OpenSearch | 🔎 Open source distributed and RESTful search engine | Search Engine library
kandi X-RAY | OpenSearch Summary
kandi X-RAY | OpenSearch Summary
Open source distributed and RESTful search engine.
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Top functions reviewed by kandi - BETA
- Restores the specified snapshot from the repository .
- Gets the legal cast .
- Visits a dot .
- Loads the list of allowlistlisted classes from the given resource .
- Matches an R statement .
- Process a new cluster info .
- Builds the index table .
- Adds a painless method to the class .
- Snapshot a shard .
- Perform recovery operation .
OpenSearch Key Features
OpenSearch Examples and Code Snippets
DO
$$
<>
DECLARE
test_variable text DEFAULT 'test';
BEGIN
RAISE NOTICE '%',test_variable;
DECLARE
test_variable text := 'inner test';
BEGIN
RAISE NOTICE '%',test_variable;
RAISE NOTICE '%', oute
//Test class
public class Test {
public static void main(String[] args) {
Node root = new Node(1, "test1", new Node[]{
new Node(2, "test2", new Node[]{
new Node(5, "test6", new Node[]{})
do {
System.out.println("Please enter your salary? (> 0)");
try {
salary = in.nextInt();
// test if user enters something other than an integer
} catch (java.util.InputMismatchException e) {
public class Test
{
public static void main(String[] args)
{
System.out.println(countFileRecords());
}
package com;
import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.util.Scann
import os
from google.cloud import bigquery
project_number = os.environ["CLOUD_ML_PROJECT_ID"]
client = bigquery.Client(project=project_number)
embedding_df = pd.DataFrame(embeddings)
test = pd.concat([test, embedding_df], axis=1)
import 'package:sqflite/sqflite.dart';
// Get a location using getDatabasesPath
var databasesPath = await getDatabasesPath();
String path = join(databasesPath, 'demo.db');
// Delete the database
await deleteDataba
Public Sub DoChangeModules()
Dim dstApp As Application
Dim dstDB As Database
Dim AO As Document
Set dstApp = Application
Set dstDB = dstApp.CurrentDb
' iterate forms's modules and insert code
Dim f As Form
SELECT distinct on (user_id) user_id, status
FROM test
where status != 'INACTIVE'
ORDER BY user_id, array_position('{ACTIVE,UPDATING}', status)
SQL> with test (col) as
2 (select 88889889 from dual union all -- valid
3 select 12345432 from dual union all -- invalid
4 select 443223 from dual union all -- valid
5 select 1221 from dual --
Community Discussions
Trending Discussions on OpenSearch
QUESTION
I have set up an AWS Opensearch instance with pretty much everything set to default values. i then have inserted some data regarding hotels. When the user searches like Good Morning B
my resulting query POST
request looks like this:
ANSWER
Answered 2022-Apr-01 at 08:57The number of documents is counted not for the whole index by Elasticsearch but by the underlying Lucene engine, and it's done per shard (each shard is a complete Lucene index). Since your documents are (probably) in different shards, their score turns out slightly different.
QUESTION
I have added a new context component MovieContext.js
, but it is causing an uncaught type error. I had a look online and it is apparently caused when trying to render multiple children. This I do not understand because as far as I can workout I am only trying to render one.
Error
...ANSWER
Answered 2022-Mar-31 at 09:25You have a named export for MovieProvider
and in the same file a default export for MovieContext;
QUESTION
I am a junior dev ops engineer and have this very basic question.
My team is currently working on providing an AWS OpenSearch cluster. Due to the type of our problem, we require the storage-optimized instances. From the amazon documentation I found that they recommend a minimum number of 3 nodes. The required storage size is known to me, in the OpenSearch Service pricing calculator I found that I can either choose 10 i3.large instances or 5 i3.xlarge ones. I checked the prices, they are the same.
So my question is, when I am faced with such a problem, do I choose the lesser bigger instances or the bigger number of smaller instances? I am particularly interested in the reason.
Thank you!
...ANSWER
Answered 2022-Mar-30 at 09:20Each VM has some overhead for the OS so 10 smaller instances would have less compute and RAM available for ES in total than 5 larger instances. Also, if you just leave the default index settings (5 primary shards, 1 replica) and actively write to only 1 index at a time, you'll effectively have only 5 nodes indexing data for you (and these nodes will have less bandwidth because they are smaller).
