56 lines
2.1 KiB
YAML
56 lines
2.1 KiB
YAML
temporary-directory: null # Directory for local disk like /tmp, /scratch, or /local
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visualization:
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engine: null # Default visualization engine to use when calling `.visualize()` on a collection
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tokenize:
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ensure-deterministic: false # If true, tokenize will error instead of falling back to uuids
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dataframe:
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backend: "pandas" # Backend dataframe library for input IO and data creation
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shuffle:
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method: null
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compression: null # compression for on disk-shuffling. Partd supports ZLib, BZ2, SNAPPY
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parquet:
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metadata-task-size-local: 512 # Number of files per local metadata-processing task
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metadata-task-size-remote: 1 # Number of files per remote metadata-processing task
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minimum-partition-size: 75000000
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convert-string: null # Whether to convert string-like data to pyarrow strings
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query-planning: null # Whether to use dask-expr
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array:
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backend: "numpy" # Backend array library for input IO and data creation
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chunk-size: "128MiB"
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chunk-size-tolerance: 1.25 # Tolerance for different algorithms when creating output chunks.
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rechunk:
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method: null # Rechunking method to use
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threshold: 4
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svg:
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size: 120 # pixels
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slicing:
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split-large-chunks: null # How to handle large output chunks in slicing. Warns by default.
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query-planning: null # Whether to use dask-expr
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optimization:
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annotations:
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fuse: true # Automatically fuse compatible annotations on layers
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fuse:
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active: null # Treat as false for dask.dataframe, true for everything else
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ave-width: 1
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max-width: null # 1.5 + ave_width * log(ave_width + 1)
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max-height: .inf
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max-depth-new-edges: null # ave_width * 1.5
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subgraphs: null # true for dask.dataframe, false for everything else
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rename-keys: true
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admin:
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traceback:
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shorten:
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- concurrent[\\\/]futures[\\\/]
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- dask[\\\/](base|core|local|multiprocessing|optimization|threaded|utils)\.py
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- dask[\\\/]array[\\\/]core\.py
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- dask[\\\/]dataframe[\\\/](core|methods)\.py
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- distributed[\\\/](client|scheduler|utils|worker)\.py
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- tornado[\\\/]gen\.py
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- pandas[\\\/]core[\\\/]
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