elasticsearch | Run Elasticsearch in Kubernetes | Continuous Deployment library
kandi X-RAY | elasticsearch Summary
kandi X-RAY | elasticsearch Summary
Run Elasticsearch in Kubernetes.
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Top functions reviewed by kandi - BETA
- pbkdf returns a key derived from hash function .
- ValidateElasticsearch validates Elasticsearch
- GetElasticClient returns a new Elasticsearch client
- EnsureCoordinatingNode ensures the coordinator node is in the cluster
- getSafeContents attempts to unmarshal a pfxPdu to a password .
- Decode extracts the private key from pfxData
- CreateClientCertificateJKS is used to create a certificate for a client certificate
- CreateSG admin certificate
- CreateNodeCertificateJKS creates a certificate for a node certificate
- PEMToJKS is used to convert a PEM encoded file to JKS
elasticsearch Key Features
elasticsearch Examples and Code Snippets
Community Discussions
Trending Discussions on elasticsearch
QUESTION
There are a lot of articles online about running an Elasticsearch multi-node cluster using docker-compose, including the official documentation for Elasticsearch 8.0. However, I cannot find a reason why you would set up multiple nodes on the same docker host. Is this the recommended setup for a production environment? Or is it an example of theory in practice?
...ANSWER
Answered 2022-Mar-04 at 15:49You shouldn't consider this a production environment. The guides are examples, often for lab environments, and testing scenarios with the application. I would not consider them production ready, and compose is often not considered a production grade tool since everything it does is to a single docker node, where in production you typically want multiple nodes spread across multiple availability zones.
QUESTION
I was installing elasticsearch following this guide, but elasticsearch is not really the part of this question.
In the first step, I need to add the key:
...ANSWER
Answered 2021-Nov-03 at 07:31QUESTION
I want to build the efk logger system by docker compose. Everything is setup, only fluentd has problem.
fluentd docker container logs
2022-02-15 02:06:11 +0000 [info]: parsing config file is succeeded path="/fluentd/etc/fluent.conf"
2022-02-15 02:06:11 +0000 [info]: gem 'fluent-plugin-elasticsearch' version '5.0.3'
2022-02-15 02:06:11 +0000 [info]: gem 'fluentd' version '1.12.0'
/usr/local/lib/ruby/2.6.0/rubygems/core_ext/kernel_require.rb:54:in `require': cannot load such file -- elasticsearch/transport/transport/connections/selector (LoadError)
my directory:
ANSWER
Answered 2022-Feb-15 at 11:35I faced the same problem, but I used to make exactly the same image where everything works to this day. I can't figure out what has changed.
But if you need to urgently solve the problem, use my in-person image:
QUESTION
Im using flask_restx for swagger API's. The versions are as follows:
...ANSWER
Answered 2022-Jan-09 at 15:27QUESTION
How to create a company specific parent dependency file which can be used across company specific gradle initiated projects
Sample libraries which I want to share across projects
...ANSWER
Answered 2021-Dec-21 at 16:44It depends on what is the goal of the parent POM? If it's only for the consolidation dependency versions, you can use a version catalog. A version catalog is a list of dependencies, represented as dependency coordinates, that a user can pick from when declaring dependencies in a build script.
settings.gradle
QUESTION
Working with large index (100,000 documents), I have a use case that spawns several threads who are trying to update documents in parallel, the source code uses two methods in updating the documents: Update
and UpdateByQuery
, so some of the threads calls Update
and some of them calls UpdateByQuery
.
For the sake of brevity, each of the threads tries to update the same property for the entire documents.
Here is a small POC that demonstrate the use case:
Indexing 100,000 documents of Product
type, and spawn 100 tasks so each task calls Update
and UpdateByQuery
in parallel. both of them uses MatchAll
query.
ANSWER
Answered 2021-Dec-15 at 12:54TL;DR:
You can pass conflicts=proceed
to the update_by_query
API if you want it to continue working even when hitting conflicts.
More details: The update_by_query page explains:
When you submit an update by query request, Elasticsearch gets a snapshot of the data stream or index when it begins processing the request and updates matching documents using internal versioning. When the versions match, the document is updated and the version number is incremented. If a document changes between the time that the snapshot is taken and the update operation is processed, it results in a version conflict and the operation fails. You can opt to count version conflicts instead of halting and returning by setting conflicts to proceed.
So basically, your update
and update_by_query
are trying to update the same documents, conflicting with each other. Using conflicts=proceed
makes that operation say "oh well, I'll just continue to update the other docs".
QUESTION
I have a mapping in elasticsearch with a field analyzer having tokenizer:
...ANSWER
Answered 2021-Dec-09 at 11:28It's not related to ES version.
Update max_expansions to more than 50.
max_expansions : Maximum number of variations created.
With 3 grams letter & digits as token_chars, ideal max_expansion will be (26 alphabets + 10 digits) * 3
QUESTION
Running elasticsearch in win10 [wsl2] docker-desktop requires to increase mmap counts to 262144 through sysctl -w vm.max_map_count=262144
ANSWER
Answered 2021-Sep-29 at 12:33Short answer:
In your Windows %userprofile%
directory (typically C:\Users\
) create or edit the file .wslconfig
with the following:
QUESTION
I'm using Spring Data Elasticsearch 4.2.5, we have a job that does ETL (extract, transform and load data) to a particular database table. I'm indexing this data using Elasticsearch while the job is running. The data will be in millions of records and more. Currently, I'm doing index on every iteration. I read that, using elasticsearch index on every iteration might take some time. I wanted to use something like bulk-index, but for that I need to add indexQuery object to List. Adding millions of records to list and doing bulk-index may bring memory issues.
I need to apply similar kind of process for deletion. When records are deleted based on some common ID, I need to delete related elastic documents and this will also be in millions and more.
Is there anyway to do indexing/deleting very fast for this requirement? Any help is much appreciated and correct me if my understanding is incorrect.
INDEXING
...ANSWER
Answered 2021-Sep-29 at 09:43For adding the documents you could use bulk indexing for example by collecting the documents to index in a list/array or whatever and when a predefined size is reached - like 500 entries - then do a bulk insert of these.
For deleting there is no bulk operation, but you could collect ids to delete in a list or array again with am maximum size and then use ElasticsearchOperations.idsQuery(List)
to create a query for these ids and pass this into the delete(query)
method.
Edit 29.09.2021:
the idsQuery
was just added in the 4.3 branch, it is simplemented like this (https://github.com/spring-projects/spring-data-elasticsearch/blob/main/src/main/java/org/springframework/data/elasticsearch/core/AbstractElasticsearchRestTransportTemplate.java#L193-L200):
QUESTION
I want to select paths of a deeply nested map to keep.
For example:
...ANSWER
Answered 2021-Sep-03 at 17:18There is no simple way to accomplish your goal. The automatic processing implied for the sequence under [:b :c]
is also problematic.
You can get partway there using the Tupelo Forest library. See the Lightning Talk video from Clojure/Conj 2017.
I did some additional work in data destructuring that you may find useful building the tupelo.core/destruct
macro (see examples here). You could follow a similar outline to build a recursive solution to your specific problem.
A related project is Meander. I have worked on my own version which is like a generalized version of tupelo.core/destruct
. Given data like this
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