Limitations of Export API for Kapa.ai Events
kapa.ai exists a limit size or number of events that i can get from export api? or the only limit is the concurrency?
kapa.ai exists a limit size or number of events that i can get from export api? or the only limit is the concurrency?
Based on the knowledge sources provided, there are indeed limits on the Raw Event Export API beyond just concurrency. Here's a summary of the key limits: 1. Rate Limits:
- 60 queries per hour
- 3 queries per second
- Maximum of 100 concurrent queries2. Event Limit:
There is a limit parameter you can use to restrict the number of events returned. From the API documentation:
"Use this parameter if you want to limit the max number of events to be returned. Value cannot be over 100000."3. Date Range:
While there isn't a specific size limit mentioned, you are required to provide a date range for your export using the from_date and to_date parameters. This indirectly limits the amount of data you can retrieve in a single query.4. Event Size Limits:
Although not specific to the export API, Mixpanel has general limits on event size that would apply to exported data:
- Each event must be smaller than 1MB of uncompressed JSON
- Events can have up to 255 properties
- Property names/values are limited to 255 characters in lengthIt's worth noting that if you exceed the rate limits, you'll receive a 429 error response.Sources:
Mixpanel API Reference
Mixpanel Rate Limits
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If you don't set a limit using the limit parameter in the Raw Event Export API, Mixpanel will return all events that match your query criteria within the specified date range. However, it's important to note a few key points: 1. Default behavior: The limit parameter is optional. If you don't specify it, the API will attempt to return all matching events.2. No explicit maximum: The knowledge sources don't mention a specific maximum number of events that will be returned if no limit is set.3. Practical limitations: While there's no explicit event limit, you may still face practical limitations: - API rate limits: As mentioned earlier, there are rate limits of 60 queries per hour, 3 queries per second, and a maximum of 100 concurrent queries. These could indirectly limit the amount of data you can retrieve in a given timeframe.
- Date range: You're required to specify a date range for your export, which naturally limits the scope of your query.
- Response size: Depending on the number of events and their properties, you might encounter limitations related to the size of the API response or the time it takes to process very large datasets.4. Performance considerations: Retrieving a very large number of events without a limit could potentially impact the performance of your application or the time it takes to complete the export.It's generally a good practice to use the limit parameter or break your export into smaller date ranges if you're dealing with large volumes of data, to ensure efficient and manageable data retrieval.Mixpanel API Reference
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Based on the knowledge sources provided, the query you've shown is mostly valid, but there are a few points to consider: 1. Query Structure: The structure of your query is generally correct. You're using the required parameters project_id, from_date, and to_date, which are all valid according to the API documentation.2. Where Clause: The where parameter you're using is valid. It allows you to filter events based on a specific time range using the $time property. This is in line with the API's capabilities for filtering events.3. Time in Milliseconds: The time_in_ms parameter is correctly used. Setting it to "true" will export event timestamps with millisecond-precision, which is a valid option.4. Date Range: Your date range is valid, but keep in mind that the API interprets these dates based on your project's timezone settings. For projects created after 1 January 2023, these dates are interpreted in UTC timezone.5. Downloading Millions of Events: While your query is structured correctly to potentially retrieve millions of events, there are some important considerations: - The API doesn't have an explicit limit on the number of events you can download in a single request if you don't use the limit parameter.
- However, you should be aware of the API's rate limits: 60 queries per hour, 3 queries per second, and a maximum of 100 concurrent queries.
- Downloading millions of events in a single request might lead to very large response sizes and long processing times.To efficiently download millions of events, you might want to consider: - Breaking your request into smaller date ranges or time chunks.
- Using the limit parameter and making multiple requests if needed.
- Being mindful of the rate limits to avoid 429 errors.Mixpanel API ReferenceRemember, while the API allows for large data exports, it's generally a good practice to manage these large exports in chunks for better performance and reliability.
