收集、分析线上日志数据实战——ELK

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我是靠谱客的博主淡淡舞蹈，最近开发中收集的这篇文章主要介绍收集、分析线上日志数据实战——ELK，觉得挺不错的，现在分享给大家，希望可以做个参考。

概述

本文来自网易云社区

作者：田躲躲

用户行为统计(User Behavior Statistics, UBS)一直是互联网产品中必不可少的环节，也俗称埋点。对于产品经理，运营人员来说，埋点当然是越多，覆盖范围越广越好。通过用户行为分析系统可洞悉用户基本操作习惯、探析用户心理。通过行为数据的补充，构建出精细、完整的用户画像，对不同特征用户做个性化营销，提升用户体验。让产品设计人员准确评估用户行为路径转化、产品改版优良、某一新功能对产品的影响几何，让运营人员做精准营销并且评估营销结果等。

目前所负责项目前期采用了前后端约定字段，埋点统计用户操作行为。数据存放在DDB中。如果用户行为日志非常大的话，这种方式肯定是不可行的。故采用了目前比较成熟的ELK代替之前的统计流程。本篇文章主要介绍ELK集群搭建，基本API封装，以及遇到的一些坑。

Elasticsearch

Elasticsearch是一个基于Lucene构建的开源、分布式、RESTful风格的搜索引擎。它被设计用于云计算中，具有实时搜索负载、稳定、快速、安装使用方便等优点。（之前用过SolrCloud，ES对用户的侵入性简直可以忽略）

集群安装：

每台机器先配置elasticsearch.yml，主要配置信息如下：

#
# ---------------------------------- Cluster -----------------------------------
#
# Use a descriptive name for your cluster:
#
cluster.name: es-commenta-event #其他机器集群名称应该保持一致
#
# ------------------------------------ Node ------------------------------------
#
# Use a descriptive name for the node:
#
node.name: es-node-c1
#
# Add custom attributes to the node:
#
#node.attr.rack: r1
#
# ----------------------------------- Paths ------------------------------------
#
# Path to directory where to store the data (separate multiple locations by comma):
#
path.data: /opt/elk/elasticsearch-5.1.1/data
#
# Path to log files:
#
path.logs: /opt/elk/elasticsearch-5.1.1/logs
#
# ----------------------------------- Memory -----------------------------------
#
# Lock the memory on startup:
#
#bootstrap.memory_lock: true
#
# Make sure that the heap size is set to about half the memory available
# on the system and that the owner of the process is allowed to use this
# limit.
#
# Elasticsearch performs poorly when the system is swapping the memory.
#
# ---------------------------------- Network -----------------------------------
#
# Set the bind address to a specific IP (IPv4 or IPv6):
#
network.host: 192.168.140.133 #本机器host
#
# Set a custom port for HTTP:
#
#http.port: 9200
#
# For more information, see the documentation at:
# <http://www.elastic.co/guide/en/elasticsearch/reference/current/modules-network.html>
#
# --------------------------------- Discovery ----------------------------------
#
# Pass an initial list of hosts to perform discovery when new node is started:
# The default list of hosts is ["127.0.0.1", "[::1]"]
#
discovery.zen.ping.unicast.hosts: ["192.168.140.133",  "192.168.140.134", "192.168.140.135"] #集群host列表

# Prevent the "split brain" by configuring the majority of nodes (total number of nodes / 2 + 1):
#
discovery.zen.minimum_master_nodes: 2复制代码

集群启动：

Q1：can not run elasticsearch as root

因为是本地虚拟机root安装的，启动的时候会报这个错。解决方案是：

group esgroup 
useradd esuser -g esgroup -p espassword
chown -R esuser:esgroup /etc/
chown -R esuser:esgroup /opt/复制代码

切换到esuser用户即可执行启动命令。

Q2：Unsupported major.minor version 52.0

目前安装的ES版本为5.1.1，需要Jdk1.8的版本，故安装下Jdk1.8，配置下环境变量，即可执行启动命令。

Q3：max virtual memory areas vm.max_map_count [65530] likely too low, increase to at least [262144]

