I am trying to populate dashboard in kibana with Elasticsearch data on date fields .
I have log file with dates and i find that i don't have #timestamp in it.
Here is mapping :
PUT test2
{
"settings": {
"index.mapping.ignore_malformed": true
},
"mappings": {
"my_type": {
"properties": {
"Size": {"type": "integer","ignore_malformed": true },
"Copy Size": {"type": "integer","ignore_malformed": true }
"Email Sent Time": {"type": "date"},
"Creation Time": {"type": "date"},
"Modification Time": {"type": "date"}
}
}
}
}
How to add default timestamp? To create area chart in kibana.
Once upon a time, Elasticsearch used to support adding default timestamps automatically to all documents you put in an index. The mapping was something like this when creating your index:
"mappings" : {
"_default_":{
"_timestamp" : {
"enabled" : true,
"store" : true
}
}
}
However, as you can see at this link, it was deprecated by version 5.x. Today, it is recommended to populate a regular date field with the current timestamp on application side.
Related
It is possible to include a "date and time" field in a document that receives elasticsearch without it being previously defined.
The date and time corresponds to the one received by the json to elasticsearch
This is the mapping:
{
"mappings": {
"properties": {
"entries":{"type": "nested"
}
}
}
}
Is it possible that it can be defined in the mapping field so that elasticsearch includes the current date automatically?
What you can do is to define an ingest pipeline to automatically add a date field when your document are indexed.
First, create a pipeline, like this (_ingest.timestamp is a built-in field that you can access):
PUT _ingest/pipeline/add-current-time
{
"description" : "automatically add the current time to the documents",
"processors" : [
{
"set" : {
"field": "#timestamp",
"value": "_ingest.timestamp"
}
}
]
}
Then when you index a new document, you need to reference the pipeline, like this:
PUT test-index/_doc/1?pipeline=add-current-time
{
"my_field": "test"
}
After indexing, the document would look like this:
GET test-index/_doc/1
=>
{
"#timestamp": "2020-08-12T15:48:00.000Z",
"my_field": "test"
}
UPDATE:
Since you're using index templates, it's even easier because you can define a default pipeline to be run for each indexed documents.
In your index templates, you need to add this to the index settings:
{
"order": 1,
"index_patterns": [
"attom"
],
"aliases": {},
"settings": {
"index": {
"number_of_shards": "5",
"number_of_replicas": "1",
"default_pipeline": "add-current-time" <--- add this
}
},
...
Then you can keep indexing documents without referencing the pipeline, it will be automatic.
"value": "{{{_ingest.timestamp}}}"
Source
I have two Elastic Search version one is 7.3 and the second is 7.1. I am using flattened data type for Elastic Search 7.3 and I also want to use this data type in Elastic Search 7.1. So that I can store my data as I stored in Elastic Search 7.3.
I researched about flattened data type and get to know that it's supported to 7.x but when I tried in 7.1 it gives me the mapper_parsing_exception error.
What I tried is as shown below.
In Elastic Search 7.3
Index Creation
PUT demo-flattened
Response:
{
"acknowledged": true,
"shards_acknowledged": true,
"index": "demo-flattened"
}
Insert Mapping
PUT demo-flattened/_mapping
{
"properties": {
"host": {
"type": "flattened"
}
}
}
Response:
{
"acknowledged": true
}
In Elastic Search 7.1
PUT demo-flattened
Response:
{
"acknowledged": true,
"shards_acknowledged": true,
"index": "demo-flattened"
}
Insert Mapping
PUT demo-flattened/_mapping
{
"properties": {
"host": {
"type": "flattened"
}
}
}
Response:
{
"error": {
"root_cause": [
{
"type": "mapper_parsing_exception",
"reason": "No handler for type [flattened] declared on field [host]"
}
],
"type": "mapper_parsing_exception",
"reason": "No handler for type [flattened] declared on field [host]"
},
"status": 400
}
I want to use the flattened data type in Elastic Search 7.1. Is there any alternative to use flattened data type in the 7.1 version because flattened data type is supported from Elastic Search 7.3.
Any help or suggestions will be appreciated.
First the flattened is available in 7.1 with X-pack (X-pack is paid feature),
so what I think you can use object type with enabled flag as false
This will help you store that field as it is without any indexing.
{
"properties": {
"host": {
"type": "object",
"enabled": false
}
}
}
Check the version of your ElasticSearch. If its the OSS version, then it won't work for you.
You can check it by running GET \ in the Kibana. You would get something like:
{
"version" : {
"number" : "7.10.2",
"build_flavor" : "oss",
}
}
But for ElasticSearch that does support flattened type, you would get something like:
"version" : {
"number" : "7.10.2",
"build_flavor" : "default",
}
}
You can find more details on the official Kibana Github page No handler for type [flattened] declared on field [state] #52324.
Interally, it works like this
Similarities in the way values are indexed, flattened fields share much of the same mapping and search functionality as keyword fields
Here, You have only one field called host. You can replace this with keyword.
What similarities:
Mapping:
"labels": {
"type": "flattened"
}
Data:
"labels": {
"priority": "urgent",
"release": ["v1.2.5", "v1.3.0"],
"timestamp": {
"created": 1541458026,
"closed": 1541457010
}
}
During indexing, tokens are created for each leaf value in the JSON object. The values are indexed as string keywords, without analysis or special handling for numbers or dates
To query them, you can use "term": {"labels": "urgent"} or "term": {"labels.release": "v1.3.0"}.
When it is keyword, you can have them as separate fields.
