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docs: explain S3 object-store configuration for SQL #1716

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27 changes: 27 additions & 0 deletions docs/source/user-guide/data-sources.md
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Original file line number Diff line number Diff line change
Expand Up @@ -100,11 +100,16 @@ Supported Object Stores are
- {py:class}`~datafusion.object_store.MicrosoftAzure`

```python
import os

from datafusion import SessionContext
from datafusion.object_store import AmazonS3

region = "us-east-1"
bucket_name = "yellow-trips"

ctx = SessionContext()

s3 = AmazonS3(
bucket_name=bucket_name,
region=region,
Expand All @@ -120,6 +125,28 @@ ctx.register_parquet("trips", path)
ctx.table("trips").show()
```

### Use S3 in SQL

Configure S3 access on an {py:class}`~datafusion.object_store.AmazonS3` object and
register it on the context before issuing SQL that uses an `s3://` location. AWS
credentials are not SQL `OPTIONS`: `aws.*` is not a recognized SQL configuration
namespace.

After registering the object store above, a SQL external table can use the same
S3 path:

```python
ctx.sql(
f"""
CREATE EXTERNAL TABLE trips_sql
STORED AS PARQUET
LOCATION '{path}'
"""
).collect()

ctx.sql("SELECT count(passenger_count) FROM trips_sql").show()
```

## Other DataFrame Libraries

DataFusion can import DataFrames directly from other libraries, such as
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