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
Related
I have confusion about elasticsearch mapping
First, I have a doc created with mapping request as
PUT /person
{
"mappings":{
"properties":{
"firstname":{
"type":"text"
}
}
}
}
Then, I want to add new property "lastname", to do that I PUT
PUT /person
{
"mappings":{
"properties":{
"lastname":{
"type":"text"
}
}
}
}
Unfortunately, the exception stops me
{
"error": {
"root_cause": [
{
"type": "resource_already_exists_exception",
"reason": "index [person/5TWopRJaQ3Clam2TiteuHg] already exists",
"index_uuid": "5TWopRJaQ3Clam2TiteuHg",
"index": "person"
}
],
"type": "resource_already_exists_exception",
"reason": "index [person/5TWopRJaQ3Clam2TiteuHg] already exists",
"index_uuid": "5TWopRJaQ3Clam2TiteuHg",
"index": "person"
},
"status": 400
}
It trys to tell me index existed, I could not update it.
But if I use,
PUT /person/_mapping
{
"properties":{
"lastname":{
"type":"text"
}
}
}
it works, and "lastname" is added into mapping.
What's the difference between /person/ {mappings:...} and /person/_mapping {...}?
They are all PUT method, shouldn't they do the same?
Or /person/ {mappings:...} could only be used as created, and /person/_mapping {...} is only for updating existed ones?
Not very make sense. What's the trick here?
https://www.elastic.co/guide/en/elasticsearch/reference/current/removal-of-types.html
Indices created in Elasticsearch 7.0.0 or later no longer accept a _default_ mapping. Indices created in 6.x will continue to function as before in Elasticsearch 6.x. Types are deprecated in APIs in 7.0, with breaking changes to the index creation, put mapping, get mapping, put template, get template and get field mappings APIs.
Hence, mappings support is deprecated in ES 7 and will be removed in ES 8
Currently, I'm trying to implement a variation of the car example here:
https://www.elastic.co/blog/managing-relations-inside-elasticsearch
If I run:
PUT /vehicle/_doc/1
{
"metadata":[
{
"key":"make",
"value":"Saturn"
},
{
"key":"year",
"value":"2015"
}
]
}
the code works correctly.
But if I delete the index and change 2015 from a string to a number:
DELETE /vehicle
PUT /vehicle/_doc/1
{
"metadata":[
{
"key":"make",
"value":"Saturn"
},
{
"key":"year",
"value":2015
}
]
}
I get the following error message:
{ "error": {
"root_cause": [
{
"type": "illegal_argument_exception",
"reason": "mapper [metadata.value] of different type, current_type [long], merged_type [text]"
}
],
"type": "illegal_argument_exception",
"reason": "mapper [metadata.value] of different type, current_type [long], merged_type [text]" }, "status": 400 }
How do I fix this error?
PUT /vehicle/_doc/1
{
"metadata":[
{
"key":"make",
"value":"Saturn"
},
{
"key":"year",
"value":2015
}
]
}
After deleting the index and then trying to index a new document as above, the following steps takes place:
When elastic could not find an index by the name of vehicle and auto index creation is enabled (which is by default enabled) it will create a new index named as vehicle.
Based on the input document elastic now tries to make best guess of the datatype for the fields of the document. This is know as dynamic field mapping.
For the above document since metadata is an array of objects the field metadata is assumed to be of object data type.
Now comes the step to decide the data type of fields of individual object. When it encounters the first object it finds two fields key and value. Both these fields have string value (make and Saturn respectively) and hence elastic identifies the datatype for both the fields as text.
Elastic then try to define the mapping as below:
{
"properties": {
"metadata": {
"properties": {
"key": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
},
"value": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
}
}
}
}
When it encounter the second object where the value of value field is numeric (2015) which it guesses the datatype as long. This results in conflict with the previously identified datatype which was text. A field can not be of mixed data type. Data types are strict, and hence the error.
To resolve the error you need to make sure the input values for the fields are of same type for each of the object as below:
PUT /vehicle/_doc/1
{
"metadata":[
{
"key":"make",
"value":2016
},
{
"key":"year",
"value":2015
}
]
}
For above it could be better used as:
PUT /vehicle/_doc/1
{
"metadata":[
{
"make":"Saturn",
"year": 2015
}
]
}
I'm new to Elasticsearch. I have successfully installed Elasticsearch with Kibana, X-pack and ingest-attachment. I have both Elasticsearch and Kibana running. I have kept it simple at the moment with the install using default options on a windows 2012 server. I have a directory on another drive w\mydocs and at the moment it just has 3 plain text files in it, but I will want to add others like pdf and doc file types. So now I want to get these files into Elasticsearches index. I have tried using the following link as a guide Attaching pdf docs in Elasticsearch, however I cannot get it to work.
