Efficiently Streaming a Large AWS S3 File via S3 Select

Stream a large S3 file into manageable chunks without downloading the whole file locally using AWS S3 Select

AWS S3 is an industry-leading object storage service. We tend to store lots of data files on S3 and at times require processing these files. If the size of the file that we are processing is small, we can basically go with traditional file processing flow, wherein we fetch the file from S3 and then process it row by row level. But the question arises, what if the file is size is more viz. > 1GB? 😓

Importing (reading) a large file leads Out of Memory error. It can also lead to a system crash event. There are libraries viz. PandasDask, etc. which are very good at processing large files but again the file is to be present locally i.e. we will have to import it from S3 to our local machine. But what if we do not want to fetch and store the whole S3 file locally? 🤔

📜 Let’s consider some of the use-cases:

  • We want to process a large CSV S3 file (~2GB) every day. It must be processed within a certain time frame (e.g. in 4 hours)
  • We are required to process large S3 files regularly from the FTP server. New files come in certain time intervals and to be processed sequentially i.e. the old file has to be processed before starting to process the newer files.

These are some very good scenarios where local processing may impact the overall flow of the system. Also, if we are running these file processing units in containers, then we have got limited disk space to work with. Hence, a cloud streaming flow is needed (which can also parallelize the processing of multiple chunks of the same file by streaming different chunks of the same file in parallel threads/processes). This is where I came across the AWS S3 Select feature. 😎

📝 This post focuses on the streaming of a large file into smaller manageable chunks (sequentially). This approach can then be used to parallelize the processing by running in concurrent threads/processes.

#aws-s3 #s3 select #aws

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Efficiently Streaming a Large AWS S3 File via S3 Select

Efficiently Streaming a Large AWS S3 File via S3 Select

Stream a large S3 file into manageable chunks without downloading the whole file locally using AWS S3 Select

AWS S3 is an industry-leading object storage service. We tend to store lots of data files on S3 and at times require processing these files. If the size of the file that we are processing is small, we can basically go with traditional file processing flow, wherein we fetch the file from S3 and then process it row by row level. But the question arises, what if the file is size is more viz. > 1GB? 😓

Importing (reading) a large file leads Out of Memory error. It can also lead to a system crash event. There are libraries viz. PandasDask, etc. which are very good at processing large files but again the file is to be present locally i.e. we will have to import it from S3 to our local machine. But what if we do not want to fetch and store the whole S3 file locally? 🤔

📜 Let’s consider some of the use-cases:

  • We want to process a large CSV S3 file (~2GB) every day. It must be processed within a certain time frame (e.g. in 4 hours)
  • We are required to process large S3 files regularly from the FTP server. New files come in certain time intervals and to be processed sequentially i.e. the old file has to be processed before starting to process the newer files.

These are some very good scenarios where local processing may impact the overall flow of the system. Also, if we are running these file processing units in containers, then we have got limited disk space to work with. Hence, a cloud streaming flow is needed (which can also parallelize the processing of multiple chunks of the same file by streaming different chunks of the same file in parallel threads/processes). This is where I came across the AWS S3 Select feature. 😎

📝 This post focuses on the streaming of a large file into smaller manageable chunks (sequentially). This approach can then be used to parallelize the processing by running in concurrent threads/processes.

#aws-s3 #s3 select #aws

Rory  West

Rory West

1627276637

How to Use the AWS CLI to Upload Files to AWS S3

Amazon Web Service, aka AWS, is a leading cloud infrastructure provider for storing your servers, applications, databases, networking, domain controllers, and active directories in a widespread cloud architecture. AWS provides a Simple Storage Service (S3) for storing your objects or data with (119’s) of data durability. AWS S3 is compliant with PCI-DSS, HIPAA/HITECH, FedRAMP, EU Data Protection Directive, and FISMA that helps satisfy regulatory requirements.

When you log in to the AWS portal, navigate to the S3 bucket, choose your required bucket, and download or upload the files. Doing it manually on the portal is quite a time-consuming task. Instead, you can use the AWS Command Line Interface (CLI) that works best for bulk file operations with easy-to-use scripts. You can schedule the execution of these scripts for an unattended object download/upload.

#aws #aws cli #aws s3

Lindsey  Koepp

Lindsey Koepp

1603936365

The Benefits of Amazon S3 Explained Through a Comic

AWS S3 is one of the most fundamental services of AWS Cloud.

It’s basically your unlimited and safest cloud storage.

Read this comic style conversation between two guys and get to know why some of the biggest companies in the world are using Amazon S3 for their business and why you should use it too.

#aws-s3 #aws #cloud-computing #cloud-storage #data-storage #aws-services #aws-top-story #aws-certification

Seamus  Quitzon

Seamus Quitzon

1601341562

AWS Cost Allocation Tags and Cost Reduction

Bob had just arrived in the office for his first day of work as the newly hired chief technical officer when he was called into a conference room by the president, Martha, who immediately introduced him to the head of accounting, Amanda. They exchanged pleasantries, and then Martha got right down to business:

“Bob, we have several teams here developing software applications on Amazon and our bill is very high. We think it’s unnecessarily high, and we’d like you to look into it and bring it under control.”

Martha placed a screenshot of the Amazon Web Services (AWS) billing report on the table and pointed to it.

“This is a problem for us: We don’t know what we’re spending this money on, and we need to see more detail.”

Amanda chimed in, “Bob, look, we have financial dimensions that we use for reporting purposes, and I can provide you with some guidance regarding some information we’d really like to see such that the reports that are ultimately produced mirror these dimensions — if you can do this, it would really help us internally.”

“Bob, we can’t stress how important this is right now. These projects are becoming very expensive for our business,” Martha reiterated.

“How many projects do we have?” Bob inquired.

“We have four projects in total: two in the aviation division and two in the energy division. If it matters, the aviation division has 75 developers and the energy division has 25 developers,” the CEO responded.

Bob understood the problem and responded, “I’ll see what I can do and have some ideas. I might not be able to give you retrospective insight, but going forward, we should be able to get a better idea of what’s going on and start to bring the cost down.”

The meeting ended with Bob heading to find his desk. Cost allocation tags should help us, he thought to himself as he looked for someone who might know where his office is.

#aws #aws cloud #node js #cost optimization #aws cli #well architected framework #aws cost report #cost control #aws cost #aws tags

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