googleapis
Version:
Google APIs Client Library for Node.js
905 lines • 556 kB
TypeScript
import { OAuth2Client, JWT, Compute, UserRefreshClient, BaseExternalAccountClient, GaxiosResponseWithHTTP2, GoogleConfigurable, MethodOptions, StreamMethodOptions, GlobalOptions, GoogleAuth, BodyResponseCallback, APIRequestContext } from 'googleapis-common';
import { Readable } from 'stream';
export declare namespace bigquery_v2 {
export interface Options extends GlobalOptions {
version: 'v2';
}
interface StandardParameters {
/**
* Auth client or API Key for the request
*/
auth?: string | OAuth2Client | JWT | Compute | UserRefreshClient | BaseExternalAccountClient | GoogleAuth;
/**
* V1 error format.
*/
'$.xgafv'?: string;
/**
* OAuth access token.
*/
access_token?: string;
/**
* Data format for response.
*/
alt?: string;
/**
* JSONP
*/
callback?: string;
/**
* Selector specifying which fields to include in a partial response.
*/
fields?: string;
/**
* API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.
*/
key?: string;
/**
* OAuth 2.0 token for the current user.
*/
oauth_token?: string;
/**
* Returns response with indentations and line breaks.
*/
prettyPrint?: boolean;
/**
* Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.
*/
quotaUser?: string;
/**
* Legacy upload protocol for media (e.g. "media", "multipart").
*/
uploadType?: string;
/**
* Upload protocol for media (e.g. "raw", "multipart").
*/
upload_protocol?: string;
}
/**
* BigQuery API
*
* A data platform for customers to create, manage, share and query data.
*
* @example
* ```js
* const {google} = require('googleapis');
* const bigquery = google.bigquery('v2');
* ```
*/
export class Bigquery {
context: APIRequestContext;
datasets: Resource$Datasets;
jobs: Resource$Jobs;
models: Resource$Models;
projects: Resource$Projects;
routines: Resource$Routines;
rowAccessPolicies: Resource$Rowaccesspolicies;
tabledata: Resource$Tabledata;
tables: Resource$Tables;
constructor(options: GlobalOptions, google?: GoogleConfigurable);
}
/**
* Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows.
*/
export interface Schema$AggregateClassificationMetrics {
/**
* Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
*/
accuracy?: number | null;
/**
* The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
*/
f1Score?: number | null;
/**
* Logarithmic Loss. For multiclass this is a macro-averaged metric.
*/
logLoss?: number | null;
/**
* Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
*/
precision?: number | null;
/**
* Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
*/
recall?: number | null;
/**
* Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
*/
rocAuc?: number | null;
/**
* Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classification models this is the confidence threshold.
*/
threshold?: number | null;
}
/**
* Represents privacy policy associated with "aggregation threshold" method.
*/
export interface Schema$AggregationThresholdPolicy {
/**
* Optional. The privacy unit column(s) associated with this policy. For now, only one column per data source object (table, view) is allowed as a privacy unit column. Representing as a repeated field in metadata for extensibility to multiple columns in future. Duplicates and Repeated struct fields are not allowed. For nested fields, use dot notation ("outer.inner")
*/
privacyUnitColumns?: string[] | null;
/**
* Optional. The threshold for the "aggregation threshold" policy.
*/
threshold?: string | null;
}
/**
* Input/output argument of a function or a stored procedure.
*/
export interface Schema$Argument {
/**
* Optional. Defaults to FIXED_TYPE.
*/
argumentKind?: string | null;
/**
* Set if argument_kind == FIXED_TYPE.
*/
dataType?: Schema$StandardSqlDataType;
/**
* Optional. Whether the argument is an aggregate function parameter. Must be Unset for routine types other than AGGREGATE_FUNCTION. For AGGREGATE_FUNCTION, if set to false, it is equivalent to adding "NOT AGGREGATE" clause in DDL; Otherwise, it is equivalent to omitting "NOT AGGREGATE" clause in DDL.
