Traditional retrieval of objects is always as whole entities, i.e GetObject for a 5 GiB object, will always return 5 GiB of data. S3 Select API allows us to retrieve a subset of data by using simple SQL expressions. By using Select API to retrieve only the data needed by the application, drastic performance improvements can be achieved.
- GZIP or BZIP2 - CSV and JSON files can be compressed using GZIP, BZIP2, [ZSTD](https://facebook.github.io/zstd/), and streaming formats of [LZ4](https://lz4.github.io/lz4/), [S2](https://github.com/klauspost/compress/tree/master/s2#s2-compression) and [SNAPPY](http://google.github.io/snappy/).
- Parquet API supports columnar compression for using GZIP, Snappy, LZ4. Whole object compression is not supported for Parquet objects.
Type inference and automatic conversion of values is performed based on the context when the value is un-typed (such as when reading CSV data). If present, the CAST function overrides automatic conversion.
- Familiarity with Python and installing dependencies.
## 2. Install boto3
Install `aws-sdk-python` from AWS SDK for Python official docs [here](https://aws.amazon.com/sdk-for-python/)
## 3. Example
As an example, let us take a gzip compressed CSV file. Without S3 Select, we would need to download, decompress and process the entire CSV to get the data you needed. With Select API, can use a simple SQL expression to return only the data from the CSV you’re interested in, instead of retrieving the entire object. Following Python example shows how to retrieve the first column `Location` from an object containing data in CSV format.
Please replace ``endpoint_url``,``aws_access_key_id``, ``aws_secret_access_key``, ``Bucket`` and ``Key`` with your local setup in this ``select.py`` file.
```py
#!/usr/bin/env/env python3
import boto3
s3 = boto3.client('s3',
endpoint_url='http://localhost:9000',
aws_access_key_id='minio',
aws_secret_access_key='minio123',
region_name='us-east-1')
r = s3.select_object_content(
Bucket='mycsvbucket',
Key='sampledata/TotalPopulation.csv.gz',
ExpressionType='SQL',
Expression="select * from s3object s where s.Location like '%United States%'",
InputSerialization={
'CSV': {
"FileHeaderInfo": "USE",
},
'CompressionType': 'GZIP',
},
OutputSerialization={'CSV': {}},
)
for event in r['Payload']:
if 'Records' in event:
records = event['Records']['Payload'].decode('utf-8')
For a more detailed SELECT SQL reference, please see [here](https://docs.aws.amazon.com/AmazonS3/latest/dev/s3-glacier-select-sql-reference-select.html)
- Large numbers (outside of the signed 64-bit range) are not yet supported.
- The Date [functions](https://docs.aws.amazon.com/AmazonS3/latest/dev/s3-glacier-select-sql-reference-date.html) `DATE_ADD`, `DATE_DIFF`, `EXTRACT` and `UTCNOW` along with type conversion using `CAST` to the `TIMESTAMP` data type are currently supported.
- AWS S3's [reserved keywords](https://docs.aws.amazon.com/AmazonS3/latest/dev/s3-glacier-select-sql-reference-keyword-list.html) list is not yet respected.
