Logstash：如何使用 Logstash 解析并摄入 JSON 数据到 Elasticsearch |
您所在的位置：网站首页 › mysql解析json数组转化对行数据 › Logstash：如何使用 Logstash 解析并摄入 JSON 数据到 Elasticsearch |
Logstash：如何使用 Logstash 解析并摄入 JSON 数据到 Elasticsearch
|
在我之前的文章 “Logstash：Data 转换，分析，提取，丰富及核心操作” 有涉及到这个话题。今天我想使用一个具体的例子来更深入地展示。 我们先来把如下的数据拷贝下来，并保存到一个叫做 sample.json 的文件中。我们可以把这个文件置于 Logstash 的安装根目录下。 sample.json 1. {"id":1,"timestamp":"2019-09-12T13:43:42Z","paymentType":"Amex","name":"Merrill Duffield","gender":"Female","ip_address":"132.150.218.21","purpose":"Toys","country":"United Arab Emirates","age":33} 2. {"id":2,"timestamp":"2019-08-11T17:55:56Z","paymentType":"Visa","name":"Darby Dacks","gender":"Female","ip_address":"77.72.239.47","purpose":"Shoes","country":"Poland","age":55} 3. {"id":3,"timestamp":"2019-07-14T04:48:25Z","paymentType":"Visa","name":"Harri Cayette","gender":"Female","ip_address":"227.6.210.146","purpose":"Sports","country":"Canada","age":27} 4. {"id":4,"timestamp":"2020-02-29T12:41:59Z","paymentType":"Mastercard","name":"Regan Stockman","gender":"Male","ip_address":"139.224.15.154","purpose":"Home","country":"Indonesia","age":34} 5. {"id":5,"timestamp":"2019-08-03T19:37:51Z","paymentType":"Mastercard","name":"Wilhelmina Polle","gender":"Female","ip_address":"252.254.68.68","purpose":"Health","country":"Ukraine","age":51} 1. $ pwd 2. /Users/liuxg/elastic/logstash-8.6.1 3. $ ls sample.json 4. sample.json 解析及过滤 JSON 文件我们有如下的几种方法： 使用 Logstash 的 Input JSON codec我们创建如下的 Logstash 配置文件： logstash_input.conf ` 1. input { 2. file { 3. path => "/Users/liuxg/elastic/logstash-8.6.1/sample.json" 4. type => "applog" 5. codec => "json" 6. start_position => "beginning" 7. sincedb_path => "/dev/null" 8. } 9. } 11. output { 12. stdout { 13. codec => rubydebug 14. } 15. } `我们运行 Logstash： 1. $ pwd 2. /Users/liuxg/elastic/logstash-8.6.1 3. $ ./bin/logstash -f logstash_input.conf在运行的 terminal 中，我们可以看到如下的结果： 从上面，我们可以看出来我们的数据已经变为结构化的数据了。 使用 JSON filter我们创建如下的一个 Logstash 配置文件： logstash_filter.conf ` 1. input { 2. file { 3. path => "/Users/liuxg/elastic/logstash-8.6.1/sample.json" 4. type => "applog" 5. start_position => "beginning" 6. sincedb_path => "/dev/null" 7. } 8. } 10. filter { 11. json { 12. source => "message" 13. } 14. } 16. output { 17. stdout { 18. codec => rubydebug 19. } 20. } `我们运行 Logstash： 1. $ pwd 2. /Users/liuxg/elastic/logstash-8.6.1 3. $ ./bin/logstash -f logstash_filter.conf在运行的 terminal 中，我们可以看到如下的结果： 从上面我们可以看出来 JSON 文件也被正确地结构化了。 接下来，我们来清理一下我们的数据，并过滤掉那些 paymentType 为 Mastercard 的文档。我们进一步修改配置文件： logstash_filter.conf ` 1. input { 2. file { 3. path => "/Users/liuxg/elastic/logstash-8.6.1/sample.json" 4. type => "applog" 5. start_position => "beginning" 6. sincedb_path => "/dev/null" 7. } 8. } 10. filter { 11. json { 12. source => "message" 13. } 15. if [paymentType] == "Mastercard" { 16. drop {} 17. } 19. mutate { 20. remove_field => ["message", "@timestamp", "path", "host", "@version", "log", "event"] 21. } 23. } 25. output { 26. stdout { 27. codec => rubydebug 28. } 29. } `在上面，我们过滤掉 paymentType 为 Mastercard 的文档，同时，我们也去除一些不需要的字段，比如 message。