*/
isAggregate?: boolean | null;
/**
* Optional. Specifies whether the argument is input or output. Can be set for procedures only.
*/
mode?: string | null;
/**
* Optional. The name of this argument. Can be absent for function return argument.
*/
name?: string | null;
}
/**
* Arima coefficients.
*/
export interface Schema$ArimaCoefficients {
/**
* Auto-regressive coefficients, an array of double.
*/
autoRegressiveCoefficients?: number[] | null;
/**
* Intercept coefficient, just a double not an array.
*/
interceptCoefficient?: number | null;
/**
* Moving-average coefficients, an array of double.
*/
movingAverageCoefficients?: number[] | null;
}
/**
* ARIMA model fitting metrics.
*/
export interface Schema$ArimaFittingMetrics {
/**
* AIC.
*/
aic?: number | null;
/**
* Log-likelihood.
*/
logLikelihood?: number | null;
/**
* Variance.
*/
variance?: number | null;
}
/**
* Model evaluation metrics for ARIMA forecasting models.
*/
export interface Schema$ArimaForecastingMetrics {
/**
* Arima model fitting metrics.
*/
arimaFittingMetrics?: Schema$ArimaFittingMetrics[];
/**
* Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case.
*/
arimaSingleModelForecastingMetrics?: Schema$ArimaSingleModelForecastingMetrics[];
/**
* Whether Arima model fitted with drift or not. It is always false when d is not 1.
*/
hasDrift?: boolean[] | null;
/**
* Non-seasonal order.
*/
nonSeasonalOrder?: Schema$ArimaOrder[];
/**
* Seasonal periods. Repeated because multiple periods are supported for one time series.
*/
seasonalPeriods?: string[] | null;
/**
* Id to differentiate different time series for the large-scale case.
*/
timeSeriesId?: string[] | null;
}
/**
* Arima model information.
*/
export interface Schema$ArimaModelInfo {
/**
* Arima coefficients.
*/
arimaCoefficients?: Schema$ArimaCoefficients;
/**
* Arima fitting metrics.
*/
arimaFittingMetrics?: Schema$ArimaFittingMetrics;
/**
* Whether Arima model fitted with drift or not. It is always false when d is not 1.
*/
hasDrift?: boolean | null;
/**
* If true, holiday_effect is a part of time series decomposition result.
*/
hasHolidayEffect?: boolean | null;
/**
* If true, spikes_and_dips is a part of time series decomposition result.
*/
hasSpikesAndDips?: boolean | null;
/**
* If true, step_changes is a part of time series decomposition result.
*/
hasStepChanges?: boolean | null;
/**
* Non-seasonal order.
*/
nonSeasonalOrder?: Schema$ArimaOrder;
/**
* Seasonal periods. Repeated because multiple periods are supported for one time series.
*/
seasonalPeriods?: string[] | null;
/**
* The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
*/
timeSeriesId?: string | null;
/**
* The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
*/
timeSeriesIds?: string[] | null;
}
/**
* Arima order, can be used for both non-seasonal and seasonal parts.
*/
export interface Schema$ArimaOrder {
/**
* Order of the differencing part.
*/
d?: string | null;
/**
* Order of the autoregressive part.
*/
p?: string | null;
/**
* Order of the moving-average part.
*/
q?: string | null;
}
/**
* (Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results.
*/
export interface Schema$ArimaResult {
/**
* This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one.
*/
arimaModelInfo?: Schema$ArimaModelInfo[];
/**
* Seasonal periods. Repeated because multiple periods are supported for one time series.
*/
seasonalPeriods?: string[] | null;
}
/**
* Model evaluation metrics for a single ARIMA forecasting model.
*/
export interface Schema$ArimaSingleModelForecastingMetrics {
/**
* Arima fitting metrics.
