from __future__ import annotations
import logging
import math
import operator
import os
from collections import OrderedDict, defaultdict
from collections.abc import Iterable
from datetime import datetime
from numbers import Number
from typing import Any, TypeVar
import numpy as np
from bokeh.core.properties import value, without_property_validation
from bokeh.io import curdoc
from bokeh.layouts import column, row
from bokeh.models import (
AdaptiveTicker,
Arrow,
BasicTicker,
BoxSelectTool,
BoxZoomTool,
CDSView,
ColorBar,
ColumnDataSource,
CustomJSHover,
DataRange1d,
FactorRange,
GroupFilter,
HelpTool,
HoverTool,
HTMLTemplateFormatter,
MultiChoice,
NumberFormatter,
NumeralTickFormatter,
OpenURL,
PanTool,
Range1d,
ResetTool,
Select,
TabPanel,
Tabs,
TapTool,
Title,
VeeHead,
WheelZoomTool,
)
from bokeh.models.widgets import DataTable, TableColumn
from bokeh.models.widgets.markups import Div
from bokeh.palettes import Viridis11
from bokeh.plotting import figure
from bokeh.themes import Theme
from bokeh.transform import cumsum, factor_cmap, linear_cmap, stack
from jinja2 import Environment, FileSystemLoader
from tlz import curry, pipe, second, valmap
from tlz.curried import concat, groupby, map
import dask
from dask import config
from dask.utils import (
format_bytes,
format_time,
funcname,
key_split,
parse_bytes,
parse_timedelta,
)
from distributed.core import Status
from distributed.dashboard.components import add_periodic_callback
from distributed.dashboard.components.shared import (
DashboardComponent,
ProfileServer,
ProfileTimePlot,
SystemMonitor,
)
from distributed.dashboard.utils import (
_DATATABLE_STYLESHEETS_KWARGS,
PROFILING,
transpose,
update,
)
from distributed.diagnostics.graph_layout import GraphLayout
from distributed.diagnostics.progress import GroupTiming
from distributed.diagnostics.progress_stream import color_of, progress_quads
from distributed.diagnostics.task_stream import TaskStreamPlugin
from distributed.diagnostics.task_stream import color_of as ts_color_of
from distributed.diagnostics.task_stream import colors as ts_color_lookup
from distributed.metrics import time
from distributed.scheduler import Scheduler
from distributed.spans import SpansSchedulerExtension
from distributed.utils import Log, log_errors, url_escape
if dask.config.get("distributed.dashboard.export-tool"):
from distributed.dashboard.export_tool import ExportTool
else:
ExportTool = None # type: ignore
T = TypeVar("T")
logger = logging.getLogger(__name__)
env = Environment(
loader=FileSystemLoader(
os.path.join(os.path.dirname(__file__), "..", "..", "http", "templates")
)
)
BOKEH_THEME = Theme(
filename=os.path.join(os.path.dirname(__file__), "..", "theme.yaml")
)
TICKS_1024 = {"base": 1024, "mantissas": [1, 2, 4, 8, 16, 32, 64, 128, 256, 512]}
XLABEL_ORIENTATION = -math.pi / 9 # slanted downwards 20 degrees
logos_dict = {
"numpy": "statics/images/numpy.png",
"pandas": "statics/images/pandas.png",
"builtins": "statics/images/python.png",
}
class Occupancy(DashboardComponent):
"""Occupancy (in time) per worker"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"occupancy": [0, 0],
"worker": ["a", "b"],
"x": [0.0, 0.1],
"y": [1, 2],
"ms": [1, 2],
"color": ["red", "blue"],
"escaped_worker": ["a", "b"],
}
)
self.root = figure(
title="Occupancy",
tools="",
toolbar_location="above",
x_axis_type="datetime",
min_border_bottom=50,
**kwargs,
)
rect = self.root.rect(
source=self.source, x="x", width="ms", y="y", height=0.9, color="color"
)
rect.nonselection_glyph = None
self.root.xaxis.minor_tick_line_alpha = 0
self.root.yaxis.visible = False
self.root.ygrid.visible = False
# fig.xaxis[0].formatter = NumeralTickFormatter(format='0.0s')
self.root.x_range.start = 0
tap = TapTool(callback=OpenURL(url="./info/worker/@escaped_worker.html"))
hover = HoverTool()
hover.tooltips = "@worker : @occupancy s."
hover.point_policy = "follow_mouse"
self.root.add_tools(hover, tap)
@without_property_validation
@log_errors
def update(self):
workers = self.scheduler.workers.values()
y = list(range(len(workers)))
occupancy = [ws.occupancy for ws in workers]
ms = [occ * 1000 for occ in occupancy]
x = [occ / 500 for occ in occupancy]
total = sum(occupancy)
color = []
for ws in workers:
if ws in self.scheduler.idle:
color.append("red")
elif ws in self.scheduler.saturated:
color.append("green")
else:
color.append("blue")
if total:
self.root.title.text = (
f"Occupancy -- total time: {format_time(total)} "
f"wall time: {format_time(total / self.scheduler.total_nthreads)}"
)
else:
self.root.title.text = "Occupancy"
if occupancy:
result = {
"occupancy": occupancy,
"worker": [ws.address for ws in workers],
"ms": ms,
"color": color,
"escaped_worker": [url_escape(ws.address) for ws in workers],
"x": x,
"y": y,
}
update(self.source, result)
class ProcessingHistogram(DashboardComponent):
"""How many tasks are on each worker"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.last = 0
self.scheduler = scheduler
self.source = ColumnDataSource(
{"left": [1, 2], "right": [10, 10], "top": [0, 0]}
)
self.root = figure(
title="Tasks Processing (count)",
name="processing",
y_axis_label="frequency",
tools="",
**kwargs,
)
self.root.xaxis.minor_tick_line_alpha = 0
self.root.ygrid.visible = False
self.root.toolbar_location = None
self.root.quad(
source=self.source,
left="left",
right="right",
bottom=0,
top="top",
color="deepskyblue",
fill_alpha=0.5,
)
@without_property_validation
def update(self):
L = [len(ws.processing) for ws in self.scheduler.workers.values()]
counts, x = np.histogram(L, bins=40)
self.source.data.update({"left": x[:-1], "right": x[1:], "top": counts})
class MemoryColor:
"""Change the color of the memory bars from blue to orange when process memory goes
above the ``target`` threshold and to red when the worker pauses.
Workers in ``closing_gracefully`` state will also be orange.
If ``target`` is disabled, change to orange on ``spill`` instead.
If spilling is completely disabled, never turn orange.
If pausing is disabled, change to red when passing the ``terminate`` threshold
instead. If both pause and terminate are disabled, turn red when passing
``memory_limit``.
Note
----
A worker will start spilling when managed memory alone passes the target threshold.
However, here we're switching to orange when the process memory goes beyond target,
which is usually earlier.
This is deliberate for the sake of simplicity and also because, when the process
memory passes the spill threshold, it will keep spilling until it falls below the
target threshold - so it's not completely wrong. Again, we don't want to track
the hysteresis cycle of the spill system here for the sake of simplicity.
In short, orange should be treated as "the worker *may* be spilling".
"""
orange: float
red: float
def __init__(
self, neutral_color="blue", target_color="orange", terminated_color="red"
):
self.neutral_color = neutral_color
self.target_color = target_color
self.terminated_color = terminated_color
target = dask.config.get("distributed.worker.memory.target")
spill = dask.config.get("distributed.worker.memory.spill")
terminate = dask.config.get("distributed.worker.memory.terminate")