我们再次运行： 很显然，我们这次没有看到 message 字段，同时 paymentType 为 Mastercard 的文档都被过滤掉了。 处理含有数值的 JSON 数据接下来我们使用另外一组数据。在这个数据里，它的 JSON 文件里含有一个数组： sample-split.json 1. {"id":1,"timestamp":"2019-06-19T23:04:47Z","paymentType":"Mastercard","name":"Ardis Shimuk","gender":"Female","ip_address":"91.33.132.38","purpose":"Home","country":"France","pastEvents":[{"eventId":1,"transactionId":"trx14224"},{"eventId":2,"transactionId":"trx23424"}],"age":34} 2. {"id":2,"timestamp":"2019-11-26T15:40:56Z","paymentType":"Amex","name":"Benoit Urridge","gender":"Male","ip_address":"26.71.230.228","purpose":"Shoes","country":"Brazil","pastEvents":[{"eventId":3,"transactionId":"63323-064"},{"eventId":4,"transactionId":"0378-3120"}],"age":51} 3. {"id":3,"timestamp":"2019-05-08T16:24:25Z","paymentType":"Visa","name":"Lindsy Ketchell","gender":"Female","ip_address":"189.216.71.184","purpose":"Home","country":"Brazil","pastEvents":[{"eventId":5,"transactionId":"68151-3826"},{"eventId":6,"transactionId":"52125-611"}],"age":26} 4. {"id":4,"timestamp":"2019-06-10T18:01:32Z","paymentType":"Visa","name":"Cary Boyes","gender":"Male","ip_address":"223.113.73.232","purpose":"Grocery","country":"Pakistan","pastEvents":[{"eventId":7,"transactionId":"63941-950"},{"eventId":8,"transactionId":"55926-0011"}],"age":46} 5. {"id":5,"timestamp":"2020-02-18T12:27:35Z","paymentType":"Visa","name":"Betteanne Diament","gender":"Female","ip_address":"159.148.102.98","purpose":"Computers","country":"Brazil","pastEvents":[{"eventId":9,"transactionId":"76436-101"},{"eventId":10,"transactionId":"55154-3330"}],"age":41}请注意上面最后面的一个空行。这样可以保证所有的文档被摄入。如上所示，它含有一个叫做 pastEvents 的字段。它是一个数组。在每个文档中，它含有 1 个或多个 eventId。我们可以通过 split 过滤器来把这些 eventId 变成单个的事件。 我们创建如下的一个 Logstash 配置文件： logstash_split.conf ` 1. input { 2. file { 3. path => "/Users/liuxg/elastic/logstash-8.6.1/sample-split.json" 4. type => "applog" 5. start_position => "beginning" 6. sincedb_path => "/dev/null" 7. } 8. } 10. filter { 11. json { 12. source => "message" 13. } 15. split { 16. field => "[pastEvents]" 17. } 19. mutate { 20. remove_field => ["message", "@timestamp", "path", "host", "@version", "log", "event"] 21. } 23. } 25. output { 26. stdout { 27. codec => rubydebug 28. } 29. } `我们可以参考官方文档 Split filter plugin | Logstash Reference [8.6] | Elastic 来了解更多关于 split 过滤的功能。 我们运行上面的 pipeline： ./bin/logstash -f logstash_split.conf我们可以看到在之前的源 JSON 文档中，它共有5个文档，但是经过 split 过滤器后，它现在变为 10 个文档了。 输出到 Elasticsearch经过上面的 input 及 filter，我们得到了我们想要的结构化的数据。我们可以参考文章 “Logstash：如何连接到带有 HTTPS 访问的集群” 把输出结果输出到 Elasticsearch 集群中。这里就不再累述了。 |
【本文地址】
今日新闻 |
推荐新闻 |