refactor Dask executor to use HighLevelGraph
MODIFY
pangeo_forge_recipes/executors/dask.py
pangeo_forge_recipes/executors/dask.py
-from typing import Any, Dict, Tuple, Union
+from typing import Any, Dict, Set, Tuple, Union
import dask
from dask.delayed import Delayed
+from dask.highlevelgraph import HighLevelGraph
from .base import Pipeline, PipelineExecutor
@@ -25,34 +26,53 @@ def checkpoint(*args):
return
+def append_token(task_name: str, token: str) -> str:
+ return f"{task_name}-{token}"
+
+
class DaskPipelineExecutor(PipelineExecutor[Delayed]):
@staticmethod
def compile(pipeline: Pipeline):
token = dask.base.tokenize(pipeline)
+
+ # we are constructing a HighLevelGraph from scratch
+ # https://docs.dask.org/en/latest/high-level-graphs.html
+ layers = dict() # type: Dict[str, Dict[Union[str, Tuple[str, int]], Any]]
+ dependencies = dict() # type: Dict[str, Set[str]]
+
+ # start with just the config as a standalone layer
# create a custom delayed object for the config
- config_task = f"config-{token}"
- dsk = {config_task: pipeline.config} # type: Dict[Union[str, Tuple[str, int]], Any]
+ config_task = "config"
+ config_token = append_token(config_task, token)
+ layers[config_task] = {config_token: pipeline.config}
+ dependencies[config_task] = set()
- prev_layer = tuple() # type: Tuple[str, ...]
+ prev_token = () # type: Tuple[str, ...]
+ prev_task = config_task
for stage in pipeline.stages:
- stage_name = f"{stage.name}-{token}"
+ stage_token = append_token(stage.name, token)
+ stage_graph = {} # type: Dict[Union[str, Tuple[str, int]], Any]
if stage.mappable is None:
func = wrap_standalone_task(stage.function)
- dsk[stage_name] = (func, config_task) + prev_layer
- prev_layer = (stage_name,)
+ stage_graph[stage_token] = (func, config_token) + prev_token
+ prev_token = (stage_token,)
else:
func = wrap_map_task(stage.function)
checkpoint_args = []
for i, m in enumerate(stage.mappable):
- key = (stage_name, i)
- dsk[key] = (func, m, config_task) + prev_layer
+ key = (stage.name, i)
+ stage_graph[key] = (func, m, config_token) + prev_token
checkpoint_args.append(key)
checkpoint_key = f"{stage.name}-checkpoint-{token}"
- dsk[checkpoint_key] = (checkpoint, *checkpoint_args)
- prev_layer = (checkpoint_key,)
-
- delayed = Delayed(prev_layer[0], dsk)
+ stage_graph[checkpoint_key] = (checkpoint, *checkpoint_args)
+ prev_token = (checkpoint_key,)
+ layers[stage.name] = stage_graph
+ dependencies[stage.name] = {prev_task}
+ prev_task = stage.name
+
+ hlg = HighLevelGraph(layers, dependencies)
+ delayed = Delayed(prev_token[0], hlg)
return delayed
@staticmethod

refactor Dask executor to use HighLevelGraph