I am working on a requirement, where i am doing multipart upload of the csv file from on prem server to S3 Bucket.
To achieve this using AWS Lambda I create a presigned url and use this url i am uploading the csv file. Now, once i have the file in AWS S3, i want it to be moved to AWS RDS Oracle DB. Initially i was planning to use AWS Lambda for this.
So once i have the file in S3, it triggers lambda(s3 event) and lambda will push this file to RDS. But with this the issue is with the file Size(600 MB).
I am looking for some other way, where whenever there is a file uploaded to S3, it should trigger any AWS service and that service will push this csv file to RDS. I have gone through AWS DMS/Data Pipeline, but not able to find any way to automate this migration
I need to automate this migration on every s3 upload, that is also cost effective.
Setup S3 Integration and build SPROCS to help automate load. Details found here.
UPDATE:
Looks like you don't even need to create a SPROC. You can just use the RDS procedure as outlined here. You would then just create an event-driven lambda function that is triggered on a given S3 event--e.g. on object PUT(), POST(), COPY, etc..--which passes the S3 metadata requisite to access the event object. Here is a simple Python example of what that Lambda and config might look like. You would then use the metadata passed on the trigger event--as outlined in the Python example--to dynamically create your procedure call then execute that procedure. You can also add the ensuing workflow logic that meets your requirements--i.e. TASK_ID fetch & operational handling, monitoring, etc...--to the same lambda function or separate those concerns by adding additional lambdas. Hope this helps!
Related
I am new to AWS. Most of example I have seen need an input file name from S3 bucket for media convert. I want to automate this process. What is the best way to do it. I want to achieve following.
API to upload a video(mp4) to a S3 bucket.
Trigger MediaConvert Job to process newly updated video and convert it to HLS.
I know how to create an API as well as MediaConvert job. What I need help with it is automating this workflow. How can I pass recently uploaded video to MediaConvert job dynamically?
I think this should actually cover what you're looking for, and is straight from the source:
https://aws.amazon.com/blogs/media/vod-automation-part-1-create-a-serverless-watchfolder-workflow-using-aws-elemental-mediaconvert/
Essentially, you'll be making use of AWS Lambda, a serverless code execution product. Lambda functions by allowing you to hook directly into "triggers" or events from within the AWS ecosystem (like uploading a file to S3).
The lambda can then execute code in a number of supported languages like Javascript or Python, which can be used to execute a MediaConvert job on the triggering object (the file uploaded to S3).
Some images which is already uploaded on AWS S3 bucket and of course there is a lot of image. I want to edit and replace those images and I want to do it on AWS server, Here I want to use aws lambda.
I already can do my job from my local pc. But it takes a very long time. So I want to do it on server.
Is it possible?
Unfortunately directly editing file in S3 is not supported Check out the thread. To overcome the situation, you need to download the file locally in server/local machine, then edit it and re-upload it again to s3 bucket. Also you can enable versions
For node js you can use Jimp
For java: ImageIO
For python: Pillow
or you can use any technology to edit it and later upload it using aws-sdk.
For lambda function you can use serverless framework - https://serverless.com/
I have made youtube videos long back. This is related to how get started with aws-lambda and serverless
https://www.youtube.com/watch?v=uXZCNnzSMkI
You can trigger a Lambda using the AWS SDK.
Write a Lambda to process a single image and deploy it.
Then locally use the AWS SDK to list the images in the bucket and invoke the Lambda (asynchronously) for each file using invoke. I would also save somewhere which files have been processed so you can continue if something fails.
Note that the default limit for Lambda is 1000 concurrent executions, so to avoid reaching the limit you can send messages to an SQS queue (which then triggers the Lambda) or just retry when invoke throws an error.
I am trying to take sql data stored in a csv file in an s3 bucket and transfer the data to AWS Redshift and automate that process. Would writing etl scripts with lambda/glue be the best way to approach this problem, and if so, how do I get the script/transfer to run periodically? If not, what would be the most optimal way to pipeline data from s3 to Redshift.
Tried using AWS Pipeline but that is not available in my region. I also tried to use the AWS documentation for Lambda and Glue but don't know where to find the exact solution to the problem
All systems (including AWS Data Pipeline) use the Amazon Redshift COPY command to load data from Amazon S3.
Therefore, you could write an AWS Lambda function that connects to Redshift and issues the COPY command. You'll need to include a compatible library (eg psycopg2) to be able to call Redshift.
