I am trying to make an scalable app using Parse with a search function provided by ElasticSearch.
It seems like I will have to host my own ElasticSearch server which connects to Parse via the ES MongoDB river.
Is this true? Or will Parse handle hosting ES.
I am new to both these solutions.
I recently had the same question. Googling site:parse.com elasticsearch currently only returns 2 results neither of which actually give us an answer. Exploring Parse's discussion forum doesn't provide much help either - the four posts even slightly related to elasticsearch hint at the possibility that Parse wont host ES.
So the answer is... drum roll... maybe :(
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I'm new to using elastic search, and I'm trying to find a datastore for our application where we can also add a front end for analytics, in this case Kibana. I'm planning to use them as a datastore for dr/cr transactions on our billing system.
Most use case I read is towards data analytics and searching related. I don't see a use case wherein it is used as a regular datastore for an application. So I'm worried I might use it on a wrong use case.
I was hoping if anyone can add their insights on this. Like why or why not use Elastic Search as authoritative/primary datastore for applications.
You should read a official blog of elasticsearch, where they clearly mentioned that databases must be robust and should not stop working unless you tell to do it.
From the robustness section of same blog
A database should be robust, especially if it is your authoritative
system of record. Ideally, a costly query should be possible to
cancel, and you certainly don't want the database to stop working
unless you tell it to.
Unfortunately, Elasticsearch (and the components it's made of) does
not currently handle OutOfMemory-errors very well. We cover this in
more depth in Elasticsearch in Production, OutOfMemory-Caused Crashes.
It is very important to provide Elasticsearch with enough memory and
be careful before running searches with unknown memory requirements on
a production cluster.
In short, you shouldn't use Elasticsearch as a primary data-store where you can't afford to loose the data.
I was trying to understand how Elastic-search compares with GraphQL when they try to solve similar purpose, or does GraphQL uses Elastic-search as a datasource? If anyone done further research share your understanding here ? Thanks in advance.
GraphQL is as the name suggests a query language (mostly for Web APIs). Elastic Search is a data store that exposes a "RESTful" interface. This interface also has some kind of a query language. In that sense they solve different problems:
GraphQL is for exposing data to web clients or apps. It is build to solve challenges faced in client server communication and app development. GraphQL tries to reduce the amount requests and the size of data sent between client and server. Furthermore it give you the ability to extend your API without versioning to keep old clients (e.g. old versions of your mobile app) working.
Elastic search is built to query large amounts of data effectively. Some of their prime use cases are advertised on their website. Usually you would not want to expose the elastic API directly to your client. GraphQL could act as a layer in between that restricts the operations allowed for clients and uses - as you said - elastic as a data source. Or maybe elastic search at some point likes GraphQL so much that they offer an API to write queries in GraphQL that would replace the REST API.
So now that we know that they solve different problems and can be used together, comparing them doesn't really make much sense.
I'm trying to use an open data portal which is CKAN . However its search platform uses solr , but i want to use elasticsearch to index my data . Is this a way to use elasticsearch with CKAN ?
Thanks.
The short answer is no.
ES is probably more popular now, but I can't think of any really good reason to switch from SOLR. They are both just wrappers around Lucene. Please do say what your reasoning is.
It's certainly doable, since the coupling with SOLR is reasonably loose. There was some work towards this here: https://github.com/ckan/ckan/pull/3118 which no doubt you'd be welcome to help resource.
We are developing a search engine application in Life Ray 7 and Elastic-Search(2.2). I’ve gone through the official documentation of Life-ray 7 API’ for elastic search but it only describes some classes we need to use and very confusing. We are not using elastic search native API and Transport client.
How to connect to EL from Life-ray? (We have gone through this official link )
How to use life-ray 7 API for indexing and searching in Elastic search?( The official doc only mentions some classes for doing this. We can't find a doc to see how to use them, even Javadoc contains nothing)
I really appreciate if someone can provide us a link to a proper tutorial or an example of how to index a document (for ex: a profile object) in Elastic search on localhost.
We are completely new to the Liferay and elastic search, pardon me for any mistake. Also, we know how to develop the above logics using Native API of elastic search and Java Transport Client.
How to connect to EL from Life-ray?
This link describes the step-by-step process required to setup Liferay with Elastic search.
How to use life-ray 7 API for indexing and searching in Elastic search?
The API's for search/indexing in Liferay 7.0 hasn't changed much. So, I would suggest referring to this link.
I personally haven't implemented Elastic Search in the past as I have used only GSA in my experience. However, I'm pretty sure this documentation is sufficient to get started.
I am new to elasticsearch, and currently studying the scriptting in ES.It would be really great if anyone who knows scripting in elasticsearch can put some light over scripting and its use in ES ?
You can start with reading elasticsearch documentation. Scripting is covered in the following topics on elasticsearch web site:
General information
Script Fields
Using script to filter the results
Using script to sort the results
Using scripts in facets (see individual facet documentation pages)
If after reviewing these pages, you still have concreate questions about scripting, don't hesitate to ask them in elasticsearch mailing list or on stackoverflow. Following guidelines on the Help page of elasticsearch website will significantly improve your chances of getting quick and useful answer.