Docs.rs
google-cloud-bigquery-0.14.0
google-cloud-bigquery 0.14.0
Docs.rs crate page
MIT
Links
Repository
crates.io
Source
Owners
coryan
codyoss
github:googleapis:google-cloud-rust-crate-publishers
Dependencies
anyhow ^1.0
normal
arrow ^53.1
normal
async-trait ^0.1
normal
backon ^1.2
normal
base64 ^0.21
normal
bigdecimal ^0.4
normal
google-cloud-auth ^0.17
normal
optional
google-cloud-gax ^0.19.2
normal
google-cloud-googleapis ^0.16.0
normal
google-cloud-token ^0.1.2
normal
num-bigint ^0.4
normal
reqwest ^0.12.4
normal
reqwest-middleware ^0.4
normal
serde ^1.0
normal
serde_json ^1.0
normal
thiserror ^1.0
normal
time ^0.3
normal
tokio ^1.32
normal
tracing ^0.1
normal
base64-serde ^0.7
dev
ctor ^0.1.26
dev
serial_test ^3.1
dev
tokio ^1.32
dev
tokio-util ^0.7
dev
tracing-subscriber ^0.3.17
dev
Versions
54.97%
of the crate is documented
Go to latest version
Platform
x86_64-unknown-linux-gnu
Feature flags
docs.rs
About docs.rs
Badges
Builds
Metadata
Shorthand URLs
Download
Rustdoc JSON
Build queue
Privacy policy
Rust
Rust website
The Book
Standard Library API Reference
Rust by Example
The Cargo Guide
Clippy Documentation
google_
cloud_
bigquery
0.14.0
Module model
Module Items
Modules
Structs
Enums
In google_
cloud_
bigquery::
http
google_cloud_bigquery
::
http
Module
model
Copy item path
Source
Modules
§
delete
get
list
patch
Structs
§
Aggregate
Classification
Metrics
Arima
Coefficients
Arima
Fitting
Metrics
Arima
Forecasting
Metrics
Arima
Model
Info
Arima
Order
Arima
Result
Arima
Single
Model
Forecasting
Metrics
Binary
Classification
Metrics
Binary
Confusion
Matrix
Categorical
Value
Category
Count
Cluster
Cluster
Info
Clustering
Metrics
Confusion
Matrix
Data
Split
Result
Dimensionality
Reduction
Metrics
Double
Candidates
Double
Range
Entry
Explanation
Feature
Value
Global
Explanation
Hparam
Search
Spaces
Hparam
Tuning
Trial
IntArray
IntArray
Hparam
Search
Space
IntCandidates
IntRange
Iteration
Result
Model
Model
Reference
Multi
Class
Classification
Metrics
Principal
Component
Info
Ranking
Metrics
Regression
Metrics
Remote
Model
Info
Row
String
Hparam
Search
Space
Training
Options
Training
Run
Enums
§
Booster
Type
Dart
Normalize
Type
Data
Frequency
Data
Split
Method
Distance
Type
Double
Hparam
Search
Space
Evaluation
Metrics
Feature
Value
Type
Feedback
Type
Holiday
Region
Hparam
Tuning
Objective
IntHparam
Search
Space
Kmeans
Initialization
Method
Learn
Rate
Strategy
Loss
Type
Model
Type
Optimization
Strategy
Remote
Service
Type
Seasonal
Period
Type
Test
Method
Tree
Method
Trial
Status