csv-dwh

🤨 wat.

local csv/json file → ☁️ data warehouse table

schematize and bulk insert local CSV or JSON files to various data warehouses... currently supporting BigQuery, Snowflake, and Redshift!

👔 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",
});

🍿 Demo

💻 CLI usage

npx csv-dwh@latest ./pathToData

when 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_table

many other options are available; to see a full list of CLI params, use the --help option:

npx csv-dwh --help

alternatively, you may use an .env configuration file to provide your configuration details.

🔌 module usage

install csv-dwh as a dependency in your project

npm i csv-dwh --save

then 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.

🗣️ configuration

when using csv-dwh, you will pass in a configuration object. The object should include settings specific to the warehouse you are targeting.

🏢 warehouse

The warehouse option specifies the target data warehouse. It can be one of "bigquery", "snowflake", or "redshift".

🔐 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",
};

🤖 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
[email protected]
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.

🎛 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