Example: Enrich your data based on exact values
editExample: Enrich your data based on exact values
editmatch enrich policies match enrich data to incoming
documents based on an exact value, such as a email address or ID, using a
term query.
The following example creates a match enrich policy that adds user name and
contact information to incoming documents based on an email address. It then
adds the match enrich policy to a processor in an ingest pipeline.
Use the create index API or index API to create a source index.
The following index API request creates a source index and indexes a new document to that index.
resp = client.index(
index="users",
id="1",
refresh="wait_for",
document={
"email": "mardy.brown@asciidocsmith.com",
"first_name": "Mardy",
"last_name": "Brown",
"city": "New Orleans",
"county": "Orleans",
"state": "LA",
"zip": 70116,
"web": "mardy.asciidocsmith.com"
},
)
print(resp)
response = client.index(
index: 'users',
id: 1,
refresh: 'wait_for',
body: {
email: 'mardy.brown@asciidocsmith.com',
first_name: 'Mardy',
last_name: 'Brown',
city: 'New Orleans',
county: 'Orleans',
state: 'LA',
zip: 70_116,
web: 'mardy.asciidocsmith.com'
}
)
puts response
const response = await client.index({
index: "users",
id: 1,
refresh: "wait_for",
document: {
email: "mardy.brown@asciidocsmith.com",
first_name: "Mardy",
last_name: "Brown",
city: "New Orleans",
county: "Orleans",
state: "LA",
zip: 70116,
web: "mardy.asciidocsmith.com",
},
});
console.log(response);
PUT /users/_doc/1?refresh=wait_for
{
"email": "mardy.brown@asciidocsmith.com",
"first_name": "Mardy",
"last_name": "Brown",
"city": "New Orleans",
"county": "Orleans",
"state": "LA",
"zip": 70116,
"web": "mardy.asciidocsmith.com"
}
Use the create enrich policy API to create an enrich policy with the
match policy type. This policy must include:
- One or more source indices
-
A
match_field, the field from the source indices used to match incoming documents - Enrich fields from the source indices you’d like to append to incoming documents
resp = client.enrich.put_policy(
name="users-policy",
match={
"indices": "users",
"match_field": "email",
"enrich_fields": [
"first_name",
"last_name",
"city",
"zip",
"state"
]
},
)
print(resp)
response = client.enrich.put_policy(
name: 'users-policy',
body: {
match: {
indices: 'users',
match_field: 'email',
enrich_fields: [
'first_name',
'last_name',
'city',
'zip',
'state'
]
}
}
)
puts response
const response = await client.enrich.putPolicy({
name: "users-policy",
match: {
indices: "users",
match_field: "email",
enrich_fields: ["first_name", "last_name", "city", "zip", "state"],
},
});
console.log(response);
PUT /_enrich/policy/users-policy
{
"match": {
"indices": "users",
"match_field": "email",
"enrich_fields": ["first_name", "last_name", "city", "zip", "state"]
}
}
Use the execute enrich policy API to create an enrich index for the policy.
POST /_enrich/policy/users-policy/_execute?wait_for_completion=false
Use the create or update pipeline API to create an ingest pipeline. In the pipeline, add an enrich processor that includes:
- Your enrich policy.
-
The
fieldof incoming documents used to match documents from the enrich index. -
The
target_fieldused to store appended enrich data for incoming documents. This field contains thematch_fieldandenrich_fieldsspecified in your enrich policy.
resp = client.ingest.put_pipeline(
id="user_lookup",
processors=[
{
"enrich": {
"description": "Add 'user' data based on 'email'",
"policy_name": "users-policy",
"field": "email",
"target_field": "user",
"max_matches": "1"
}
}
],
)
print(resp)
const response = await client.ingest.putPipeline({
id: "user_lookup",
processors: [
{
enrich: {
description: "Add 'user' data based on 'email'",
policy_name: "users-policy",
field: "email",
target_field: "user",
max_matches: "1",
},
},
],
});
console.log(response);
PUT /_ingest/pipeline/user_lookup
{
"processors" : [
{
"enrich" : {
"description": "Add 'user' data based on 'email'",
"policy_name": "users-policy",
"field" : "email",
"target_field": "user",
"max_matches": "1"
}
}
]
}
Use the ingest pipeline to index a document. The incoming document should
include the field specified in your enrich processor.
resp = client.index(
index="my-index-000001",
id="my_id",
pipeline="user_lookup",
document={
"email": "mardy.brown@asciidocsmith.com"
},
)
print(resp)
const response = await client.index({
index: "my-index-000001",
id: "my_id",
pipeline: "user_lookup",
document: {
email: "mardy.brown@asciidocsmith.com",
},
});
console.log(response);
PUT /my-index-000001/_doc/my_id?pipeline=user_lookup
{
"email": "mardy.brown@asciidocsmith.com"
}
To verify the enrich processor matched and appended the appropriate field data, use the get API to view the indexed document.
resp = client.get(
index="my-index-000001",
id="my_id",
)
print(resp)
response = client.get( index: 'my-index-000001', id: 'my_id' ) puts response
const response = await client.get({
index: "my-index-000001",
id: "my_id",
});
console.log(response);
GET /my-index-000001/_doc/my_id
The API returns the following response:
{
"found": true,
"_index": "my-index-000001",
"_id": "my_id",
"_version": 1,
"_seq_no": 55,
"_primary_term": 1,
"_source": {
"user": {
"email": "mardy.brown@asciidocsmith.com",
"first_name": "Mardy",
"last_name": "Brown",
"zip": 70116,
"city": "New Orleans",
"state": "LA"
},
"email": "mardy.brown@asciidocsmith.com"
}
}