*/
arimaFittingMetrics?: Schema$ArimaFittingMetrics;
/**
* Is arima model fitted with drift or not. It is always false when d is not 1.
*/
hasDrift?: boolean | null;
/**
* If true, holiday_effect is a part of time series decomposition result.
*/
hasHolidayEffect?: boolean | null;
/**
* If true, spikes_and_dips is a part of time series decomposition result.
*/
hasSpikesAndDips?: boolean | null;
/**
* If true, step_changes is a part of time series decomposition result.
*/
hasStepChanges?: boolean | null;
/**
* Non-seasonal order.
*/
nonSeasonalOrder?: Schema$ArimaOrder;
/**
* Seasonal periods. Repeated because multiple periods are supported for one time series.
*/
seasonalPeriods?: string[] | null;
/**
* The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
*/
timeSeriesId?: string | null;
/**
* The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
*/
timeSeriesIds?: string[] | null;
}
/**
* Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] \}, { "log_type": "DATA_WRITE" \}, { "log_type": "ADMIN_READ" \} ] \}, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" \}, { "log_type": "DATA_WRITE", "exempted_members": [ "user:aliya@example.com" ] \} ] \} ] \} For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts `jose@example.com` from DATA_READ logging, and `aliya@example.com` from DATA_WRITE logging.
*/
export interface Schema$AuditConfig {
/**
* The configuration for logging of each type of permission.
*/
auditLogConfigs?: Schema$AuditLogConfig[];
/**
* Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.
*/
service?: string | null;
}
/**
* Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] \}, { "log_type": "DATA_WRITE" \} ] \} This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.
*/
export interface Schema$AuditLogConfig {
/**
* Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.
*/
exemptedMembers?: string[] | null;
/**
* The log type that this config enables.
*/
logType?: string | null;
}
/**
* Options for external data sources.
*/
export interface Schema$AvroOptions {
/**
* Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
*/
useAvroLogicalTypes?: boolean | null;
}
/**
* Request message for the BatchDeleteRowAccessPoliciesRequest method.
*/
export interface Schema$BatchDeleteRowAccessPoliciesRequest {
/**
* If set to true, it deletes the row access policy even if it's the last row access policy on the table and the deletion will widen the access rather narrowing it.
*/
force?: boolean | null;
/**
* Required. Policy IDs of the row access policies.
*/
policyIds?: string[] | null;
}
/**
* Reason why BI Engine didn't accelerate the query (or sub-query).
*/
export interface Schema$BiEngineReason {
/**
* Output only. High-level BI Engine reason for partial or disabled acceleration
*/
code?: string | null;
/**
* Output only. Free form human-readable reason for partial or disabled acceleration.
*/
message?: string | null;
}
/**
* Statistics for a BI Engine specific query. Populated as part of JobStatistics2
*/
export interface Schema$BiEngineStatistics {
/**
* Output only. Specifies which mode of BI Engine acceleration was performed (if any).
*/
accelerationMode?: string | null;
/**
* Output only. Specifies which mode of BI Engine acceleration was performed (if any).
*/
biEngineMode?: string | null;
/**
* In case of DISABLED or PARTIAL bi_engine_mode, these contain the explanatory reasons as to why BI Engine could not accelerate. In case the full query was accelerated, this field is not populated.
*/
biEngineReasons?: Schema$BiEngineReason[];
}
/**
* Configuration for BigQuery tables for Apache Iceberg (formerly BigLake managed tables.)
*/
export interface Schema$BigLakeConfiguration {
/**
* Optional. The connection specifying the credentials to be used to read and write to external storage, such as Cloud Storage. The connection_id can have the form `{project\}.{location\}.{connection_id\}` or `projects/{project\}/locations/{location\}/connections/{connection_id\}".
*/
connectionId?: string | null;
/**
* Optional. The file format the table data is stored in.