# These values can be False. It's also common to configure them to impossibly
# high values to achieve the same effect.
self.orange = min(target or math.inf, spill or math.inf)
self.red = min(terminate or math.inf, 1.0)
def _memory_color(self, current: int, limit: int, status: Status) -> str:
if status != Status.running:
return self.terminated_color
if not limit:
return self.neutral_color
if current >= limit * self.red:
return self.terminated_color
if current >= limit * self.orange:
return self.target_color
return self.neutral_color
class ClusterMemory(DashboardComponent, MemoryColor):
"""Total memory usage on the cluster"""
@log_errors
def __init__(self, scheduler, width=600, **kwargs):
DashboardComponent.__init__(self)
MemoryColor.__init__(self)
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"width": [0] * 4,
"x": [0] * 4,
"y": [0] * 4,
"color": ["blue", "blue", "blue", "grey"],
"alpha": [1, 0.7, 0.4, 1],
"proc_memory": [0] * 4,
"managed": [0] * 4,
"unmanaged_old": [0] * 4,
"unmanaged_recent": [0] * 4,
"spilled": [0] * 4,
}
)
self.root = figure(
title="Bytes stored on cluster",
tools="",
width=int(width / 2),
name="cluster_memory",
min_border_bottom=50,
**kwargs,
)
rect = self.root.rect(
source=self.source,
x="x",
y="y",
width="width",
height=0.9,
color="color",
alpha="alpha",
)
rect.nonselection_glyph = None
self.root.axis[0].ticker = BasicTicker(**TICKS_1024)
self.root.xaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.root.xaxis.major_label_orientation = XLABEL_ORIENTATION
self.root.xaxis.minor_tick_line_alpha = 0
self.root.x_range = Range1d(start=0)
self.root.yaxis.visible = False
self.root.ygrid.visible = False
self.root.toolbar_location = "above"
self.root.yaxis.visible = False
hover = HoverTool(
point_policy="follow_mouse",
tooltips="""
Process memory (RSS):
@proc_memory{0.00 b}
Managed:
@managed{0.00 b}
Unmanaged (old):
@unmanaged_old{0.00 b}
Unmanaged (recent):
@unmanaged_recent{0.00 b}
Spilled to disk:
@spilled{0.00 b}
""",
)
help_ = HelpTool(
redirect="https://docs.dask.org/en/stable/dashboard.html#bytes-stored-and-bytes-per-worker",
description="Description of bytes stored plots",
)
self.root.add_tools(hover, help_)
def _cluster_memory_color(self) -> str:
colors = {
self._memory_color(
current=ws.memory.process,
limit=getattr(ws, "memory_limit", 0),
status=ws.status,
)
for ws in self.scheduler.workers.values()
}
assert colors.issubset({"red", "orange", "blue"})
if "red" in colors:
return "red"
elif "orange" in colors:
return "orange"
else:
return "blue"
@without_property_validation
@log_errors
def update(self):
limit = sum(ws.memory_limit for ws in self.scheduler.workers.values())
meminfo = self.scheduler.memory
color = self._cluster_memory_color()
width = [
meminfo.managed,
meminfo.unmanaged_old,
meminfo.unmanaged_recent,
meminfo.spilled,
]
result = {
"width": width,
"x": [sum(width[:i]) + w / 2 for i, w in enumerate(width)],
"color": [color, color, color, "grey"],
"proc_memory": [meminfo.process] * 4,
"managed": [meminfo.managed] * 4,
"unmanaged_old": [meminfo.unmanaged_old] * 4,
"unmanaged_recent": [meminfo.unmanaged_recent] * 4,
"spilled": [meminfo.spilled] * 4,
}
x_end = max(limit, meminfo.process + meminfo.spilled)
self.root.x_range.end = x_end
title = f"Bytes stored: {format_bytes(meminfo.process)}"
if meminfo.spilled:
title += f" + {format_bytes(meminfo.spilled)} spilled to disk"
self.root.title.text = title
update(self.source, result)
class WorkersMemory(DashboardComponent, MemoryColor):
"""Memory usage for single workers"""
@log_errors
def __init__(self, scheduler, width=600, **kwargs):
DashboardComponent.__init__(self)
MemoryColor.__init__(self)
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"width": [],
"x": [],
"y": [],
"color": [],
"alpha": [],
"worker": [],
"escaped_worker": [],
"proc_memory": [],
"managed": [],
"unmanaged_old": [],
"unmanaged_recent": [],
"spilled": [],
}
)
self.root = figure(
title="Bytes stored per worker",
tools="",
width=int(width / 2),
name="workers_memory",
min_border_bottom=50,
**kwargs,
)
rect = self.root.rect(
source=self.source,
x="x",
y="y",
width="width",
height=0.9,
color="color",
fill_alpha="alpha",
line_width=0,
)
rect.nonselection_glyph = None
self.root.axis[0].ticker = BasicTicker(**TICKS_1024)
self.root.xaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.root.xaxis.major_label_orientation = XLABEL_ORIENTATION
self.root.xaxis.minor_tick_line_alpha = 0
self.root.x_range = Range1d(start=0)
self.root.yaxis.visible = False
self.root.ygrid.visible = False
self.root.toolbar_location = None
tap = TapTool(callback=OpenURL(url="./info/worker/@escaped_worker.html"))
self.root.add_tools(tap)
hover = HoverTool(
point_policy="follow_mouse",
tooltips="""
Worker:
@worker
Process memory (RSS):
@proc_memory{0.00 b}
Managed:
@managed{0.00 b}
Unmanaged (old):
@unmanaged_old{0.00 b}
Unmanaged (recent):
@unmanaged_recent{0.00 b}
Spilled to disk:
@spilled{0.00 b}
""",
)
self.root.add_tools(hover)
@without_property_validation
@log_errors
def update(self):
def quadlist(i: Iterable[T]) -> list[T]:
out = []
for ii in i:
out += [ii, ii, ii, ii]
return out
workers = self.scheduler.workers.values()
width = []
x = []
color = []
max_limit = 0
procmemory = []
managed = []
spilled = []
unmanaged_old = []
unmanaged_recent = []
for ws in workers:
meminfo = ws.memory
limit = getattr(ws, "memory_limit", 0)
max_limit = max(max_limit, limit, meminfo.process + meminfo.spilled)
color_i = self._memory_color(meminfo.process, limit, ws.status)
width += [
meminfo.managed,
meminfo.unmanaged_old,
meminfo.unmanaged_recent,
meminfo.spilled,
]
x += [sum(width[-4:i]) + width[i] / 2 for i in range(-4, 0)]
color += [color_i, color_i, color_i, "grey"]
# memory info
procmemory.append(meminfo.process)
managed.append(meminfo.managed)
unmanaged_old.append(meminfo.unmanaged_old)
unmanaged_recent.append(meminfo.unmanaged_recent)
spilled.append(meminfo.spilled)
result = {
"width": width,
"x": x,
"color": color,
"alpha": [1, 0.7, 0.4, 1] * len(workers),
"worker": quadlist(ws.address for ws in workers),
"escaped_worker": quadlist(url_escape(ws.address) for ws in workers),
"y": quadlist(range(len(workers))),
"proc_memory": quadlist(procmemory),
"managed": quadlist(managed),
"unmanaged_old": quadlist(unmanaged_old),
"unmanaged_recent": quadlist(unmanaged_recent),
"spilled": quadlist(spilled),
}
# Remove rectangles with width=0
result = {k: [vi for vi, w in zip(v, width) if w] for k, v in result.items()}
self.root.x_range.end = max_limit
update(self.source, result)
class WorkersMemoryHistogram(DashboardComponent):
"""Histogram of memory usage, showing how many workers there are in each bucket of
usage. Replaces the per-worker graph when there are >= 50 workers.
"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.last = 0
self.scheduler = scheduler
self.source = ColumnDataSource(
{"left": [1, 2], "right": [10, 10], "top": [0, 0]}
)
self.root = figure(
title="Bytes stored per worker",
name="workers_memory",
y_axis_label="frequency",
tools="",
**kwargs,
)
self.root.xaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.root.xaxis.ticker = AdaptiveTicker(**TICKS_1024)
self.root.xaxis.major_label_orientation = XLABEL_ORIENTATION
self.root.xaxis.minor_tick_line_alpha = 0
self.root.ygrid.visible = False
self.root.toolbar_location = None
self.root.quad(
source=self.source,
left="left",
right="right",
bottom=0,
top="top",
color="deepskyblue",
fill_alpha=0.5,
)
@without_property_validation
def update(self):
nbytes = np.asarray(
[ws.metrics["memory"] for ws in self.scheduler.workers.values()]
)
counts, x = np.histogram(nbytes, bins=40)
d = {"left": x[:-1], "right": x[1:], "top": counts}
update(self.source, d)
class WorkersTransferBytes(DashboardComponent):
"""Size of open data transfers from/to other workers per worker"""
@log_errors
def __init__(self, scheduler, width=600, **kwargs):
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"escaped_worker": [],
"transfer_incoming_bytes": [],
"transfer_outgoing_bytes": [],
"worker": [],
"y_incoming": [],
"y_outgoing": [],
}
)
self.root = figure(
title=f"Bytes transferring: {format_bytes(0)}",
tools="",
width=int(width / 2),
name="workers_transfer_bytes",
min_border_bottom=50,
**kwargs,
)
# transfer_incoming_bytes
self.root.hbar(
name="transfer_incoming_bytes",
y="y_incoming",
right="transfer_incoming_bytes",
line_color=None,
left=0,
height=0.5,
fill_color="red",
source=self.source,
)
# transfer_outgoing_bytes
self.root.hbar(
name="transfer_outgoing_bytes",
y="y_outgoing",
right="transfer_outgoing_bytes",
line_color=None,
left=0,
height=0.5,
fill_color="blue",
source=self.source,
)
self.root.axis[0].ticker = BasicTicker(**TICKS_1024)
self.root.xaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.root.xaxis.major_label_orientation = XLABEL_ORIENTATION
self.root.xaxis.minor_tick_line_alpha = 0
self.root.x_range = Range1d(start=0)
self.root.yaxis.visible = False
self.root.ygrid.visible = False
self.root.toolbar_location = None
tap = TapTool(callback=OpenURL(url="./info/worker/@escaped_worker.html"))
hover = HoverTool(
tooltips=[
("Worker", "@worker"),
("Incoming", "@transfer_incoming_bytes{0.00 b}"),
("Outgoing", "@transfer_outgoing_bytes{0.00 b}"),
],
point_policy="follow_mouse",
)
self.root.add_tools(hover, tap)
@without_property_validation
@log_errors
def update(self):
wss = self.scheduler.workers.values()
h = 0.1
y_incoming = [i + 0.75 + i * h for i in range(len(wss))]
y_outgoing = [i + 0.25 + i * h for i in range(len(wss))]
transfer_incoming_bytes = [
ws.metrics["transfer"]["incoming_bytes"] for ws in wss
]
transfer_outgoing_bytes = [
ws.metrics["transfer"]["outgoing_bytes"] for ws in wss
]
workers = [ws.address for ws in wss]
escaped_workers = [url_escape(worker) for worker in workers]
if wss:
x_limit = max(
max(transfer_incoming_bytes),
max(transfer_outgoing_bytes),
max(ws.memory_limit for ws in wss),
)
else:
x_limit = 0
self.root.x_range.end = x_limit
result = {
"escaped_worker": escaped_workers,
"transfer_incoming_bytes": transfer_incoming_bytes,
"transfer_outgoing_bytes": transfer_outgoing_bytes,
"worker": workers,
"y_incoming": y_incoming,
"y_outgoing": y_outgoing,
}
self.root.title.text = (
f"Bytes transferring: {format_bytes(sum(transfer_incoming_bytes))}"
)
update(self.source, result)
