So im working on a system that logs bad data sent to an api and what the full request was. Would love to be able to see this in Kibana.
Issue is the datatypes could be random, so when I send them to the bad_data field it fails if it dosen't match the original mapping.
Anyone have a suggestion for the right way to handle this?
(2.X Es is required due to a sub dependancy)
You could use ignore_malformed flag in your field mappings. In that case wrong format values will not be indexed and your document will be saved.
See elastic documentation for more information.
If you want to be able to query such fields as original text you could use fields in your mapping for multi-type indexing, to get fast queries on raw text values.
Related
The documentation and recommendation for using stored_fields feature in ElasticSearch has been changing. In the latest version (7.9), stored_fields is not recommended - https://www.elastic.co/guide/en/elasticsearch/reference/7.9/search-fields.html
Is there a reason for this?
Where as in version 7.4.0, there is no such negative comment - https://www.elastic.co/guide/en/elasticsearch/reference/7.4/mapping-store.html
What is the guidance in using this feature? Is using _source filtering a better option? I ask because in some other doc, _source filtering is supposed to kill performance - https://www.elastic.co/blog/found-optimizing-elasticsearch-searches
If you use _source or _fields you will quickly kill performance. They access the stored fields data structure, which is intended to be used when accessing the resulting hits, not when processing millions of documents.
What is the best way to filter fields and not kill performance with Elastic Search?
source filtering is the recommended way to fetch the fields and you are getting confused due to the blog, but you seem to miss the very important concept and use-case where it is applicable. Please read the below statement carefully.
_source is intended to be used when accessing the resulting hits, not when processing millions of documents.
By default, elasticsearch returns only 10 hits/search results which can be changed based on the size parameter and if in your search results, you want to fetch few fields value than using source_filter makes perfect sense as it's done on the final result set(not all the documents matching search results),
While if you use the script, and using source value try to read field-value and filter the search result, this will cause queries to scan all the index which is the second part of the above-mentioned statement(not when processing millions of documents.)
Apart from the above, as all the field values are already stored as part of _source field which is enabled by default, you need not allocate extra space if you explicitly mark few fields as stored(disabled by default to save the index size) to retrieve field-values.
I've been given a set up where I have a program creating live data and posting them into Elasticsearch.
I am trying to visualise this data in Kibana, but I'm coming across many problems such as numbers for a field being of type string instead of integers or there being certain missing fields.
But mainly for now certain fields being integer instead of string would be useful. How do I go about this? Is it possible?
I have no access to source code of the system creating the live events data.
Thanks in advance.
Update: I should also mention additionally that for now I am restricted to Elasticsearch version 2.4
If your data is coming straight into Elasticsearch, your options are limited.
The best option is to have the program that is creating the data send valid, properly formatted data.
If that's not an option, you can set your Elasticsearch mapping to force the field to be numeric. This will have the side-effect of dropping all documents where this field is not numeric.
There is also the elasticsearch injest node, which allows for some (logstash-like) transformations of the data. Converting the type is one such allowed "processor".
Basic usecase that we are trying to solve is for users to be able to search from the contents of the log file .
Lets say a simple situation where user searches for a keyword and this is present in a log file which i want to render it back to the user.
We plan to use ElasticSearch for handling this. The idea that i have in mind is to use elastic search as a mechanism to store the indexed log files.
Having this concept in mind, i went through https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html
Couple of questions i have,
1) I understand the input provided to elastic search is a JSON doc. It is going to scan this JSON provided and create/update indexes. So i need a mechanism to convert my input log files to JSON??
2) Elastic search would scan this input document and create/update inverted indexes. These inverted indexes actually point to the exact document. So does that mean, ES would store these documents somewhere?? Would it store them as JSON docs? Is it purely in memory or on file sytem/database?
3) No when user searches for a keyword , ES returns back the document which contains the searched keyword. Now do i need to have the ability to convert back this JSON doc to the original log document that user expects??
Clearly im missing something.. Sorry for asking questions this silly , but im trying to improve my skills and its WIP.
Also , i understand that there is ELK stack out there. For some reasons we just want to use ES and not the LogStash and Kibana part of the stack..
Thanks
Logs needs to be parsed to JSON before they can be inserted into Elasticsearch
All documents are stored on the filesystem and some data is kept in memory but all data is persistent.
When you search Elasticsearch you get back matching JSON documents. If you want to display the original error message, you can store that original message in one of the JSON fields and display just that.
So if you just want to store log messages and not break them into fields or anything, you can simply take each row and send it to Elasticsearch like so:
{ "message": "This is my log message" }
To parse logs, break them into fields and add some logic, you will need to use some sort of app, like Logstash for example.
I am about to index tweets coming from Apache NiFi to Elasticsearch as POST and want to do the following:
Make create_at field as date. Should I use mapping or index template for this?
make some fields not analyzed. Like hashtags, URLs, etc.
Want to store not entire tweet but some important fields. Like text, not all user information but some field, hashtags, URLs from entities (in post URLs). Don't need quoted source. Etc.
What should I use in this case? template? Pre-process tweets with some ETL process in order to extract data I need and index in ES?
I am a bit confused. Will really appreciate advise.
Thanks in advance.
I guess in your NiFi you have something like GetTwitter and PostHTTP configured. NiFi is already some sort of ETL, so you probably don't need another one. However, since you don't want to index the whole JSOn coming out of Twitter, you clearly need another NiFi process inbetween to select what you want and transform the raw JSON into another more lightweight one. Here is an example on how to do it for Solr, but I'm not sure the same processor exists for Elasticsearch.
This article about streaming Twitter data to Elasticsearch using Logstash shows a possible index template that you could use in order to mold your own (i.e. add the create_at data field if you like).
The way to go for you since you don't want to index everything, is clearly to come up with your own mapping, which you can then use in an index template. Using index templates, you will be able to create daily/weekly/monthly twitter indices as you see fit.
I'm having some issues getting elasticsearch to interpret an epoch millis timestamp field. I have some old bro logs I want to ingest and have them be in the proper orders and spacing. Thanks to Logstash filter to convert "$epoch.$microsec" to "$epoch_millis"
I've been able to convert the field holding the bro timestamp to the proper length of digits. I've also inserted a mapping into elasticsearch for that field, and it says that the type is "Date" with the format being the default. However, when I go and look at the entries it still has a little "t" next to it instead of a little clock. And hence I can't use it for my filter view reference in kibana.
Anyone have any thoughts or have dealt with this before? Unfortunately it's a stand alone system so I would have to manually enter any of the configs I'm using.
I did try and convert my field "ts" back to an integer after using the method described in the link above. So It should be a logstash integer before hitting the elasticsearch mapping.
So I ended up just deleting all my mappings in Kibana, and elasticsearch. I then resubmitted and this time it worked. Must have been some old junk in there that was messing me up. But now it's working great!