Logstash處理json格式日志文件的三種方法

假設日志文件中的每一行記錄格式為json的，如：

{"Method":"JSAPI.JSTicket","Message":"JSTicket:kgt8ON7yVITDhtdwci0qeZg4L-Dj1O5WF42Nog47n_0aGF4WPJDIF2UA9MeS8GzLe6MPjyp2WlzvsL0nlvkohw","CreateTime":"2015/10/13 9:39:59","AppGUID":"cb54ba2d-1d38-45f2-9ed1-abff0bf7dd3d","_PartitionKey":"cb54ba2d-1d38-45f2-9ed1-abff0bf7dd3d","_RowKey":"1444700398710_ad4d33ce-a9d9-4d11-932e-e2ccebdb726c","_UnixTS":1444700398710}

默認配置下，logstash處理插入進elasticsearch后，查到的結果是這樣的：

{
    "_index": "logstash-2015.10.16",
    "_type": "voip_feedback",
    "_id": "sheE9eXiQASMDVtRJ0EYcg",
    "_version": 1,
    "found": true,
    "_source": { "message": "{\"Method\":\"JSAPI.JSTicket\",\"Message\":\"JSTicket:kgt8ON7yVITDhtdwci0qeZg4L-Dj1O5WF42Nog47n_0aGF4WPJDIF2UA9MeS8GzLe6MPjyp2WlzvsL0nlvkohw\",\"CreateTime\":\"2015/10/13 9:39:59\",\"AppGUID\":\"cb54ba2d-1d38-45f2-9ed1-abff0bf7dd3d\",\"_PartitionKey\":\"cb54ba2d-1d38-45f2-9ed1-abff0bf7dd3d\",\"_RowKey\":\"1444700398710_ad4d33ce-a9d9-4d11-932e-e2ccebdb726c\",\"_UnixTS\":1444700398710}", "@version": "1", "@timestamp": "2015-10-16T00:39:51.252Z", "type": "voip_feedback", "host": "ipphone", "path": "/usr1/data/voip_feedback.txt" } }

即會將json記錄做為一個字符串放到”message”下，但是我是想讓logstash自動解析json記錄，將各字段放入elasticsearch中。有三種配置方式可以實現。

第一種，直接設置format => json

    file {
        type => "voip_feedback" path => ["/usr1/data/voip_feedback.txt"] format => json sincedb_path => "/home/jfy/soft/logstash-1.4.2/voip_feedback.access" }

這種方式查詢出的結果是：

{
    "_index": "logstash-2015.10.16",
    "_type": "voip_feedback",
    "_id": "NrNX8HrxSzCvLl4ilKeyCQ",
    "_version": 1,
    "found": true,
    "_source": { "Method": "JSAPI.JSTicket", "Message": "JSTicket:kgt8ON7yVITDhtdwci0qeZg4L-Dj1O5WF42Nog47n_0aGF4WPJDIF2UA9MeS8GzLe6MPjyp2WlzvsL0nlvkohw", "CreateTime": "2015/10/13 9:39:59", "AppGUID": "cb54ba2d-1d38-45f2-9ed1-abff0bf7dd3d", "_PartitionKey": "cb54ba2d-1d38-45f2-9ed1-abff0bf7dd3d", "_RowKey": "1444700398710_ad4d33ce-a9d9-4d11-932e-e2ccebdb726c", "_UnixTS": 1444700398710, "@version": "1", "@timestamp": "2015-10-16T00:16:11.455Z", "type": "voip_feedback", "host": "ipphone", "path": "/usr1/data/voip_feedback.txt" } }

可以看到，json記錄已經被直接解析成各字段放入到了_source中，但是原始記錄內容沒有被保存

第二種，使用codec => json

    file {
        type => "voip_feedback" path => ["/usr1/data/voip_feedback.txt"] sincedb_path => "/home/jfy/soft/logstash-1.4.2/voip_feedback.access" codec => json { charset => "UTF-8" } }

這種方式查詢出的結果與第一種一樣，字段被解析，原始記錄內容也沒有保存

第三種，使用filter json

filter {
    if [type] == "voip_feedback" { json { source => "message" #target => "doc" #remove_field => ["message"] } } }

這種方式查詢出的結果是這樣的：

{
    "_index": "logstash-2015.10.16",
    "_type": "voip_feedback",
    "_id": "CUtesLCETAqhX73NKXZfug",
    "_version": 1,
    "found": true,
    "_source": { "message": "{\"Method222\":\"JSAPI.JSTicket\",\"Message\":\"JSTicket:kgt8ON7yVITDhtdwci0qeZg4L-Dj1O5WF42Nog47n_0aGF4WPJDIF2UA9MeS8GzLe6MPjyp2WlzvsL0nlvkohw\",\"CreateTime\":\"2015/10/13 9:39:59\",\"AppGUID\":\"cb54ba2d-1d38-45f2-9ed1-abff0bf7dd3d\",\"_PartitionKey\":\"cb54ba2d-1d38-45f2-9ed1-abff0bf7dd3d\",\"_RowKey\":\"1444700398710_ad4d33ce-a9d9-4d11-932e-e2ccebdb726c\",\"_UnixTS\":1444700398710}", "@version": "1", "@timestamp": "2015-10-16T00:28:20.018Z", "type": "voip_feedback", "host": "ipphone", "path": "/usr1/data/voip_feedback.txt", "Method222": "JSAPI.JSTicket", "Message": "JSTicket:kgt8ON7yVITDhtdwci0qeZg4L-Dj1O5WF42Nog47n_0aGF4WPJDIF2UA9MeS8GzLe6MPjyp2WlzvsL0nlvkohw", "CreateTime": "2015/10/13 9:39:59", "AppGUID": "cb54ba2d-1d38-45f2-9ed1-abff0bf7dd3d", "_PartitionKey": "cb54ba2d-1d38-45f2-9ed1-abff0bf7dd3d", "_RowKey": "1444700398710_ad4d33ce-a9d9-4d11-932e-e2ccebdb726c", "_UnixTS": 1444700398710, "tags": [ "111", "222" ] } }

可以看到，原始記錄被保存，同時字段也被解析保存。如果確認不需要保存原始記錄內容，可以加設置：remove_field => [“message”]

比較以上三種方法，最方便直接的就是在file中設置format => json

另外需要注意的是，logstash會在向es插入數據時默認會在_source下增加type,host,path三個字段，如果json內容中本身也含有type,host,path字段，那么解析后將覆蓋掉logstash默認的這三個字段，尤其是type字段，這個同時也是做為index/type用的，覆蓋掉后，插入進es中的index/type就是json數據記錄中的內容，將不再是logstash config中配置的type值。

這時需要設置filter.json.target，設置該字段后json原始內容將不會放在_source下，而是放到設置的”doc”下：

{
    "_index": "logstash-2015.10.20",
    "_type": "3alogic_log",
    "_id": "xfj3ngd5S3iH2YABjyU6EA",
    "_version": 1,
    "found": true,
    "_source": { "@version": "1", "@timestamp": "2015-10-20T11:36:24.503Z", "type": "3alogic_log", "host": "server114", "path": "/usr1/app/log/mysql_3alogic_log.log", "doc": { "id": 633796, "identity": "13413602120", "type": "EAP_TYPE_PEAP", "apmac": "88-25-93-4E-1F-96", "usermac": "00-65-E0-31-62-5D", "time": "20151020-193624", "apmaccompany": "TP-LINK TECHNOLOGIES CO.,LTD", "usermaccompany": "" } } }

這樣就不會覆蓋掉_source下的type,host,path值
而且在kibana中顯示時字段名稱為doc.type,doc.id…