> For the complete documentation index, see [llms.txt](https://upsolver.gitbook.io/content/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://upsolver.gitbook.io/content/support-1/troubleshooting/jobs/problem-ingesting-amazon-s3-data.md).

# Problem Ingesting Amazon S3 Data

If you are trying to ingest data from an Amazon S3 bucket not partitioned by date, note that the `START_FROM` option is set to `NOW`. 

This means that if no new data has arrived since you started running the job, no data has been ingested into your staging table.

To resolve this, you can set the `START_FROM` option to `BEGINNING` or to a specific timestamp when there is data, but this is only possible when reading from a bucket partitioned by `DATE_PATTERN`.

#### Example:

If the list of files is:

* `s3://bucket/input/a/2019/01/01/00/00/file.json`
* `s3://bucket/input/a/2019/01/01/00/01/file.json`
* `s3://bucket/input/a/2019/01/01/00/02/file.json`
* `s3://bucket/input/a/2019/01/01/00/03/file.json`

You can read your data from these files as follows:

```sql
CREATE JOB copy_from_s3
    CONTENT_TYPE = JSON
    START_FROM = timestamp '2019-01-01'
    DATE_PATTERN = 'yyyy/MM/dd/HH/mm'
AS COPY FROM S3 my_s3_connection 
    BUCKET = 'bucket' 
    PREFIX = 'input/a'
INTO default_glue_catalog.schema_name.table_name;
```

{% hint style="info" %}
If you are still experiencing issues, please raise a ticket via the [Upsolver Support Portal](https://support.upsolver.com/hc/en-us).
{% endhint %}


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