class Hardware(DashboardComponent):
"""Occupancy (in time) per worker"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
# Disk
self.disk_source = ColumnDataSource(
{
"size": [],
"bandwidth": [],
}
)
self.disk_figure = figure(
title="Disk Bandwidth -- Computing ...",
tools="",
toolbar_location="above",
x_range=FactorRange(factors=[]),
**kwargs,
)
self.disk_figure.vbar(
x="size", top="bandwidth", width=0.9, source=self.disk_source
)
hover = HoverTool(
mode="vline", tooltips=[("Bandwidth", "@bandwidth{0.00 b}/s")]
)
self.disk_figure.add_tools(hover)
self.disk_figure.yaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.disk_figure.xgrid.visible = False
# Memory
self.memory_source = ColumnDataSource(
{
"size": [],
"bandwidth": [],
}
)
self.memory_figure = figure(
title="Memory Bandwidth -- Computing ...",
tools="",
toolbar_location="above",
x_range=FactorRange(factors=[]),
**kwargs,
)
self.memory_figure.vbar(
x="size", top="bandwidth", width=0.9, source=self.memory_source
)
hover = HoverTool(
mode="vline", tooltips=[("Bandwidth", "@bandwidth{0.00 b}/s")]
)
self.memory_figure.add_tools(hover)
self.memory_figure.yaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.memory_figure.xgrid.visible = False
# Network
self.network_source = ColumnDataSource(
{
"size": [],
"bandwidth": [],
}
)
self.network_figure = figure(
title="Network Bandwidth -- Computing ...",
tools="",
toolbar_location="above",
x_range=FactorRange(factors=[]),
**kwargs,
)
self.network_figure.vbar(
x="size", top="bandwidth", width=0.9, source=self.network_source
)
hover = HoverTool(
mode="vline", tooltips=[("Bandwidth", "@bandwidth{0.00 b}/s")]
)
self.network_figure.add_tools(hover)
self.network_figure.yaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.network_figure.xgrid.visible = False
self.root = row(
self.memory_figure,
self.disk_figure,
self.network_figure,
)
self.memory_data = {
"size": [],
"bandwidth": [],
}
self.disk_data = {
"size": [],
"bandwidth": [],
}
self.network_data = {
"size": [],
"bandwidth": [],
}
async def f():
result = await self.scheduler.benchmark_hardware()
for size in sorted(result["disk"], key=parse_bytes):
bandwidth = result["disk"][size]
self.disk_data["size"].append(size)
self.disk_data["bandwidth"].append(bandwidth)
for size in sorted(result["memory"], key=parse_bytes):
bandwidth = result["memory"][size]
self.memory_data["size"].append(size)
self.memory_data["bandwidth"].append(bandwidth)
for size in sorted(result["network"], key=parse_bytes):
bandwidth = result["network"][size]
self.network_data["size"].append(size)
self.network_data["bandwidth"].append(bandwidth)
self.scheduler.loop.add_callback(f)
def update(self):
if (
not self.disk_data["size"]
or self.disk_figure.title.text == "Disk Bandwidth"
):
return
self.network_figure.x_range.factors = self.network_data["size"]
self.disk_figure.x_range.factors = self.disk_data["size"]
self.memory_figure.x_range.factors = self.memory_data["size"]
update(self.disk_source, self.disk_data)
update(self.memory_source, self.memory_data)
update(self.network_source, self.network_data)
self.memory_figure.title.text = "Memory Bandwidth"
self.disk_figure.title.text = "Disk Bandwidth"
self.network_figure.title.text = "Network Bandwidth"
class BandwidthTypes(DashboardComponent):
"""Bar chart showing bandwidth per type"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.last = 0
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"bandwidth": [1, 2],
"bandwidth-half": [0.5, 1],
"type": ["a", "b"],
"bandwidth_text": ["1", "2"],
}
)
self.root = figure(
title="Bandwidth by Type",
tools="",
name="bandwidth_type_histogram",
y_range=["a", "b"],
**kwargs,
)
self.root.xaxis.major_label_orientation = -0.5
rect = self.root.rect(
source=self.source,
x="bandwidth-half",
y="type",
width="bandwidth",
height=0.9,
color="blue",
)
self.root.x_range.start = 0
self.root.xaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.root.xaxis.ticker = AdaptiveTicker(**TICKS_1024)
rect.nonselection_glyph = None
self.root.xaxis.minor_tick_line_alpha = 0
self.root.ygrid.visible = False
self.root.toolbar_location = None
hover = HoverTool()
hover.tooltips = "@type: @bandwidth_text / s"
hover.point_policy = "follow_mouse"
self.root.add_tools(hover)
@without_property_validation
@log_errors
def update(self):
bw = self.scheduler.bandwidth_types
self.root.y_range.factors = list(sorted(bw))
result = {
"bandwidth": list(bw.values()),
"bandwidth-half": [b / 2 for b in bw.values()],
"type": list(bw.keys()),
"bandwidth_text": [format_bytes(x) for x in bw.values()],
}
self.root.title.text = "Bandwidth: " + format_bytes(self.scheduler.bandwidth)
update(self.source, result)
class BandwidthWorkers(DashboardComponent):
"""How many tasks are on each worker"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.last = 0
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"bandwidth": [1, 2],
"source": ["a", "b"],
"destination": ["a", "b"],
"bandwidth_text": ["1", "2"],
}
)
values = [hex(x)[2:] for x in range(64, 256)][::-1]
mapper = linear_cmap(
field_name="bandwidth",
palette=["#" + x + x + "FF" for x in values],
low=0,
high=1,
)
self.root = figure(
title="Bandwidth by Worker",
tools="",
name="bandwidth_worker_heatmap",
x_range=["a", "b"],
y_range=["a", "b"],
**kwargs,
)
self.root.xaxis.major_label_orientation = XLABEL_ORIENTATION
self.root.rect(
source=self.source,
x="source",
y="destination",
color=mapper,
height=1,
width=1,
)
self.color_map = mapper["transform"]
color_bar = ColorBar(
color_mapper=self.color_map,
label_standoff=12,
border_line_color=None,
location=(0, 0),
)
color_bar.formatter = NumeralTickFormatter(format="0.0 b")
color_bar.ticker = AdaptiveTicker(**TICKS_1024)
self.root.add_layout(color_bar, "right")
self.root.toolbar_location = None
hover = HoverTool()
hover.tooltips = """
Source: @source
Destination: @destination
Bandwidth: @bandwidth_text / s
"""
hover.point_policy = "follow_mouse"
self.root.add_tools(hover)
@without_property_validation
@log_errors
def update(self):
bw = self.scheduler.bandwidth_workers
if not bw:
return
def name(address):
try:
ws = self.scheduler.workers[address]
except KeyError:
return address
if ws.name is not None:
return str(ws.name)
return address
x, y, value = zip(*((name(a), name(b), c) for (a, b), c in bw.items()))
self.color_map.high = max(value)
factors = list(sorted(set(x + y)))
self.root.x_range.factors = factors
self.root.y_range.factors = factors[::-1]
result = {
"source": x,
"destination": y,
"bandwidth": value,
"bandwidth_text": list(map(format_bytes, value)),
}
self.root.title.text = "Bandwidth: " + format_bytes(self.scheduler.bandwidth)
update(self.source, result)
class WorkerNetworkBandwidth(DashboardComponent):
"""Worker network bandwidth chart
Plots horizontal bars with the host_net_io.read_bps and host_net_io.write_bps worker
state
"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"y_read": [],
"y_write": [],
"x_read": [],
"x_write": [],
"x_read_disk": [],
"x_write_disk": [],
}
)
self.bandwidth = figure(
title="Worker Network Bandwidth",
tools="",
name="worker_network_bandwidth",
**kwargs,
)
# host_net_io.read_bps
self.bandwidth.hbar(
y="y_read",
right="x_read",
line_color=None,
left=0,
height=0.5,
fill_color="red",
legend_label="read",
source=self.source,
)
# host_net_io.write_bps
self.bandwidth.hbar(
y="y_write",
right="x_write",
line_color=None,
left=0,
height=0.5,
fill_color="blue",
legend_label="write",
source=self.source,
)
self.bandwidth.axis[0].ticker = BasicTicker(**TICKS_1024)
self.bandwidth.xaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.bandwidth.xaxis.major_label_orientation = XLABEL_ORIENTATION
self.bandwidth.xaxis.minor_tick_line_alpha = 0
self.bandwidth.x_range = Range1d(start=0)
self.bandwidth.yaxis.visible = False
self.bandwidth.ygrid.visible = False
self.bandwidth.toolbar_location = None
self.disk = figure(
title="Workers Disk",
tools="",
name="worker_disk",
**kwargs,
)
# host_disk_io.read_bps
self.disk.hbar(
y="y_read",
right="x_read_disk",
line_color=None,
left=0,
height=0.5,
fill_color="red",
legend_label="read",
source=self.source,
)
# host_disk_io.write_bps
self.disk.hbar(
y="y_write",
right="x_write_disk",
line_color=None,
left=0,
height=0.5,
fill_color="blue",
legend_label="write",
source=self.source,
)
self.disk.axis[0].ticker = BasicTicker(**TICKS_1024)
self.disk.xaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.disk.xaxis.major_label_orientation = XLABEL_ORIENTATION
self.disk.xaxis.minor_tick_line_alpha = 0
self.disk.x_range = Range1d(start=0)
self.disk.yaxis.visible = False
self.disk.ygrid.visible = False
self.disk.toolbar_location = None
@without_property_validation
@log_errors
def update(self):
workers = self.scheduler.workers.values()
h = 0.1
y_read = [i + 0.75 + i * h for i in range(len(workers))]
y_write = [i + 0.25 + i * h for i in range(len(workers))]
x_read = []
x_write = []
x_read_disk = []
x_write_disk = []
for ws in workers:
x_read.append(ws.metrics["host_net_io"]["read_bps"])
x_write.append(ws.metrics["host_net_io"]["write_bps"])
x_read_disk.append(ws.metrics.get("host_disk_io", {}).get("read_bps", 0))
x_write_disk.append(ws.metrics.get("host_disk_io", {}).get("write_bps", 0))
if self.scheduler.workers:
self.bandwidth.x_range.end = max(
max(x_read),
max(x_write),
100_000_000,
0.95 * self.bandwidth.x_range.end,
)
self.disk.x_range.end = max(
max(x_read_disk),
max(x_write_disk),
100_000_000,
0.95 * self.disk.x_range.end,
)
else:
self.bandwidth.x_range.end = 100_000_000
self.disk.x_range.end = 100_000_000
result = {
"y_read": y_read,
"y_write": y_write,
"x_read": x_read,
"x_write": x_write,
"x_read_disk": x_read_disk,
"x_write_disk": x_write_disk,
}
update(self.source, result)
class SystemTimeseries(DashboardComponent):
"""Timeseries for worker network bandwidth, cpu, memory and disk.
bandwidth
Plots the average of host_net_io.read_bps and host_net_io.write_bps for the
workers as a function of time
cpu
Plots the average of cpu for the workers as a function of time
memory
Plots the average of memory for the workers as a function of time
disk
Plots the average of host_disk_io.read_bps and host_disk_io.write_bps for the
workers as a function of time
The metrics plotted come from the aggregation of from ws.metrics[key] for ws in
scheduler.workers.values() divided by number of workers.