ES启动占用更大的内存。修改如下：

sysctl -w vm.max_map_count=262144复制代码

每个ES服务设置好后，就可以真正启动了。依次启动机器的时候，可以看下机器日志是否有node加入到集群。如：

curl '192.168.140.133:9200'{    "name": "es-node-c1", 
    "cluster_name": "es-commenta-event", 
    "cluster_uuid": "wi_1VOWoRqecjIht3Ra3mg", 
    "version": {        "number": "5.1.1", 
        "build_hash": "5395e21", 
        "build_date": "2016-12-06T12:36:15.409Z", 
        "build_snapshot": false, 
        "lucene_version": "6.3.0"
    }, 
    "tagline": "You Know, for Search"}复制代码

目前有3台虚拟机，默认ES有5个节点，可以通过命令创建3个节点的index，每个主节点有一个复制节点。

curl -XPUT 'http://192.168.140.133:9200/commenta' -d '{"settings" : {"number_of_shards" : 3,"number_of_replicas" : 1}}'复制代码

集群状态：

curl 'http://192.168.140.133:9200/_cluster/health?pretty'{  "cluster_name" : "es-commenta-event",  "status" : "green",  "timed_out" : false,  "number_of_nodes" : 3,  "number_of_data_nodes" : 3,  "active_primary_shards" : 3,  "active_shards" : 6,  "relocating_shards" : 0,  "initializing_shards" : 0,  "unassigned_shards" : 0,  "delayed_unassigned_shards" : 0,  "number_of_pending_tasks" : 0,  "number_of_in_flight_fetch" : 0,  "task_max_waiting_in_queue_millis" : 0,  "active_shards_percent_as_number" : 50.0}复制代码

安装插件：

通过类SQL转化成DSL
bin/elasticsearch-plugin install install https://github.com/NLPchina/elasticsearch-sql/releases/download/5.1.1.0/elasticsearch-sql-5.1.1.0.zip复制代码

X-Pack集成了权限、监控等功能，是一款非常有用的插件。但是商用的，收费。
bin/elasticsearch-plugin install x-pack复制代码

Logstash

Logstash是一款轻量级的日志搜集处理框架，可以方便的把分散的、多样化的日志搜集起来，并进行自定义的处理，然后传输到指定的位置。

安装：

到官网下载logstash5.1.1版本即可。

启动：

1、无配置文件启动

bin/logstash -e 'input{ stdin{} } output{ stdout{} }'Sending Logstash's logs to /home/webedit/logstash/logstash-5.1.1/logs which is now configured via log4j2.properties
The stdin plugin is now waiting for input:
[2017-04-27T15:47:38,023][INFO ][logstash.pipeline        ] Starting pipeline {"id"=>"main", "pipeline.workers"=>4, "pipeline.batch.size"=>125, "pipeline.batch.delay"=>5, "pipeline.max_inflight"=>500}
[2017-04-27T15:47:38,039][INFO ][logstash.pipeline        ] Pipeline main started
[2017-04-27T15:47:38,115][INFO ][logstash.agent           ] Successfully started Logstash API endpoint {:port=>9600}
hello elastic
2017-04-27T07:49:00.966Z localhost.localdomain hello elastic复制代码

logstash会采集命令行输入的命令

2、配置文件启动

假设我们需要采集的日志记录是这种格式的：

INFO  [17.04.27 16:12:12][com.netease.mail.vip.commenta.filter.EventLogFilter]: |44171|1|1|1|1493280732227|0.0|123.58.160.131|133001|COMMENTA-B54C43F5-4FCB-4D10-B9EC-67862FBF0055|1493280732440|huiping_mp|0.7.0|null|1|复制代码

如何采集这种格式的日志呢？这里采用正则表达式去匹配，具体配置文件如下：

input {

file {
    type => "commenta"
    path => ["/home/logs/commenta/stdout.log"]
    start_position => "beginning"
    codec => plain { charset => "Windows-1252" }
}

