Global Bulk Number Generation Optimization Guide: Task Splitting, Performance Improvement, and Competitor Comparison

When your overseas marketing team needs to validate hundreds of thousands or even millions of phone numbers at once, bulk generation optimization becomes the core factor determining project timelines and budgets. Many operators are accustomed to putting all numbers into a single generation task, only to encounter issues like task queuing, data duplication, and soaring verification costs. This article starts with performance bottleneck analysis, provides actionable task splitting strategies and practical tips, and objectively compares platforms like 007data, thdata, to help you achieve an efficient pipeline for generating millions of numbers.

Why Bulk Generation Needs Optimization? — Where Performance Bottlenecks Lie

During bulk generation (over 100,000 records at once), performance bottlenecks typically concentrate on three levels: platform concurrency limits, network I/O blocking, and hidden consumption from duplicate data. Submitting without optimization may result in task timeouts in mild cases or significant waste of balance in severe cases.

Concurrency Cap and Queuing

Most number verification platforms impose implicit limits on the number of concurrent tasks per user. For example, some packages of 007data only allow a limited number of tasks per day; thdata also sets an upper limit on the number of numbers per single task. When you submit a request to generate 500,000 numbers at once, the platform places it in a queue and processes it sequentially. If multiple users submit similar-sized tasks at the same time, your task might wait for hours or longer. This queuing effect is especially evident in bulk scenarios.

In KK-DATA, although there is no explicit upper limit on the number of numbers per generation task (verification tasks can handle up to about 1 million at once), to achieve more stable processing speed, it is recommended to split large batches into smaller sub-tasks and leverage the platform’s multi-task parallelism to reduce overall waiting time.

Hidden Consumption from Duplicate Numbers

Another easily overlooked bottleneck is duplicate numbers. Suppose you generate two batches of US numbers: the first batch covers the range 100001–200000, and the second covers 150001–250000. The numbers 150001–200000 appear in both batches. When you later verify these numbers, the platform charges you again for the duplicates. Without a deduplication mechanism, this duplicate detection wastes nearly half your budget. This is why a data deduplication warehouse is so important in bulk optimization — it automatically merges duplicate records across batches before verification, ensuring one-time detection with no repeat charges.

Task Splitting Strategy — How to Split Millions into Efficient Sub‑tasks

To efficiently complete generation tasks involving millions of numbers, the core principle is: split small, parallelize, deduplicate. Below are two proven splitting methods.

Split by Country/Region (Recommended)

In the “Global Number Generation” module, you can select target countries and specify quantities. For example:

• USA (+1): Generate 100,000 numbers, submit Task A.
• UK (+44): Generate 50,000 numbers, submit Task B.
• Germany (+49): Generate 50,000 numbers, submit Task C.

The advantage of submitting by country is that each task runs independently without interference; delays in one country’s number range do not affect other tasks; subsequent verification can be processed per country or merged as needed, offering higher flexibility. For competitor platforms like 007data, since their packages usually limit the number of tasks per day (though not unlimited tasks), submitting by country also applies — just ensure the daily task count does not exceed the package limit. thdata has a similar mechanism but lacks a deduplication warehouse, so duplicate numbers across countries cannot be automatically merged, potentially increasing charges.

Split by Custom Number Range CSV

If you already have a target number range CSV file (e.g., purchased from carriers or third parties), you can directly upload the CSV on KK-DATA’s “Global Number Generation” page. Recommended rule: keep each CSV file between 50,000 and 100,000 rows, so you can fully utilize the platform’s concurrency while avoiding upload timeouts due to oversized files.

After splitting, you can see the status of each sub‑task in the task list: queuing, generating, completed. Once all sub‑tasks are done, merge their generation results (or directly import them into the verification module separately). Note: Do not create too many sub‑tasks (recommended no more than 20), as managing them becomes cumbersome. The platform typically supports submitting multiple tasks simultaneously, but it is advisable to keep active tasks to five or fewer to avoid being rate‑limited.

Performance Optimization Practices — Full‑Chain Acceleration from Submission to Export

Task splitting is only the first step. To truly achieve bulk generation optimization, you also need to focus on the following three practical points.