"""
@log_errors
def __init__(self, scheduler, follow_interval=20000, **kwargs):
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"time": [],
"host_net_io.read_bps": [],
"host_net_io.write_bps": [],
"cpu": [],
"memory": [],
"host_disk_io.read_bps": [],
"host_disk_io.write_bps": [],
}
)
update(self.source, self.get_data())
x_range = DataRange1d(
follow="end", follow_interval=follow_interval, range_padding=0
)
tools = "reset, xpan, xwheel_zoom"
self.bandwidth = figure(
title="Worker Network Bandwidth (average)",
x_axis_type="datetime",
tools=tools,
x_range=x_range,
name="worker_network_bandwidth-timeseries",
**kwargs,
)
self.bandwidth.line(
source=self.source,
x="time",
y="host_net_io.read_bps",
color="red",
legend_label="read (mean)",
)
self.bandwidth.line(
source=self.source,
x="time",
y="host_net_io.write_bps",
color="blue",
legend_label="write (mean)",
)
self.bandwidth.legend.location = "top_left"
self.bandwidth.yaxis.axis_label = "bytes / second"
self.bandwidth.yaxis[0].formatter = NumeralTickFormatter(format="0.0b")
self.bandwidth.y_range.start = 0
self.bandwidth.yaxis.minor_tick_line_alpha = 0
self.bandwidth.xgrid.visible = False
self.cpu = figure(
title="Worker CPU Utilization (average)",
x_axis_type="datetime",
tools=tools,
x_range=x_range,
name="worker_cpu-timeseries",
**kwargs,
)
self.cpu.line(
source=self.source,
x="time",
y="cpu",
)
self.cpu.yaxis.axis_label = "Utilization"
self.cpu.y_range.start = 0
self.cpu.yaxis.minor_tick_line_alpha = 0
self.cpu.xgrid.visible = False
self.memory = figure(
title="Worker Memory Use (average)",
x_axis_type="datetime",
tools=tools,
x_range=x_range,
name="worker_memory-timeseries",
**kwargs,
)
self.memory.line(
source=self.source,
x="time",
y="memory",
)
self.memory.yaxis.axis_label = "Bytes"
self.memory.yaxis[0].formatter = NumeralTickFormatter(format="0.0b")
self.memory.y_range.start = 0
self.memory.yaxis.minor_tick_line_alpha = 0
self.memory.xgrid.visible = False
self.disk = figure(
title="Worker Disk Bandwidth (average)",
x_axis_type="datetime",
tools=tools,
x_range=x_range,
name="worker_disk-timeseries",
**kwargs,
)
self.disk.line(
source=self.source,
x="time",
y="host_disk_io.read_bps",
color="red",
legend_label="read (mean)",
)
self.disk.line(
source=self.source,
x="time",
y="host_disk_io.write_bps",
color="blue",
legend_label="write (mean)",
)
self.disk.legend.location = "top_left"
self.disk.yaxis.axis_label = "bytes / second"
self.disk.yaxis[0].formatter = NumeralTickFormatter(format="0.0b")
self.disk.y_range.start = 0
self.disk.yaxis.minor_tick_line_alpha = 0
self.disk.xgrid.visible = False
def get_data(self):
workers = self.scheduler.workers.values()
net_read_bps = 0
net_write_bps = 0
cpu = 0
memory = 0
disk_read_bps = 0
disk_write_bps = 0
time = 0
for ws in workers:
net_read_bps += ws.metrics["host_net_io"]["read_bps"]
net_write_bps += ws.metrics["host_net_io"]["write_bps"]
cpu += ws.metrics["cpu"]
memory += ws.metrics["memory"]
disk_read_bps += ws.metrics.get("host_disk_io", {}).get("read_bps", 0)
disk_write_bps += ws.metrics.get("host_disk_io", {}).get("write_bps", 0)
time += ws.metrics["time"]
result = {
# use `or` to avoid ZeroDivision when no workers
"time": [time / (len(workers) or 1) * 1000],
"host_net_io.read_bps": [net_read_bps / (len(workers) or 1)],
"host_net_io.write_bps": [net_write_bps / (len(workers) or 1)],
"cpu": [cpu / (len(workers) or 1)],
"memory": [memory / (len(workers) or 1)],
"host_disk_io.read_bps": [disk_read_bps / (len(workers) or 1)],
"host_disk_io.write_bps": [disk_write_bps / (len(workers) or 1)],
}
return result
@without_property_validation
@log_errors
def update(self):
self.source.stream(self.get_data(), 1000)
if self.scheduler.workers:
y_end_cpu = sum(
ws.nthreads or 1 for ws in self.scheduler.workers.values()
) / len(self.scheduler.workers.values())
y_end_mem = sum(
ws.memory_limit for ws in self.scheduler.workers.values()
) / len(self.scheduler.workers.values())
else:
y_end_cpu = 1
y_end_mem = 100_000_000
self.cpu.y_range.end = y_end_cpu * 100
self.memory.y_range.end = y_end_mem
class ComputePerKey(DashboardComponent):
"""Bar chart showing time spend in action by key prefix"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.last = 0
self.scheduler = scheduler
if TaskStreamPlugin.name not in self.scheduler.plugins:
self.scheduler.add_plugin(TaskStreamPlugin(self.scheduler))
compute_data = {
"times": [0.2, 0.1],
"formatted_time": ["0.2 ms", "2.8 us"],
"angles": [3.14, 0.785],
"color": [ts_color_lookup["transfer"], ts_color_lookup["compute"]],
"names": ["sum", "sum_partial"],
}
self.compute_source = ColumnDataSource(data=compute_data)
fig = figure(
title="Compute Time Per Task",
tools="",
name="compute_time_per_key",
x_range=["a", "b"],
**kwargs,
)
rect = fig.vbar(
source=self.compute_source,
x="names",
top="times",
width=0.7,
color="color",
)
fig.y_range.start = 0
fig.yaxis.axis_label = "Time (s)"
fig.yaxis[0].formatter = NumeralTickFormatter(format="0")
fig.yaxis.ticker = AdaptiveTicker(**TICKS_1024)
fig.xaxis.major_label_orientation = XLABEL_ORIENTATION
rect.nonselection_glyph = None
fig.xaxis.minor_tick_line_alpha = 0
fig.xgrid.visible = False
fig.toolbar_location = None
hover = HoverTool()
hover.tooltips = """
Name: @names
Time: @formatted_time
"""
hover.point_policy = "follow_mouse"
fig.add_tools(hover)
fig.add_layout(
Title(
text="Note: tasks less than 2% of max are not displayed",
text_font_style="italic",
),
"below",
)
self.fig = fig
tab1 = TabPanel(child=fig, title="Bar Chart")
fig2 = figure(
title="Compute Time Per Task",
tools="",
name="compute_time_per_key-pie",
x_range=(-0.5, 1.0),
**kwargs,
)
fig2.wedge(
x=0,
y=1,
radius=0.4,
start_angle=cumsum("angles", include_zero=True),
end_angle=cumsum("angles"),
line_color="white",
fill_color="color",
legend_field="names",
source=self.compute_source,
)
fig2.axis.axis_label = None
fig2.axis.visible = False
fig2.grid.grid_line_color = None
fig2.add_layout(
Title(
text="Note: tasks less than 2% of max are not displayed",
text_font_style="italic",
),
"below",
)
hover = HoverTool()
hover.tooltips = """
Name: @names
Time: @formatted_time
"""
hover.point_policy = "follow_mouse"
fig2.add_tools(hover)
self.wedge_fig = fig2
tab2 = TabPanel(child=fig2, title="Pie Chart")
self.root = Tabs(tabs=[tab1, tab2], sizing_mode="stretch_both")
@without_property_validation
@log_errors
def update(self):
compute_times = defaultdict(float)
for name, tp in self.scheduler.task_prefixes.items():
for action, t in tp.all_durations.items():
if action == "compute":
compute_times[name] += t
if not compute_times:
return
# order by largest time first
compute_times = sorted(compute_times.items(), key=second, reverse=True)
# Keep only times which are 2% of max or greater
max_time = compute_times[0][1] * 0.02
compute_colors = []
compute_names = []
compute_time = []
total_time = 0
for name, t in compute_times:
if t < max_time:
break
compute_names.append(name)
compute_colors.append(ts_color_of(name))
compute_time.append(t)
total_time += t
angles = [t / total_time * 2 * math.pi for t in compute_time]
self.fig.x_range.factors = compute_names
compute_result = dict(
angles=angles,
times=compute_time,
color=compute_colors,
names=compute_names,
formatted_time=[format_time(t) for t in compute_time],
)
update(self.compute_source, compute_result)
class AggregateAction(DashboardComponent):
"""Bar chart showing time spend in action by key prefix"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.last = 0
self.scheduler = scheduler
if TaskStreamPlugin.name not in self.scheduler.plugins:
self.scheduler.add_plugin(TaskStreamPlugin(self.scheduler))
action_data = {
"times": [0.2, 0.1],
"formatted_time": ["0.2 ms", "2.8 us"],
"color": [ts_color_lookup["transfer"], ts_color_lookup["compute"]],
"names": ["transfer", "compute"],
}
self.action_source = ColumnDataSource(data=action_data)
self.root = figure(
title="Aggregate Per Action",
tools="",
name="aggregate_per_action",
x_range=["a", "b"],
**kwargs,
)
rect = self.root.vbar(
source=self.action_source,
x="names",
top="times",
width=0.7,
color="color",
)
self.root.y_range.start = 0
self.root.yaxis[0].formatter = NumeralTickFormatter(format="0")
self.root.yaxis.axis_label = "Time (s)"
self.root.yaxis.ticker = AdaptiveTicker(**TICKS_1024)
self.root.xaxis.major_label_orientation = XLABEL_ORIENTATION
self.root.xaxis.major_label_text_font_size = "16px"
rect.nonselection_glyph = None
self.root.xaxis.minor_tick_line_alpha = 0
self.root.xgrid.visible = False
self.root.toolbar_location = None
hover = HoverTool()
hover.tooltips = """
Name: @names
Time: @formatted_time
"""
hover.point_policy = "follow_mouse"
self.root.add_tools(hover)
@without_property_validation
@log_errors
def update(self):
agg_times = defaultdict(float)
for ts in self.scheduler.task_prefixes.values():
for action, t in ts.all_durations.items():
agg_times[action] += t
# order by largest time first
agg_times = sorted(agg_times.items(), key=lambda x: x[1], reverse=True)
agg_colors = list()
agg_names = list()
agg_time = list()
for action, t in agg_times:
agg_names.append(action)
if action == "compute":
agg_colors.append("purple")
else:
agg_colors.append(ts_color_lookup[action])
agg_time.append(t)
self.root.x_range.factors = agg_names
self.root.title.text = "Aggregate Time Per Action"
action_result = dict(
times=agg_time,
color=agg_colors,
names=agg_names,
formatted_time=[format_time(t) for t in agg_time],
)
update(self.action_source, action_result)
class MemoryByKey(DashboardComponent):
"""Bar chart showing memory use by key prefix"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.last = 0
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"name": ["a", "b"],
"nbytes": [100, 1000],
"count": [1, 2],
"color": ["blue", "blue"],
}
)
self.root = figure(
title="Memory Use",
tools="",
name="memory_by_key",
x_range=["a", "b"],
**kwargs,
)
rect = self.root.vbar(
source=self.source, x="name", top="nbytes", width=0.9, color="color"
)
self.root.yaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.root.yaxis.ticker = AdaptiveTicker(**TICKS_1024)
self.root.xaxis.major_label_orientation = XLABEL_ORIENTATION
rect.nonselection_glyph = None
self.root.xaxis.minor_tick_line_alpha = 0
self.root.ygrid.visible = False
self.root.toolbar_location = None
hover = HoverTool()
hover.tooltips = "@name: @nbytes_text"
hover.tooltips = """
Name: @name
Bytes: @nbytes_text
Count: @count objects
"""
hover.point_policy = "follow_mouse"
self.root.add_tools(hover)
@without_property_validation
@log_errors
def update(self):
counts = defaultdict(int)
nbytes = defaultdict(int)
for ws in self.scheduler.workers.values():
for ts in ws.has_what:
ks = key_split(ts.key)
counts[ks] += 1
nbytes[ks] += ts.nbytes
names = list(sorted(counts))
self.root.x_range.factors = names
result = {
"name": names,
"count": [counts[name] for name in names],
"nbytes": [nbytes[name] for name in names],
"nbytes_text": [format_bytes(nbytes[name]) for name in names],
"color": [color_of(name) for name in names],
}
self.root.title.text = "Total Use: " + format_bytes(sum(nbytes.values()))
update(self.source, result)
class CurrentLoad(DashboardComponent):
"""Tasks and CPU usage on each worker"""
@log_errors
def __init__(self, scheduler, width=600, **kwargs):
self.last = 0
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"nprocessing": [],
"nprocessing-half": [],
"nprocessing-color": [],
"cpu": [],
"cpu-half": [],
"y": [],
"worker": [],
"escaped_worker": [],
}
)
processing = figure(
title="Tasks Processing",
tools="",
name="processing",
width=int(width / 2),
min_border_bottom=50,
**kwargs,
)
rect = processing.rect(
source=self.source,
x="nprocessing-half",
y="y",
width="nprocessing",
height=0.9,
color="nprocessing-color",
)
processing.x_range.start = 0
rect.nonselection_glyph = None
cpu = figure(
title="CPU Utilization",
tools="",
width=int(width / 2),
name="cpu_hist",
x_range=(0, 100),
min_border_bottom=50,
**kwargs,
)
rect = cpu.rect(
source=self.source,
x="cpu-half",
y="y",
width="cpu",
height=0.9,
color="blue",
)
rect.nonselection_glyph = None
for fig in (processing, cpu):
fig.xaxis.minor_tick_line_alpha = 0
fig.yaxis.visible = False
fig.ygrid.visible = False
tap = TapTool(callback=OpenURL(url="./info/worker/@escaped_worker.html"))
fig.add_tools(tap)
fig.toolbar_location = None
fig.yaxis.visible = False
hover = HoverTool()
hover.tooltips = "@worker : @nprocessing tasks"
hover.point_policy = "follow_mouse"
processing.add_tools(hover)
hover = HoverTool()
hover.tooltips = "@worker : @cpu %"
hover.point_policy = "follow_mouse"
cpu.add_tools(hover)
self.processing_figure = processing
self.cpu_figure = cpu
@without_property_validation
@log_errors
def update(self):
workers = self.scheduler.workers.values()
now = time()
if not any(ws.processing for ws in workers) and now < self.last + 1:
return
self.last = now
cpu = [int(ws.metrics["cpu"]) for ws in workers]
nprocessing = [len(ws.processing) for ws in workers]
nprocessing_color = []
for ws in workers:
if ws in self.scheduler.idle:
nprocessing_color.append("red")
elif ws in self.scheduler.saturated:
nprocessing_color.append("green")
else:
nprocessing_color.append("blue")
result = {
"cpu": cpu,
"cpu-half": [c / 2 for c in cpu],
"nprocessing": nprocessing,
"nprocessing-half": [np / 2 for np in nprocessing],
"nprocessing-color": nprocessing_color,
"worker": [ws.address for ws in workers],
"escaped_worker": [url_escape(ws.address) for ws in workers],
"y": list(range(len(workers))),
}
if self.scheduler.workers:
xrange = max(ws.nthreads or 1 for ws in workers)
else:
xrange = 1
self.cpu_figure.x_range.end = xrange * 100
update(self.source, result)
class StealingTimeSeries(DashboardComponent):
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"time": [time() * 1000, time() * 1000 + 1],
"idle": [0, 0],
"saturated": [0, 0],
}
)
x_range = DataRange1d(follow="end", follow_interval=20000, range_padding=0)
self.root = figure(
title="Idle and Saturated Workers Over Time",
x_axis_type="datetime",
tools="",
x_range=x_range,
**kwargs,
)
self.root.line(source=self.source, x="time", y="idle", color="red")
self.root.line(source=self.source, x="time", y="saturated", color="green")
self.root.yaxis.minor_tick_line_color = None
self.root.add_tools(
ResetTool(), PanTool(dimensions="width"), WheelZoomTool(dimensions="width")
)
@without_property_validation
@log_errors
def update(self):
result = {
"time": [time() * 1000],
"idle": [len(self.scheduler.idle)],
"saturated": [len(self.scheduler.saturated)],
}
if PROFILING:
curdoc().add_next_tick_callback(lambda: self.source.stream(result, 10000))
else:
self.source.stream(result, 10000)
class StealingEvents(DashboardComponent):
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.steal = scheduler.extensions["stealing"]
self.last = 0
self.source = ColumnDataSource(
{
"time": [time() - 60, time()],
"level": [0, 15],
"color": ["white", "white"],
"duration": [0, 0],
"radius": [1, 1],
"cost_factor": [0, 10],
"count": [1, 1],
}
)
x_range = DataRange1d(follow="end", follow_interval=20000, range_padding=0)
self.root = figure(
title="Stealing Events",
x_axis_type="datetime",
tools="",
x_range=x_range,
**kwargs,
)
self.root.scatter(
source=self.source,
x="time",
y="level",
color="color",
size="radius",
alpha=0.5,
)
self.root.yaxis.axis_label = "Level"
hover = HoverTool()
hover.tooltips = "Level: @level, Duration: @duration, Count: @count, Cost factor: @cost_factor"
hover.point_policy = "follow_mouse"
self.root.add_tools(
hover,
ResetTool(),
PanTool(dimensions="width"),
WheelZoomTool(dimensions="width"),
)
def convert(self, msgs):
"""Convert a log message to a glyph"""
total_duration = 0
for msg in msgs:
time, level, key, duration, sat, occ_sat, idl, occ_idl = msg[:8]
total_duration += duration
try:
color = Viridis11[level]
except (KeyError, IndexError):
color = "black"
radius = math.sqrt(min(total_duration, 10)) * 30 + 2
d = {
"time": time * 1000,
"level": level,
"count": len(msgs),
"color": color,
"duration": total_duration,
"radius": radius,
"cost_factor": self.steal.cost_multipliers[level],
}
return d
@without_property_validation
@log_errors
def update(self):
topic = self.scheduler._broker._topics["stealing"]
log = log = topic.events
n = min(topic.count - self.last, len(log))
if log:
log = [log[-i][1][1] for i in range(1, n + 1) if log[-i][1][0] == "request"]
self.last = topic.count
if log:
new = pipe(
log,
map(groupby(1)),
map(dict.values),
concat,
map(self.convert),
list,
transpose,
)
if PROFILING:
curdoc().add_next_tick_callback(lambda: self.source.stream(new, 10000))
else:
self.source.stream(new, 10000)
class Events(DashboardComponent):
def __init__(self, scheduler, name, height=150, **kwargs):
self.scheduler = scheduler
self.action_ys = dict()
self.last = 0
self.name = name
self.source = ColumnDataSource(
{"time": [], "action": [], "hover": [], "y": [], "color": []}
)
x_range = DataRange1d(follow="end", follow_interval=200000)
self.root = figure(
title=name,
x_axis_type="datetime",
height=height,
tools="",
x_range=x_range,
**kwargs,
)
self.root.scatter(
source=self.source,
x="time",
y="y",
color="color",
size=50,
alpha=0.5,
legend_field="action",
)
self.root.yaxis.axis_label = "Action"
self.root.legend.location = "top_left"
hover = HoverTool()
hover.tooltips = "@action
@hover"
hover.point_policy = "follow_mouse"
self.root.add_tools(
hover,
ResetTool(),
PanTool(dimensions="width"),
WheelZoomTool(dimensions="width"),
)
@without_property_validation
@log_errors
def update(self):
topic = self.scheduler._broker._topics[self.name]
log = topic.events
n = min(topic.count - self.last, len(log))
if log:
log = [log[-i] for i in range(1, n + 1)]
self.last = topic.count
if log:
actions = []
times = []
hovers = []
ys = []
colors = []
for msg_time, msg in log:
times.append(msg_time * 1000)
action = msg["action"]
actions.append(action)
try:
ys.append(self.action_ys[action])
except KeyError:
self.action_ys[action] = len(self.action_ys)
ys.append(self.action_ys[action])
colors.append(color_of(action))
hovers.append("TODO")
new = {
"time": times,
"action": actions,
"hover": hovers,
"y": ys,
"color": colors,
}
if PROFILING:
curdoc().add_next_tick_callback(lambda: self.source.stream(new, 10000))
else:
self.source.stream(new, 10000)
class TaskStream(DashboardComponent):
def __init__(self, scheduler, n_rectangles=1000, clear_interval="20s", **kwargs):
self.scheduler = scheduler
self.offset = 0
if TaskStreamPlugin.name not in self.scheduler.plugins:
self.scheduler.add_plugin(TaskStreamPlugin(self.scheduler))
self.plugin = self.scheduler.plugins[TaskStreamPlugin.name]
self.index = max(0, self.plugin.index - n_rectangles)
self.workers = dict()
self.n_rectangles = n_rectangles
clear_interval = parse_timedelta(clear_interval, default="ms")
self.clear_interval = clear_interval
self.last = 0
self.last_seen = 0
self.source, self.root = task_stream_figure(clear_interval, **kwargs)
# Required for update callback
self.task_stream_index = [0]
@without_property_validation
@log_errors
def update(self):
if self.index == self.plugin.index:
return
if self.index and len(self.source.data["start"]):
start = min(self.source.data["start"])
duration = max(self.source.data["duration"])
boundary = (self.offset + start - duration) / 1000
else:
boundary = self.offset
rectangles = self.plugin.rectangles(
istart=self.index, workers=self.workers, start_boundary=boundary
)
n = len(rectangles["name"])
self.index = self.plugin.index
if not rectangles["start"]:
return
# If it has been a while since we've updated the plot
if time() > self.last_seen + self.clear_interval:
new_start = min(rectangles["start"]) - self.offset
old_start = min(self.source.data["start"])
old_end = max(
map(
operator.add,
