I want to send queries to Elasticsearch through the Elasticsearch plugin within Logstash for every event in process. However, Logstash sends requests to Elasticsearch in bulk and indexed events are not immediately made available for search in Elasticsearch. It seems to me that there will be a lag (up to in process a second or more) between an index passing through Logstash and it being searchable. I don't know how to solve this.
Do you have any idea ?
Thank you for your time.
Joe
Related
I want to log all the queries made to Elasticsearch along with their response bodies in kibana.
Is there a way to do that?
I came to know a way to set. t he slowlogs threshold to 0 and log all the queries i slowlogs and then use filebeat to push those queries to kibana.
Is there any other way to do that
As far as I know, this is not available atleast in basic and free version and even if you set search slowlog threshold to 0ms it will just log the search query and other metadata of search query but wouldn't log the search query response.
It would be better to do this in your application which generated the search query and parse the response, then using filebeat you can send the application logs to Elasticsearch.
I have a large ingestion pipeline, and sometimes it takes awhile for things to progress from source to the Elasticsearch index. Currently, when we parse our messages with Logstash, we parse the #timestamp field based on when the message was written by the source. However, due to large volumes of messages, it takes a currently unknown and possibly very inconsistent length of time to travel from the source producer before it's ingested by Logstash and sent to the Elasticsearch index.
Is there a way to add a field to the Elasticsearch output plugin for Logstash that will mark when a message is sent to Elasticsearch?
You can try to add a ruby filter as your last filter to create a field with the current time.
ruby {
code => "event.set('fieldName', Time.now())"
}
You can do it in an ingest pipeline. That means the script is executed in elasticsearch, so it has the advantage of including any delays caused by back-pressure from the output.
I am trying to search and fetch the documents from Elasticsearch but in some cases, I am not getting the updated documents. By updated I mean, we update the documents periodically in Elasticsearch. The documents in ElasticSearch are updated at an interval of 30 seconds, and the number of documents could range from 10-100 Thousand. I am aware that the update is generally a slow process in Elasticsearch.
I am suspecting it is happening because Elasticsearch though accepted the documents but the documents were not available for searching. Hence I have the following questions:
Is there a way to measure the time between indexing and the documents being available for search? There is setting in Elasticsearch which can log more information in Elasticsearch logs?
Is there a setting in Elasticsearch which enables logging whenever the merge operation happens?
Any other suggestion to help in optimizing the performance?
Thanks in advance for your help.
By default the refresh_interval parameter is set to 1 second, so unless you changed this parameter each update will be searchable after maximum 1 second.
If you want to make the results searchable as soon as you have performed the update operation you can use the refresh parameter.
Using refresh=wait_for the endpoint will respond once a refresh has occured. If you use refresh=true a refresh operation will be triggered. Be careful using refresh=true if you have many update since it can impact performances.
Is there a way to get the date and time that an elastic search document was written?
I am running es queries via spark and would prefer NOT to look through all documents that I have already processed. Instead I would like read the only documents that were ingested between the last time the program ran and now.
What is the best most efficient way to do this?
I have looked at;
updating to add a field with an array with booleans for if its been looked at by which analytic. The negative is waiting for the update to occur.
index per time frame method, which would be to break down the current indexes into smaller ones so by hour.The negative I see is the number of open file descriptors.
??
Elasticsearch version 5.6
I posted the question on the elasticsearch discussion board and it appears using the ingest pipeline is the best option.
I am running es queries via spark and would prefer NOT to look through
all documents that I have already processed. Instead I would like read
the only documents that were ingested between the last time the
program ran and now.
A workaround could be :
While inserting data using Logstash to Elasticsearch, Logstash appends a #timestamp key to the document which represents the time (in UTC) at which the document is created or we can use an ingest pipline
After that we can query based on the timestamp.
For more on this please have a look at :
Mapping changes
There is no way to ask ES to insert a timestamp at index time
Elasticsearch doesn't have such functionality.
You need manually save with each document date. In this case you will be able to search by date range.
I'm using CouchDB river plugin with Elastic Search. In my web application, I am using CouchDB's bulk insert to insert documents into CouchDB. This triggers the changes feed and ES reads this to index my documents. The problem now is that my web ui isn't showing anything because ES is still indexing the documents.
I'm using PyES to "talk" to ES by the way. Is there any function I can call to know whether Elastic Search is busy indexing?
Thanks a million.
Even if ES is indexing, ES should answer to queries.
Could you check with a
curl localhost:9200/_search?q=*
That your index has docs in it while indexing from couchDb?
[UPDATE]
You have to know that Elasticsearch is a Near Real Time search engine. So, you have to wait some seconds to be able to search for your docs.
You can retrieve your docs immediatly but you need to wait for the refresh process.
You can trigger manually the refresh API. But it could slow down dramatically your insertions.
Does it help?