Here's how I have set up the index and pipeline:
PUT _ingest/pipeline/docs
{
"description": "documents",
"processors" : [
{
"attachment" : {
"field": "data",
"indexed_chars" : -1
}
}]
}
PUT myindex
{
"mappings" : {
"documents" : {
"properties" : {
"attachment.data" : {
"type": "text",
"analyzer": "standard"
}
}
}
}
}
Then to get the first document in I use the following:
PUT localhost:9200/documents/1?pipeline=docs -d #/w/mydocs/README.TXT
and the error that I receive is:
{
"error": {
"root_cause": [
{
"type": "parse_exception",
"reason": "request body is required"
}
],
"type": "parse_exception",
"reason": "request body is required"
},
"status": 400
}
you still have to send valid JSON to Elasticsearch, even when indexing binary data. This means, that you have to encode your document as base64 and then put it into a JSON document like this
{
"data" : "base64encodedcontentofyourfile"
}
I was advised not to use the ingest-attachment, but instead to use FsCrawler. I managed to get Fscrawler working without having to convert anything to base64.
when I want to index a document in elasticsearch this problem occurring:
message [MapperParsingException[failed to parse]; nested: IllegalArgumentException[unknown field name [output], must be one of [input, weight, contexts]];]
I know that the output field removed from elasticsearch in version 5 but why? and what I have to do for getting single result for inputs?
output field removed from ElasticSearch in version 5, now _source filed returns with the suggestion. Example shown in below.
Mapping
{
"user": {
"properties": {
"name": {
"type": "string"
},
"suggest": {
"type": "completion",
"analyzer": "simple",
"search_analyzer": "simple"
}
}
}
}
Data
{
"id": "123",
"name": "Abc",
"suggest":
{
"input": "Abc::123"
},
"output": "Abc::123"
}
Query
POST - http://localhost:9200/user*/_suggest?pretty
{
"type-suggest": {
"text": "Abc",
"completion": {
"field": "suggest"
}
}
}
Elastic mentions the following
As suggestions are document-oriented, suggestion metadata (e.g. output) should now be specified as a field in the document. The support for specifying output when indexing suggestion entries has been removed. Now suggestion result entry’s text is always the un-analyzed value of the suggestion’s input (same as not specifying output while indexing suggestions in pre-5.0 indices).
Source
Update
I was able to get a single output from multiple inputs in ES 5.1.1. You can find the answere here
hi I want to set custom routing on specific field "userId" on my Es v2.0.
But it giving me error.I don't know how to set custom routing on ES v2.0
Please guys help me out.Thanks in advance.Below is error message, while creating custom routing with existing index.
{
"error": {
"root_cause": [
{
"type": "mapper_parsing_exception",
"reason": "Mapping definition for [_routing] has unsupported parameters: [path : userId]"
}
],
"type": "mapper_parsing_exception",
"reason": "Mapping definition for [_routing] has unsupported parameters: [path : userId]"
},
"status": 400
}
In ES 2.0, the _routing.path meta-field has been removed. So now you need to do it like this instead:
In your mapping, you can only specify that routing is required (but you cannot specify path anymore):
PUT my_index
{
"mappings": {
"my_type": {
"_routing": {
"required": true
},
"properties": {
"name": {
"type": "string"
}
}
}
}
}
And then when you index a document, you can specify the routing value in the query string like this:
PUT my_index/my_type/1?routing=bar
{
"name": "foo"
}
You can still use custom routing based on a field from the data being indexed. You can setup a simple pipeline and then use the pipeline every time you index a document, or you can also change the index settings to use the pipeline whenever the index receives a document indexing request.
Read about the pipeline here
Do read above and below the docs for more clarity. It's not meant for setting custom routing, but can be used for the purpose. Custom routing was disabled for a good reason that the field to be used can turn out to have null values leading to unexpected behavior. Hence take care of that issue by yourself.
For routing, here is a sample pipeline PUT :
PUT localhost:9200/_ingest/pipeline/nameRouting
Content-Type: application/json
{
"description" : "Set's the routing value from name field in document",
"processors" : [
{
"set" : {
"field": "_routing",
"value": "{{_source.name}}"
}
}
]
}
The index settings will be :
{
"settings" : {
"index" : {
"default_pipeline" : "nameRouting"
}
}
}