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What is the purpose of gsutil and how does it facilitate faster transfer jobs?

by EITCA Academy / Wednesday, 02 August 2023 / Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Further steps in Machine Learning, Big data for training models in the cloud, Examination review

The purpose of gsutil in the context of Google Cloud Machine Learning is to facilitate faster transfer jobs by providing a command-line tool for managing and interacting with Google Cloud Storage. gsutil allows users to perform various operations such as uploading, downloading, copying, and deleting files and objects in Google Cloud Storage. It also enables users to set access control permissions, manage storage classes, and perform other administrative tasks.

One of the key ways in which gsutil facilitates faster transfer jobs is through its ability to perform parallel uploads and downloads. This means that gsutil can transfer multiple files or objects simultaneously, utilizing the available network bandwidth more efficiently. By dividing the data into smaller chunks and transferring them in parallel, gsutil reduces the overall transfer time and improves the speed of the transfer job.

For example, let's say we have a large dataset consisting of multiple files that need to be uploaded to Google Cloud Storage. Without gsutil, we would have to upload each file sequentially, which can be time-consuming. However, by using gsutil's parallel upload feature, we can upload multiple files concurrently, significantly reducing the overall upload time.

In addition to parallel transfers, gsutil also utilizes various optimization techniques to enhance transfer performance. It employs resumable transfers, which allow interrupted transfers to be resumed from where they left off, rather than starting from scratch. This is particularly useful when dealing with large files or unstable network connections, as it ensures that progress is not lost and allows for more efficient transfer management.

Furthermore, gsutil employs compression techniques to reduce the size of the data being transferred. By compressing the data before transferring it, gsutil can reduce the amount of network bandwidth required, resulting in faster transfer times. This is especially beneficial when dealing with large datasets or when transferring data over networks with limited bandwidth.

Gsutil serves the purpose of facilitating faster transfer jobs in Google Cloud Machine Learning by providing a command-line tool for managing and interacting with Google Cloud Storage. It achieves this through parallel transfers, resumable transfers, and compression techniques, ultimately optimizing the transfer process and reducing overall transfer times.

Other recent questions and answers regarding Big data for training models in the cloud:

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View more questions and answers in Big data for training models in the cloud

More questions and answers:

  • Field: Artificial Intelligence
  • Programme: EITC/AI/GCML Google Cloud Machine Learning (go to the certification programme)
  • Lesson: Further steps in Machine Learning (go to related lesson)
  • Topic: Big data for training models in the cloud (go to related topic)
  • Examination review
Tagged under: Artificial Intelligence, Compression Techniques, Google Cloud Storage, Gsutil, Parallel Transfers, Resumable Transfers
Home » Artificial Intelligence / Big data for training models in the cloud / EITC/AI/GCML Google Cloud Machine Learning / Examination review / Further steps in Machine Learning » What is the purpose of gsutil and how does it facilitate faster transfer jobs?

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