amazon-s3

问题 Just wondering if Parquet predicate pushdown also works on S3, not only HDFS. Specifically if we use Spark (non EMR). Further explanation might be helpful since it might involve understanding on distributed file system. 回答1: Yes. Filter pushdown does not depend on the underlying file system. It only depends on the spark.sql.parquet.filterPushdown and the type of filter (not all filters can be pushed down). See https://github.com/apache/spark/blob/v2.2.0/sql/core/src/main/scala/org/apache

问题 Just wondering if Parquet predicate pushdown also works on S3, not only HDFS. Specifically if we use Spark (non EMR). Further explanation might be helpful since it might involve understanding on distributed file system. 回答1: Yes. Filter pushdown does not depend on the underlying file system. It only depends on the spark.sql.parquet.filterPushdown and the type of filter (not all filters can be pushed down). See https://github.com/apache/spark/blob/v2.2.0/sql/core/src/main/scala/org/apache

问题 Just wondering if Parquet predicate pushdown also works on S3, not only HDFS. Specifically if we use Spark (non EMR). Further explanation might be helpful since it might involve understanding on distributed file system. 回答1: Yes. Filter pushdown does not depend on the underlying file system. It only depends on the spark.sql.parquet.filterPushdown and the type of filter (not all filters can be pushed down). See https://github.com/apache/spark/blob/v2.2.0/sql/core/src/main/scala/org/apache

问题 Just wondering if Parquet predicate pushdown also works on S3, not only HDFS. Specifically if we use Spark (non EMR). Further explanation might be helpful since it might involve understanding on distributed file system. 回答1: Yes. Filter pushdown does not depend on the underlying file system. It only depends on the spark.sql.parquet.filterPushdown and the type of filter (not all filters can be pushed down). See https://github.com/apache/spark/blob/v2.2.0/sql/core/src/main/scala/org/apache

问题 I am using docker-compose to set up a scalable airflow cluster. I based my approach off of this Dockerfile https://hub.docker.com/r/puckel/docker-airflow/ My problem is getting the logs set up to write/read from s3. When a dag has completed I get an error like this *** Log file isn't local. *** Fetching here: http://ea43d4d49f35:8793/log/xxxxxxx/2017-06-26T11:00:00 *** Failed to fetch log file from worker. *** Reading remote logs... Could not read logs from s3://buckets/xxxxxxx/airflow/logs

问题 I get an error AWS::S3::Errors::InvalidRequest The authorization mechanism you have provided is not supported. Please use AWS4-HMAC-SHA256. when I try upload file to S3 bucket in new Frankfurt region. All works properly with US Standard region. Script: backup_file = '/media/db-backup_for_dev/2014-10-23_02-00-07/slave_dump.sql.gz' s3 = AWS::S3.new( access_key_id: AMAZONS3['access_key_id'], secret_access_key: AMAZONS3['secret_access_key'] ) s3_bucket = s3.buckets['test-frankfurt'] # Folder and

问题 <speak> <audio src = "https://s3.amazonaws.com/morsecodesounds/Is.mp3" /> <audio src = "https://s3.amazonaws.com/morsecodesounds/Ie.mp3" /> <audio src = "https://s3.amazonaws.com/morsecodesounds/Il.mp3" /> <audio src = "https://s3.amazonaws.com/morsecodesounds/Ie.mp3" /> <audio src = "https://s3.amazonaws.com/morsecodesounds/Ic.mp3" /> <audio src = "https://s3.amazonaws.com/morsecodesounds/It.mp3" /> </speak> This is what i tested on the alexa developer console did not play it. 回答1: Just to

问题 I am trying to download a file from Amazon S3 to a predefined folder in the local machine. This is the code and it works fine. But when the file is saved, it saves with lastname of the path. How should I correct this? import boto3 import os S3_Object = boto3.client('s3', aws_access_key_id='##', aws_secret_access_key='##') BUCKET_NAME = '##' filename2 = [] Key2 = [] bucket = S3_Object.list_objects(Bucket=BUCKET_NAME)['Contents'] download_path = target_file_path = os.path.join('..', 'data', 'lz

问题 I follow the steps described in the link: http://docs.aws.amazon.com/cognito/latest/developerguide/amazon-cognito-integrating-user-pools-with-identity-pools.html to integrate my user pool with cognito identity. But every time I am trying to access amazone S3 using the Authentication providers I get the following error: E/CognitoCachingCredentialsProvider: Failure to get credentials com.amazonaws.services.cognitoidentity.model.NotAuthorizedException: Logins don't match. Please include at least

问题 I get the below error: Traceback (most recent call last): File "/var/task/lambda_function.py", line 22, in lambda_handler outEvent = str(event['awslogs']['data']) KeyError: 'awslogs' Code in use: import boto3 import logging import json import gzip import urllib import time from io import StringIO logger = logging.getLogger() logger.setLevel(logging.INFO) s3 = boto3.client('s3') def lambda_handler(event, context): #set the name of the S3 bucket bucketS3 = 'test-flowlogs' folderS3 = 'ArcSight'