Debugging a search pipeline
The verbose_pipeline parameter provides detailed information about the data flow and transformations for the search request, search response, and search phase processors in the search pipeline. It helps with troubleshooting and optimizing the pipeline and ensures transparency in handling search requests and responses.
Enabling debugging
To enable pipeline debugging, specify verbose_pipeline=true as a query parameter in your search request. This functionality is available for all three search pipeline methods:
Default search pipeline
To use verbose_pipeline with a default search pipeline, set the pipeline as the default in the index settings and include verbose_pipeline=true in the query:
PUT /my_index/_settings
{
"index.search.default_pipeline": "my_pipeline"
}
GET /my_index/_search?verbose_pipeline=true
For more information about default search pipelines, see Setting a default pipeline for all requests in an index.
Specific search pipeline
To use verbose_pipeline with a specific search pipeline, specify the pipeline ID and include verbose_pipeline=true in the query:
GET /my_index/_search?search_pipeline=my_pipeline&verbose_pipeline=true
For more information about using specific search pipelines, see Specifying an existing pipeline for a request.
Temporary search pipeline
To use verbose_pipeline with a temporary search pipeline, define the pipeline directly in the request body and include verbose_pipeline=true in the query:
POST /my_index/_search?verbose_pipeline=true
{
"query": {
"match": { "text_field": "some search text" }
},
"search_pipeline": {
"request_processors": [
{
"filter_query": {
"query": { "term": { "visibility": "public" } }
}
}
],
"response_processors": [
{
"collapse": {
"field": "category"
}
}
]
}
}
For more information about using a temporary search pipeline, see Using a temporary pipeline for a request.
Example response
When the verbose_pipeline parameter is enabled, the response contains an additional processor_results field that provides information about the transformations applied by each processor in the pipeline:
Response
{
"took": 27,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 0.18232156,
"hits": [
{
"_index": "my_index",
"_id": "1",
"_score": 0.18232156,
"_source": {
"notification": "This is a public message",
"visibility": "public"
}
}
]
},
"processor_results": [
{
"processor_name": "filter_query",
"tag": "tag1",
"duration_millis": 288541,
"status": "success",
"input_data": {
"verbose_pipeline": true,
"query": {
"bool": {
"adjust_pure_negative": true,
"must": [
{
"match": {
"message": {
"auto_generate_synonyms_phrase_query": true,
"query": "this",
"zero_terms_query": "NONE",
"fuzzy_transpositions": true,
"boost": 1.0,
"prefix_length": 0,
"operator": "OR",
"lenient": false,
"max_expansions": 50
}
}
}
],
"boost": 1.0
}
}
},
"output_data": {
"verbose_pipeline": true,
"query": {
"bool": {
"filter": [
{
"term": {
"visibility": {
"boost": 1.0,
"value": "public"
}
}
}
],
"adjust_pure_negative": true,
"must": [
{
"bool": {
"adjust_pure_negative": true,
"must": [
{
"match": {
"message": {
"auto_generate_synonyms_phrase_query": true,
"query": "this",
"zero_terms_query": "NONE",
"fuzzy_transpositions": true,
"boost": 1.0,
"prefix_length": 0,
"operator": "OR",
"lenient": false,
"max_expansions": 50
}
}
}
],
"boost": 1.0
}
}
],
"boost": 1.0
}
}
}
},
{
"processor_name": "rename_field",
"duration_millis": 250042,
"status": "success",
"input_data": [
{
"_index": "my_index",
"_id": "1",
"_score": 0.18232156,
"_source": {
"message": "This is a public message",
"visibility": "public"
}
}
],
"output_data": [
{
"_index": "my_index",
"_id": "1",
"_score": 0.18232156,
"_source": {
"notification": "This is a public message",
"visibility": "public"
}
}
]
}
]
}