I am trying to Use my Elastic search server installed in my local machine to use Postman .i.e., With the help of Postman I want to Post Data and retrieve it with a get operation but unable to do it as I am getting error unknown key [High] for create index
So please help me with the same.
If you want to add a document to your index,
your url should look something like this ( for document ID 1 ) :
PUT http://localhost:9200/test/_doc/1
A good place to start :
https://www.elastic.co/guide/en/elasticsearch/reference/current/getting-started-index.html
For indexing document in the index
PUT http://localhost:9200/my_index/_doc/1
Retrieving indexed document
GET http://localhost:9200/my_index/_doc/1
Introduction:
Elasticsearch is a distributed, RESTful search and analytics engine capable of addressing a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data for lightning fast search, fine‑tuned relevancy, and powerful analytics that scale with ease.
Kibana is a free and open user interface that lets you visualize your Elasticsearch data and navigate the Elastic Stack. Do anything from tracking query load to understanding the way requests flow through your apps.
Logstash is a free and open server-side data processing pipeline that ingests data from a multitude of sources, transforms it, and then sends it to your favorite “stash.” .
Elasticsearch exposes itself through rest API so in this case you don't have to use logstash as we are directly adding data to elastic search
How to add it directly
you can create an index and type using :
{{url}}/index/type
where index is like a table and type is like just a unique data type that we will be storing to the index. Eg {{url}/movielist/movie
https://praveendavidmathew.medium.com/visualization-using-kibana-and-elastic-search-d04b388a3032
Related
Elastic search is a search engine, according to Wikipedia. This implies it is not a database, and does not store the data it is indexing (but presumably does store its indexes)
There are presumably 2 ways to get data into Es. Log shipping or directly via api.
Let’s say my app wants to write an old fashioned log file entry:
Logger.error(now() + “ something bad happened in module “ + module + “;” + message”
This could either write to a file or put the data directly in es using a rest api.
If it was done via rest api, does es store the entire log message, in which case you dont need to waste disk writing the logs to files for compliance etc. Or does it only index the data, so you need to keep a separate copy? If you delete or move the original log file, how does es know, and is what it Deos store still usefull?
If you write to a log file, then use log stash or similar to “put the log data in es” does es store the entire log file as well as any indexes?
How does es parse or index arbitrary log files? Does it treat a log line as a single string, or does it require logs to have a specific format such as cvs or Jason?
Does anyone know of a resource with this key info?
Elasticsearch does store the data you are indexing.
When you ingest data into elasticsearch, this data is stored in one or more index and then it can be searched. To be able to search something with elasticsearch you need to store the data in elasticsearch, it can not for example search on external files.
In your example, if you have an app sending logs do elasticsearch, it will store the entire message you send and after it is in elasticsearch you don't need the original log anymore.
If you need to parse your documents in different fields you can do it before sending the log to elasticsearch as a json document, use logstash to do this or use an ingest pipeline in elasticsearch.
A good starting point to know more about how it works is the official documentation
Disclaimer: I am very new to ELK Stack, so this question can be very basic.
I am setting up ELK stack now. I have below basic questions about ElasticSearch.
What is the storage model elastic search is following?
For example Oracle is using relational model ,Alfresco is using "document model" and Apache Jackrabbit is using "hierarchial model"
2.Log data stored in elastic search is persistent/permanent ? Or ElasticSearch deletes log data after certain period?
3.How we will manage/backup this data?
4.Log/data files in Elastic Search is human-readable?
Any help/route to documentation will be appreciated.
the storage model is a Document model. Everything is a document. The documents are of a particular type and they are stored in an index.
Data send to ES is stored on disk. It can be then read, searched or deleted through a REST API.
The Data is managed through the rest API. Usually for log centralisation, the logs are stored in date-based index (one index for today, one for yesterday and so on), so to delete the logs from one day, you delete the relevant index. Curator can help in this case. ES offers a backup and restore module.
To access the data in ES, you'll have to use the REST API or use the Kibana client.
Documentation:
https://www.elastic.co/guide/en/elasticsearch/guide/current/index.html
https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html
I started looking into ElasticSearch, and most examples of creating and reading involve POSTing data to the ElasticSearch server and then doing a GET to retrieve them.
Is this data that is POSTed stored separately by the ElasticSearch server? So, if I want to use ElasticSearch with MongoDB, does the raw data, not including the search indices, get stored twice (once copy for MongoDB and one for ElasticSearch)?
In conjunction with an answer to this question, a description or a link to a description of how ElasticSearch and the primary data store interact would be very helpful.
Yes, ElasticSearch can only search within its own data store, so a separate copy will be there.
You can use the mongodb connector to keep the data in elastic in sync with the mongo database: https://github.com/mongodb-labs/mongo-connector
I have been working on ways to import Google Analytics raw data without having to use a premium account .So far this is the nearest link to what I want to do
How to extract data from Google Analytics and build a data warehouse (webhouse) from it?
I want to load that data into elastic search and display using kibana .What is the best ETL approach for this ? Has anyone tried to display GA data using ELK stack ?
You should do it in two times
First, get the info, a very very useful site is https://developers.google.com/webmaster-tools/v3/how-tos/search_analytics but you have first to have a google wembaster tool account and create oauth credential on https://console.developers.google.com/apis
Then once you have your data, find a way to import them in elasticsearch, I'm still looking for the best way to do so, maybe transform the result table into csv and then using https://www.elastic.co/guide/en/logstash/current/plugins-filters-csv.html
Have a look at this:
https://www.elastic.co/guide/en/logstash/current/plugins-inputs-http_poller.html
You can use this to poll an endpoint, in this case GA, and load the response data into Elasticsearch. You may want to filter the response with the Split and / or Mutate plugins as well.
I have done this same setup.
Extracted data from Google Analytics with 7 Dimensions and 6 Metrics, out of which 2 Dimensions were primary key (Timestamp and ID). This was done using R.
Did some transformations on the data using linux awk and sed commands.
Loaded the data into Apache Hive with the row column formatting, created like total 9 tables.
Joined all the 9 tables in Hive using Hive Join queries, with 2 primary keys.
Used elasticsearch-hadoop connector to load the final resulting table to elasticsearch. Had to do a little data transformations to match Hive and Elasticsearch data types.
Used Kibana to visualize the data in Elasticsearch.
Now I am planning to avoid all the manual steps and somehow automate all the steps above.
I am a newbie to Elasticsearch. We are currently using Splunk platform for our analytics application and looking to migrate to ELK. Splunk provides options to schedule searches to run in background periodically and to store the search results in a separate summary index. Is similar functionality available in Elasticsearch? If so, please point me to the documentation containing the process.
Thanks,
Keerthana
This is a great use case. Of course Elasticsearch can perform such tasks, but it is more manual. You have to write your own script. So for example, if you want to summarize data, you can use ElasticSearch aggregations, and take the result (which comes in JSON format) and store it back into an index where you keep summary data. This way, even if you delete your raw data, your summary data lives on.
Elasticsearch comes with different clients. I like to use the Python Elasticsearch DSL library.