You can use Amazon CloudWatch Events to call the Lambda function on a regular schedule. Or, you could get fancy and configure Amazon S3 Events so that, when a file is dropped in an S3 bucket, it automatically triggers the Lambda function.
If you don't want to write it yourself, you could search for existing code on the web, including:
The very simply Python-based christianhxc/aws-lambda-redshift-copy: AWS Lambda function that runs the copy command into Redshift
A more fully-featured node-based A Zero-Administration Amazon Redshift Database Loader | AWS Big Data Blog
This feature is not clear to me about the benefits (I didn't find any good documentation):
Is it just faster in the case you reuse the same zip for many lambda functions because you upload only 1 time and you just give the S3 link URL to each lambda function?
If you use an S3 link, will all your lambda functions be updated with the latest code automatically when you re-upload the zip file, meaning is the zip file on S3 a "reference" to use at each call to a lambda function?
Thank you.
EDIT:
I have been asked "Why do you want the same code for multiple Lambda functions anyway?"
Because I use AWS Lambda with AWS API Gateway so I have 1 project with all my handlers which are actual "endpoints" for my RESTful API.
EDIT #2:
I confirm that uploading a modified version of the zip file on S3 doesn't change the existing lambda functions result.
If an AWS guy reads this message, that would be great to have a kind of batch update feature that updates a set of selected lambda functions with 1 zip file on S3 in 1 click (or even an "automatic update" feature that detects when the file has been updated ;-))
Let's say you have 50 handlers in 1 project, then you modify something global impacting all of them, currently you have to go through all your lambda functions and update the zip file manually...
The code is imported from the zip to Lambda. It is exactly the same as uploading the zip file through the Lambda console or API. However, if your Lambda function is big (they say >10MB), they recommend uploading to S3 and then using the S3 import functionality because that is more stable than directly uploading from the Lambda page. Other than that, there is no benefit.
So for question 1: no. Why do you want the same code for multiple Lambda functions anyway?
Question 2: If you overwrite the zip you will not update the Lambda function code.
To add to other people's use cases, having the ability to update a Lambda function from S3 is extremely useful within an automated deployment / CI process.
The instructions under New Deployment Options for AWS Lambda include a simple Lambda function that can be used to copy a ZIP file from S3 to Lambda itself, as well as instructions for triggering its execution when a new file is uploaded.
As an example of how easy this can make development and deployment, my current workflow is:
I update my Node lambda application on my local machine, and git commit it to a remote repository.
A Jenkins instance picks up the commit, pulls down the appropriate files, adds them into a ZIP file and uploads this to an S3 bucket.
The LambdaDeployment function then automatically deploys this new version for me, without me needing to even leave my development environment.
To answer what I think is the essence of your question, AWS allows you to use S3 as the origin for your Lambda zip file because sometimes uploading large files via your browser can timeout. Also, storing your code on S3 allows you to store it centrally, rather than on your computer and I'm sure there is a CodeCommit tie-in there as well.
Using the S3 method of uploading your code to Lambda also allows you to upload larger files (AWS has a 10MB limit when uploading via web browser).
#!/bin/bash
cd /your/workspace
#zips up the new code
zip -FSr yourzipfile.zip . -x *.git* *bin/\* *.zip
#Updates function code of lambda and pushes new zip file to s3bucket for cloudformation lambda:codeuri source
aws lambda update-function-code --function-name arn:aws:lambda:us-west-2:YOURID:function:YOURFUNCTIONNAME --zip-file file://yourzipfile.zip
Depends on aws-cli install and aws profile setup
aws --profile yourProfileName configure
I'm new to AWS and have a feasibility question for a file management system I'm trying to build. I would like to set up a system where people will use the Amazon S3 browser and drop either a csv or excel file into their specific bucket. Then I would like to automate the process of taking that csv/excel file and inserting that into a table within RDS. Now this is assuming that the table has already been built and those excel/csv file will always be formatted the same and will be in the same exact place every single time. Is it possible to automate this process or at least get it to point where very minimal human interference is needed. I'm new to AWS so I'm not exactly sure of the limits of S3 to RDS. Thank you in advance.
It's definitely possible. AWS supports notifications from S3 to SNS, which can be forwarded automatically to SQS: http://aws.amazon.com/blogs/aws/s3-event-notification/
S3 can also send notifications to AWS Lambda to run your own code directly.