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Based on the information you've provided and the knowledge sources available, there are a few potential reasons why you might be seeing a growing number of events when repeatedly executing the same query: 1. Late-arriving data: Mixpanel allows for late-arriving data, which means events can be ingested after their actual occurrence time. This is particularly relevant for the Raw Event Export API. According to the Mixpanel Data Pipelines documentation, there's a latency policy for exported events of up to 24 hours end-to-end, with an additional 24-hour allowance for late-arriving data. This means that events can continue to arrive and be processed for up to 48 hours after their timestamp.2. Data Sync: If you have Data Sync enabled (which is not applicable to the Raw Event Export API but worth mentioning), it can cause variations in event counts over time. The Data Pipelines FAQ mentions that "Late-arriving data may take up to one day to sync from Mixpanel to your destination, leading to temporary discrepancies."3. Time interpretation: Ensure that you're interpreting the time consistently. For projects created after 1 January 2023, Mixpanel interprets the from_date and to_date parameters in UTC. For older projects, it uses the project's timezone. Inconsistent timezone interpretation could lead to varying results.4. Backfilled data: If there's any data backfilling happening in your project, it could cause the number of events to increase over time for the same date range.To address this issue and ensure consistent results, you could try the following: 1. Allow for a buffer period: Wait at least 48 hours after the end of your desired date range before running your export to account for late-arriving data.2. Use the time_in_ms parameter: As you're already doing, use "time_in_ms": "true" to get millisecond precision, which can help in more accurate filtering.3. Double-check timezone settings: Ensure your project's timezone settings align with your expectations and that you're consistently interpreting the times in your where clause.4. Monitor for backfills: Check if there are any data import or backfill processes running in your project that might be adding historical data.If the issue persists after considering these factors, it might be worth contacting Mixpanel support for further investigation, as there could be project-specific factors at play that aren't covered in the general documentation.Mixpanel Data Pipelines FAQ
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Based on the information provided in the knowledge sources and our previous conversation, there are several reasons why the number of events for a specific date (in this case, February 1st, 2024) might continue to change even after some time has passed: 1. Late-arriving data: As mentioned in our previous discussion, Mixpanel allows for late-arriving data. According to the Mixpanel Data Pipelines FAQ, there's a latency policy that allows for:
- Up to 24 hours end-to-end for exported events
- An additional 24-hour allowance for late-arriving data This means that events can continue to arrive and be processed for up to 48 hours after their timestamp.2. Data Sync: If you have Data Sync enabled for other pipelines (though not applicable to the Raw Event Export API), it can cause variations in event counts over time. The documentation states that "Late-arriving data may take up to one day to sync from Mixpanel to your destination, leading to temporary discrepancies."3. Backfilled data: If there's any data backfilling happening in your project, it could cause the number of events to increase over time for the same date range.4. Time interpretation: Ensure that you're interpreting the time consistently. For projects created after January 1, 2023, Mixpanel interprets the from_date and to_date parameters in UTC. For older projects, it uses the project's timezone. This could potentially lead to inconsistencies if not accounted for.To get more stable results, you could try the following: 1. Allow for a buffer period: Wait at least 48-72 hours after February 1st before running your export to account for late-arriving data.2. Use the time_in_ms parameter: Set "time_in_ms": "true" to get millisecond precision, which can help in more accurate filtering.3. Use a where clause: To ensure you're only getting events from February 1st, you could add a where clause to your query, like this:
```LBKSLBKS This will filter events based on their exact timestamp, potentially giving you more consistent results.LBKS4. Check for backfills: Verify if there are any data import or backfill processes running in your project that might be adding historical data for February 1st.LBKSIf you continue to see significant changes in event counts after implementing these suggestions, it may be worth contacting Mixpanel support for a more detailed investigation of your specific project setup and data flow.LBKS<https://docs.mixpanel.com/docs/data-pipelines#faq|Mixpanel Data Pipelines FAQ>
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