15 releases (breaking)
0.13.1 | Sep 22, 2024 |
---|---|
0.12.0 | Jul 12, 2024 |
0.7.0 | Feb 27, 2024 |
0.6.0 | Dec 28, 2023 |
0.3.0 | Jul 21, 2023 |
#2027 in Web programming
5,011 downloads per month
Used in google-cloud-default
8MB
145K
SLoC
google-cloud-bigquery
Google Cloud Platform BigQuery Client library.
Installation
[dependencies]
google-cloud-bigquery = version
Quick Start
CreateClient
The function create()
will try and read the credentials from a file specified in the environment variable GOOGLE_APPLICATION_CREDENTIALS
, GOOGLE_APPLICATION_CREDENTIALS_JSON
or
from a metadata server.
This is also described in google-cloud-auth
use google_cloud_bigquery::client::{ClientConfig, Client};
async fn run() {
let (config, project_id) = ClientConfig::new_with_auth().await.unwrap();
let client = Client::new(config).await.unwrap();
}
When you can't use the gcloud
authentication but you have a different way to get your credentials (e.g a different environment variable)
you can parse your own version of the 'credentials-file' and use it like that:
use google_cloud_auth::credentials::CredentialsFile;
// or google_cloud_bigquery::client::google_cloud_auth::credentials::CredentialsFile
use google_cloud_bigquery::client::{ClientConfig, Client};
async fn run(cred: CredentialsFile) {
let (config, project_id) = ClientConfig::new_with_credentials(cred).await.unwrap();
let client = Client::new(config).await.unwrap();
}
Read Data
Query
use google_cloud_bigquery::http::job::query::QueryRequest;
use google_cloud_bigquery::query::row::Row;
use google_cloud_bigquery::client::Client;
async fn run(client: &Client, project_id: &str) {
let request = QueryRequest {
query: "SELECT * FROM dataset.table".to_string(),
..Default::default()
};
let mut iter = client.query::<Row>(project_id, request).await.unwrap();
while let Some(row) = iter.next().await.unwrap() {
let col1 = row.column::<String>(0);
let col2 = row.column::<Option<String>>(1);
}
}
Read Table
use google_cloud_bigquery::storage::row::Row;
use google_cloud_bigquery::client::Client;
use google_cloud_bigquery::http::table::TableReference;
async fn run(client: &Client, project_id: &str) {
let table = TableReference {
project_id: project_id.to_string(),
dataset_id: "dataset".to_string(),
table_id: "table".to_string(),
};
let mut iter = client.read_table::<Row>(&table, None).await.unwrap();
while let Some(row) = iter.next().await.unwrap() {
let col1 = row.column::<String>(0);
let col2 = row.column::<Option<String>>(1);
}
}
Values
Default supported types to decode by row.column::<T>()
are
- String (for STRING)
- bool (for BOOL)
- i64 (for INT64)
- f64 (for FLOAT)
- bigdecimal::BigDecimal (for NUMERIC, BIGNUMERIC)
- Vec (for BINARY)
- time::OffsetDateTime (for TIMESTAMP)
- time::Date (for DATE)
- time::Time (for TIME)
- T: StructDecodable (for STRUCT)
- Option (for all NULLABLE)
- Vec (for ARRAY)
Insert Data
Table data API
use google_cloud_bigquery::http::tabledata::insert_all::{InsertAllRequest, Row};
use google_cloud_bigquery::client::Client;
#[derive(serde::Serialize)]
pub struct TestData {
pub col1: String,
#[serde(with = "time::serde::rfc3339::option")]
pub col_timestamp: Option<time::OffsetDateTime>,
// Must serialize as base64 string to insert binary data
// #[serde(default, with = "Base64Standard")]
pub col_binary: Vec<u8>
}
async fn run(client: &Client, project_id: &str, data: TestData) {
let data1 = Row {
insert_id: None,
json: data,
};
let request = InsertAllRequest {
rows: vec![data1],
..Default::default()
};
let result = client.tabledata().insert(project_id, "dataset", "table", &request).await.unwrap();
let error = result.insert_errors;
}
Run loading job
ex) Loading CSV data from GCS
use google_cloud_bigquery::client::Client;
use google_cloud_bigquery::http::bigquery_job_client::BigqueryJobClient;
use google_cloud_bigquery::http::job::cancel::CancelJobRequest;
use google_cloud_bigquery::http::job::get::GetJobRequest;
use google_cloud_bigquery::http::job::get_query_results::GetQueryResultsRequest;
use google_cloud_bigquery::http::job::query::QueryRequest;
use google_cloud_bigquery::http::job::{Job, JobConfiguration, JobConfigurationLoad, JobReference, JobState, JobType, OperationType, TrainingType, WriteDisposition};
use google_cloud_bigquery::http::table::{SourceFormat, TableReference};
async fn run(client: &Client, project_id: &str, data_path: &str) {
let job = Job {
job_reference: JobReference {
project_id: project_id.to_string(),
job_id: "job_id".to_string(),
location: Some("asia-northeast1".to_string())
},
// CSV configuration
configuration: JobConfiguration {
job: JobType::Load(JobConfigurationLoad {
source_uris: vec![format!("gs://{}.csv",data_path)],
source_format: Some(SourceFormat::Csv),
field_delimiter: Some("|".to_string()),
encoding: Some("UTF-8".to_string()),
skip_leading_rows: Some(0),
autodetect: Some(true),
write_disposition: Some(WriteDisposition::WriteTruncate),
destination_table: TableReference {
project_id: project_id.to_string(),
dataset_id: "dataset".to_string(),
table_id: "table".to_string(),
},
..Default::default()
}),
..Default::default()
},
..Default::default()
};
// Run job
let created = client.job().create(&job).await.unwrap();
// Check status
assert!(created.status.errors.is_none());
assert!(created.status.error_result.is_none());
assert!(created.status.state == JobState::Running || created.status.state == JobState::Done);
}
Features
HTTP API
Streaming
Dependencies
~30–47MB
~875K SLoC