So, I would usually recommend running a few larger instances instead of many smaller ones. There are some special cases where it won't be true (like a concurrent-search-heavy cluster) but for those, I'd recommend going with even larger instances in the first place.
QUESTION
I'm new to OpenSearch, and I'm following the indexing pattern mentioned here for a POC.
I'm trying to test the mapping mentioned here : https://github.com/spryker/search/blob/master/src/Spryker/Shared/Search/IndexMap/search.json in OpenSearch dev console.
...ANSWER
Answered 2022-Mar-30 at 03:46You need to replace page
by _doc
(or remove it altogether) as there's no more mapping types
QUESTION
Since AWS has replaced ElasticSearch with OpenSearch, some clients have issues connecting to the OpenSearch Service.
To avoid that, we can enable compatibility mode during the cluster creation.
Certain Elasticsearch OSS clients, such as Logstash, check the cluster version before connecting. Compatibility mode sets OpenSearch to report its version as 7.10 so that these clients continue to work with the service.
I'm trying to use CloudFormation to create a cluster using AWS::OpenSearchService::Domain instead of AWS::Elasticsearch::Domain but I can't see a way to enable compatibility mode.
...ANSWER
Answered 2021-Nov-10 at 11:23The AWS::OpenSearchService::Domain
CloudFormation resource has a property called AdvancedOptions
.
As per documentation, you should pass override_main_response_version
to the advanced options to enable compatibility mode.
Example:
QUESTION
I'm not seeing how an AWS Kinesis Firehose lambda can send update and delete requests to ElasticSearch (AWS OpenSearch service).
Elasticsearch document APIs provides for CRUD operations: https://www.elastic.co/guide/en/elasticsearch/reference/current/docs.html
The examples I've found deals with the Create case, but doesn't show how to do delete
or update
requests.
https://aws.amazon.com/blogs/big-data/ingest-streaming-data-into-amazon-elasticsearch-service-within-the-privacy-of-your-vpc-with-amazon-kinesis-data-firehose/
https://github.com/amazon-archives/serverless-app-examples/blob/master/python/kinesis-firehose-process-record-python/lambda_function.py
The output format in the examples do not show a way to specify create
, update
or delete
requests:
ANSWER
Answered 2022-Mar-03 at 04:20Firehose uses lambda function to transform records before they are being delivered to the destination in your case OpenSearch(ES) so they are only used to modify the structure of the data but can't be used to influence CRUD actions. Firehose can only insert records into a specific index. If you need a simple option to remove records from ES index after a certain period of time have a look at "Index rotation" option when specifying destination for your Firehose stream.
If you want to use CRUD actions with ES and keep using Firehose I would suggest to send records to S3 bucket in the raw format and then trigger a lambda function on object upload event that will perform a CRUD action depending on fields in your payload.
A good example of performing CRUD actions against ES from lambda https://github.com/chankh/ddb-elasticsearch/blob/master/src/lambda_function.py
This particular example is built to send data from DynamoDB streams into ES but it should be a good starting point for you
QUESTION
When adding sorting configuration for data in OpenSearch, I came across a situation where the data's field that I want to sort on had only null values. OpenSearch return an error that says [query_shard_exception] Reason: No mapping found for [MY_NULL_FIELD] in order to sort on
. That being said, if I add ONE value, then the sort functions as expected. Is there a way around this?
ANSWER
Answered 2022-Mar-03 at 04:41You can define null_value
properties while configuring index mapping.
QUESTION
I am using AWS Opensearch to retrieve the logs from all my Kubernetes applications.
I have the following pods: Kube-proxy
, Fluent-bit
, aws-node
, aws-load-balancer-controller
, and all my apps (around 10).
While fluent-bit successfully send all the logs from Kube-proxy
, Fluent-bit
, aws-node
and aws-load-balancer-controller
, none of the logs from my applications are sent. My applications had DEBUG
, INFO
, ERROR
logs, and none are sent by fluent bit.
Here is my fluent bit configuration:
...ANSWER
Answered 2022-Feb-25 at 15:15have you seen this article from official side? Pay attention on Log files overview section.
When deploying Fluent Bit to Kubernetes, there are three log files that you need to pay attention to. C:\k\kubelet.err.log
Also you can find Fluent GitHub Community and create an issue there to have better support from its contributors
There is a Slack channel for Fluent
QUESTION
I have a CSV data of 65K. I need to do some processing for each csv line which generates a string at the end. I have to write/append that string in a file.