*/
fileFormat?: string | null;
/**
* Optional. The fully qualified location prefix of the external folder where table data is stored. The '*' wildcard character is not allowed. The URI should be in the format `gs://bucket/path_to_table/`
*/
storageUri?: string | null;
/**
* Optional. The table format the metadata only snapshots are stored in.
*/
tableFormat?: string | null;
}
export interface Schema$BigQueryModelTraining {
/**
* Deprecated.
*/
currentIteration?: number | null;
/**
* Deprecated.
*/
expectedTotalIterations?: string | null;
}
/**
* Information related to a Bigtable column.
*/
export interface Schema$BigtableColumn {
/**
* Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. PROTO_BINARY - indicates values are encoded using serialized proto messages. This can only be used in combination with JSON type. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
*/
encoding?: string | null;
/**
* Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
*/
fieldName?: string | null;
/**
* Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
*/
onlyReadLatest?: boolean | null;
/**
* Optional. Protobuf-specific configurations, only takes effect when the encoding is PROTO_BINARY.
*/
protoConfig?: Schema$BigtableProtoConfig;
/**
* [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as `.` field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
*/
qualifierEncoded?: string | null;
/**
* Qualifier string.
*/
qualifierString?: string | null;
/**
* Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
*/
type?: string | null;
}
/**
* Information related to a Bigtable column family.
*/
export interface Schema$BigtableColumnFamily {
/**
* Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as `.`. Other columns can be accessed as a list through the `.Column` field.
*/
columns?: Schema$BigtableColumn[];
/**
* Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. PROTO_BINARY - indicates values are encoded using serialized proto messages. This can only be used in combination with JSON type. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
*/
encoding?: string | null;
/**
* Identifier of the column family.
*/
familyId?: string | null;
/**
* Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
*/
onlyReadLatest?: boolean | null;
/**
* Optional. Protobuf-specific configurations, only takes effect when the encoding is PROTO_BINARY.
*/
protoConfig?: Schema$BigtableProtoConfig;
/**
* Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
*/
type?: string | null;
}
/**
* Options specific to Google Cloud Bigtable data sources.
*/
export interface Schema$BigtableOptions {
/**
* Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
*/
columnFamilies?: Schema$BigtableColumnFamily[];
/**
* Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
*/
ignoreUnspecifiedColumnFamilies?: boolean | null;
/**
* Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
*/
outputColumnFamiliesAsJson?: boolean | null;
/**
* Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
*/
readRowkeyAsString?: boolean | null;
}
/**
* Information related to a Bigtable protobuf column.
*/
export interface Schema$BigtableProtoConfig {
/**
* Optional. The fully qualified proto message name of the protobuf. In the format of "foo.bar.Message".
*/
protoMessageName?: string | null;
/**
* Optional. The ID of the Bigtable SchemaBundle resource associated with this protobuf. The ID should be referred to within the parent table, e.g., `foo` rather than `projects/{project\}/instances/{instance\}/tables/{table\}/schemaBundles/foo`. See [more details on Bigtable SchemaBundles](https://docs.cloud.google.com/bigtable/docs/create-manage-protobuf-schemas).
*/
schemaBundleId?: string | null;
}
/**
* Evaluation metrics for binary classification/classifier models.
*/
export interface Schema$BinaryClassificationMetrics {
/**
* Aggregate classification metrics.
*/
aggregateClassificationMetrics?: Schema$AggregateClassificationMetrics;
/**
* Binary confusion matrix at multiple thresholds.
*/
binaryConfusionMatrixList?: Schema$BinaryConfusionMatrix[];
/**
* Label representing the negative class.
*/
negativeLabel?: string | null;
/**
* Label representing the positive class.
*/
positiveLabel?: string | null;
}
/**
* Confusion matrix for binary classification models.
*/
export interface Schema$BinaryConfusionMatrix {
/**
* The fraction of predictions given the correct label.
*/
accuracy?: number | null;
/**
* The equally weighted average of recall and precision.
*/
f1Score?: number | null;
/**
* Number of false samples predicted as false.
