(feat): Sql registry search #105
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| @@ -1063,6 +1066,80 @@ def create_project_if_not_exists(self, project): | |||
| if new_project: | |||
| self._set_last_updated_metadata(update_datetime, project) | |||
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| def search( | |||
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I was under the impression search should be implemented using full text search. Is pagination implemented in this?
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About Full Text Search, is that expectation set with Workbench team?
About Pagination, We are planning to switch to Feast Remote Registry. How does that impact the functionality?
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Remote registry leverages, Sql Registry so we will have the functionality. We don't need to reimplement. Just method definition in remote registry should help until we contribute the functionality. Looking for answers to my questions above.
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Full text search in this context means "feature view and project names".
That is, the names of all feature views and all projects should be searchable using this functionality. That's what's indicated by the UI design that has been given to us.
| @@ -55,6 +55,8 @@ require ( | |||
| github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f // indirect | |||
| github.com/goccy/go-json v0.10.2 // indirect | |||
| github.com/golang/snappy v0.0.4 // indirect | |||
| github.com/gonuts/commander v0.1.0 // indirect | |||
| @@ -173,6 +173,10 @@ github.com/golang/protobuf v1.5.3/go.mod h1:XVQd3VNwM+JqD3oG2Ue2ip4fOMUkwXdXDdiu | |||
| github.com/golang/snappy v0.0.0-20180518054509-2e65f85255db/go.mod h1:/XxbfmMg8lxefKM7IXC3fBNl/7bRcc72aCRzEWrmP2Q= | |||
| github.com/golang/snappy v0.0.4 h1:yAGX7huGHXlcLOEtBnF4w7FQwA26wojNCwOYAEhLjQM= | |||
| github.com/golang/snappy v0.0.4/go.mod h1:/XxbfmMg8lxefKM7IXC3fBNl/7bRcc72aCRzEWrmP2Q= | |||
| github.com/gonuts/commander v0.1.0 h1:EcDTiVw9oAVORFjQOEOuHQqcl6OXMyTgELocTq6zJ0I= | |||
What this PR does / why we need it:
This adds a function to the SQL registry to allow searching in accordance with the parameters set by the AI workbench team.
You will notice that we're not doing this search in a SQL query. That is because the database schemas are a proto stored as a
VARCHARand a little bit of metadata. As such, we have to pull all potentially relevant objects from the DB and then filter in memory. This is not ideal, but it's the only approach that will work.