}

filter {if [type] == "commenta" {
    grok {
      match => { "message" => "%{DATA:className}|%{BASE16FLOAT:id}|%{DATA:eventType:int}|%{DATA:page:int}|%{DATA:eventFrom:int}|%{DATA:eventTime}|%{BASE16FLOAT:eventWeight}|%{DATA:ip}|%{BASE16FLOAT:userId}|%{DATA:uniqueCode}|%{DATA:createTime}|%{DATA:clientFrom}|%{DATA:appVersion}|%{DATA:data}|%{DATA:eventStep:int}|"}
          remove_field => ["message"]
        }
}if '_grokparsefailure' in [tags] { #过滤掉不匹配的事件
	drop{}
}

	mutate  { #数据类型转换  
                        convert => [ "eventWeight", "float"]
                        convert => [ "id", "float"]
                        convert => [ "userId", "float"]
                }


}
output{
       
       stdout { codec => rubydebug } #打印出行为日志记录在控制台

       elasticsearch{
             hosts => ["192.168.140.133:9200","192.168.140.134:9200","192.168.140.135:9200"]
             index => "commenta"
        }
}复制代码

下面我们可以启动logstash看下效果：

./bin/logstash -f ./config/logstash.conf{     "appVersion" => "0.7.0",           "data" => "null",             "ip" => "XXXXXXXXX",      "className" => "INFO  [17.04.27 16:12:12][com.netease.mail.vip.commenta.filter.EventLogFilter]: ",      "eventType" => 1,           "type" => "commenta",    "eventWeight" => 0.0,         "userId" => 133001.0,           "tags" => [],           "path" => "/home/logs/commenta/stdout.log",     "@timestamp" => 2017-04-27T08:18:58.245Z,     "uniqueCode" => "COMMENTA-B54C43F5-4FCB-4D10-B9EC-67862FBF0055",     "createTime" => "1493280732440",       "@version" => "1",           "host" => "testfb-m126-161",      "eventTime" => "1493280732227",      "eventStep" => 1,     "clientFrom" => "huiping_mp",             "id" => 44171.0,           "page" => 1,      "eventFrom" => 1}复制代码

通过打印在控制台的日志可以看到我们已经通过logstash收集到了行为日志记录（部分数据已脱敏）。当然我们也可以通过Kibana看到这些数据，下部分将会讲到。

3、启动问题

Q1：Unsupported major.minor version 52.0

使用的是Logstash版本为5.1.1，需要Jdk1.8的环境，故安装下Jdk1.8，配置下环境变量，即可执行启动命令。

Q2：unknown setting host for elasticsearch

配置Logstash的启动文件时，注意版本的问题，如host-->hosts

Kibana

Kibana是一个开源的分析与可视化平台，设计出来用于和Elasticsearch一起使用的。你可以用kibana搜索、查看、交互存放在Elasticsearch索引里的数据，使用各种不同的图表、表格、地图等kibana能够很轻易地展示高级数据分析与可视化。

安装：

到官网下载Kibana5.1.1版本即可。

启动：

主要配置如下：

# Kibana is served by a back end server. This setting specifies the port to use.
#server.port: 5601

# Specifies the address to which the Kibana server will bind. IP addresses and host names are both valid values.
# The default is 'localhost', which usually means remote machines will not be able to connect.
# To allow connections from remote users, set this parameter to a non-loopback address.
server.host: "192.168.140.133"

# Enables you to specify a path to mount Kibana at if you are running behind a proxy. This only affects
# the URLs generated by Kibana, your proxy is expected to remove the basePath value before forwarding requests
# to Kibana. This setting cannot end in a slash.
#server.basePath: ""

# The maximum payload size in bytes for incoming server requests.
#server.maxPayloadBytes: 1048576

# The Kibana server's name.  This is used for display purposes.
#server.name: "your-hostname"

# The URL of the Elasticsearch instance to use for all your queries.
elasticsearch.url: "http://192.168.140.133:9200"
.......复制代码

