Release Version 2.47
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This release note also includes the fixes provided in all the minor releases since 2.46.
To know the complete list of features available for early adoption before these are made generally available to all customers, read our Early Access page.
In this Release
New and Changed Features
Sources
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Automatic Handling of Timeout Errors in NetSuite ERP (Added in Release 2.46.1)
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Enhanced the handling of timeout errors encountered while fetching data from NetSuite ERP. Hevo fetches data in pages, requesting 1000 records per page by default. NetSuite enforces a time limit for processing these requests. If the records are not returned within this timeframe, a timeout error occurs. Previously, resolving this issue required contacting Hevo Support to manually reduce the page size.
With this enhancement, when a timeout error is encountered:
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Hevo automatically reduces the page size by 50% and retries the request.
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If the timeout persists, the page size is further reduced by 50%. This process continues until the request succeeds.
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The minimum supported page size is 10 records.
Once data is successfully fetched with a reduced page size, Hevo continues using that page size for ingesting data from all the objects in the Pipeline. This change eliminates manual intervention and ensures seamless data ingestion when timeout errors occur.
Note: Reducing the page size increases the number of API calls made to NetSuite. If your Source contains large volumes of data, this may increase data ingestion time.
This enhancement applies to all new and existing Pipelines.
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Improved Flattening of Nested Fields in NetSuite ERP (Added in Release 2.46.1)
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Enhanced how nested fields are flattened for objects configured with the Advanced Search poll strategy. Previously, when a field contained a JSON value, Hevo flattened only the first two layers of data. Any additional data was loaded as JSON in the corresponding Destination column. As a result, data from these additional layers had to be manually extracted for analysis.
With this enhancement, Hevo now flattens all nested layers within the JSON value and loads the data into the corresponding Destination column. This ensures that data from all layers is directly available for querying and analysis, eliminating the need to manually extract data from JSON. To enable the enhancement for your new and existing Pipelines, contact Hevo Support.
Note: For existing Pipelines, if a nested field contains more than two layers of data and you want those additional layers to be flattened, first enable the enhancement and then restart the historical load for the object.
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Fixes and Improvements
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Handling Ingestion Failure Issue in Front (Fixed in Release 2.46.1)
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Fixed an issue where ingestion for certain objects could get stuck when an API request made by Hevo referenced an inbox record that no longer existed or was inaccessible. This issue occurred when Hevo attempted to fetch an inbox that had been deleted or renamed. In such cases, the Front API returned a
404 "Unknown inbox ID"error, causing the ingestion to fail.With this fix, Hevo now skips inboxes that return this error and continues processing the remaining records, preventing the Pipeline from getting stuck and allowing ingestion to proceed normally.
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Handling Missing Data Issue in Google Analytics 4 (Fixed in Release 2.46.3)
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Fixed an issue where some data was not fully ingested for GA4 Pipelines, particularly when the dataset being fetched exceeded 100,000 records. The GA4 API returns data in batches, with each API request fetching up to 100,000 records. Due to an incorrect calculation of the last fetched record, Hevo assumed all data had been retrieved after the first batch and stopped the ingestion process. This caused the remaining records to be skipped, resulting in missing data in your Destination.
With this fix, Hevo now correctly tracks the last fetched record and continues fetching subsequent batches until all available records are ingested, ensuring complete data ingestion. This fix applies to all new and existing Pipelines, regardless of dataset size. For existing Pipelines, if your GA4 dataset contains more than 100,000 records for a given object and you observe missing data in your Destination, you must restart the historical load for the object to ensure all data is ingested.
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Documentation Updates
The following pages have been created, enhanced, or removed in Release 2.47: