[英]Elastic search API Vs Spring data Vs logstash
I am planing to use elastic search for our dashboard using spring boot based rest services. 我计划使用基于Spring Boot的休息服务对我们的仪表板进行弹性搜索。 After research i see top 3 options 经过研究,我看到了前3个选项
Option A: 选项A:
Option B: 选项B:
Or shall I use logstash approach to Sync data between postgressql and elastic search using logstash ? 还是应该使用logstash方法在postgressql和使用logstash的弹性搜索之间同步数据?
Which one among them will be long term approach to get near real time data from ES in high load scenario ?? 在高负载情况下,其中哪一种是从ES获得接近实时数据的长期方法?
Usecase: I need to save some data from postgresql table to elastic search for my dashboard (near real time ) 用例:我需要从postgresql表中保存一些数据以弹性搜索我的仪表板(接近实时)
Update is frequent for both tables and es to maintain current state 两个表和es都经常更新,以保持当前状态
Load is going to increase in couple of week 负载将在几周内增加
The options you listed, in essence, are: should you go with a ready to use solution (logstash) or should you implement your own. 从本质上讲,列出的选项是:应该使用现成的解决方案(logstash),还是应该实现自己的解决方案。
Try logstash first to see if it works for you - it'll take less time than implementing your own solution, and you can get working solution in minutes (if it's not hundreds of tables) 首先尝试使用logstash看看它是否对您有用-比实施自己的解决方案所需的时间更少,而且您可以在数分钟内获得可行的解决方案(如果不是数百张表)
If you want near-real time, then you need to figure out if it allows you to: 如果要近乎实时,则需要弄清楚它是否允许您:
If you decide to go with your own solution, keep in mind that spring-data-elasticsearch is a higher level wrapper for underlying elasticsearch client. 如果您决定采用自己的解决方案,请记住,spring-data-elasticsearch是底层Elasticsearch客户端的高级包装。 If there are latency goals, then working on the lower level (elasticsearch clients) may give you better control and more options to tune the pipeline. 如果有延迟目标,那么在较低级别上工作(elasticsearch客户端)可能会为您提供更好的控制和更多选项来调整管道。
Otherwise, the client choice will not matter that much as data feed features (volume/update frequency) and db/es cluster configuration. 否则,客户端的选择与数据馈送功能(卷/更新频率)和db / es集群配置无关紧要。
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