启动成功后，我们可以监控commenta*的索引（安装ES的时候，创建了）

bin/kibana复制代码

这时候就可以看到Logstash收集到的数据日志了

当然我们也可以配置一些统计：

为了更直观的展示，我们可以把统计“拖拽”到Dashboard中。

至此，ELK已经搭建完成，并提供一些简单的功能。但是有一些统计Kibana是做不了的。这时候我们程序需要处理一下。

Java API

HandleEsClientServer

/* ES服务器列表 */
    private String serverList;    /* 设置client.transport.sniff为true来使客户端去嗅探整个集群的状态，把集群中其它机器的ip地址加到客户端中，它会自动帮你添加，并且自动发现新加入集群的机器 */
    private Boolean sniff = false;    /* 集群名称 */
    private String clusterName;    /* 连接客户端 */
    private Client client;    /* 搜索基本工具类 */
    private SearchDao searchDao;    public HandleEsClientServer() {
    }    public HandleEsClientServer(String serverList, Boolean sniff, String clusterName) {        this.serverList = serverList;        this.sniff = sniff;        this.clusterName = clusterName;
    }    @Override
    public void afterPropertiesSet() throws Exception {

        logger.info("es server start at time={}, serverList={}, clusterName={}, sniff={}", DateUtil.toStr(new Date(),DateUtil.YYYY_MM_DD_HH_MM_SS),
                serverList, clusterName, sniff);        if (this.getServerList() == null || this.getServerList().length() == 0) {
            logger.error("es serverList is null...");            return;
        }

        List clusterList = Splitter.on(",").trimResults().omitEmptyStrings().splitToList(this.getServerList());

        List transportAddresses = new ArrayList<>();        for (String cluster : clusterList) {
            List host = Splitter.on(":").trimResults().omitEmptyStrings().splitToList(cluster);
            String ip = host.get(0);
            Integer port = Integer.valueOf(host.get(1));            try {
                transportAddresses.add(new InetSocketTransportAddress(InetAddress.getByAddress(getIpByte(ip)), port == null ? 9300 : port));
            } catch (UnknownHostException e) {
                logger.error("init es client error={} at time={} ", e, DateUtil.toStr(new Date(),DateUtil.YYYY_MM_DD_HH_MM_SS));                return;
            }
        }        //配置启动参数
        Settings settings = Settings.builder()
                .put("cluster.name", clusterName)
                .put("client.transport.sniff", sniff)
                .build();        //初始化Client
        this.client = new PreBuiltTransportClient(settings)
                .addTransportAddresses(transportAddresses.toArray(new TransportAddress[transportAddresses.size()]));        this.searchDao = new SearchDao(this.client);

        logger.info("es server start success at time={}", DateUtil.toStr(new Date(),DateUtil.YYYY_MM_DD_HH_MM_SS));

    }复制代码

HandleEsData

 /**
     * 根据elasticsearch-sql插件的sql语句查询结果。
     * @param query
     * @return
     * @throws SqlParseException
     * @throws SQLFeatureNotSupportedException
     */
    public SqlResponse selectBySQL(String query) throws SqlParseException, SQLFeatureNotSupportedException {

        logger.info("selectBySQL, query={}",query);        try{
            SqlElasticSearchRequestBuilder select = (SqlElasticSearchRequestBuilder) searchDao.explain(query).explain();            return new SqlResponse((SearchResponse)select.get());
        }catch (Exception e){
            logger.error(e.getMessage(),e);
        }        return null;

    }/**
     * 批量插入数据，使用Obj的id字段。
     * @param _index
     * @param _type
     * @param data
     * @param generate_id
     * @param 
     * @return
     */
    public  BulkResponse batchObjIndex(String _index, String _type, List data, boolean generate_id){

        logger.info("batchObjIndex, index={}, type={}, data={}, generate_id={}", _index, _type, data, generate_id);

        Assert.notEmpty(data, "data is not allowed empty");

        BulkRequestBuilder bulkRequest = client.prepareBulk();        for (T tObj : data) {
            Class clazz = tObj.getClass();
            String json = JSONObject.toJSONString(tObj, SerializerFeature.WriteMapNullValue);            if(generate_id){
                bulkRequest.add(client.prepareIndex(_index.toLowerCase(), _type.toLowerCase()).setSource(json));
            } else {                try {
                    Object value = clazz.getDeclaredMethod("getId").invoke(tObj);
                    String _id = String.valueOf(value);
                    bulkRequest.add(client.prepareIndex(_index.toLowerCase(), _type.toLowerCase(), _id).setSource(json));
                } catch (Exception e) {
                    logger.error(e.getMessage(),e);
                }
            }
        }        return bulkRequest.execute().actionGet();
    }复制代码