I have a hacky way of achieving this using boto3 (1.4.4), pyarrow (0.4.1) and pandas (0.20.3).
First, I can read a single parq
Thanks! Your question actually tell me a lot. This is how I do it now with pandas (0.21.1), which will call pyarrow, and boto3 (1.3.1).
import boto3
import io
import pandas as pd
# Read single parquet file from S3
def pd_read_s3_parquet(key, bucket, s3_client=None, **args):
if s3_client is None:
s3_client = boto3.client('s3')
obj = s3_client.get_object(Bucket=bucket, Key=key)
return pd.read_parquet(io.BytesIO(obj['Body'].read()), **args)
# Read multiple parquets from a folder on S3 generated by spark
def pd_read_s3_multiple_parquets(filepath, bucket, s3=None,
s3_client=None, verbose=False, **args):
if not filepath.endswith('/'):
filepath = filepath + '/' # Add '/' to the end
if s3_client is None:
s3_client = boto3.client('s3')
if s3 is None:
s3 = boto3.resource('s3')
s3_keys = [item.key for item in s3.Bucket(bucket).objects.filter(Prefix=filepath)
if item.key.endswith('.parquet')]
if not s3_keys:
print('No parquet found in', bucket, filepath)
elif verbose:
print('Load parquets:')
for p in s3_keys:
print(p)
dfs = [pd_read_s3_parquet(key, bucket=bucket, s3_client=s3_client, **args)
for key in s3_keys]
return pd.concat(dfs, ignore_index=True)
Then you can read multiple parquets under a folder from S3 by
df = pd_read_s3_multiple_parquets('path/to/folder', 'my_bucket')
(One can simplify this code a lot I guess.)