Architecting Bulk WHOIS Data Ingestion
Processing hundreds of thousands of domain records daily requires efficient database architecture and high-throughput ingestion pipelines. SpiralBig packages daily and historical archives in industry-standard CSV, JSON, and pre-formatted MySQL .sql dumps.
Recommended MySQL Table Schema
CREATE TABLE `daily_whois_leads` (
`id` BIGINT UNSIGNED NOT NULL AUTO_INCREMENT,
`domain_name` VARCHAR(255) NOT NULL,
`registrar_name` VARCHAR(255) DEFAULT NULL,
`creation_date` DATETIME DEFAULT NULL,
`expiration_date` DATETIME DEFAULT NULL,
`nameservers` TEXT DEFAULT NULL,
`owner_name` VARCHAR(255) DEFAULT NULL,
`organization` VARCHAR(255) DEFAULT NULL,
`city` VARCHAR(128) DEFAULT NULL,
`state` VARCHAR(128) DEFAULT NULL,
`country` VARCHAR(3) DEFAULT NULL,
`email` VARCHAR(191) DEFAULT NULL,
`phone` VARCHAR(64) DEFAULT NULL,
`created_at` TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (`id`),
UNIQUE KEY `idx_domain` (`domain_name`),
KEY `idx_country_created` (`country`, `creation_date`),
KEY `idx_email` (`email`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci;High-Speed Bulk Ingestion with Python
Using Python and LOAD DATA INFILE allows ingesting a 150,000-row daily CSV file in under 3.5 seconds:
import pymysql
conn = pymysql.connect(
host='localhost',
user='db_user',
password='secret_password',
database='domain_intelligence',
local_infile=True
)
cursor = conn.cursor()
load_query = """
LOAD DATA LOCAL INFILE 'daily_whois_feed.csv'
INTO TABLE daily_whois_leads
FIELDS TERMINATED BY ',' ENCLOSED BY '"'
LINES TERMINATED BY '\n'
IGNORE 1 LINES
(domain_name, registrar_name, creation_date, expiration_date, nameservers, owner_name, organization, city, state, country, email, phone);
"""
cursor.execute(load_query)
conn.commit()
print("Ingestion complete.")Daily Automated FTP Sync
Every active SpiralBig subscription includes direct FTP credentials. Developers can configure a simple cron job to synchronize the latest daily archive at 08:05 UTC every morning without manual dashboard logins.