self.source.data["start"],
self.source.data["duration"],
)
)
density = (
sum(self.source.data["duration"])
/ len(self.workers)
/ (old_end - old_start)
)
# If whitespace is more than 3x the old width
if (new_start - old_end) > (old_end - old_start) * 2 or density < 0.05:
self.source.data.update({k: [] for k in rectangles}) # clear
self.offset = min(rectangles["start"]) # redefine offset
rectangles["start"] = [x - self.offset for x in rectangles["start"]]
self.last_seen = time()
# Convert to numpy for serialization speed
if n >= 10 and np:
for k, v in rectangles.items():
if isinstance(v[0], Number):
rectangles[k] = np.array(v)
if PROFILING:
curdoc().add_next_tick_callback(
lambda: self.source.stream(rectangles, self.n_rectangles)
)
else:
self.source.stream(rectangles, self.n_rectangles)
def task_stream_figure(clear_interval="20s", **kwargs):
"""
kwargs are applied to the bokeh.models.plots.Plot constructor
"""
clear_interval = parse_timedelta(clear_interval, default="ms")
source = ColumnDataSource(
data=dict(
start=[time() - clear_interval],
duration=[0.1],
key=["start"],
name=["start"],
color=["white"],
duration_text=["100 ms"],
worker=["foo"],
y=[0],
worker_thread=[1],
alpha=[0.0],
)
)
x_range = DataRange1d(range_padding=0)
y_range = DataRange1d(range_padding=0)
root = figure(
name="task_stream",
title="Task Stream",
x_range=x_range,
y_range=y_range,
toolbar_location="above",
x_axis_type="datetime",
y_axis_location=None,
tools="",
min_border_bottom=50,
**kwargs,
)
rect = root.rect(
source=source,
x="start",
y="y",
width="duration",
height=0.4,
fill_color="color",
line_color="color",
line_alpha=0.6,
fill_alpha="alpha",
line_width=3,
)
rect.nonselection_glyph = None
root.yaxis.major_label_text_alpha = 0
root.yaxis.minor_tick_line_alpha = 0
root.yaxis.major_tick_line_alpha = 0
root.xgrid.visible = False
hover = HoverTool(
point_policy="follow_mouse",
tooltips="""
@name:
@duration_text
""",
)
tap = TapTool(callback=OpenURL(url="./profile?key=@name"))
help_ = HelpTool(
redirect="https://docs.dask.org/en/stable/dashboard.html#task-stream",
description="A description of the TaskStream and its color palette.",
)
root.add_tools(
hover,
tap,
BoxZoomTool(),
ResetTool(),
PanTool(dimensions="width"),
WheelZoomTool(dimensions="width"),
help_,
)
if ExportTool: # type: ignore
export = ExportTool()
export.register_plot(root)
root.add_tools(export)
return source, root
class TaskGraph(DashboardComponent):
"""
A dynamic node-link diagram for the task graph on the scheduler
See also the GraphLayout diagnostic at
distributed/diagnostics/graph_layout.py
"""
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.layout = GraphLayout(scheduler)
scheduler.add_plugin(self.layout)
self.invisible_count = 0 # number of invisible nodes
self.node_source = ColumnDataSource(
{"x": [], "y": [], "name": [], "state": [], "visible": [], "key": []}
)
self.edge_source = ColumnDataSource({"x": [], "y": [], "visible": []})
filter = GroupFilter(column_name="visible", group="True")
node_view = CDSView(filter=filter)
edge_view = CDSView(filter=filter)
node_colors = factor_cmap(
"state",
factors=["waiting", "queued", "processing", "memory", "released", "erred"],
palette=["gray", "yellow", "green", "red", "blue", "black"],
)
self.root = figure(title="Task Graph", **kwargs)
self.subtitle = Title(text=" ", text_font_style="italic")
self.root.add_layout(self.subtitle, "above")
self.root.multi_line(
xs="x",
ys="y",
source=self.edge_source,
line_width=1,
view=edge_view,
color="black",
alpha=0.3,
)
rect = self.root.scatter(
x="x",
y="y",
size=10,
color=node_colors,
source=self.node_source,
view=node_view,
legend_field="state",
marker="square",
)
self.root.xgrid.grid_line_color = None
self.root.ygrid.grid_line_color = None
self.root.xaxis.visible = False
self.root.yaxis.visible = False
hover = HoverTool(
point_policy="follow_mouse",
tooltips="@name: @state",
renderers=[rect],
)
tap = TapTool(callback=OpenURL(url="info/task/@key.html"), renderers=[rect])
rect.nonselection_glyph = None
self.root.add_tools(hover, tap)
self.max_items = config.get("distributed.dashboard.graph-max-items", 5000)
@without_property_validation
@log_errors
def update(self):
# If there are too many tasks in the scheduler we'll disable this
# compoonents to not overload scheduler or client. Once we drop
# below the threshold, the data is filled up again as usual
if len(self.scheduler.tasks) > self.max_items:
self.subtitle.text = "Scheduler has too many tasks to display."
for container in [self.node_source, self.edge_source]:
container.data = {col: [] for col in container.column_names}
else:
# occasionally reset the column data source to remove old nodes
if self.invisible_count > len(self.node_source.data["x"]) / 2:
self.layout.reset_index()
self.invisible_count = 0
update = True
else:
update = False
new, self.layout.new = self.layout.new, []
new_edges = self.layout.new_edges
self.layout.new_edges = []
self.add_new_nodes_edges(new, new_edges, update=update)
self.patch_updates()
if len(self.scheduler.tasks) == 0:
self.subtitle.text = "Scheduler is empty."
else:
self.subtitle.text = " "
@without_property_validation
def add_new_nodes_edges(self, new, new_edges, update=False):
if new or update:
node_key = []
node_x = []
node_y = []
node_state = []
node_name = []
edge_x = []
edge_y = []
x = self.layout.x
y = self.layout.y
tasks = self.scheduler.tasks
for key in new:
try:
task = tasks[key]
except KeyError:
continue
xx = x[key]
yy = y[key]
node_key.append(url_escape(str(key)))
node_x.append(xx)
node_y.append(yy)
node_state.append(task.state)
node_name.append(task.prefix.name)
for a, b in new_edges:
try:
edge_x.append([x[a], x[b]])
edge_y.append([y[a], y[b]])
except KeyError:
pass
node = {
"x": node_x,
"y": node_y,
"state": node_state,
"name": node_name,
"key": node_key,
"visible": ["True"] * len(node_x),
}
edge = {"x": edge_x, "y": edge_y, "visible": ["True"] * len(edge_x)}
if update or not len(self.node_source.data["x"]):
# see https://github.com/bokeh/bokeh/issues/7523
self.node_source.data.update(node)
self.edge_source.data.update(edge)
else:
self.node_source.stream(node)
self.edge_source.stream(edge)
@without_property_validation
def patch_updates(self):
"""
Small updates like color changes or lost nodes from task transitions
"""
n = len(self.node_source.data["x"])
m = len(self.edge_source.data["x"])
if self.layout.state_updates:
state_updates = self.layout.state_updates
self.layout.state_updates = []
updates = [(i, c) for i, c in state_updates if i < n]
self.node_source.patch({"state": updates})
if self.layout.visible_updates:
updates = self.layout.visible_updates
updates = [(i, c) for i, c in updates if i < n]
self.layout.visible_updates = []
self.node_source.patch({"visible": updates})
self.invisible_count += len(updates)
if self.layout.visible_edge_updates:
updates = self.layout.visible_edge_updates
updates = [(i, c) for i, c in updates if i < m]
self.layout.visible_edge_updates = []
self.edge_source.patch({"visible": updates})
def __del__(self):
self.scheduler.remove_plugin(name=self.layout.name)
class TaskGroupGraph(DashboardComponent):
"""
Task Group Graph
Creates a graph layout for TaskGroups on the scheduler. It assigns
(x, y) locations to all the TaskGroups and lays them out by according
to their dependencies. The layout gets updated every time that new
TaskGroups are added.
Each task group node incodes information about task progress, memory,
and output type into glyphs, as well as a hover tooltip with more detailed
information on name, computation time, memory, and tasks status.
"""
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.nodes_layout = {}
self.arrows_layout = {}
self.old_counter = -1
self.nodes_source = ColumnDataSource(
{
"x": [],
"y": [],
"w_box": [],
"h_box": [],
"name": [],
"tot_tasks": [],
"color": [],
"x_start": [],
"x_end": [],
"y_start": [],
"y_end": [],
"x_end_progress": [],
"mem_alpha": [],
"node_line_width": [],
"comp_tasks": [],
"url_logo": [],
"x_logo": [],
"y_logo": [],
"w_logo": [],
"h_logo": [],
"in_processing": [],
"in_memory": [],
"in_released": [],
"in_erred": [],
"compute_time": [],
"memory": [],
}
)
self.arrows_source = ColumnDataSource({"xs": [], "ys": [], "xe": [], "ye": []})
self.root = figure(title="Task Groups Graph", match_aspect=True, **kwargs)
self.root.axis.visible = False
self.subtitle = Title(text=" ", text_font_style="italic")
self.root.add_layout(self.subtitle, "above")
rect = self.root.rect(
x="x",
y="y",
width="w_box",
height="h_box",
color="color",
fill_alpha="mem_alpha",
line_color="black",
line_width="node_line_width",
source=self.nodes_source,
)
# plot tg log
self.root.image_url(
url="url_logo",
x="x_logo",
y="y_logo",
w="w_logo",
h="h_logo",
anchor="center",
source=self.nodes_source,
)
# progress bar plain box
self.root.quad(
left="x_start",
right="x_end",
bottom="y_start",
top="y_end",
color=None,
line_color="black",
source=self.nodes_source,
)
# progress bar
self.root.quad(
left="x_start",
right="x_end_progress",
bottom="y_start",
top="y_end",
color="color",
line_color=None,
fill_alpha=0.6,
source=self.nodes_source,
)
self.arrows = Arrow(
end=VeeHead(size=8),
line_color="black",
line_alpha=0.5,
line_width=1,
x_start="xs",
y_start="ys",
x_end="xe",
y_end="ye",
source=self.arrows_source,
)
self.root.add_layout(self.arrows)
self.root.xgrid.grid_line_color = None
self.root.ygrid.grid_line_color = None
self.root.x_range.range_padding = 0.5
self.root.y_range.range_padding = 0.5
hover = HoverTool(
point_policy="follow_mouse",
tooltips="""
Name:
@name
Compute time:
@compute_time
Memory:
@memory
Tasks:
@tot_tasks
Completed:
@comp_tasks
Processing:
@in_processing
In memory:
@in_memory
Erred:
@in_erred
Released:
@in_released
""",
renderers=[rect],
)
self.root.add_tools(hover)
@without_property_validation
@log_errors
def update_layout(self):
