Is it possible to update index built using elastic search without the overheads of http and serialization?
I am searching for an elasticsearch equivalent of EmbeddedSolrServer available with solrj.
Sure it is, with elasticsearch you can easily start up a local node and embed it in your application.
With local node I mean with local discovery, local within the jvm.
Have a look at the Java API documentation, where there's an example on how to startup a local node:
Node node = nodeBuilder().local(true).node();
Client client = node.client();
Don't forget to shut it down when you're done:
node.close();
Have a look at this blog I wrote too: elasticsearch beyond big data - running elasticsearch embedded.
Related
I have a neo instance and a Elasticsearch instance running on a docker compose container.
I would like to eventually create visualization using Elasticsearch using Neo4j data but first I need to find a way to get the two to talk. I have the APOC plugin also if that is relevant. What is the syntax for talking to neo from Devtools in Elastic? Here is what I have so far
Works on Neo4j:
call apoc.bolt.load("bolt://neo4j:fall2021#localhost:7687","match(n) RETURN n LIMIT 5")
Does not work on Elastic:
GET apoc.bolt.load("bolt://neo4j:fall2021#localhost:7687")
To echo the above comments, you cannot do this.
Kibana will only ever talk to the Elasticsearch instance it has been configured to talk to.
I have elastic search cluster.
Currently designing a python service for client for read and write query to my elastic search. The python service will not be maintained by me. Only internally python service will call our elastic search for fetching and writing
Is there any way to configure the elastic search so that we get to know that the requests are coming from python service, Or any way we can pass some extra fields while querying based on that fields we will get the logs
There is no online feature in elasticsearch to resolve your request. (you want to check the source and add fields to query).
but there is a solution for audit logs.
https://www.elastic.co/guide/en/elasticsearch/reference/current/enable-audit-logging.html
What you can do is placing a proxy in front of it and do the logging there, we have an Apache in front of our Elastic clusters to enable SSL-offloading there and add logging and ACL possibilities.
can kibana's console (in Dev Tools) be used for writing and implementing elasticsearch ? I am new to elasticsearch and very confused when it comes to doing hands-on it. thank you in advance.
kibana Dev tools makes calling elastic search API's easier so you can develop what ever you want in kibana Dev tools to make aggregation call or make query string to call the API's.
on the other hand you should use it with an SDK in your application like Elasticsearch JS for javascript so you can use the developed queries and aggregations in kibana to be used in your application and more you can monitor your shards health or put mapping for your indexes and more of functionality which can be found in Documentation, Although, you can find JS API's Documentation here
You can use Kibana Dev Tools to invoke REST API commands to perform cluster level actions such as taking snapshots, restore etc and also index simple documents. But, if you are looking to writing data to Elastic on a regular basis like ingesting server/ app logs or server metrics (CPU, memory, Disk usage etc) you should look at installing filebeats or metricbeats.
Migrating to mongo is well documented but I could not find a reference/guidelines for configuring the server to work with an n-node mongo cluster.
Mlabs suggest that if using anything other than single node (aka sandbox) users should run tests to cover primary node failure.
Has anyone configured parse server on let's say a 3-node mongo? How?
Alternatively, what volume of users/requests should prompt an n-node mongo cluster set up?
use the uri you're given by the likes of mlab (mongo labs) - parse server will sort it out...
I have a couchbase cluster setup as the primary source for data. From this a subset of data is synced to a elasticsearch cluster via the Couchbase Transport Plugin for ElasticSearch(https://github.com/couchbaselabs/elasticsearch-transport-couchbase) which sets up an XDCR stream from couchbase to elasticsearch.
Due to some issues with the elasticsearch cluster all data needs to be synced again from couchbase to elasticsearch. I have tried recreating XDCR but that does not seem to help as it only copies a very small subset of documents. Is there a way by which this can be achieved?
Additional details
Couchbase version: 3.1.0
Number of couchbase documents: 50K+
Documents synced to elasticsearch: around 700 (expected 20K+)
If a document in couchbase is modified it is successfully synced to elasticsearch
The issue you're experiencing is likely in one of the following: XDCR, the Couchbase Transport Plugin for Elasticsearch, or Elasticsearch itself.
Start by checking for XDCR errors. You can find your XDCR logs using these instructions. Be aware that the Transport Plugin uses XDCR v1 and almost everything else in Couchbase uses v2.
Consult the advice in troubleshooting the Couchbase Transport Plugin for Elasticsearch. Instructions should work for you even though they are from the 4.0 docs.
Pay attention to how your documents are being mapped to Elasticsearch. You mention that you're expecting only a subset of documents to be synced to Elasticsearch, so it's possible that you have lost a setting or misconfigured something. You can enable logging and observe a small set of test data. At TRACE level, you should be able to see each document that is inspected.
If all of that fails, make sure the basics are working by indexing the beer sample dataset, following the directions in the Couchbase docs. ES is probably not the issue, but test with a fresh ES instance will rule out problems on that side.