Configure your server to read stored requests from the filesystem:
stored_requests:
filesystem: true
Choose an ID to reference your stored request data. Throughout this doc, replace {id} with the ID you’ve chosen.
Add the file stored_requests/data/by_id/stored_imps/{id}.json
and populate it with some Imp data.
{
"id": "test-imp-id",
"banner": {
"format": [
{
"w": 300,
"h": 250
},
{
"w": 300,
"h": 600
}
]
},
"ext": {
"prebid": {
"bidder": {
"appnexus": {
"placement_id": 12883451
}
}
}
}
}
Start your server.
go build .
./prebid-server
And then POST
to /openrtb2/auction
with your chosen ID.
{
"id": "test-request-id",
"imp": [
{
"ext": {
"prebid": {
"storedrequest": {
"id": "{id}"
}
}
}
}
]
}
The auction will occur as if the HTTP request had included the content from stored_requests/data/by_id/stored_imps/{id}.json
instead.
You can also store part of the Imp on the server. For example:
{
"banner": {
"format": [
{
"w": 300,
"h": 250
},
{
"w": 300,
"h": 600
}
]
},
"ext": {
"prebid": {
"bidder": {
"appnexus": {
"placement_id": 12883451
}
}
}
}
}
This is not fully legal OpenRTB imp
data, since it lacks an id
.
However, incoming HTTP requests can fill in the missing data to complete the OpenRTB request:
{
"id": "test-request-id",
"imp": [
{
"id": "test-imp-id",
"ext": {
"prebid": {
"storedrequest": {
"id": "{id}"
}
}
}
}
]
}
If the Stored Request and the HTTP request have conflicting properties, they will be resolved with a JSON Merge Patch. HTTP request properties will overwrite the Stored Request ones.
So far, our examples have only used Stored Imp data. However, Stored Requests are also allowed on the BidRequest. These work exactly the same way, but support storing properties like timeouts and price granularity.
For example, assume the following stored_requests/data/by_id/stored_requests/stored-request.json
:
{
"tmax": 1000,
"ext": {
"prebid": {
"targeting": {
"pricegranularity": "low",
}
}
}
}
Then an HTTP request like:
{
"id": "test-request-id",
"imp": [
"Any valid Imp data in here"
],
"ext": {
"prebid": {
"storedrequest": {
"id": "stored-request"
}
}
}
}
will produce the same auction as if the HTTP request had been:
{
"id": "test-request-id",
"tmax": 1000,
"imp": [
"Any valid Imp data in here"
],
"ext": {
"prebid": {
"targeting": {
"pricegranularity": "low",
}
}
}
}
Prebid Server does allow Stored BidRequests and Stored Imps in the same HTTP Request. The Stored BidRequest patch will be applied first, and then the Stored Imp patches after.
Beware: Stored Request data will not be applied recursively. If a Stored BidRequest includes Imps with their own Stored Request IDs, then the data for those Stored Imps not be resolved.
Stored Requests do not need to be saved to files. Other backends are supported with different configuration options. For example:
stored_requests:
postgres:
host: localhost
port: 5432
user: db-username
dbname: database-name
query: SELECT id, requestData, 'request' as type FROM stored_requests WHERE id in %REQUEST_ID_LIST% UNION ALL SELECT id, impData, 'imp' as type FROM stored_imps WHERE id in %IMP_ID_LIST%;
stored_requests:
http:
endpoint: http://stored-requests.prebid.com
amp_endpoint: http://stored-requests.prebid.com?amp=true
If you need support for a backend that you don’t see, please contribute it.
Stored Request data can also be cached or updated while PBS is running. Conceptually, Stored Request data is managed by three separate interfaces in the code:
Fetcher: These pull data directly from a backend. Cache: Duplicates data which the Fetcher could find so that it can be accessed more quickly. EventProducer: Returns some Channels which can be used to signal changes to Stored Request data.
Fetchers, Caches, and EventProducers can also be chosen in the the app config. At least one Fetcher is required to make use of Stored Requests.
If more than one Fetcher is defined, they will be ordered and used as fallback data sources. This isn’t a great idea for Prod in the long-term, but may be useful temporarily if you’re trying to transition from one backend to another.
If more than one Cache is defined, they will be composed into a single Cache. Saves will propagate to all Cache layers. Any concrete Fetcher in the project will be composed with any Cache(s) to create a new Fetcher.
EventProducer events are used to Save or Invalidate values from the Cache(s). Saves and invalidates will propagate to all Cache layers.
Here is an example pbs.yaml
file which looks for Stored Requests first from Postgres, and then from an HTTP endpoint.
It will use an in-memory LRU cache to store data locally, and poll another HTTP endpoint to listen for updates.
stored_requests:
postgres:
host: localhost
port: 5432
user: db-username
dbname: database-name
query: SELECT id, requestData, 'request' as type FROM stored_requests WHERE id in %REQUEST_ID_LIST% UNION ALL SELECT id, impData, 'imp' as type FROM stored_imps WHERE id in %IMP_ID_LIST%;
http:
endpoint: http://stored-requests.prebid.com
amp_endpoint: http://stored-requests.prebid.com?amp=true
in_memory_cache:
ttl_seconds: 300 # 5 minutes
request_cache_size_bytes: 107374182 # 0.1GB
imp_cache_size_bytes: 107374182 # 0.1GB
http_events:
endpoint: http://stored-requests.prebid.com
amp_endpoint: http://stored-requests.prebid.com?amp=true
refresh_rate_seconds: 60
timeout_ms: 100