How Does a Million-Level Number Verification System Support Large-Scale Tasks? A Case Study of KK-DATA

When an overseas team needs to batch verify 1 million or even several million Telegram or WhatsApp numbers, the stability and performance of the number verification system directly determine project success or failure. Numbers come from diverse sources (group collections, number segment generation, purchased lists), but once a file contains hundreds of thousands of lines, common scripts or entry-level tools often suffer from timeouts, freezes, and result loss. This article analyzes the core challenges of million-level verification tasks from a system architecture perspective, and uses KK-DATA as an example to illustrate how capabilities like intelligent splitting, queue mechanisms, and deduplication repositories prevent large-scale detection from spiraling out of control. Finally, we will objectively compare mainstream verification tools such as 007data and THData in terms of task limits and concurrency strategies, helping you choose the best million-level verification system.

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Challenges of Million-Level Verification Tasks: System Performance and Data Integrity

Batch verification of 1 million numbers is not simply sending a file line by line to an API. Three typical problems arise:

• Stability: A single long connection is prone to timeouts, and network jitter can cause some numbers to be missed. If a script implements retries on its own, code complexity skyrockets.
• Speed and Concurrency: Platform APIs often have rate limits; brute-force concurrency leads to bans or throttling. Intelligent request interval distribution is needed while maintaining high throughput.
• Result Consistency: Tasks may span several hours. If the network drops or the process crashes midway, are already tested parts lost? Can resumable uploads be supported?

Small tools or generic scripts often cannot handle these scenarios. Professional verification systems address them from three dimensions: task splitting, queue scheduling, and state persistence.

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How Does KK-DATA Achieve Stable Execution of 1 Million Tasks? – Task Splitting and Queue Mechanism

KK-DATA encapsulates complex scheduling logic on the backend. Users only need to upload a number file, and the system automatically performs intelligent splitting, asynchronous queuing, and resumable uploads.

Single Task Limit and Intelligent Splitting Logic

KK-DATA supports a maximum of approximately 1 million numbers per single verification task. Why set this limit? From an engineering perspective:

• Over 1 million numbers, the overhead of file parsing, progress tracking, and result aggregation increases linearly, potentially causing sluggish console responses.
• 1 million is a reasonable threshold; it allows mainstream detection (e.g., Telegram activation checks) to complete within a few hours (approximately 2–4 hours) while maintaining system load balance.

For data exceeding 1 million, the platform offers flexibility: you can split into multiple tasks or contact customer service @kkdata_cc for a custom solution. More importantly, the backend automatically splits large tasks into batches. Each batch independently queues, verifies, and records states. This way, even if a temporary exception occurs in one batch, only that batch retries without affecting others.

Real-Time Task Progress Feedback and Automatic Retry

After submitting a task in the console, you will see a clear progress bar showing “Checked X / Total Y”. This is thanks to real-time status reporting for each batch. If a number times out due to network fluctuations, the system automatically retries (up to 3 times) without requiring additional manual operations.

Deduction Timing: The balance is deducted only after the task is fully completed, based on the actual number of successful checks. Tasks stopped manually or that fail midway incur no charges. This avoids the common pain point of “partial timeouts causing repeated uploads and repeated deductions.”

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Notification Mechanism and Export Capabilities: Keeping Large-Scale Verification Under Control

Million-level tasks often take hours to complete. Constantly refreshing the console is neither practical nor time-efficient. KK-DATA allows you to “submit and forget” through the following features.

Telegram Notification on Completion, Avoid Repeated Refreshing

After binding your Telegram account in the console settings, you will receive a message from the official bot (@kkdata_cc_bot) as soon as the task finishes, containing a summary of results:

• Total checked numbers
• Quantity per category (activated/valid/active/gender identified)
• A direct link to the download page

This lets you know the task status immediately on your mobile phone, without needing to log into a computer.

Multi-format Export and Data Deduplication Repository

Results can be exported in CSV and TXT formats. More practically, you can export filtered by detection results:

• Export only “Telegram activated” numbers
• Export only “Active in last 7 days” numbers
• Export only “Male/Female” identification results

Additionally, the data deduplication repository automatically records all verified numbers. The next time you upload the same numbers (possibly from another collected file), the system identifies them as “already verified” and skips them, without charging again. This saves significant balances in multi-batch expansion scenarios.

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Competitor Comparison: Performance of 007data, THData and Other Systems in Large-Scale Tasks

To help overseas teams make informed choices, the following table compares key differences among several mainstream verification platforms for million-level tasks. All data is based on public documentation and community feedback; please refer to each platform’s official website for real-time information.

