Dask: the definitive guide
The exponentially-increasing volume and complexity of data make scalability and reliability increasingly challenging issues. But while modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing, many Python tools weren't designed to leverage this parallelism....
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Main Authors: | , , |
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Format: | Electronic eBook |
Language: | English |
Published: |
Sebastopol, CA
O'Reilly Media, Inc.
2023
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Edition: | [First edition]. |
Subjects: | |
Links: | https://learning.oreilly.com/library/view/-/9781098117139/?ar |
Summary: | The exponentially-increasing volume and complexity of data make scalability and reliability increasingly challenging issues. But while modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing, many Python tools weren't designed to leverage this parallelism. Using Dask to parallelize Python workflows delivers a competitive advantage by reducing turn-around time, freeing you to work on more interesting or complex data problems. |
Item Description: | "Early release, raw & unedited." |
Physical Description: | 1 Online-Ressource (78 Seiten) illustrations |
ISBN: | 9781098117139 1098117131 |
Staff View
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isbn | 9781098117139 1098117131 |
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spelling | Rocklin, Matthew VerfasserIn aut Dask the definitive guide by Matthew Rocklin, Matthew Powers, and Richard Pelgrim [First edition]. Sebastopol, CA O'Reilly Media, Inc. 2023 1 Online-Ressource (78 Seiten) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier "Early release, raw & unedited." The exponentially-increasing volume and complexity of data make scalability and reliability increasingly challenging issues. But while modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing, many Python tools weren't designed to leverage this parallelism. Using Dask to parallelize Python workflows delivers a competitive advantage by reducing turn-around time, freeing you to work on more interesting or complex data problems. Python (Computer program language) Data mining Electronic data processing Distributed processing Information visualization Electronic data processing ; Distributed processing Powers, Matthew VerfasserIn aut Pelgrim, Richard VerfasserIn aut |
spellingShingle | Rocklin, Matthew Powers, Matthew Pelgrim, Richard Dask the definitive guide Python (Computer program language) Data mining Electronic data processing Distributed processing Information visualization Electronic data processing ; Distributed processing |
title | Dask the definitive guide |
title_auth | Dask the definitive guide |
title_exact_search | Dask the definitive guide |
title_full | Dask the definitive guide by Matthew Rocklin, Matthew Powers, and Richard Pelgrim |
title_fullStr | Dask the definitive guide by Matthew Rocklin, Matthew Powers, and Richard Pelgrim |
title_full_unstemmed | Dask the definitive guide by Matthew Rocklin, Matthew Powers, and Richard Pelgrim |
title_short | Dask |
title_sort | dask the definitive guide |
title_sub | the definitive guide |
topic | Python (Computer program language) Data mining Electronic data processing Distributed processing Information visualization Electronic data processing ; Distributed processing |
topic_facet | Python (Computer program language) Data mining Electronic data processing Distributed processing Information visualization Electronic data processing ; Distributed processing |
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