Control Concurrency and Retry Strategy

Do not submit 10 million‑level tasks all at once! A reasonable approach: submit 3–5 tasks, observe the processing speed, then add more based on queue conditions. KK-DATA provides a “Task Notification” feature — you’ll receive a Telegram notification when a task is completed. Use this mechanism: submit the next sub‑task only after you receive a notification. This effectively balances concurrency with queuing and prevents being rate‑limited due to over‑submission.

Additionally, if a task fails due to network fluctuations or system errors, do not blindly retry. First, check the failure reason: is it because the number count exceeded the limit, or a format issue? Fix it before resubmitting. When batch retrying, wait 5–10 minutes between attempts.

Reduce Invalid Data Before Verification

Bulk optimization is not limited to the generation phase; you must reduce invalid data at the source to lower subsequent verification costs. During generation, take the following measures:

• Use the “filter carrier” feature (if supported by the platform) to exclude known inactive ranges (e.g., ranges from carriers that have ceased service).
• In custom CSV files, keep only correctly formatted numbers (correct digit count, no special characters).
• Use KK-DATA’s “Global Number Generation” module to select “valid number ranges” by country, avoiding obsolete ranges.

This way, the numbers entering the verification phase are relatively clean, so the rejection rate is lower, and the number of charged verifications decreases. This strategy also applies to 007data and thdata, but the latter lack number range filtering, requiring users to clean data themselves.

Step‑by‑Step Demonstration: Implementing Million‑Level Generation Optimization on KK-DATA

Below, using the KK-DATA console as an example, we show the complete pipeline from generation to export. Suppose you need to generate and verify 500,000 active US Telegram users.

Step 1: Split Tasks
Log in to KK-DATA Console → Go to “Global Number Generation” → Select country “United States” → Enter quantity 100,000 → Click “Generate”. Repeat this operation 5 times to create 5 sub‑tasks (each with 100,000 numbers).

Step 2: Wait and Merge Results
After each sub‑task completes, export the result as a CSV or TXT file. Merge all files into one CSV, or keep multiple files if the subsequent verification task allows uploading multiple files. Note: Generation is completely free, with no charges at this stage.

Step 3: Data Deduplication
Import the merged number list into the “Data Deduplication Warehouse”. The system will automatically compare with numbers from previous tasks and remove duplicates. This step prevents the verification module from charging again for duplicate numbers.

Step 4: Submit Verification Task
In the “Number Verification” module, select “Telegram Verification”, upload the deduplicated number list, choose the detection type (e.g., “valid”, “active (30 days)”), and submit the task. After verification completes, charges are based on the actual number of verified numbers.

Step 5: Export Results
On the verification task detail page, select “Export Results”. Supports CSV, TXT, etc. You can set splitting by 100,000 numbers per file to avoid oversized files.

Through these steps, you leverage KK-DATA’s multi‑task parallelism and save verification fees via the deduplication warehouse. The total time depends on the current platform load, but is typically 2–3 times faster than submitting 500,000 numbers in a single task.

Common Misconceptions and Pitfalls — Avoid Performance Degradation

In bulk generation optimization, users often make the following mistakes, which actually degrade performance.

Misconception 1: Submitting 1 million numbers in one go
Even if the platform allows it, a single million‑level task can take a very long time (hours). If it fails midway, all progress is lost. The correct approach is to split into 100,000‑number sub‑tasks and process them in parallel.

Misconception 2: Ignoring the Deduplication Warehouse
If you do not merge duplicate numbers across different batches, verification will detect duplicates again, wasting balance. It is advisable to run the deduplication warehouse after each generation, especially when generating numbers for the same country or range multiple times.

Misconception 3: Submitting large tasks during network fluctuations
When using a VPN or proxy, unstable connections can cause upload interruptions. Submit in a stable network environment, or break tasks into smaller, multiple submissions.

Misconception 4: Mixing numbers from different countries together
Mixing numbers from multiple countries not only increases task complexity but can also confuse verification settings. For example, Telegram and WhatsApp verification have different activity windows for different countries; mixing them makes fine‑grained control impossible. Splitting by country is a better choice.

