minio/docs/select
Klaus Post ddea0bdf11 Concurrent CSV parsing and reduce S3 select allocations (#8200)
```
CSV parsing, BEFORE:
BenchmarkReaderBasic-12         	    2842	    407533 ns/op	  397860 B/op	     957 allocs/op
BenchmarkReaderReplace-12       	    2718	    429914 ns/op	  397844 B/op	     957 allocs/op
BenchmarkReaderReplaceTwo-12    	    2718	    435556 ns/op	  397855 B/op	     957 allocs/op
BenchmarkAggregateCount_100K-12    	     171	   6798974 ns/op	16667102 B/op	  308077 allocs/op
BenchmarkAggregateCount_1M-12    	      19	  65657411 ns/op	168057743 B/op	 3146610 allocs/op
BenchmarkSelectAll_10M-12    	       1	20882119900 ns/op	2758799896 B/op	41978762 allocs/op

CSV parsing, AFTER:
BenchmarkReaderBasic-12         	    3721	    312549 ns/op	  101920 B/op	     338 allocs/op
BenchmarkReaderReplace-12       	    3776	    318810 ns/op	  101993 B/op	     340 allocs/op
BenchmarkReaderReplaceTwo-12    	    3610	    330967 ns/op	  102012 B/op	     341 allocs/op
BenchmarkAggregateCount_100K-12    	     295	   4149588 ns/op	 3553623 B/op	  103261 allocs/op
BenchmarkAggregateCount_1M-12    	      30	  37746503 ns/op	33827931 B/op	 1049435 allocs/op
BenchmarkSelectAll_10M-12    	       1	17608495800 ns/op	1416504040 B/op	21007082 allocs/op

~ benchcmp old.txt new.txt
benchmark                           old ns/op       new ns/op       delta
BenchmarkReaderBasic-12             407533          312549          -23.31%
BenchmarkReaderReplace-12           429914          318810          -25.84%
BenchmarkReaderReplaceTwo-12        435556          330967          -24.01%
BenchmarkAggregateCount_100K-12     6798974         4149588         -38.97%
BenchmarkAggregateCount_1M-12       65657411        37746503        -42.51%
BenchmarkSelectAll_10M-12           20882119900     17608495800     -15.68%

benchmark                           old allocs     new allocs     delta
BenchmarkReaderBasic-12             957            338            -64.68%
BenchmarkReaderReplace-12           957            340            -64.47%
BenchmarkReaderReplaceTwo-12        957            341            -64.37%
BenchmarkAggregateCount_100K-12     308077         103261         -66.48%
BenchmarkAggregateCount_1M-12       3146610        1049435        -66.65%
BenchmarkSelectAll_10M-12           41978762       21007082       -49.96%

benchmark                           old bytes      new bytes      delta
BenchmarkReaderBasic-12             397860         101920         -74.38%
BenchmarkReaderReplace-12           397844         101993         -74.36%
BenchmarkReaderReplaceTwo-12        397855         102012         -74.36%
BenchmarkAggregateCount_100K-12     16667102       3553623        -78.68%
BenchmarkAggregateCount_1M-12       168057743      33827931       -79.87%
BenchmarkSelectAll_10M-12           2758799896     1416504040     -48.66%
```

```
BenchmarkReaderHuge/97K-12         	    2200	    540840 ns/op	 184.32 MB/s	 1604450 B/op	     687 allocs/op
BenchmarkReaderHuge/194K-12        	    1522	    752257 ns/op	 265.04 MB/s	 2143135 B/op	    1335 allocs/op
BenchmarkReaderHuge/389K-12        	    1190	    947858 ns/op	 420.69 MB/s	 3221831 B/op	    2630 allocs/op
BenchmarkReaderHuge/778K-12        	     806	   1472486 ns/op	 541.61 MB/s	 5201856 B/op	    5187 allocs/op
BenchmarkReaderHuge/1557K-12       	     426	   2575269 ns/op	 619.36 MB/s	 9101330 B/op	   10233 allocs/op
BenchmarkReaderHuge/3115K-12       	     286	   4034656 ns/op	 790.66 MB/s	12397968 B/op	   16099 allocs/op
BenchmarkReaderHuge/6230K-12       	     172	   6830563 ns/op	 934.05 MB/s	16008416 B/op	   26844 allocs/op
BenchmarkReaderHuge/12461K-12      	     100	  11409467 ns/op	1118.39 MB/s	22655163 B/op	   48107 allocs/op
BenchmarkReaderHuge/24922K-12      	      66	  19780395 ns/op	1290.19 MB/s	35158559 B/op	   90216 allocs/op
BenchmarkReaderHuge/49844K-12      	      34	  37282559 ns/op	1369.03 MB/s	60528624 B/op	  174497 allocs/op
```
2019-09-13 14:18:35 -07:00
..
README.md Concurrent CSV parsing and reduce S3 select allocations (#8200) 2019-09-13 14:18:35 -07:00
select.py Add select docs and fix return values for Select API (#6300) 2018-08-17 17:11:39 -07:00

README.md

Select API Quickstart Guide Slack

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.

You can use the Select API to query objects with following features:

  • CSV, JSON and Parquet - Objects must be in CSV, JSON, or Parquet format.
  • UTF-8 is the only encoding type the Select API supports.
  • GZIP or BZIP2 - CSV and JSON files can be compressed using GZIP or BZIP2. The Select API supports columnar compression for Parquet using GZIP, Snappy, LZ4. Whole object compression is not supported for Parquet objects.
  • Server-side encryption - The Select API supports querying objects that are protected with server-side encryption.

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.

1. Prerequisites

  • Install MinIO Server from here.
  • Familiarity with AWS S3 API.
  • Familiarity with Python and installing dependencies.

2. Install boto3

Install aws-sdk-python from AWS SDK for Python official docs here

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 youre 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.

#!/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')
        print(records)
    elif 'Stats' in event:
        statsDetails = event['Stats']['Details']
        print("Stats details bytesScanned: ")
        print(statsDetails['BytesScanned'])
        print("Stats details bytesProcessed: ")
        print(statsDetails['BytesProcessed'])

4. Run the Program

Upload a sample dataset to MinIO using the following commands.

$ curl "https://esa.un.org/unpd/wpp/DVD/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2017_TotalPopulationBySex.csv" > TotalPopulation.csv
$ mc mb myminio/mycsvbucket
$ gzip TotalPopulation.csv
$ mc cp TotalPopulation.csv.gz myminio/mycsvbucket/sampledata/

Now let us proceed to run our select example to query for Location which matches United States.

$ python3 select.py
840,United States of America,2,Medium,1950,1950.5,79233.218,79571.179,158804.395

840,United States of America,2,Medium,1951,1951.5,80178.933,80726.116,160905.035

840,United States of America,2,Medium,1952,1952.5,81305.206,82019.632,163324.851

840,United States of America,2,Medium,1953,1953.5,82565.875,83422.307,165988.190
....
....
....

Stats details bytesScanned:
6758866
Stats details bytesProcessed:
25786743

For a more detailed SELECT SQL reference, please see here

5. Explore Further

6. Implementation Status

  • Full AWS S3 SELECT SQL syntax is supported.
  • All operators are supported.
  • All aggregation, conditional, type-conversion and string functions are supported.
  • JSON path expressions such as FROM S3Object[*].path are not yet evaluated.
  • Large numbers (outside of the signed 64-bit range) are not yet supported.
  • The Date functions 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 list is not yet respected.
  • CSV input fields (even quoted) cannot contain newlines even if RecordDelimiter is something else.