*/
falseNegatives?: string | null;
/**
* Number of false samples predicted as true.
*/
falsePositives?: string | null;
/**
* Threshold value used when computing each of the following metric.
*/
positiveClassThreshold?: number | null;
/**
* The fraction of actual positive predictions that had positive actual labels.
*/
precision?: number | null;
/**
* The fraction of actual positive labels that were given a positive prediction.
*/
recall?: number | null;
/**
* Number of true samples predicted as false.
*/
trueNegatives?: string | null;
/**
* Number of true samples predicted as true.
*/
truePositives?: string | null;
}
/**
* Associates `members`, or principals, with a `role`.
*/
export interface Schema$Binding {
/**
* The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
*/
condition?: Schema$Expr;
/**
* Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid\}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid\}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid\}.svc.id.goog[{namespace\}/{kubernetes-sa\}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid\}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain\}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `principal://iam.googleapis.com/locations/global/workforcePools/{pool_id\}/subject/{subject_attribute_value\}`: A single identity in a workforce identity pool. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id\}/group/{group_id\}`: All workforce identities in a group. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id\}/attribute.{attribute_name\}/{attribute_value\}`: All workforce identities with a specific attribute value. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id\}/x`: All identities in a workforce identity pool. * `principal://iam.googleapis.com/projects/{project_number\}/locations/global/workloadIdentityPools/{pool_id\}/subject/{subject_attribute_value\}`: A single identity in a workload identity pool. * `principalSet://iam.googleapis.com/projects/{project_number\}/locations/global/workloadIdentityPools/{pool_id\}/group/{group_id\}`: A workload identity pool group. * `principalSet://iam.googleapis.com/projects/{project_number\}/locations/global/workloadIdentityPools/{pool_id\}/attribute.{attribute_name\}/{attribute_value\}`: All identities in a workload identity pool with a certain attribute. * `principalSet://iam.googleapis.com/projects/{project_number\}/locations/global/workloadIdentityPools/{pool_id\}/x`: All identities in a workload identity pool. * `deleted:user:{emailid\}?uid={uniqueid\}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid\}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid\}?uid={uniqueid\}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid\}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid\}?uid={uniqueid\}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid\}` and the recovered group retains the role in the binding. * `deleted:principal://iam.googleapis.com/locations/global/workforcePools/{pool_id\}/subject/{subject_attribute_value\}`: Deleted single identity in a workforce identity pool. For example, `deleted:principal://iam.googleapis.com/locations/global/workforcePools/my-pool-id/subject/my-subject-attribute-value`.
*/
members?: string[] | null;
/**
* Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`. For an overview of the IAM roles and permissions, see the [IAM documentation](https://cloud.google.com/iam/docs/roles-overview). For a list of the available pre-defined roles, see [here](https://cloud.google.com/iam/docs/understanding-roles).
*/
role?: string | null;
}
export interface Schema$BqmlIterationResult {
/**
* Deprecated.
*/
durationMs?: string | null;
/**
* Deprecated.
*/
evalLoss?: number | null;
/**
* Deprecated.
*/
index?: number | null;
/**
* Deprecated.
*/
learnRate?: number | null;
/**
* Deprecated.
*/
trainingLoss?: number | null;
}
export interface Schema$BqmlTrainingRun {
/**
* Deprecated.
*/
iterationResults?: Schema$BqmlIterationResult[];
/**
* Deprecated.
*/
startTime?: string | null;
/**
* Deprecated.
*/
state?: string | null;
/**
* Deprecated.
*/
trainingOptions?: {
earlyStop?: boolean;
l1Reg?: number;
l2Reg?: number;
learnRate?: number;
learnRateStrategy?: string;
lineSearchInitLearnRate?: number;
maxIteration?: string;
minRelProgress?: number;
warmStart?: boolean;
} | null;
}
/**
* Representative value of a categorical feature.