Competitor Comparison: 007data, thdata, and KK-DATA in Bulk Scenarios

To help you choose the most suitable platform for bulk optimization, an objective comparison is provided below from three dimensions: task splitting flexibility, deduplication mechanism, and billing transparency.

Dimension	007data	thdata	KK-DATA
Task Splitting Flexibility	Package-based; some packages limit daily maximum tasks; single task has an upper limit; excess needs to be split manually	Similar package model; low single-task limit; no custom CSV import	No subscription, no task limit; supports custom CSV import for free splitting
Deduplication Mechanism	No built‑in deduplication warehouse; users must handle duplicates themselves	No deduplication feature	Built‑in data deduplication warehouse, automatically merging duplicates across tasks
Billing Transparency	Pre‑purchased packages; consumption speed varies; unused quota not refunded	Similar prepaid quota; risk of expiry on unused balance	Pay‑per‑number; estimated fee shown before task; balance never expires
Generation Fee	Usually free, but packages include some verification quota	Generation is free	Generation is completely free; verification charged per number
Maximum Single Verification	Typically 100k–200k (depends on package)	Approximately 500k	Approximately 1 million

From the table, KK-DATA’s deduplication warehouse and no‑subscription pay‑per‑number model significantly reduce duplicate detection costs and control spending in bulk scenarios. While 007data and thdata have their own strengths (e.g., coverage on specific channels), they are less flexible and cost‑effective for frequent, high‑volume users compared to KK-DATA.

Summary and Next Steps

The core principles of bulk generation optimization can be summarized in three keywords: split, deduplicate, control concurrency. Split tasks to utilize parallelism, use a deduplication warehouse to eliminate duplicate charges, and control concurrency to avoid rate limiting. Regardless of which platform you use, following these principles will improve efficiency and reduce costs.

If you are looking for a platform that supports flexible splitting, has a built‑in deduplication warehouse, and charges per number without mandatory subscription, try KK-DATA:

• Go to KK-DATA Console to experience global number generation and task splitting.
• Read the usage documentation for detailed steps.
• For bulk pricing inquiries, contact customer service via Telegram @kkdata_cc.

Frequently Asked Questions

Q: In bulk generation, what is the maximum number per task?

A: Limits vary by platform. For KK-DATA, there is no explicit upper limit for generation tasks (but recommended not to exceed 100,000 for stable speed); verification tasks can handle up to about 1 million at once. Check the console page for specifics. 007data and thdata usually have lower single‑task limits and require multiple batches.

Q: Does splitting tasks increase the total cost?

A: No. Generation on KK-DATA is completely free; verification is charged per actual number. Splitting only changes how you submit, not the fee. In fact, using the deduplication warehouse reduces duplicate charges, saving money. For 007data and thdata, splitting tasks does not incur extra fees, but with limited package quotas, excessive duplicates still waste resources.

Q: Which is better for bulk number generation: 007data or KK-DATA?

A: 007data uses a package model, consuming pre‑purchased quota per number, but lacks a deduplication warehouse; concurrency limits are also stricter (some packages restrict daily task count). KK-DATA has no subscription, charges per number, and provides a deduplication warehouse, making it more suitable for users who need flexible batch sizes. The choice depends on your budget and export requirements. If you need to generate large numbers repeatedly each month, KK-DATA’s deduplication mechanism can save you 10%–30% on verification fees.

Q: Is there a way to generate numbers for multiple countries using the same API?

A: Platforms usually provide a “Global Number Generation” interface where you can select multiple countries at once. However, for stable performance, it is recommended to generate per country. KK-DATA supports three modes: by country, by custom number range, and by uploading a number range CSV. You can combine them as needed. For example, generate by country first, then merge and deduplicate, then verify all together.

Q: In bulk optimization, does the export step also require performance attention?

A: Yes. When verification results are extremely large (over 500,000 rows), exporting all at once may time out or fail. It is recommended to export in batches (e.g., split results into CSV volumes of 100,000 rows each) or use the platform’s built‑in segmented TXT export feature. KK-DATA supports multiple export formats and allows splitting by row count to avoid large file issues.