Summary of entries of Classes for dataqna.
Classes
AutoSuggestionServiceAsyncClient
This stateless API provides automatic suggestions for natural language queries for the data sources in the provided project and location.
The service provides a resourceless operation suggestQueries
that can be called to get a list of suggestions for a given
incomplete query and scope (or list of scopes) under which the query
is to be interpreted.
There are two types of suggestions, ENTITY for single entity suggestions and TEMPLATE for full sentences. By default, both types are returned.
Example Request:
::
GetSuggestions({ parent: "locations/us/projects/my-project" scopes: "//bigquery.googleapis.com/projects/my-project/datasets/my-dataset/tables/my-table" query: "top it" })
The service will retrieve information based on the given scope(s) and give suggestions based on that (e.g. "top item" for "top it" if "item" is a known dimension for the provided scope).
::
suggestions { suggestion_info { annotated_suggestion { text_formatted: "top item by sum of usd_revenue_net" markups { type: DIMENSION start_char_index: 4 length: 4 } markups { type: METRIC start_char_index: 19 length: 15 } } query_matches { start_char_index: 0 length: 6 } } suggestion_type: TEMPLATE ranking_score: 0.9 } suggestions { suggestion_info { annotated_suggestion { text_formatted: "item" markups { type: DIMENSION start_char_index: 4 length: 2 } } query_matches { start_char_index: 0 length: 6 } } suggestion_type: ENTITY ranking_score: 0.8 }
AutoSuggestionServiceClient
This stateless API provides automatic suggestions for natural language queries for the data sources in the provided project and location.
The service provides a resourceless operation suggestQueries
that can be called to get a list of suggestions for a given
incomplete query and scope (or list of scopes) under which the query
is to be interpreted.
There are two types of suggestions, ENTITY for single entity suggestions and TEMPLATE for full sentences. By default, both types are returned.
Example Request:
::
GetSuggestions({ parent: "locations/us/projects/my-project" scopes: "//bigquery.googleapis.com/projects/my-project/datasets/my-dataset/tables/my-table" query: "top it" })
The service will retrieve information based on the given scope(s) and give suggestions based on that (e.g. "top item" for "top it" if "item" is a known dimension for the provided scope).
::
suggestions { suggestion_info { annotated_suggestion { text_formatted: "top item by sum of usd_revenue_net" markups { type: DIMENSION start_char_index: 4 length: 4 } markups { type: METRIC start_char_index: 19 length: 15 } } query_matches { start_char_index: 0 length: 6 } } suggestion_type: TEMPLATE ranking_score: 0.9 } suggestions { suggestion_info { annotated_suggestion { text_formatted: "item" markups { type: DIMENSION start_char_index: 4 length: 2 } } query_matches { start_char_index: 0 length: 6 } } suggestion_type: ENTITY ranking_score: 0.8 }
QuestionServiceAsyncClient
Service to interpret natural language queries. The service allows to
create Question
resources that are interpreted and are filled
with one or more interpretations if the question could be
interpreted. Once a Question
resource is created and has at
least one interpretation, an interpretation can be chosen for
execution, which triggers a query to the backend (for BigQuery, it
will create a job). Upon successful execution of that
interpretation, backend specific information will be returned so
that the client can retrieve the results from the backend.
The Question
resources are named
projects/*/locations/*/questions/*
.
The Question
resource has a singletion sub-resource
UserFeedback
named
projects/*/locations/*/questions/*/userFeedback
, which allows
access to user feedback.
QuestionServiceClient
Service to interpret natural language queries. The service allows to
create Question
resources that are interpreted and are filled
with one or more interpretations if the question could be
interpreted. Once a Question
resource is created and has at
least one interpretation, an interpretation can be chosen for
execution, which triggers a query to the backend (for BigQuery, it
will create a job). Upon successful execution of that
interpretation, backend specific information will be returned so
that the client can retrieve the results from the backend.
The Question
resources are named
projects/*/locations/*/questions/*
.
The Question
resource has a singletion sub-resource
UserFeedback
named
projects/*/locations/*/questions/*/userFeedback
, which allows
access to user feedback.
AnnotatedString
Describes string annotation from both semantic and formatting perspectives. Example:
User Query:
top countries by population in Africa
0 4 14 17 28 31 37
Table Data:
- "country" - dimension
- "population" - metric
- "Africa" - value in the "continent" column
text_formatted = "top countries by population in Africa"
html_formatted =
"top <b>countries</b> by <b>population</b> in <i>Africa</i>"
::
markups = [ {DIMENSION, 4, 12}, // 'countries' {METRIC, 17, 26}, // 'population' {FILTER, 31, 36} // 'Africa' ]
Note that html formattings for 'DIMENSION' and 'METRIC' are the same, while semantic markups are different.
SemanticMarkup
Semantic markup denotes a substring (by index and length) with markup information.
SemanticMarkupType
Semantic markup types.
BigQueryJob
BigQuery job information. This can be used to query the BigQuery API
and retrieve the current job's status (using
jobs.get <https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/get>
__).
CreateQuestionRequest
Request to create a question resource.
DataQuery
Representation of the data query for the backend. This is provided
for informational purposes only. Clients should not use it to send
it to the backend directly, but rather use the execute
RPC to
trigger the execution. Using the execute
RPC is needed in order
to track the state of a question and report on it correctly to the
data administrators.
DebugFlags
Configuriation of debug flags.
ExecuteQuestionRequest
Request to execute an interpretation.
ExecutionInfo
Information about the backend status (such as BigQuery) of the execution.
JobExecutionState
Enum of possible job execution statuses.
GetQuestionRequest
A request to get a previously created question.
GetUserFeedbackRequest
Request to get user feedback.
HumanReadable
Human readable interpretation.
InterpretEntity
Query entities of an interpretation.
InterpretError
Details on the failure to interpret the question.
InterpretAmbiguityDetails
Details about a query that was too ambiguous. Currently, the message has no fields and its presence signals that there was ambiguity.
InterpretErrorCode
The interpret error code provides an error category why the interpretation failed.
InterpretErrorDetails
Details on interpretation failure.
InterpretIncompleteQueryDetails
Details about an incomplete query.
InterpretUnsupportedDetails
Details about unsupported parts in a query.
Interpretation
An interpretation of a natural language query.
InterpretationStructure
Information about the interpretation structure that helps to understand and visualize the response.
ColumnInfo
Information about a column.
VisualizationType
Enumeration of visualzation types to use for query response data.
Question
The question resource represents a natural language query, its settings, understanding generated by the system, and answer retrieval status. A question cannot be modified.
SuggestQueriesRequest
Request for query suggestions.
SuggestQueriesResponse
Response to SuggestQueries.
Suggestion
A suggestion for a query with a ranking score.
SuggestionInfo
Detailed information about the suggestion.
MatchInfo
MatchInfo describes which part of suggestion matched with data in user typed query. This can be used to highlight matching parts in the UI. This is different from the annotations provided in annotated_suggestion. The annotated_suggestion provides information about the semantic meaning, while this provides information about how it relates to the input.
Example: user query: top products
::
annotated_suggestion { text_formatted = "top product_group" html_formatted = "top product_group" markups { {type: TEXT, start_char_index: 0, length: 3} {type: DIMENSION, start_char_index: 4, length: 13} } }
query_matches { { start_char_index: 0, length: 3 } { start_char_index: 4, length: 7} }
SuggestionType
The type of suggestion.
UpdateUserFeedbackRequest
Request to updates user feedback.
UserFeedback
Feedback provided by a user.
UserFeedbackRating
Enumeration of feedback ratings.