Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows.
Input/output argument of a function or a stored procedure.
ARIMA model fitting metrics.
Model evaluation metrics for ARIMA forecasting models.
Arima order, can be used for both non-seasonal and seasonal parts.
Model evaluation metrics for a single ARIMA forecasting model.
Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both allServices and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { “audit_configs”: [ { “service”: “allServices”, “audit_log_configs”: [ { “log_type”: “DATA_READ”, “exempted_members”: [ “user:jose@example.com” ] }, { “log_type”: “DATA_WRITE” }, { “log_type”: “ADMIN_READ” } ] }, { “service”: “sampleservice.googleapis.com”, “audit_log_configs”: [ { “log_type”: “DATA_READ” }, { “log_type”: “DATA_WRITE”, “exempted_members”: [ “user:aliya@example.com” ] } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.
Provides the configuration for logging a type of permissions. Example: { “audit_log_configs”: [ { “log_type”: “DATA_READ”, “exempted_members”: [ “user:jose@example.com” ] }, { “log_type”: “DATA_WRITE” } ] } This enables ‘DATA_READ’ and ‘DATA_WRITE’ logging, while exempting jose@example.com from DATA_READ logging.
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Central instance to access all Bigquery related resource activities
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Evaluation metrics for binary classification/classifier models.
Confusion matrix for binary classification models.
Associates members, or principals, with a role.
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[Output-only, Beta] Training options used by this training run. These options are mutable for subsequent training runs. Default values are explicitly stored for options not specified in the input query of the first training run. For subsequent training runs, any option not explicitly specified in the input query will be copied from the previous training run.
Representative value of a categorical feature.
Represents the count of a single category within the cluster.
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Message containing the information about one cluster.
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Evaluation metrics for clustering models.
Confusion matrix for multi-class classification models.
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Data split result. This contains references to the training and evaluation data tables that were used to train the model.
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[Optional] An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
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Deletes the dataset specified by the datasetId value. Before you can delete a dataset, you must delete all its tables, either manually or by specifying deleteContents. Immediately after deletion, you can create another dataset with the same name.
Returns the dataset specified by datasetID.
Creates a new empty dataset.
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Lists all datasets in the specified project to which you have been granted the READER dataset role.
An array of the dataset resources in the project. Each resource contains basic information. For full information about a particular dataset resource, use the Datasets: get method. This property is omitted when there are no datasets in the project.
A builder providing access to all methods supported on
dataset resources.
It is not used directly, but through the
Bigquery hub.
Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource. This method supports patch semantics.
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[Optional]The tags associated with this dataset. Tag keys are globally unique.
Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource.
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Model evaluation metrics for dimensionality reduction models.
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Discrete candidates of a double hyperparameter.
Search space for a double hyperparameter.
Range of a double hyperparameter.
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A single entry in the confusion matrix.
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Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models.
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Explanation for a single feature.
Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: “Summary size limit” description: “Determines if a summary is less than 100 chars” expression: “document.summary.size() < 100” Example (Equality): title: “Requestor is owner” description: “Determines if requestor is the document owner” expression: “document.owner == request.auth.claims.email” Example (Logic): title: “Public documents” description: “Determine whether the document should be publicly visible” expression: “document.type != ‘private’ && document.type != ‘internal’” Example (Data Manipulation): title: “Notification string” description: “Create a notification string with a timestamp.” expression: “’New message received at ’ + string(document.create_time)” The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.
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Representative value of a single feature within the cluster.
Request message for GetIamPolicy method.
Encapsulates settings provided to GetIamPolicy.
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Global explanations containing the top most important features after training.
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Hyperparameter search spaces. These should be a subset of training_options.
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An array of int.
Search space for int array.
Discrete candidates of an int hyperparameter.
Search space for an int hyperparameter.
Range of an int hyperparameter.
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Requests that a job be cancelled. This call will return immediately, and the client will need to poll for the job status to see if the cancel completed successfully. Cancelled jobs may still incur costs.
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Requests the deletion of the metadata of a job. This call returns when the job’s metadata is deleted.
Returns information about a specific job. Job information is available for a six month period after creation. Requires that you’re the person who ran the job, or have the Is Owner project role.
Retrieves the results of a query job.
Starts a new asynchronous job. Requires the Can View project role.
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Lists all jobs that you started in the specified project. Job information is available for a six month period after creation. The job list is sorted in reverse chronological order, by job creation time. Requires the Can View project role, or the Is Owner project role if you set the allUsers property.
List of jobs that were requested.
A builder providing access to all methods supported on
job resources.
It is not used directly, but through the
Bigquery hub.
Runs a BigQuery SQL query synchronously and returns query results if the query completes within a specified timeout.
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[Output only] Job resource usage breakdown by reservation.
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[Output-only] Job resource usage breakdown by reservation.
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Represents a single JSON object.
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Response message for the ListRowAccessPolicies method.
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[Output-only, Beta] Model options used for the first training run. These options are immutable for subsequent training runs. Default values are used for any options not specified in the input query.
Deletes the model specified by modelId from the dataset.
Gets the specified model resource by model ID.
Lists all models in the specified dataset. Requires the READER dataset role. After retrieving the list of models, you can get information about a particular model by calling the models.get method.
A builder providing access to all methods supported on
model resources.
It is not used directly, but through the
Bigquery hub.
Patch specific fields in the specified model.
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Evaluation metrics for multi-class classification/classifier models.
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An Identity and Access Management (IAM) policy, which specifies access controls for Google Cloud resources. A
Policy is a collection of
bindings. A
binding binds one or more
members, or principals, to a single
role. Principals can be user accounts, service accounts, Google groups, and domains (such as G Suite). A
role is a named list of permissions; each
role can be an IAM predefined role or a user-created custom role. For some types of Google Cloud resources, a
binding can also specify a
condition, which is a logical expression that allows access to a resource only if the expression evaluates to
true. A condition can add constraints based on attributes of the request, the resource, or both. To learn which resources support conditions in their IAM policies, see the
IAM documentation.
JSON example: { “bindings”: [ { “role”: “roles/resourcemanager.organizationAdmin”, “members”: [ “user:mike@example.com”, “group:admins@example.com”, “domain:google.com”, “serviceAccount:my-project-id@appspot.gserviceaccount.com” ] }, { “role”: “roles/resourcemanager.organizationViewer”, “members”: [ “user:eve@example.com” ], “condition”: { “title”: “expirable access”, “description”: “Does not grant access after Sep 2020”, “expression”: “request.time < timestamp(‘2020-10-01T00:00:00.000Z’)”, } } ], “etag”: “BwWWja0YfJA=”, “version”: 3 }
YAML example: bindings: - members: - user:mike@example.com - group:admins@example.com - domain:google.com - serviceAccount:my-project-id@appspot.gserviceaccount.com role: roles/resourcemanager.organizationAdmin - members: - user:eve@example.com role: roles/resourcemanager.organizationViewer condition: title: expirable access description: Does not grant access after Sep 2020 expression: request.time < timestamp(‘2020-10-01T00:00:00.000Z’) etag: BwWWja0YfJA= version: 3 For a description of IAM and its features, see the
IAM documentation.
Returns the email address of the service account for your project used for interactions with Google Cloud KMS.
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Lists all projects to which you have been granted any project role.
Projects to which you have at least READ access.
A builder providing access to all methods supported on
project resources.
It is not used directly, but through the
Bigquery hub.
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[Optional] The types of the fields of this struct, in order, if this is a struct.
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[TrustedTester] [Required] Defines the ranges for range partitioning.
Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit.
Evaluation metrics for regression and explicit feedback type matrix factorization models.
Options for a remote user-defined function.
A user-defined function or a stored procedure.
Deletes the routine specified by routineId from the dataset.
Gets the specified routine resource by routine ID.
Creates a new routine in the dataset.
Lists all routines in the specified dataset. Requires the READER dataset role.
A builder providing access to all methods supported on
routine resources.
It is not used directly, but through the
Bigquery hub.
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Updates information in an existing routine. The update method replaces the entire Routine resource.
A single row in the confusion matrix.
Represents access on a subset of rows on the specified table, defined by its filter predicate. Access to the subset of rows is controlled by its IAM policy.
Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
Lists all row access policies on the specified table.
A builder providing access to all methods supported on
rowAccessPolicy resources.
It is not used directly, but through the
Bigquery hub.
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Sets the access control policy on the specified resource. Replaces any existing policy. Can return NOT_FOUND, INVALID_ARGUMENT, and PERMISSION_DENIED errors.
Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may “fail open” without warning.
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Request message for SetIamPolicy method.
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Options for a user-defined Spark routine.
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The data type of a variable such as a function argument. Examples include: * INT64: {"typeKind": "INT64"} * ARRAY: { “typeKind”: “ARRAY”, “arrayElementType”: {“typeKind”: “STRING”} } * STRUCT>: { “typeKind”: “STRUCT”, “structType”: { “fields”: [ { “name”: “x”, “type”: {“typeKind”: “STRING”} }, { “name”: “y”, “type”: { “typeKind”: “ARRAY”, “arrayElementType”: {“typeKind”: “DATE”} } } ] } }
A field or a column.
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A table type
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Search space for string and enum.
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The rows to insert.
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An array of errors for rows that were not inserted.
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Deletes the table specified by tableId from the dataset. If the table contains data, all the data will be deleted.
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[Optional] The categories attached to this field, used for field-level access control.
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Gets the specified table resource by table ID. This method does not return the data in the table, it only returns the table resource, which describes the structure of this table.
Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
Creates a new, empty table in the dataset.
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Lists all tables in the specified dataset. Requires the READER dataset role.
Tables in the requested dataset.
Additional details for a view.
A builder providing access to all methods supported on
table resources.
It is not used directly, but through the
Bigquery hub.
Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource. This method supports patch semantics.
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Sets the access control policy on the specified resource. Replaces any existing policy. Can return NOT_FOUND, INVALID_ARGUMENT, and PERMISSION_DENIED errors.
Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may “fail open” without warning.
Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource.
Streams data into BigQuery one record at a time without needing to run a load job. Requires the WRITER dataset role.
Retrieves table data from a specified set of rows. Requires the READER dataset role.
A builder providing access to all methods supported on
tabledata resources.
It is not used directly, but through the
Bigquery hub.
Request message for TestIamPermissions method.
Response message for TestIamPermissions method.
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Options used in model training.
Information about a single training query run for the model.
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This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION … ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
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