Over the years, Elasticsearch and the ecosystem of components that’s grown around it called the “Elastic Stack” has been used for a growing number of use cases, from simple search on a website or document, collecting and analyzing log data, to a business intelligence tool for data analysis and visualization. But the truth is, all of these answers are correct and that’s part of the appeal of Elasticsearch. Depending on your level of familiarity with this technology, these answers may either bring you closer to an ah-ha moment or further confuse you. When people ask, “what is Elasticsearch?”, some may answer that it’s “an index”, “a search engine”, an “analytics database”, “a big data solution”, that “it’s fast and scalable”, or that “it’s kind of like Google”. You can also set up a 15 minute call with a member of our team to see if Knowi may be a good BI solution for your project. So we need to know what we query (index/type), what is the query (request) and the pagination we use (from/size).Before we jump into it, if you have a project and are trying to visualize your Elasticsearch data, take a look at our Elasticsearch Analytics page. So what will look our search API (we'll not handle other endpoints in this post since it is more or less the same thing but this one is the most common): public JsonObject search(String index, String type, Simple Elasticsearch request with JAX-RS and JSON-P So we justified we can go with JAX-RS so now why JSON-P? Here the answer is more trivial: cause it is a built-in and native solution to build JSON limiting error factors on the structure and this is what we'll use to communicate with Elasticsearch. What do you loose with that solution compared to the rest client? Mainly the blacklisting of hosts.well this is not really true since CXF provides some failover and circuit breaker features you can integrate with CXF JAX-RS client (see ). it will be as expressive as the rest client since the API is still bound on HTTP at the moment.the API is stable, known and not a custom one.if you need advanced async features you can still do it (typically CXF can also use http async client as transport).it is there so no need to mess up dependencies.The nice things with JAX-RS for the HTTP part of the client are: This is true but if you step back and check what the rest client really do ( ) you will realize it can be overkill and if you are in a EE server you can just desire to rely on what is there: JAX-RS. You will probably answer me "fine but why not just using JSON-P". Why is it an issue? Simply cause it enforces you to build string and you can do a lot of errors - yes typos. So now you should probably wonder why I spoke of JAX-RS? Simply cause this client - still in beta when I write this post - has the same pitfall than the historical HTTP client "Jest" which is to rely on String for the requests. It is built on top of http client and provides asynchronism through the async version of httpclient. The first one forces you to make your application part of the cluster which is rarely a good idea or even what you want so we have the HTTP solution.īefore Elasticsearch 5.0 you were quite naked but since 5.0 elasticsearch provides a java REST client. , Romain Manni-Bucau,, 4 min and 24 sec readĮlasticsearch proposes API for java developers.
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