*/
export interface Schema$CategoricalValue {
/**
* Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories.
*/
categoryCounts?: Schema$CategoryCount[];
}
/**
* Represents the count of a single category within the cluster.
*/
export interface Schema$CategoryCount {
/**
* The name of category.
*/
category?: string | null;
/**
* The count of training samples matching the category within the cluster.
*/
count?: string | null;
}
/**
* Information about base table and clone time of a table clone.
*/
export interface Schema$CloneDefinition {
/**
* Required. Reference describing the ID of the table that was cloned.
*/
baseTableReference?: Schema$TableReference;
/**
* Required. The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
*/
cloneTime?: string | null;
}
/**
* Message containing the information about one cluster.
*/
export interface Schema$Cluster {
/**
* Centroid id.
*/
centroidId?: string | null;
/**
* Count of training data rows that were assigned to this cluster.
*/
count?: string | null;
/**
* Values of highly variant features for this cluster.
*/
featureValues?: Schema$FeatureValue[];
}
/**
* Information about a single cluster for clustering model.
*/
export interface Schema$ClusterInfo {
/**
* Centroid id.
*/
centroidId?: string | null;
/**
* Cluster radius, the average distance from centroid to each point assigned to the cluster.
*/
clusterRadius?: number | null;
/**
* Cluster size, the total number of points assigned to the cluster.
*/
clusterSize?: string | null;
}
/**
* Configures table clustering.
*/
export interface Schema$Clustering {
/**
* One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. For additional information, see [Introduction to clustered tables](https://cloud.google.com/bigquery/docs/clustered-tables#limitations).
*/
fields?: string[] | null;
}
/**
* Evaluation metrics for clustering models.
*/
export interface Schema$ClusteringMetrics {
/**
* Information for all clusters.
*/
clusters?: Schema$Cluster[];
/**
* Davies-Bouldin index.
*/
daviesBouldinIndex?: number | null;
/**
* Mean of squared distances between each sample to its cluster centroid.
*/
meanSquaredDistance?: number | null;
}
/**
* Confusion matrix for multi-class classification models.
*/
export interface Schema$ConfusionMatrix {
/**
* Confidence threshold used when computing the entries of the confusion matrix.
*/
confidenceThreshold?: number | null;
/**
* One row per actual label.
*/
rows?: Schema$Row[];
}
/**
* A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration * **service_account**: indicates the service account to use to run a continuous query. If set, the query job uses the service account to access Google Cloud resources. Service account access is bounded by the IAM permissions that you have granted to the service account. Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error.
*/
export interface Schema$ConnectionProperty {
/**
* The key of the property to set.
*/
key?: string | null;
/**
* The value of the property to set.
*/
value?: string | null;
}
/**
* Information related to a CSV data source.
*/
export interface Schema$CsvOptions {
/**
* Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
*/
allowJaggedRows?: boolean | null;
/**
* Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
*/
allowQuotedNewlines?: boolean | null;
/**
* Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
*/
encoding?: string | null;
/**
* Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
*/
fieldDelimiter?: string | null;
/**
* Optional. Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when querying a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.
*/
nullMarker?: string | null;
/**
* Optional. A list of strings represented as SQL NULL value in a CSV file. null_marker and null_markers can't be set at the same time. If null_marker is set, null_markers has to be not set. If null_markers is set, null_marker has to be not set. If both null_marker and null_markers are set at the same time, a user error would be thrown. Any strings listed in null_markers, including empty string would be interpreted as SQL NULL. This applies to all column types.
*/
nullMarkers?: string[] | null;
/**
* Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
*/
preserveAsciiControlCharacters?: boolean | null;
/**
* Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
*/
quote?: string | null;
/**
* Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N \> 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
*/
skipLeadingRows?: string | null;
/**
* Optional. Controls the strategy used to match loaded columns to the schema. If not set, a sensible default is chosen based on how the schema is provided. If autodetect is used, then columns are matched by name. Otherwise, columns are matched by position. This is done to keep the behavior backward-compatible. Acceptable values are: POSITION - matches by position. This assumes that the columns are ordered the same way as the schema. NAME - matches by name. This reads the header row as column names and reorders columns to match the field names in the schema.
