airbytehq / airbytehq/airbyte

[source-linkedin-pages] share_statistics_time_bound generates sub-24h time interval, rejected by LinkedIn API

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area/connectors autoteam community connectors/source/linkedin-pages needs-triage team/extensibility type/bug
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説明

### Connector Name

source-linkedin-pages

### Connector Version

1.1.25

### What step the error happened?

During the sync

### Relevant information

The connector generates a DAY-granularity time interval shorter than one full day for the share_statistics_time_bound stream. LinkedIn's API requires DAY intervals to span at least one full day, so the request is rejected. The stream fails after 5 retries with 0 records, and the sync has been stuck since June 7.
Because the interval is generated inside the connector, changing destination, auth, or retrying does not resolve it.
This stream carries post-performance metrics (impressionCount, uniqueImpressionsCount, clickCount, engagement, likeCount, etc. inside totalShareStatistics), so disabling it loses all LinkedIn Page post analytics downstream — not an acceptable long-term workaround.
Steps to reproduce:

Configure source-linkedin-pages v1.1.25 with the share_statistics_time_bound stream enabled
Run a sync
The stream fails with a LinkedIn API time-interval validation error

Expected: the connector should generate time intervals spanning at least one full day for DAY granularity.

[linkedin_pages___bigquery_logs_89864863_txt.txt](https://github.com/user-attachments/files/29052314/linkedin_pages___bigquery_logs_89864863_txt.txt)

### Relevant log output

```shell

```

### Contribute

- [ ] Yes, I want to contribute

---
**Internal Tracking:** https://github.com/airbytehq/oncall/issues/12908

コントリビューションガイド

コントリビューションガイドを開く

調査の方向性

Start with the source-linkedin-pages connector and its share_statistics_time_bound stream, then reproduce the sync using version 1.1.25. Trace where the DAY-granularity interval is generated and verify that the resulting interval spans at least one full day and the stream can return post-performance metrics without the LinkedIn API validation error.

索引モデルが issue の本文から書いたものです。

評価

技術スタック
python
領域
api, data-engineering
issue の種類
バグ
難易度
3/5
見積もり時間
1〜2日
活発さ
静か
明瞭さ
おおむね明確
初心者へのやさしさ
64/100

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