Reindex uses scroll searches to read the source data. It is more efficient
to read more data in one search scroll round then several. I think 10000
is a good sweet spot.
Relates to #32789
its own helper method to determine alias / policy base name.
This way both the enrich processor and policy runner use the same logic
to determine the alias to use.
Relates to #32789
Backports #41088
Adds the foundation of the execution logic to execute an enrich policy. Validates
the source index existence as well as mappings, creates a new enrich index for
the policy, reindexes the source index into the new enrich index, and swaps the
enrich alias for the policy to the new index.
The enrich processor performs a lookup in a locally allocated
enrich index shard using a field value from the document being enriched.
If there is a match then the _source of the enrich document is fetched.
The document being enriched then gets the decorate values from the
enrich document based on the configured decorate fields in the pipeline.
Note that the usage of the _source field is temporary until the enrich
source field that is part of #41521 is merged into the enrich branch.
Using the _source field involves significant decompression which not
desired for enrich use cases.
The policy contains the information what field in the enrich index
to query and what fields are available to decorate a document being
enriched with.
The enrich processor has the following configuration options:
* `policy_name` - the name of the policy this processor should use
* `enrich_key` - the field in the document being enriched that holds to lookup value
* `ignore_missing` - Whether to allow the key field to be missing
* `enrich_values` - a list of fields to decorate the document being enriched with.
Each entry holds a source field and a target field.
The source field indicates what decorate field to use that is available in the policy.
The target field controls the field name to use in the document being enriched.
The source and target fields can be the same.
Example pipeline config:
```
{
"processors": [
{
"policy_name": "my_policy",
"enrich_key": "host_name",
"enrich_values": [
{
"source": "globalRank",
"target": "global_rank"
}
]
}
]
}
```
In the above example documents are being enriched with a global rank value.
For each document that has match in the enrich index based on its host_name field,
the document gets an global rank field value, which is fetched from the `globalRank`
field in the enrich index and saved as `global_rank` in the document being enriched.
This is PR is part one of #41521
move put policy api yaml test to this rest module.
The main benefit is that all tests will then be run when running:
`./gradlew -p x-pack/plugin/enrich check`
The rest qa module starts a node with default distribution and basic
license.
This qa module will also be used for adding different rest tests (not yaml),
for example rest tests needed for #41532
Also when we are going to work on security integration then we can
add a security qa module under the qa folder. Also at some point
we should add a multi node qa module.
There is no need to create a enrich store component for the transport
layer since the inner components of the store are either present in the
master node calls or via an already injected ClusterService. This commit
cleans up the class, adds the forthcoming delete call and tests the new
code.
Martijn van Groningen
James Baiera
Michael Basnight