Currently, I have set few JSON fields as "object" in model but I want these fields to be JSON in database. However, when I am auto migrating it, fields are getting created as text in MySQL? How to fix this?
"education": {
"type": "object"
},
"technology": {
"type": "object"
},
"certificationsAndAchievements": {
"type": "object"
}
You can use the mysql option on your models and set dataType to JSON. Now when you migrate it this will be the column type
{
"education": {
"type": "object",
"mysql": {
"dataType":"JSON"
}
},
"technology": {
"type": "object",
"mysql": {
"dataType":"JSON"
}
},
"certificationsAndAchievements": {
"type": "object",
"mysql": {
"dataType":"JSON"
}
}
}
Related
Using AWS Glue schema registry, I'm trying to register a schema of JSON format with FULL compatibility mode but the schema version [refer version(2) below] is getting failed due to compatibility issues.
Version(1)
{
"type": "object",
"properties": {
"foo": { "type": "string" },
"bar": { "type": "string" }
},
"additionalProperties": { "type": "string" }
}
Version(2)
{
"type": "object",
"properties": {
"foo": { "type": "string" },
"bar": { "type": "string" },
"zap": { "type": "string" }
},
"additionalProperties": { "type": "string" }
}
I've referred https://yokota.blog/2021/03/29/understanding-json-schema-compatibility/ for creating the sample schemas.
Scenario:
We are using AWS ElasticSearch 6.8. We got an index (index-A) with a mapping structure consist of multiple nested objects and JSON hierarchy. We need to create new index (index-B) and move all documents from index-A to index-B.
We need to create index-B with only specific fields.
We need to rename field names while reindexing
e.g.
index-A mapping:
{
"userdata": {
"properties": {
"payload": {
"type": "object",
"properties": {
"Alldata": {
"Username": {
"type": "keyword"
},
"Designation": {
"type": "keyword"
},
"Company": {
"type": "keyword"
},
"Region": {
"type": "keyword"
}
}
}
}
}
}}
Expected structure of index-B mapping after reindexing with rename (Company-cnm, Region-rg) :-
{
"userdata": {
"properties": {
"cnm": {
"type": "keyword"
},
"rg": {
"type": "keyword"
}
}
}}
Steps we are Following:
First we are using Create index API to create index-B with above mapping structure
Once index is created we are creating an ingest pipeline.
PUT ElasticSearch domain endpoint/_ingest/pipeline/my_rename_pipeline
{
"description": "rename field pipeline",
"processors": [{
"rename": {
"field": "payload.Company",
"target_field": "cnm",
"ignore_missing": true
}
},
{
"rename": {
"field": "payload.Region",
"target_field": "rg",
"ignore_missing": true
}
}
]
}
Perform reindexing operation, payload for the same below
let reindexParams = {
wait_for_completion: false,
slices: "auto",
body: {
"conflicts": "proceed",
"source": {
"size": 8000,
"index": "index-A",
"_source": ["payload.Company", "payload.Region"]
},
"dest": {
"index": "index-B",
"pipeline": "my_rename_pipeline",
"version_type": "external"
}
}
};
Problem:
Once the reindexing is complete as expected all documents transferred to new index with renamed fields but there is one additional field which is not selected. As you can see below the "payload" object with metadata is also added to the new index after reindexing. This field is empty and consist of no data.
index-B looks like below after reindexing:
{
"userdata": {
"properties": {
"cnm": {
"type": "keyword"
},
"rg": {
"type": "keyword"
},
"payload": {
"properties": {
"Alldata": {
"type": "object"
}
}
}
}
}}
We are unable to find the workaround and need help how to stop this field from creating. Any help will be appreciated.
Great job!! You're almost there, you simply need to remove the payload field within your pipeline using the remove processor and you're good:
{
"description": "rename field pipeline",
"processors": [
{
"rename": {
"field": "payload.Company",
"target_field": "cnm",
"ignore_missing": true
}
},
{
"rename": {
"field": "payload.Region",
"target_field": "rg",
"ignore_missing": true
}
},
{
"remove": { <--- add this processor
"field": "payload"
}
}
]
}
I'm looking into Loopback and stuck in finding a solution when two models (let's say Customer/Orders) have a one-to-many relationship but the primary key (id) of the parent isn't a foreign key in child table, but rather some non-key field.
For example, consider following two tables
Customer[ id(pk), name, social_security_number]
Order [ id(pk), social_security_number(fk)]
I'm not able to create the relationship based on the above scenario. Loopback isn't returning orders when I query against a particular customer. Here is my actual code snippet (partial). I'm using default id field as Primary Key
{
"name": "Customer",
"properties": {
"name": {
"type": "string",
"required": true
},
"social_security_number": {
"type": "number",
"required": true
}
},
"relations": {
"orders": {
"type": "hasMany",
"model": "Order",
"foreignKey": "social_security_number"
}
}
}
{
"name": "Order",
"base": "PersistedModel",
"properties": {
"social_security_number": {
"type": "number",
"required": true
}
},
"relations": {
"customer": {
"type": "belongsTo",
"model": "Customer",
"foreignKey": "social_security_number"
}
}
}
How can I make this work?
I have defined my own template to be used by logstash where I have deactivate the dynamic mapping:
{
"my_index": {
"order": 0,
"template": "my_index",
"settings": {
"index": {
"mapper": {
"dynamic": "false"
},
"analysis": {
"analyzer": {
"nlp_analyzer": {
"filter": [
"lowercase"
],
"type": "custom",
"tokenizer": "nlp_tokenizer"
}
},
"tokenizer": {
"nlp_tokenizer": {
"pattern": ""
"(\w+)|(\s*[\s+])"
"",
"type": "pattern"
}
}
},
"number_of_shards": "1",
"number_of_replicas": "0"
}
},
"mappings": {
"author": {
"properties": {
"author_name": {
"type": "keyword"
},
"author_pseudo": {
"type": "keyword"
},
"author_location": {
"type": "text",
"fields": {
"standard": {
"analyzer": "standard",
"term_vector": "yes",
"type": "text"
},
"nlp": {
"analyzer": "nlp_analyzer",
"term_vector": "yes",
"type": "text"
}
}
}
}
}
}
}
}
To test if elasticsearch won’t generate new field I try to let a field in my events that is not present in my mapping, let’s say that I have this event:
{
“type” => “author”,
“author_pseudo” => “chloemdelorenzo”,
“author_name” => “Chloe DeLorenzo”,
“author_location” => “US”,
}
Elasticsearch will generate a new field in the mapping when indexing this event:
"type": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
}
I know that Logstash is using my template because in my mapping I use a custom analyser and I can find it back into the mapping generated. But apparently it doesn’t take into consideration that the dynamic field is disabled.
I want elasticsearch to ignore fields that are not present in my mapping but to index the field that have a defined mapping. How can I avoid logstash to create new field?
You should enforce the mapping at the document type level.
https://www.elastic.co/guide/en/elasticsearch/reference/current/dynamic-mapping.html
Regardless of the value of this setting, types can still be added
explicitly when creating an index or with the PUT mapping API.
So your mapping will look like:
"mappings": {
"author": {
"dynamic": false,
"properties": {
"author_name": {
"type": "keyword"
},
"author_pseudo": {
"type": "keyword"
},
"author_location": {
"type": "text",
"fields": {
"standard": {
"analyzer": "standard",
"term_vector": "yes",
"type": "text"
},
"nlp": {
"analyzer": "nlp_analyzer",
"term_vector": "yes",
"type": "text"
}
}
}
}
}
}
This answer is not exactly what you are requesting, but you can manually remove fields with a logstash filter like this:
filter {
mutate {
remove_field => ["fieldname"]
}
}
If your events have a defined list of fields, you could solve your problem this way.
I have an index in Elasticsearch (v 1.5.0) that has a mapping that looks like this:
{
"storedash": {
"mappings": {
"outofstock": {
"_ttl": {
"enabled": true,
"default": 1296000000
},
"properties": {
"CompositeSKUProductId": {
"type": "string"
},
"Hosts": {
"type": "nested",
"properties": {
"HostName": {
"type": "string"
},
"SKUs": {
"type": "nested",
"properties": {
"CompositeSKUProductId": {
"type": "string",
"index": "not_analyzed"
},
"Count": {
"type": "long"
},
"ProductId": {
"type": "string",
"index": "not_analyzed",
"copy_to": [
"CompositeSKUProductId"
]
},
"SKU": {
"type": "string",
"index": "not_analyzed",
"copy_to": [
"CompositeSKUProductId"
]
}
}
}
}
},
"Timestamp": {
"type": "date",
"format": "dateOptionalTime"
}
}
}
}
}
}
Look at how field CompositeSKUProductId is created as a composition of both the SKU and ProductId fields.
I now want to perform an aggregation on that composite field, but it doesn't seem to work; the relevant part of my query looks like this:
"aggs": {
"hostEspecifico": {
"filter": {
"term": { "Hosts.HostName": "www.example.com"}
},
"aggs": {
"skus": {
"nested": {
"path": "Hosts.SKUs"
},
"aggs": {
"valores": {
"terms": {
"field": "Hosts.SKUs.CompositeSKUProductId", "order": { "media": "desc" }, "size": 100 },
"aggs": {
"media": {
"avg": {
"field": "Hosts.SKUs.Count"
}
}
}
}
}
}
}
}
}
Thing is, this aggregation returned zero buckets, as though it weren't even there.
I checked that the very same query works if only I change CompositeSKUProductId by another field like ProductId.
Any ideas as to what I can do to solve my problem?
N.B.: I'm using the AWS Elasticsearch Service, which does not allow scripting.
The problem here is that you have misunderstood the concept of copy_to functionality. It simply copies the field values of various fields and does not combine the way you would expect.
If SKU is 123 and product id is 456 then composite field will have them as separate values and not 123 456. You can verify this by querying your field.
You would have to do this on server side, ideally with script but it is not allowed. Personally we used AWS ES service but faced multiple problems, major being not able to change elasticsearch.yml file and not able to use scripts. You might want to look at Found.
Hope this helps!
In order to copy_to another field in the nested doc, you need to supply the full path to the field you want to copy to in your mapping. You have only provided "CompositeSKUProductId", which causes the data to be copied to a field in your root document, instead of your nested SKUs type document.
Try updating your mapping for your "SKUs" type to copy_to the fully qualified field "Hosts.SKUs.CompositeSKUProductId" instead.
Like this:
{
"storedash": {
"mappings": {
"outofstock": {
"_ttl": {
"enabled": true,
"default": 1296000000
},
"properties": {
"CompositeSKUProductId": {
"type": "string"
},
"Hosts": {
"type": "nested",
"properties": {
"HostName": {
"type": "string"
},
"SKUs": {
"type": "nested",
"properties": {
"CompositeSKUProductId": {
"type": "string",
"index": "not_analyzed"
},
"Count": {
"type": "long"
},
"ProductId": {
"type": "string",
"index": "not_analyzed",
"copy_to": [
"Hosts.SKUs.CompositeSKUProductId"
]
},
"SKU": {
"type": "string",
"index": "not_analyzed",
"copy_to": [
"Hosts.SKUs.CompositeSKUProductId"
]
}
}
}
}
},
"Timestamp": {
"type": "date",
"format": "dateOptionalTime"
}
}
}
}
}
}
You may find this discussion helpful, when a similar issue was opened on github.