#MAC CLIENT FOR S3 HOW TO#

Both s4cmd and AWS’ own aws-cli do make concurrent connections, and are much faster for many files or large transfers (since multipart uploads allow parallelism).Īnother approach is with EMR, using Hadoop to parallelize the problem.

Many common AWS S3 libraries (including the widely used s3cmd) do not by default make many connections at once to transfer data. So what determines your overall throughput in moving many objects is the concurrency level of the transfer: How many worker threads (connections) on one instance and how many instances are used. Each S3 operation is an API request with significant latency - tens to hundreds of milliseconds, which adds up to pretty much forever if you have millions of objects and try to work with them one at a time. Thirdly, and critically if you are dealing with lots of items, concurrency matters.

#MAC CLIENT FOR S3 HOW TO#

How to use concurrency to improve AWS S3 latency and performance You can see this if you sort by “Network Performance” on the excellent list. If you’re using EC2 servers, some instance types have higher bandwidth network connectivity than others. How to Improve S3 performance by using higher bandwidth networks For distributing content quickly to users worldwide, remember you can use BitTorrent support, CloudFront, or another CDN with S3 as its origin. You have to pay for that too, the equivalent of 1-2 months of storage cost for the transfer in either direction. Alternately, you can use S3 Transfer Acceleration to get data into AWS faster simply by changing your API endpoints. If your servers are in a major data center but not in EC2, you might consider using DirectConnect ports to get significantly higher bandwidth (you pay per port). More surprisingly, even when moving data within the same region, Oregon (a newer region) comes in faster than Virginia on some benchmarks.

Obviously, if you’re moving data within AWS via an EC2 instance or through various buckets, such as off of an EBS volume, you’re better off if your EC2 instance and S3 region correspond. The first takeaway from this is that regions and connectivity matter. How to improve S3 latency by paying attention to regions and connectivity

The level of concurrency used for requests when uploading or downloading (including multipart uploads).

The size of the pipe between the source (typically a server on premises or EC2 instance) and S3.

But almost always you’re hit with one of two bottlenecks: A good example is S3DistCp, which uses many workers and instances. S3 is highly scalable, so in principle, with a big enough pipe or enough instances, you can get arbitrarily high throughput. Cutting down time you spend uploading and downloading files can be remarkably valuable in indirect ways - for example, if your team saves 10 minutes every time you deploy a staging build, you are improving engineering productivity significantly. If you’re moving data on a frequent basis, there’s a good chance you can speed it up. Getting data into and out of AWS S3 takes time. How to improve S3 performance by getting log data into and out of S3 faster

Mac client for s3