# Get dependencies per task group.
# In some cases there are tg that have themselves as dependencies - we remove those.
dependencies = {
k: {ds.name for ds in ts.dependencies if ds.name != k}
for k, ts in self.scheduler.task_groups.items()
}
import dask
order = dask.order.order(
dsk={group.name: 1 for k, group in self.scheduler.task_groups.items()},
dependencies=dependencies,
)
ordered = sorted(self.scheduler.task_groups, key=order.get)
xs = {}
ys = {}
locations = set()
nodes_layout = {}
arrows_layout = {}
for tg in ordered:
if dependencies[tg]:
x = max(xs[dep] for dep in dependencies[tg]) + 1
y = max(ys[dep] for dep in dependencies[tg])
if (
len(dependencies[tg]) > 1
and len({ys[dep] for dep in dependencies[tg]}) == 1
):
y += 1
else:
x = 0
y = max(ys.values()) + 1 if ys else 0
while (x, y) in locations: # avoid collisions by moving up
y += 1
locations.add((x, y))
xs[tg], ys[tg] = x, y
# info needed for node layout to column data source
nodes_layout[tg] = {"x": xs[tg], "y": ys[tg]}
# info needed for arrow layout
arrows_layout[tg] = {
"nstart": dependencies[tg],
"nend": [tg] * len(dependencies[tg]),
}
return nodes_layout, arrows_layout
def compute_size(self, x, min_box, max_box):
start = 0.4
end = 0.8
y = (end - start) / (max_box - min_box) * (x - min_box) + start
return y
@without_property_validation
def update(self):
if self.scheduler.transition_counter == self.old_counter:
return
self.old_counter = self.scheduler.transition_counter
if not self.scheduler.task_groups:
self.subtitle.text = "Scheduler is empty."
else:
self.subtitle.text = " "
if self.nodes_layout.keys() != self.scheduler.task_groups.keys():
self.nodes_layout, self.arrows_layout = self.update_layout()
nodes_data = {
"x": [],
"y": [],
"w_box": [],
"h_box": [],
"name": [],
"color": [],
"tot_tasks": [],
"x_start": [],
"x_end": [],
"y_start": [],
"y_end": [],
"x_end_progress": [],
"mem_alpha": [],
"node_line_width": [],
"comp_tasks": [],
"url_logo": [],
"x_logo": [],
"y_logo": [],
"w_logo": [],
"h_logo": [],
"in_processing": [],
"in_memory": [],
"in_released": [],
"in_erred": [],
"compute_time": [],
"memory": [],
}
arrows_data = {
"xs": [],
"ys": [],
"xe": [],
"ye": [],
}
durations = set()
nbytes = set()
for tg in self.scheduler.task_groups.values():
if tg.duration and tg.nbytes_total:
durations.add(tg.duration)
nbytes.add(tg.nbytes_total)
durations_min = min(durations, default=0)
durations_max = max(durations, default=0)
nbytes_min = min(nbytes, default=0)
nbytes_max = max(nbytes, default=0)
box_dim = {}
for key, tg in self.scheduler.task_groups.items():
comp_tasks = (
tg.states["released"] + tg.states["memory"] + tg.states["erred"]
)
tot_tasks = sum(tg.states.values())
# compute width and height of boxes
if (
tg.duration
and tg.nbytes_total
and comp_tasks
and len(durations) > 1
and len(nbytes) > 1
):
# scale duration (width)
width_box = self.compute_size(
tg.duration / comp_tasks * tot_tasks,
min_box=durations_min / comp_tasks * tot_tasks,
max_box=durations_max / comp_tasks * tot_tasks,
)
# need to scale memory (height)
height_box = self.compute_size(
tg.nbytes_total / comp_tasks * tot_tasks,
min_box=nbytes_min / comp_tasks * tot_tasks,
max_box=nbytes_max / comp_tasks * tot_tasks,
)
else:
width_box = 0.6
height_box = width_box / 2
box_dim[key] = {"width": width_box, "height": height_box}
for key, tg in self.scheduler.task_groups.items():
x = self.nodes_layout[key]["x"]
y = self.nodes_layout[key]["y"]
width = box_dim[key]["width"]
height = box_dim[key]["height"]
# main boxes layout
nodes_data["x"].append(x)
nodes_data["y"].append(y)
nodes_data["w_box"].append(width)
nodes_data["h_box"].append(height)
comp_tasks = (
tg.states["released"] + tg.states["memory"] + tg.states["erred"]
)
tot_tasks = sum(tg.states.values())
nodes_data["name"].append(tg.prefix.name)
nodes_data["color"].append(color_of(tg.prefix.name))
nodes_data["tot_tasks"].append(tot_tasks)
# memory alpha factor by 0.4 if not get's too dark
nodes_data["mem_alpha"].append(
(tg.states["memory"] / sum(tg.states.values())) * 0.4
)
# main box line width
if tg.states["processing"]:
nodes_data["node_line_width"].append(5)
else:
nodes_data["node_line_width"].append(1)
# progress bar data update
nodes_data["x_start"].append(x - width / 2)
nodes_data["x_end"].append(x + width / 2)
nodes_data["y_start"].append(y - height / 2)
nodes_data["y_end"].append(y - height / 2 + height * 0.4)
nodes_data["x_end_progress"].append(
x - width / 2 + width * comp_tasks / tot_tasks
)
# arrows
arrows_data["xs"] += [
self.nodes_layout[k]["x"] + box_dim[k]["width"] / 2
for k in self.arrows_layout[key]["nstart"]
]
arrows_data["ys"] += [
self.nodes_layout[k]["y"] for k in self.arrows_layout[key]["nstart"]
]
arrows_data["xe"] += [
self.nodes_layout[k]["x"] - box_dim[k]["width"] / 2
for k in self.arrows_layout[key]["nend"]
]
arrows_data["ye"] += [
self.nodes_layout[k]["y"] for k in self.arrows_layout[key]["nend"]
]
# LOGOS
if len(tg.types) == 1:
logo_type = next(iter(tg.types)).split(".")[0]
try:
url_logo = logos_dict[logo_type]
except KeyError:
url_logo = ""
else:
url_logo = ""
nodes_data["url_logo"].append(url_logo)
nodes_data["x_logo"].append(x + width / 3)
nodes_data["y_logo"].append(y + height / 3)
ratio = width / height
if ratio > 1:
nodes_data["h_logo"].append(height * 0.3)
nodes_data["w_logo"].append(width * 0.3 / ratio)
else:
nodes_data["h_logo"].append(height * 0.3 * ratio)
nodes_data["w_logo"].append(width * 0.3)
# compute_time and memory
nodes_data["compute_time"].append(format_time(tg.duration))
nodes_data["memory"].append(format_bytes(tg.nbytes_total))
# Add some status to hover
tasks_processing = tg.states["processing"]
tasks_memory = tg.states["memory"]
tasks_relased = tg.states["released"]
tasks_erred = tg.states["erred"]
nodes_data["comp_tasks"].append(
f"{comp_tasks} ({comp_tasks / tot_tasks * 100:.0f} %)"
)
nodes_data["in_processing"].append(
f"{tasks_processing} ({tasks_processing / tot_tasks * 100:.0f} %)"
)
nodes_data["in_memory"].append(
f"{tasks_memory} ({tasks_memory / tot_tasks * 100:.0f} %)"
)
nodes_data["in_released"].append(
f"{tasks_relased} ({tasks_relased / tot_tasks * 100:.0f} %)"
)
nodes_data["in_erred"].append(
f"{tasks_erred} ({tasks_erred / tot_tasks * 100:.0f} %)"
)
self.nodes_source.data.update(nodes_data)
self.arrows_source.data.update(arrows_data)
class TaskGroupProgress(DashboardComponent):
"""Stacked area chart showing task groups through time"""
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.source = ColumnDataSource()
# The length of timeseries to chart (in units of plugin.dt)
self.npts = 180
if GroupTiming.name not in scheduler.plugins:
scheduler.add_plugin(plugin=GroupTiming(scheduler))
self.plugin = scheduler.plugins[GroupTiming.name]
self.source.add(np.array(self.plugin.time) * 1000.0, "time")
x_range = DataRange1d(range_padding=0)
y_range = Range1d(0, max(self.plugin.nthreads))
self.root = figure(
title="Task Group Progress",
name="task_group_progress",
toolbar_location="above",
min_border_bottom=50,
x_range=x_range,
y_range=y_range,
tools="",
x_axis_type="datetime",
y_axis_location=None,
**kwargs,
)
self.root.yaxis.major_label_text_alpha = 0
self.root.yaxis.minor_tick_line_alpha = 0
self.root.yaxis.major_tick_line_alpha = 0
self.root.xgrid.visible = False
self.root.add_tools(
BoxZoomTool(),
ResetTool(),
PanTool(dimensions="width"),
WheelZoomTool(dimensions="width"),
)
self._hover = None
self._last_drawn = None
self._offset = time()
self._last_transition_count = scheduler.transition_counter
# OrderedDict so we can make a reverse iterator later and get the
# most-recently-added glyphs.
self._renderers = OrderedDict()
self._line_renderers = OrderedDict()
def _should_add_new_renderers(self) -> bool:
"""
Whether to add new renderers to the chart.
When a new set of task groups enters the scheduler we'd like to start rendering
them. But it can be expensive to add new glyps, so we do it deliberately,
checking whether we have to do it and whether the scheduler seems busy.
"""
# Always draw if we have not before
if not self._last_drawn:
return True
# Don't draw if there have been no new tasks completed since the last update,
# or if the scheduler CPU is occupied.
if (
self._last_transition_count == self.scheduler.transition_counter
or self.scheduler.proc.cpu_percent() > 50
):
return False
# Only return true if there are new task groups that we have not yet added
# to the ColumnDataSource.
return not set(self.plugin.compute.keys()) <= set(self.source.data.keys())
def _should_update(self) -> bool:
"""
Whether to update the ColumnDataSource. This is cheaper than redrawing,
but still not free, so we check whether we need it and whether the scheudler
is busy.
"""
return (
self._last_transition_count != self.scheduler.transition_counter
and self.scheduler.proc.cpu_percent() < 50
)
def _get_timeseries(self, restrict_to_existing=False):
"""
Update the ColumnDataSource with our time series data.
restrict_to_existing determines whether to add new task groups
which might have been added since the last time we rendered.
This is important as we want to add new stackers very deliberately.
