csv-dwh v1.0.5
csv-dwh
๐คจ wat.
local csv/json file โ โ๏ธ data warehouse table
schematize and bulk insert local CSV or JSON files to various data warehouses... currently supporting BigQuery, Snowflake, and Redshift!
๐ tldr;
this module can be used in two ways:
- as a CLI, standalone script via:
npx csv-dwh file.csv --options- as a module in code via
//for esm:
import csvDwh from "csv-dwh";
//for cjs:
const csvDwh = require("csv-dwh");
const result = await csvDwh({
warehouse: "bigquery",
csv_file: "./path/to/data.csv",
});๐ฟ Demo
๐ป CLI usage
npx csv-dwh@latest ./pathToDatawhen running as a CLI, pathToData should be a .csv or .json file.
when using the CLI, supply params as options in the form --option value, for example your warehouse configuration:
npx csv-dwh ./data.csv --warehouse bigquery --bigquery_dataset my_dataset --table_name my_tablemany other options are available; to see a full list of CLI params, use the --help option:
npx csv-dwh --helpalternatively, you may use an .env configuration file to provide your configuration details.
๐ module usage
install csv-dwh as a dependency in your project
npm i csv-dwh --savethen use it in code:
const csvDwh = require("csv-dwh");
const config = {
warehouse: "bigquery",
csv_file: "./path/to/data.csv",
bigquery_dataset: "my_dataset",
// other options...
};
const result = await csvDwh(config);
console.log(result);
/*
{
version: '1.0.0',
PARAMS: { ... },
results: [ ... ],
e2eDuration: 1234,
clockTime: '00:20',
recordsPerSec: 500,
totalRows: 10000,
intermediateSchema: [ ... ]
}
*/read more about config below.
๐ฃ๏ธ configuration
when using csv-dwh, you will pass in a configuration object. The object should include settings specific to the warehouse you are targeting.
๐ข warehouse
The warehouse option specifies the target data warehouse. It can be one of "bigquery", "snowflake", or "redshift".
๐ authentication
Each warehouse requires specific authentication details:
BigQuery:
const config = {
warehouse: "bigquery",
// optional: path to your Google Cloud service account key file
bigquery_keyfile: "/path/to/keyfile.json",
};note: if no bigquery_keyfile is provided, the module will attempt to use Application Default Credentials.
Snowflake:
const config = {
warehouse: "snowflake",
snowflake_account: "your_account",
snowflake_user: "your_user",
snowflake_password: "your_password",
snowflake_database: "your_database",
snowflake_schema: "your_schema",
snowflake_warehouse: "your_warehouse",
snowflake_role: "your_role",
};Redshift:
const config = {
warehouse: "redshift",
redshift_workgroup: "your_workgroup",
redshift_database: "your_database",
redshift_access_key_id: "your_access_key_id",
redshift_secret_access_key: "your_secret_access_key",
redshift_region: "your_region",
redshift_schema_name: "your_schema",
};๐ค environment variables:
You can also provide the configuration details using a .env file:
# bigquery
bigquery_project=my-gcp-project
bigquery_dataset=my_dataset
bigquery_table=my_table
bigquery_keyfile=myfile.json
bigquery_service_account=my-service-acct@foo.com
bigquery_service_account_pass=****
# snowflake
snowflake_account=accountId
snowflake_user=foo
snowflake_password=****
snowflake_database=DEMO
snowflake_schema=PUBLIC
snowflake_warehouse=COMPUTE_WH
snowflake_role=ACCOUNTADMIN
# redshift
redshift_workgroup=my-workgroup
redshift_database=my_db
redshift_access_key_id=my-key
redshift_secret_access_key=my-secret
redshift_schema_name=public
redshift_region=us-east-2
# optional
redshift_session_token=none^ ensure the .env file is in the root of your project, and the module will automatically read the configuration details from it; no need to pass them in as options.
๐ options
Additional options can be provided to customize the behavior of the module:
const config = {
batch_size: 1000, // number of records per batch
dry_run: false, // if true, does not actually upload data
verbose: true, // if true, logs detailed information
};thanks for reading.
found a bug? have an idea? let me know