Amazon S3 PUT range header - amazon-web-services

I am currently using the range header for GET request on Amazon S3 but I can't find an equivalent for PUT requests.
Do I have to upload the entire file again or can I specify where in the file I want to update? Thanks

Need to upload it again. S3 does not have a concept of either append and/or editing afile
However, if its a long file, you can do something called "Multipart Upload", and send several pieces of file, and merge it back at AWS:
http://docs.amazonwebservices.com/AmazonS3/latest/dev/uploadobjusingmpu.html

Related

AWS Glue - fixed width text file - with header and footer

I'm a beginner in AWS, so please bare with me, if certain things are a bit off :)
I have a task, where I need to load in a fixed width text file, that contains both a header record and a footer record. And of cause a lot of data in between. The data needs some simple changes, before written into the destination file, which also should be a fixed width file.
Would like to utilize AWS Glue for this, but am a little in doubt how to attack this. I guess since the data has header and footer, spark would be my best option to both read and write the file?
The Glue job should be triggered by the input file being uploaded into a S3 bucket.
What would be the flow here?
Uploading file to S3
S3 notification event triggering what? Lambda?
Lambda starting up Glue job with spark script:
a) Load txt file data into table
b) reading and transforming data
c) Writing txt file in S3
Do I need a crawler in between somewhere?
Thanks in advance.

Update data in csv table which is stored in AWS S3 bucket

I need a solution for entering new data in csv that is stored in S3 bucket in AWS.
At this point we are downloading the file, editing and then uploading it again in s3 and we would like to automatize this process.
We need to add one row in a three column.
Thank you in advance!
I think you will be able to do that using Lambda Functions. You will need to programmatically make the modifications you need over the CSV but there are multiple programming languages that allow you to do that. One quick example is using python and the csv library
Then you can invoke that lambda or add more logic to the operations you want to do using an AWS API Gateway.
You can access the CSV file (object) inside the S3 Bucket from the lambda code using the AWS SDK and append the new rows with data you pass as parameters to the function
There is no way to directly modify the csv stored in S3 (if that is what you're asking). The process will always entail some version of download, modify, upload. There are many examples of how you can do this, for example here

Continuously write to S3 file

I want to store user action logs continuously to s3 file for that session.
Requirements:
for a session single file
continuous write operations to s3
should be able to download that file at the end of the session.
Dont want to create new file for single session, want to update same file. Please suggest only AWS solutions.
Do i need to create stream and use it with s3 or using mediator storage system and push once in while.
Objects in Amazon S3 are immutable -- they cannot be modified after they are created.
From your description, a good solution would be to use Amazon Kinesis Data Firehose. Your app can stream data to the Firehose and it will combine data together based on size or time. A long session might therefore produce multiple output files, so you would need a separate process that combines those files together into a single file.

AWS S3: .csv file is downloaded as .csv

I have 2 AWC accounts, each of them has one S3 bucket. I uploaded two same-size .CSV files to each of the S3 bucket.
When I try to Download or Download As, this file is downloaded as .CSV file in first account. BUT(!!) When I try to download this file from second account - it is downloading it as .TXT.
How can this happen? Both files are created in the same way: through Redshift UNLOAD query, that perform copying of selected data from Redshift to S3.
UPDATE:
Can it be because in this account for this document , **Server side encryption is equal to AWS-KMS?
I noticed that file, that converted from .csv to .txt has "Server side encryption: AWS-KMS", while .csv file that is downloaded as .csv - has "Server side encryption: NONE"
UPDATE: tried in different browsers - same result
Check the headers for each object in the AWS S3 console and compare the Content-Type values. Content-Type provides a hint to web browsers on what data the object contains.
If Content-Type does not exist or does not contain text/csv, add or modify the header in the S3 console or via your favorite S3 application such as CloudBerry.
John is right about the Content-Type not being text/csv. Sometimes, S3 will get it right and sometimes it won't. If you can't manually correct this yourself, you can run a Lambda function to do this for you everytime you upload a new object. You can use a Python 2.7 template Lambda function to download the object from the bucket, employ mimetypes library to guess_type for your S3 object, and then re-upload the file in the same bucket. You will need to trigger this function with S3 object upload and give it the necessary permissions (S3:GetObject).
P.S. This will work for files with any extension. If you know you are only going to upload .csv files, you can ignore the mimetypes and directly re-upload the object with
bucket.upload_fileobj(filename, key, ExtraArgs={'ContentType': 'text/csv'})
If the mimetypes cannot guess the typethen you might need to add the types, look at an example here https://www.programcreek.com/python/example/5209/mimetypes.add_type
Good Luck!
Here is scala solution (to specify content type):
val settingsLine: String = "csvdata1,csvdata2,csvdata3"
val settingsStream: InputStream = new ByteArrayInputStream(settingsLine.getBytes())
val metadata: ObjectMetadata = new ObjectMetadata()
metadata.setContentType("text/csv")
s3Client.putObject(bucketName, prefix, settingsStream, metadata)

CSV Export using Api Gateway and Lambda

What I would like to do:
What I would like to do is have a url which would return to the caller a CSV file which is essentially a export of data. I would like this to remain to be a serverless solution.
What I have done:
I have created an AWS API Gateway with the URL I want. I have created a lambda that will query the database and create a CSV string of that data. That data is placed in a JSON object and returned. API gateway then gets the CSV data from the json object and returns CSV to the caller with appropriate headers to indicate tht it is a CSV and attachment. Testing from the browser I get the download automatically just like I intended.
The problem I see:
This works well until there is a sizable amount of data at which point I start getting "body size is too long".
My attempts to resolve:
I did some googling around and I see others have had similar issues. In one solution I saw that they return a link to the file that they created. This solution seems viable for them because they had a server. For my serverless architecture it seems to be a little trickier. I could take and store the file into S3 but then i would have to return a link to S3. That seems like it could work but doesn't feel right like im missing a configuration option. It also feels like im exposing the implementation by returning the s3 urls as well.
I have looked around for tutorials and example of people doing similar things and i haven't found any.
My Questions:
Is there a way to do this?
Is there another solution that i dont know of?
How do i return a file, in this case CSV, from API Gateway of a larger size
There is a limit of 6 MB for AWS Lambda response payloads. If the files you need to server are larger than that you won't be able to serve them directly from Lambda.
Using S3 to store and serve the files is the standard way of doing something like this. I would leave the S3 bucket private and generate S3 Pre-signed URLs in the Lambda function. That will limit the time that the CSV file is available for download, and it will prevent people from being able to guess the URLs of files you are serving. You would use an S3 Lifecycle Policy to archive or delete the files after a period of time.