Scaling Python with Dask

Index

A

• accelerated processing, Where Does Dask Fit in the Ecosystem?
• accelerator libraries, Installing the Libraries-Installing the Libraries
• accelerators
  • freeing resources, Freeing Accelerator Resources
  • non-transparent, Transparent Versus Non-transparent Accelerators
  • transparent, Transparent Versus Non-transparent Accelerators
• Active Memory Manager, Worker Memory Management
• actor model, What Is the Actor Model?-What Is the Actor Model?
• ActorFuture, Your First Actor (It’s a Bank Account)
  • serializability, Your First Actor (It’s a Bank Account)
• actors
  • creating, Your First Actor (It’s a Bank Account)
  • futures, Your First Actor (It’s a Bank Account)
  • implementing, Your First Actor (It’s a Bank Account)
  • limitations, Limitations
  • scaling, Scaling Dask Actors-Scaling Dask Actors
  • submitting, Your First Actor (It’s a Bank Account)
  • use cases, When to Use Dask Actors
• adaptive deployments, Auto-scaling
• adaptive scaling, Setting Up Dask in a Remote Cluster, Adaptive/Auto-scaling
• aggregation
  • built-in, Aggregations
  • by key, Aggregations
  • partial, Aggregations
  • shuffles, Aggregations-Aggregations
  • slow, Aggregations
  • sublinear, Aggregations
• algorithms, recursive, Handling Recursive Algorithms
• Amazon Web Services (AWS), Where Does Dask Fit in the Ecosystem?
• arrays, Dask arrays, Dask Arrays
  • chunks, Dask Arrays
  • converting to/from Dask bags, Loading/Saving
  • formats, Loading/Saving
  • functions, Special Dask Functions
  • loading/saving, Loading/Saving
  • not using, When Not to Use Dask Arrays
  • use cases, Common Use Cases
• at-least-once execution, Limitations, ...