术的兴起，看似简单的一个应用，后台可能有几十个甚至几百个服务在支撑；一个前端的请求可能须要屡次的服务调用最后才能完成；当请求变慢或者不可用时，咱们没法得知是哪一个后台服务引发的，这时就须要解决如何快速定位服务故障点，Zipkin分布式跟踪系统就能很好的解决这样的问题。

三种启动方式

docker 启动

docker run -d -p 9411:9411 openzipkin/zipkin

java  启动

curl -sSL https://zipkin.io/quickstart.sh | bash -s
java -jar zipkin.jar

springboot  启动

依赖

<dependency>
   <groupId>io.zipkin.java</groupId>
   <artifactId>zipkin-server</artifactId>
</dependency>
<dependency>
   <groupId>io.zipkin.java</groupId>
   <artifactId>zipkin-autoconfigure-ui</artifactId>
</dependency>

默认内存存储

添加mysql 存储

<dependency>
   <groupId>io.zipkin.java</groupId>
   <artifactId>zipkin-autoconfigure-storage-mysql</artifactId>
</dependency>
<dependency>
   <groupId>mysql</groupId>
   <artifactId>mysql-connector-java</artifactId>
</dependency>
<dependency>
   <groupId>org.springframework.boot</groupId>
   <artifactId>spring-boot-starter-jdbc</artifactId>
</dependency>
<dependency>
   <groupId>com.zaxxer</groupId>
   <artifactId>HikariCP</artifactId>
</dependency>

配置 数据库

#数据库脚本建立地址，当有多个是可以使用[x]表示集合第几个元素
spring.datasource.schema[0]=classpath:/sql/zipkin.sql
spring.datasource.name=zipkin
spring.datasource.driver-class-name=com.mysql.jdbc.Driver
spring.datasource.url=jdbc:mysql://local-pc-node1:3306/snjx?characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=false
spring.datasource.username=snjx
spring.datasource.password=kRqKjGw1s;RH
spring.datasource.type=com.zaxxer.hikari.HikariDataSource
spring.datasource.hikari.minimum-idle=5
spring.datasource.hikari.maximum-pool-size=15
spring.datasource.hikari.auto-commit=true
spring.datasource.hikari.idle-timeout=30000
spring.datasource.hikari.pool-name=DatebookHikariCP
spring.datasource.hikari.max-lifetime=1800000
spring.datasource.hikari.connection-timeout=30000
spring.datasource.hikari.connection-test-query=SELECT 1

zipkin.sql  文件

CREATE TABLE IF NOT EXISTS zipkin_spans (
  `trace_id_high` BIGINT NOT NULL DEFAULT 0 COMMENT 'If non zero, this means the trace uses 128 bit traceIds instead of 64 bit',
  `trace_id` BIGINT NOT NULL,
  `id` BIGINT NOT NULL,
  `name` VARCHAR(255) NOT NULL,
  `parent_id` BIGINT,
  `debug` BIT(1),
  `start_ts` BIGINT COMMENT 'Span.timestamp(): epoch micros used for endTs query and to implement TTL',
  `duration` BIGINT COMMENT 'Span.duration(): micros used for minDuration and maxDuration query'
) ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;

ALTER TABLE zipkin_spans ADD UNIQUE KEY(`trace_id_high`, `trace_id`, `id`) COMMENT 'ignore insert on duplicate';
ALTER TABLE zipkin_spans ADD INDEX(`trace_id_high`, `trace_id`, `id`) COMMENT 'for joining with zipkin_annotations';
ALTER TABLE zipkin_spans ADD INDEX(`trace_id_high`, `trace_id`) COMMENT 'for getTracesByIds';
ALTER TABLE zipkin_spans ADD INDEX(`name`) COMMENT 'for getTraces and getSpanNames';
ALTER TABLE zipkin_spans ADD INDEX(`start_ts`) COMMENT 'for getTraces ordering and range';

CREATE TABLE IF NOT EXISTS zipkin_annotations (
  `trace_id_high` BIGINT NOT NULL DEFAULT 0 COMMENT 'If non zero, this means the trace uses 128 bit traceIds instead of 64 bit',
  `trace_id` BIGINT NOT NULL COMMENT 'coincides with zipkin_spans.trace_id',
  `span_id` BIGINT NOT NULL COMMENT 'coincides with zipkin_spans.id',
  `a_key` VARCHAR(255) NOT NULL COMMENT 'BinaryAnnotation.key or Annotation.value if type == -1',
  `a_value` BLOB COMMENT 'BinaryAnnotation.value(), which must be smaller than 64KB',
  `a_type` INT NOT NULL COMMENT 'BinaryAnnotation.type() or -1 if Annotation',
  `a_timestamp` BIGINT COMMENT 'Used to implement TTL; Annotation.timestamp or zipkin_spans.timestamp',
  `endpoint_ipv4` INT COMMENT 'Null when Binary/Annotation.endpoint is null',
  `endpoint_ipv6` BINARY(16) COMMENT 'Null when Binary/Annotation.endpoint is null, or no IPv6 address',
  `endpoint_port` SMALLINT COMMENT 'Null when Binary/Annotation.endpoint is null',
  `endpoint_service_name` VARCHAR(255) COMMENT 'Null when Binary/Annotation.endpoint is null'
) ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;

ALTER TABLE zipkin_annotations ADD UNIQUE KEY(`trace_id_high`, `trace_id`, `span_id`, `a_key`, `a_timestamp`) COMMENT 'Ignore insert on duplicate';
ALTER TABLE zipkin_annotations ADD INDEX(`trace_id_high`, `trace_id`, `span_id`) COMMENT 'for joining with zipkin_spans';
ALTER TABLE zipkin_annotations ADD INDEX(`trace_id_high`, `trace_id`) COMMENT 'for getTraces/ByIds';
ALTER TABLE zipkin_annotations ADD INDEX(`endpoint_service_name`) COMMENT 'for getTraces and getServiceNames';
ALTER TABLE zipkin_annotations ADD INDEX(`a_type`) COMMENT 'for getTraces';
ALTER TABLE zipkin_annotations ADD INDEX(`a_key`) COMMENT 'for getTraces';
ALTER TABLE zipkin_annotations ADD INDEX(`trace_id`, `span_id`, `a_key`) COMMENT 'for dependencies job';

CREATE TABLE IF NOT EXISTS zipkin_dependencies (
  `day` DATE NOT NULL,
  `parent` VARCHAR(255) NOT NULL,
  `child` VARCHAR(255) NOT NULL,
  `call_count` BIGINT,
  `error_count` BIGINT
) ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;

ALTER TABLE zipkin_dependencies ADD UNIQUE KEY(`day`, `parent`, `child`);

client 端的配置

<dependency>
   <groupId>org.springframework.cloud</groupId>
   <artifactId>spring-cloud-starter-sleuth</artifactId>
</dependency>
<dependency>
   <groupId>org.springframework.cloud</groupId>
   <artifactId>spring-cloud-sleuth-zipkin</artifactId>
</dependency>

#zipkin采样率，默认为0.1，改成1后全采样，可是会下降接口调用效率
spring.sleuth.sampler.percentage=1.0
#服务链路追踪
spring.zipkin.base-url=http://localhost:8867

spring.zipkin.base-url=http://localhost:8867  这个主意不须要添加/zipkin 后缀

启动运行的结果图

服务之间依赖调用关系图

ps :  zikpin 还提供其余方式的存贮 如 Cassandra，Elasticsearch