Psuedo Code:
...ANSWER
Answered 2022-Feb-23 at 19:25Q : " Writing to a file parallely while processing in a loop in python ... "
A :
Frankly speaking, the file-I/O is not your performance-related enemy.
"With all due respect to the colleagues, Python (since ever) used GIL-lock to avoid any level of concurrent execution ( actually re-SERIAL-ising the code-execution flow into dancing among any amount of threads, lending about 100 [ms] of code-interpretation time to one-AFTER-another-AFTER-another, thus only increasing the interpreter's overhead times ( and devastating all pre-fetches into CPU-core caches on each turn ... paying the full mem-I/O costs on each next re-fetch(es) ). So threading is ANTI-pattern in python (except, I may accept, for network-(long)-transport latency masking ) – user3666197 44 mins ago "
Given about the 65k files, listed in CSV, ought get processed ASAP, the performance-tuned orchestration is the goal, file-I/O being just a negligible ( and by-design well latency-maskable ) part thereof ( which does not mean, we can't screw it even more ( if trying to organise it in another performance-devastating ANTI-pattern ), can we? )
Tip #1 : avoid & resist to use any low-hanging fruit SLOCs if The Performance is the goal
If the code starts with a cheapest-ever iterator-clause,
be it a mock-up for aRow in aCsvDataSET: ...
or the real-code for i in range( len( queries ) ): ...
- these (besides being known for ages to be awfully slow part of the python code-interpretation capabilites, the second one being even an iterator-on-range()-iterator in Py3 and even a silent RAM-killer in Py2 ecosystem for any larger sized ranges) look nice in "structured-programming" evangelisation, as they form a syntax-compliant separation of a deeper-level part of the code, yet it does so at an awfully high costs impacts due to repetitively paid overhead-costs accumulation. A finally injected need to "coordinate" unordered concurrent file-I/O operations, not necessary in principle at all, if done smart, are one such example of adverse performance impacts if such a trivial SLOC's ( and similarly poor design decisions' ) are being used.
Better way?
- a ) avoid the top-level (slow & overhead-expensive) looping
- b ) "split" the 65k-parameter space into not much more blocks than how many memory-I/O-channels are present on your physical device ( the scoring process, I can guess from the posted text, is memory-I/O intensive, as some model has to go through all the texts for scoring to happen )
- c ) spawn
n_jobs
-many process workers, that willjoblib.Parallel( n_jobs = ... )( delayed( <_scoring_fun_> )( block_start, block_end, ...<_params_>... ) )
and run thescoring_fun(...)
for such distributed block-part of the 65k-long parameter space. - d ) having computed the scores and related outputs, each worker-process can and shall file-I/O its own results in its private, exclusively owned, conflicts-prevented output file
- e ) having finished all partial block-parts' processing, the
main
-Python process can just join the already ( just-[CONCURRENTLY] created, smoothly & non-blocking-ly O/S-buffered / interleaved-flow, real-hardware-deposited ) stored outputs, if such a need is ...,
and
finito - we are done ( knowing there is no faster way to compute the same block-of-tasks, that are principally embarrasingly independent, besides the need to orchestrate them collision-free with minimised-add-on-costs).
If interested in tweaking a real-system End-to-End processing-performance,
start with lstopo
-map
next verify the number of physical memory-I/O-channels
and
may a bit experiment with Python joblib.Parallel()
-process instantiation, under-subscribing or over-subscribing the n_jobs
a bit lower or a bit above the number of physical memory-I/O-channels. If the actual processing has some, hidden to us, maskable latencies, there might be chances to spawn more n_jobs
-workers, until the End-to-End processing performance keeps steadily growing, until a system-noise hides any such further performance-tweaking effects
A Bonus part - why un-managed sources of latency kill The Performance
QUESTION
I have been trying to scrap data from https://gov.gitcoin.co/u/owocki/summary using python's BeautifulSoup. image: https://i.stack.imgur.com/0EgUk.png
Inspecting the page with Dev tools gives an idea but with the following code, I'm not getting the full HTML code returned or as it seems the site isn't allowing scraping if I'm correct.
...ANSWER
Answered 2022-Feb-20 at 08:45As mentioned in the comments content of website is provided dynamically, so you won't get your information with requests
on that specific ressource / url, cause it is not able to render the website like a browser would do.
It do not need beautifulsoup
for that task, cause there are ressources that will give you structured json data:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install OpenSearch
You can use OpenSearch like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the OpenSearch component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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