*/
sourceColumnMatch?: string | null;
}
/**
* Options for data format adjustments.
*/
export interface Schema$DataFormatOptions {
/**
* Optional. The API output format for a timestamp. This offers more explicit control over the timestamp output format as compared to the existing `use_int64_timestamp` option.
*/
timestampOutputFormat?: string | null;
/**
* Optional. Output timestamp as usec int64. Default is false.
*/
useInt64Timestamp?: boolean | null;
}
/**
* Statistics for data-masking.
*/
export interface Schema$DataMaskingStatistics {
/**
* Whether any accessed data was protected by the data masking.
*/
dataMaskingApplied?: boolean | null;
}
/**
* Data policy option. For more information, see [Mask data by applying data policies to a column](https://cloud.google.com/bigquery/docs/column-data-masking#data-policies-on-column/).
*/
export interface Schema$DataPolicyOption {
/**
* Data policy resource name in the form of projects/project_id/locations/location_id/dataPolicies/data_policy_id.
*/
name?: string | null;
}
/**
* Represents a BigQuery dataset.
*/
export interface Schema$Dataset {
/**
* Optional. An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER; If you patch a dataset, then this field is overwritten by the patched dataset's access field. To add entities, you must supply the entire existing access array in addition to any new entities that you want to add.
*/
access?: Array<{
condition?: Schema$Expr;
dataset?: Schema$DatasetAccessEntry;
domain?: string;
groupByEmail?: string;
iamMember?: string;
role?: string;
routine?: Schema$RoutineReference;
specialGroup?: string;
userByEmail?: string;
view?: Schema$TableReference;
}> | null;
/**
* Output only. The time when this dataset was created, in milliseconds since the epoch.
*/
creationTime?: string | null;
/**
* Required. A reference that identifies the dataset.
*/
datasetReference?: Schema$DatasetReference;
/**
* Optional. Defines the default collation specification of future tables created in the dataset. If a table is created in this dataset without table-level default collation, then the table inherits the dataset default collation, which is applied to the string fields that do not have explicit collation specified. A change to this field affects only tables created afterwards, and does not alter the existing tables. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
*/
defaultCollation?: string | null;
/**
* The default encryption key for all tables in the dataset. After this property is set, the encryption key of all newly-created tables in the dataset is set to this value unless the table creation request or query explicitly overrides the key.
*/
defaultEncryptionConfiguration?: Schema$EncryptionConfiguration;
/**
* This default partition expiration, expressed in milliseconds. When new time-partitioned tables are created in a dataset where this property is set, the table will inherit this value, propagated as the `TimePartitioning.expirationMs` property on the new table. If you set `TimePartitioning.expirationMs` explicitly when creating a table, the `defaultPartitionExpirationMs` of the containing dataset is ignored. When creating a partitioned table, if `defaultPartitionExpirationMs` is set, the `defaultTableExpirationMs` value is ignored and the table will not be inherit a table expiration deadline.
*/
defaultPartitionExpirationMs?: string | null;
/**
* Optional. Defines the default rounding mode specification of new tables created within this dataset. During table creation, if this field is specified, the table within this dataset will inherit the default rounding mode of the dataset. Setting the default rounding mode on a table overrides this option. Existing tables in the dataset are unaffected. If columns are defined during that table creation, they will immediately inherit the table's default rounding mode, unless otherwise specified.
*/
defaultRoundingMode?: string | null;
/**
* Optional. The default lifetime of all tables in the dataset, in milliseconds. The minimum lifetime value is 3600000 milliseconds (one hour). To clear an existing default expiration with a PATCH request, set to 0. Once