I'm not sure why my data points aren't visualized in the tile-map. I'm dynamically adding the data points through the elasticsearch python client (https://elasticsearch-py.readthedocs.org/en/master/). The visualization keeps returning
Furthermore, here is initial mapping of the geo_point.
{
"mappings": {
"geo": {
"properties": {
"location": {
"type": "geo_point",
"geohash": true,
"geohash_prefix": true
}
}
}
}
}
EDIT:
If your mapping is not set up correctly, Kibana doesn't let you select the geohash aggregation in the config panel on the left. This rather seems to be a problem with the indexed data.
What does the timestamp in your mapping look like? Do you have such recent data that your time selection should return some results for the last 15 minutes? Please check the selection at the top right corner...
Related
I have to store documents with a single field contains a single Json object. this object has a variable depth and variable schema.
I config a mapping like this:
"mappings": {
"properties": {
"#timestamp": {
"type": "date"
},
"message": {
"type": "object"
}
}
}
It works fine and Elasticsearch creates and updates mapping with documents that received.
The problem is that after some updates in mapping, it rejects new documents and do not update mapping anymore. At this time I change the indices and mapping update occurred for that indies. I'm looking forward to know the right solution.
for example the first document is:
{
personalInfo:{
fistName: "tom"
}
moviesStatistics: {
count: 100
}
}
the second document that will update Elasticsearch mapping is:
{
personalInfo:{
fistName: "tom",
lastName: "hanks"
},
moviesStatistics: {
count: 100
},
education: {
title: "a title..."
}
}
Elasticsearch creates mapping with doc1 and updates it with doc2, doc3, ... until a number of documents received. After that it starts to reject every document that is not matched to the last mapping fields.
After all I found the solution in the home page of Elasticsearch https://www.elastic.co/guide/en/elasticsearch/reference/7.13//dynamic-field-mapping.html
We can use Dynamic mapping and simply use this mapping:
"mappings": {
"dynamic": "true"
}
You should also change some default restrictions that mentioned here:
https://www.elastic.co/guide/en/elasticsearch/reference/7.13//mapping-settings-limit.html
On our project we're using NEST to insert data into ElasticSearch (1.7). We'd like to be able to force ES to truncate all dates towards the mapped format.
Mapping example:
"dateFrom" : {
"type": "date",
"format": "dateHourMinute" // Or yyyy-MM-dd'T'HH:mm
}
Data example:
{
"dateFrom" : 2015-12-21T15:55:00.000Z
}
Inserting this data throws an IllegalArgumentException:
Invalid format: "2015-12-21T15:55:00.000Z" is malformed at ":00.000Z"
Obviously we don't need the last part of the date. Can't we configure ES to just truncate it instead of erroring out?
Keep in mind we're using 1.7 right now, since date formatting seems to have changed in recent versions...
In order to get the data to index correctly I could change the data type to date_optional_time (supported in 1.7)
PUT my_index
{
"mappings": {
"my_type": {
"properties": {
"date": {
"type": "date",
"format": "date_optional_time"
}
}
}
}
}
This will allow you to contribute date with time being optional.
such as:
PUT /my_index/my_type/1
{
"date": "2015-12-21"
}
or as you have it
PUT /my_index/my_type/2
{
"date": "2015-12-21T15:55:00.000Z"
}
Both are now valid submissions. I don't know of any transformation approaches within ES to support a truncation or transformation of field data at time of index. I would think if you want to parse the data and remove the time pre-submission you will need to do that outside of ES when you create the JSON object.
It appears ES is currently not capable of editing dates through a custom mapping. We ended up using JsonConverters (like this) to drop seconds and millis before inserting them into ES.
I am new to elastic search, I want to updated the existing mapping under my index. My existing mapping looks like
"load":{
"mappings": {
"load": {
"properties":{
"customerReferenceNumbers": {
"type": "string",
"index": "no"
}
}
}
}
}
I would like to update this field from my mapping to be analyzed, so that my 'customerReferenceNumber' field will be available for search.
I am trying to run the following query in Sense plugin to do so,
PUT /load/load/_mapping { "load": {
"properties": {
"customerReferenceNumbers": {
"type": "string",
"index": "analyzed"
}
}
}}
but I am getting following error with this command,
MergeMappingException[Merge failed with failures {[mapper customerReferenceNumbers] has different index values]
Though there exist data associated with these mappings, here I am unable to understand why elastic search not allowing me to update mapping from no-index to indexed?
Thanks in advance!!
ElasticSearch doesn't allow this kind of change.
And even if it was possible, as you will have to reindex your data for your new mapping to be used, it is faster for you to create a new index with the new mapping, and reindex your data into it.
If you can't afford any downtime, take a look at the alias feature which is designed for these use cases.
This is by design. You cannot change the mapping of an existing field in this way. Read more about this at https://www.elastic.co/blog/changing-mapping-with-zero-downtime and https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-put-mapping.html.
I would like to add some custom geo search functions to my program(not geoip, translating ip address into coordinate). How do i filter custom lat and lng data into elasticsearch geo_type format data so that i can visualize in kibana tile map?
so as you may have found out, there is a (somewhat clunky) solution.
basically you need to set the mapping of the geo_point field before you could log data that way (I also used ES python module directly instead logging via logstash.. just to be sure).
so how do you set the correct mapping?
make sure you use a fresh instance of elasticsearch (or at least that the mapping for both the index and the type you will use is not set yet)
run from sense (or use the appropriate curl command)
PUT <index_name>
{
"mappings": {
"<type_name>": {
"properties": {
"timestamp": {
"type": "date"
},
"message": {
"type": "string"
},
"location": {
"type": "geo_point"
}
<etc.>
}
}
}
}
now you're golden, just make sure that your geo_points are in a format that ES excepts
more on mapping geo_points here:
ElasticSearch how to setup geo_point
and here:
https://discuss.elastic.co/t/geo-point-logging-from-python-to-elasticsearch/37336
I have created an Elasticsearch index from a data set containing geodata. I have set up mapping for the data. Then I tried to create Kibana visualisation using this data set. Kibana detects the geodata property but finds no result even though there plenty of. Then I ran a test on another data set with different and much simpler layout, and Kibana properly visualised geodata.
Here's the sample that works:
"location": {
"lat": 56.290525,
"lon": -30.163298
},
and this is its mapping:
"location": {
"type": "geo_point",
"lat_lon": true,
"geohash": true
}
And this one doesn't work:
"groupOfLocations": {
"#type": "Point",
"locationForDisplay": {
"lat": 59.21232,
"lon": 9.603803
}
}
And this is its mapping:
{
... // nested type
"locationForDisplay": {
"type": "geo_point",
"lat_lon": true,
"geohash": true
}
...
}
There are only two things that are different between working and non-working versions:
The one that works has a JSON element called "location" while the
other one is called "locationForDisplay"
The one that works has a JSON element ("location") as a top level
element, while in the other one it's an element in the nested type.
Apart from these two differences (which I believe shouldn't mean anything) I can't find anything else. What can make Kibana fail?
Kibana can not work with nested Json,
You need to change it to the standard Json.