Task Submission Limits and Concurrency Restrictions

Feature	KK-DATA	007data	THData
Single task limit	Approx. 1 million	Common 500k (adjustable with some plans)	Common 300k
Concurrent tasks	Supports multiple tasks simultaneously; queue auto-schedules	Typically limited to 1-2 concurrent tasks	Customized per plan
Task splitting mechanism	Automatic intelligent splitting, no manual effort	Batch size can be manually set, requires some experience	Users must split files manually
Resumable upload	Supported; failed batches auto-retry	Supported in some scenarios; requires manual resubmission	Weak support

From the table, KK-DATA’s higher task limit and automatic splitting better meet the needs of large-scale users, reducing manual intervention.

Billing Models and Data Accuracy Differences

• Billing Model: KK-DATA adopts a fully per-item deduction model with no fixed plans, paying only for what you use, avoiding wasted monthly fees. 007data and THData offer plan packages; overages are charged per item or require plan upgrades.
• Active Determination Criteria: Each platform defines “active” differently (e.g., session in 7 days vs. 30 days). KK-DATA supports specifying active windows (7/15/30 days), while others are usually fixed at 7 or 15 days, offering slightly less flexibility.
• Gender Recognition Accuracy: Mostly based on avatar recognition, not 100% accurate. KK-DATA labels results in the console as “Based on avatar recognition” and allows filtering by gender during export.

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Best Practices: How to Plan a Million-Level Verification Task (Number Preparation, Task Splitting, Budget Control)

Based on actual operational experience, here is a practical large-scale verification workflow:

1. Clean and Deduplicate Number Sources
   Use Excel, Notepad++, or dedicated deduplication tools to remove duplicates. The more duplicate numbers, the more wasted detection fees. Also check that the format includes country codes (e.g., 8613800138000) and avoid invalid characters.

2. Test with a Small Sample Before Large-Scale Submission
   It is recommended to test with 5,000–10,000 numbers first to confirm platform response, detection types, and export results meet expectations. After testing, submit batches of 100,000–200,000 numbers at a time. This way, any anomalies incur manageable losses.

3. Use Deduplication Repository to Avoid Repeated Detection
   If your numbers come from multiple groups or number segment generation, first upload all numbers and run a “global deduplication” task (free) to keep only undetected numbers before submitting verification tasks. KK-DATA’s deduplication repository handles this automatically.

4. Budget Estimation and Batch Deduction
   Log into the console to check the current unit price for the detection type (prices vary by platform and type). For example, checking 1 million Telegram activations, estimated cost = 1 million × unit price. Actual deduction only applies to successfully checked numbers, deducted from the recharged balance. An estimated cost is displayed before task submission; ensure sufficient balance.

5. Perform Tasks Separated by Platform and Type
   If you need to check both Telegram and WhatsApp, submit them as two separate tasks; do not mix them in one file. Detection logic and unit prices differ by platform, and mixing will confuse console statistics.

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Frequently Asked Questions

Q: What is the maximum number of numbers KK-DATA can verify at one time?
A: A single verification task supports up to approximately 1 million numbers. If the number exceeds 1 million, it is recommended to split into multiple tasks or contact customer service for a custom plan.

Q: Which is better for million-level verification, 007data or KK-DATA?
A: Both support large-scale tasks, but 007data’s task limit is typically around 500k, while KK-DATA’s limit is about 1 million. They differ in notifications, exports, and deduplication repositories. It is advisable to try both based on your budget, detection types, and export needs. Specific prices are subject to each platform’s official website.

Q: How long does it take to check 1 million Telegram numbers? How much does it cost?
A: Time depends on detection type (activation-only about 2–4 hours; active detection takes longer) and platform load. Cost is per number; unit prices vary by detection type. Check real-time prices in the console; an estimated cost is shown before submission.

Q: How can I avoid wasteful repeated detection fees after large-scale verification?
A: KK-DATA provides a data deduplication repository. All verified numbers are automatically recorded. When you upload the same numbers again, the system skips them and displays “Already checked” without charging again.

Q: What are the differences between THData and KK-DATA in export capabilities?
A: Both support CSV/TXT export. KK-DATA additionally supports categorized export by detection results (e.g., only valid numbers, only active numbers) and integrates with the deduplication repository. For specific differences, it is recommended to try both firsthand.

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If you are planning a million-level verification task, welcome to log into the KK-DATA Console and start experiencing it. Refer to the documentation for task splitting guidance, or contact Telegram support @kkdata_cc for a custom plan.