{
"host":{
"type":"keyword"
}
}
Reference
I am new to elastic search and I am struggling with date range query. I have to query the records which fall between some particular dates.The JSON records pushed into elastic search database are as follows:
"messageid": "Some message id",
"subject": "subject",
"emaildate": "2020-01-01 21:09:24",
"starttime": "2020-01-02 12:30:00",
"endtime": "2020-01-02 13:00:00",
"meetinglocation": "some location",
"duration": "00:30:00",
"employeename": "Name",
"emailid": "abc#xyz.com",
"employeecode": "141479",
"username": "username",
"organizer": "Some name",
"organizer_email": "cde#xyz.com",
I have to query the records which has start time between "2020-01-02 12:30:00" to "2020-01-10 12:30:00". I have written a query like this :
{
"query":
{
"bool":
{
"filter": [
{
"range" : {
"starttime": {
"gte": "2020-01-02 12:30:00",
"lte": "2020-01-10 12:30:00"
}
}
}
]
}
}
}
This query is not giving results as expected. I assume that the person who has pushed the data into elastic search database at my office has not set the mapping and Elastic Search is dynamically deciding the data type of "starttime" as "text". Hence I am getting inconsistent results.
I can set the mapping like this :
PUT /meetings
{
"mappings": {
"dynamic": false,
"properties": {
.
.
.
.
"starttime": {
"type": "date",
"format":"yyyy-MM-dd HH:mm:ss"
}
.
.
.
}
}
}
And the query will work but I am not allowed to do so (office policies). What alternatives do I have so that I can achieve my task.
Update :
I assumed the data type to be "Text" but by default Elastic Search applies both "Text" and "Keyword" so that we can implement both Full Text and Keyword based searches. If it is also set as "Keyword" . Will this benefit me in any case. I do not have access to lots of stuff in the office that's why I am unable to debug the query.I only have the search API for which I have to build the query.
GET /meetings/_mapping output :
'
'
'
"starttime" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
}
}
}
'
'
'
Date range queries will not work on text field, for that, you have to use the date field
Since you are working on date fields , best practice is to use the date field.
I would suggest you to reindex your index to another index so that you can change the type of your text field to date field
Step1-: Create index2 using index1 mapping and make sure to change the type of your date field which is text to date type
Step 2-: Run the elasticsearch reindex and reindex all your data from index1 to index2. Since you have changed your field type to date field type. Elasticsearch will now recognize this field as date
POST _reindex
{
"source":{ "index": "index1" },
"dest": { "index": "index2" }
}
Now you can run your Normal date queries on index2
As #jzzfs suggested the idea is to add a date sub-field to the starttime field. You first need to modify the mapping like this:
PUT meetings/_mapping
{
"properties": {
"starttime" : {
"type" : "text",
"fields" : {
"keyword" : {
"type" : "keyword",
"ignore_above" : 256
},
"date": {
"type" : "date",
"format" : "yyyy-MM-dd HH:mm:ss",
}
}
}
}
}
When done, you need to reindex your data using the update by query API so that the starttime.date field gets populated and index:
POST meetings/_update_by_query
When the update is done, you'll be able to leverage the starttime.date sub-field in your query:
{
"query": {
"bool": {
"filter": [
{
"range": {
"starttime.date": {
"gte": "2020-01-02 12:30:00",
"lte": "2020-01-10 12:30:00"
}
}
}
]
}
}
}
There are ways of parsing text fields as dates at search time but the overhead is impractical... You could, however, keep the starttime as text by default but make it a multi-field and query it using starttime.as_date, for example.
I'm trying to create an index with mappings.
I need it to contain default timestamp in each of his documents.
I searched everywhere on the Internet and did exactly what they asked me. but the code does not work.
curl -X PUT "localhost:9200/demo-index-new12345" -H 'Content-Type:
application/json' -d'
{
"mappings": {
"doco" : {
"properties" : {
"test_date": {
"type": "date",
"format": "yyyy-MM-dd"
},
"test_status": {
"type": "string"
}
},
"default":{
"_timestamp" : {
"enabled" : true,
"store" : true
}
}
}
}
}
'
What version of Elasticsearch are you running? Default timestamps were deprecated in 2.x and removed. If you need a timestamp field to be on every document, you need to add a field on the mapping, call it "timestamp", or "created" or something. Then you can do one of two things:
Send "timestamp" field with the current date from your app for each document populated.
Add an ingest pipeline that your app uses. Example for setting a date field to the current time with the ingest pipeline: https://www.elastic.co/guide/en/elasticsearch/reference/current/accessing-data-in-pipelines.html#accessing-ingest-metadata. For more information on ingest pipelines, see here, here, and here
I have memory problems with aggregation queries.
my elastic version is 1.3.2
I tired to define _timestamp as doc value ,
but when I checked the mapping I can see it didn't work
It didn't happen in other fields.
Is there any known issue with timestamp field and doc values?
Lib
Have you tried this mapping?
{
"tweet" : {
"_timestamp" : {
"enabled" : true,
"format" : "YYYY-MM-dd"
}
}
I'm using specified version (13.2). I set up custom date field in my project like this and it's worked for me:
PUT 'http://127.0.0.1:9200/a252e39969665bb4d065/' -d
'{
"a252e39969665bb4d065": {
"mappings": {
"_default_": {
"properties": {
"createdDate": {
"type": "date",
"format": "dateOptionalTime"
}
}
}
}
}
}'
Please, note that i'm using default mapping here (default mapping for all types in index). You can use specified type in an index by replacing "default" in mapping.