"""
# Get the front/back indices for most recent npts bins out of the timeseries
front = max(len(self.plugin.time) - self.npts, 0)
back = None
# Remove any periods of zero compute at the front or back of the timeseries
if len(self.plugin.compute):
agg = sum(np.array(v[front:]) for v in self.plugin.compute.values())
front2 = len(agg) - len(np.trim_zeros(agg, trim="f"))
front += front2
back = len(np.trim_zeros(agg, trim="b")) - len(agg) or None
prepend = (
self.plugin.time[front - 1]
if front >= 1
else self.plugin.time[front] - self.plugin.dt
)
timestamps = np.array(self.plugin.time[front:back])
dt = np.diff(timestamps, prepend=prepend)
if restrict_to_existing:
new_data = {
k: np.array(v[front:back]) / dt
for k, v in self.plugin.compute.items()
if k in self.source.data
}
else:
new_data = valmap(
lambda x: np.array(x[front:back]) / dt,
self.plugin.compute,
)
new_data["time"] = (
timestamps - self._offset
) * 1000.0 # bokeh likes milliseconds
new_data["nthreads"] = np.array(self.plugin.nthreads[front:back])
return new_data
@without_property_validation
@log_errors
def update(self):
"""
Maybe update the chart. This is somewhat expensive to draw, so we update
it pretty defensively.
"""
if self._should_add_new_renderers():
# Update the chart, allowing for new task groups to be added.
new_data = self._get_timeseries(restrict_to_existing=False)
self.source.data = new_data
# Possibly update the y range if the number of threads has increased.
max_nthreads = max(self.plugin.nthreads)
if self.root.y_range.end != max_nthreads:
self.root.y_range.end = max_nthreads
stackers = list(self.plugin.compute.keys())
colors = [color_of(key_split(k)) for k in stackers]
for i, (group, color) in enumerate(zip(stackers, colors)):
# If we have already drawn the group, but it is all zero,
# set it to be invisible.
if group in self._renderers:
if not np.count_nonzero(new_data[group]) > 0:
self._renderers[group].visible = False
self._line_renderers[group].visible = False
else:
self._renderers[group].visible = True
self._line_renderers[group].visible = True
continue
# Draw the new area and line glyphs.
renderer = self.root.varea(
x="time",
y1=stack(*stackers[:i]),
y2=stack(*stackers[: i + 1]),
color=color,
alpha=0.5,
source=self.source,
)
self._renderers[group] = renderer
line_renderer = self.root.line(
x="time",
y=stack(*stackers[: i + 1]),
color=color,
alpha=1.0,
source=self.source,
)
self._line_renderers[group] = line_renderer
# Don't add hover until there is something to show, as bokehjs seems to
# have trouble with custom hovers when there are no renderers.
if self.plugin.compute and self._hover is None:
# Add a hover that will show occupancy for all currently active
# task groups. This is a little tricky, bokeh doesn't (yet) support
# hit tests for stacked area charts: https://github.com/bokeh/bokeh/issues/9182
# Instead, show a single vline hover which lists the currently active task
# groups. A custom formatter in JS-land pulls the relevant data index and
# assembles the tooltip.
formatter = CustomJSHover(code="return '';")
self._hover = HoverTool(
tooltips="""
Worker thread occupancy
$index{custom}
""",
mode="vline",
line_policy="nearest",
attachment="horizontal",
formatters={"$index": formatter},
)
self.root.add_tools(self._hover)
if self._hover:
# Create a custom tooltip that:
# 1. Includes nthreads
# 2. Filters out inactive task groups
# (ones without any compute during the relevant dt)
# 3. Colors the labels appropriately.
formatter = CustomJSHover(
code="""
const colormap = %s;
const divs = [];
for (let k of Object.keys(source.data)) {
const val = source.data[k][value];
const color = colormap[k];
if (k === "time" || k === "nthreads" || val < 1.e-3) {
continue;
}
const label = k.length >= 20 ? k.slice(0, 20) + '…' : k;
// Unshift so that the ordering of the labels is the same as
// the ordering of the stackers.
divs.unshift(
''
+ ''
+ label
+ ''
+ ': '
+ val.toFixed(1)
+ '
'
)
}
divs.unshift(
''
+ 'nthreads: '
+ source.data.nthreads[value]
+ '
'
);
return divs.join('\\n')
"""
% dict(
zip(stackers, colors)
), # sneak the color mapping into the callback
args={"source": self.source},
)
# Add the HoverTool to the top line renderer.
top_line = None
for line in reversed(self._line_renderers.values()):
if line.visible:
top_line = line
break
self._hover.renderers = [top_line]
self._hover.formatters = {"$index": formatter}
self._last_drawn = time()
self._last_transition_count = self.scheduler.transition_counter
elif self._should_update():
# Possibly update the y range if new threads have been added
max_nthreads = max(self.plugin.nthreads)
if self.root.y_range.end != max_nthreads:
self.root.y_range.end = max_nthreads
# Update the data, only including existing columns, rather than redrawing
# the whole chart.
self.source.data = self._get_timeseries(restrict_to_existing=True)
self._last_transition_count = self.scheduler.transition_counter
class TaskProgress(DashboardComponent):
"""Progress bars per task type"""
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
data = progress_quads(
dict(all={}, memory={}, erred={}, released={}, processing={}, queued={})
)
self.source = ColumnDataSource(data=data)
x_range = DataRange1d(range_padding=0)
y_range = Range1d(-8, 0)
self.root = figure(
title="Progress",
name="task_progress",
x_range=x_range,
y_range=y_range,
toolbar_location="above",
tools="",
min_border_bottom=50,
**kwargs,
)
self.root.line( # just to define early ranges
x=[0, 0.9], y=[-1, 0], line_color="#FFFFFF", alpha=0.0
)
self.root.quad(
source=self.source,
top="top",
bottom="bottom",
left="left",
right="right",
fill_color="#aaaaaa",
line_color="#aaaaaa",
fill_alpha=0.1,
line_alpha=0.3,
)
self.root.quad(
source=self.source,
top="top",
bottom="bottom",
left="left",
right="released-loc",
fill_color="color",
line_color="color",
fill_alpha=0.6,
)
self.root.quad(
source=self.source,
top="top",
bottom="bottom",
left="released-loc",
right="memory-loc",
fill_color="color",
line_color="color",
fill_alpha=1.0,
)
self.root.quad(
source=self.source,
top="top",
bottom="bottom",
left="memory-loc",
right="erred-loc",
fill_color="black",
fill_alpha=0.5,
line_alpha=0,
)
self.root.quad(
source=self.source,
top="top",
bottom="bottom",
left="erred-loc",
right="processing-loc",
fill_color="gray",
fill_alpha=0.35,
line_alpha=0,
)
self.root.quad(
source=self.source,
top="top",
bottom="bottom",
left="processing-loc",
right="queued-loc",
fill_color="gray",
hatch_pattern="/",
hatch_color="white",
fill_alpha=0.35,
line_alpha=0,
)
self.root.quad(
source=self.source,
top="top",
bottom="bottom",
left="queued-loc",
right="no-worker-loc",
fill_color="red",
hatch_pattern="/",
hatch_color="black",
fill_alpha=0.35,
line_alpha=0,
)
self.root.text(
source=self.source,
text="show-name",
y="bottom",
x="left",
x_offset=5,
text_font_size=value("10pt"),
)
self.root.text(
source=self.source,
text="done",
y="bottom",
x="right",
x_offset=-5,
text_align="right",
text_font_size=value("10pt"),
)
self.root.ygrid.visible = False
self.root.yaxis.minor_tick_line_alpha = 0
self.root.yaxis.visible = False
self.root.xgrid.visible = False
self.root.xaxis.minor_tick_line_alpha = 0
self.root.xaxis.visible = False
hover = HoverTool(
point_policy="follow_mouse",
tooltips="""
Name:
@name
All:
@all
Queued:
@queued
No-worker:
@no_worker
Processing:
@processing
Memory:
@memory
Erred:
@erred
""",
)
help_ = HelpTool(
redirect="https://docs.dask.org/en/stable/dashboard.html#progress",
description="A description of the progress bars plot.",
)
self.root.add_tools(hover, help_)
@without_property_validation
@log_errors
def update(self):
state = {
"memory": {},
"erred": {},
"released": {},
"processing": {},
"waiting": {},
"queued": {},
"no_worker": {},
}
for tp in self.scheduler.task_prefixes.values():
states = tp.states
if any(states.get(s) for s in state.keys()):
state["memory"][tp.name] = states["memory"]
state["erred"][tp.name] = states["erred"]
state["released"][tp.name] = states["released"]
state["processing"][tp.name] = states["processing"]
state["waiting"][tp.name] = states["waiting"]
state["queued"][tp.name] = states["queued"]
state["no_worker"][tp.name] = states["no-worker"]
state["all"] = {k: sum(v[k] for v in state.values()) for k in state["memory"]}
if not state["all"] and not len(self.source.data["all"]):
return
d = progress_quads(state)
update(self.source, d)
totals = {
k: sum(state[k].values())
for k in [
"all",
"memory",
"erred",
"released",
"waiting",
"queued",
"no_worker",
]
}
totals["processing"] = totals["all"] - sum(
v for k, v in totals.items() if k != "all"
)
self.root.title.text = (
"Progress -- total: %(all)s, "
"waiting: %(waiting)s, "
"queued: %(queued)s, "
"processing: %(processing)s, "
"in-memory: %(memory)s, "
"no-worker: %(no_worker)s, "
"erred: %(erred)s" % totals
)
class FinePerformanceMetrics(DashboardComponent):
"""
The main overview of the Fine Performance Metrics page.
"""
BASE_TOOLS = ["pan", "wheel_zoom", "box_zoom", "reset"]
scheduler: Scheduler
task_exec_by_prefix_src: ColumnDataSource
task_exec_by_prefix_xmax: float
task_exec_by_activity_src: ColumnDataSource
get_data_by_activity_src: ColumnDataSource
substantial_change: bool
visible_functions: list[str]
visible_activities: list[str]
stacked_chart_visible_activities: list[str]
function_selector: MultiChoice
span_tag_selector: MultiChoice
unit_selector: Select
task_exec_by_activity_chart: figure | None
task_exec_by_prefix_chart: figure | None
get_data_by_activity_chart: figure | None
@log_errors
def __init__(self, scheduler: Scheduler, **kwargs: Any):
self.scheduler = scheduler
self.task_exec_by_prefix_src = ColumnDataSource(data={})
self.task_exec_by_prefix_xmax = 0.0
self.task_exec_by_activity_src = ColumnDataSource(data={})
self.get_data_by_activity_src = ColumnDataSource(data={})
self.substantial_change = False
self.visible_functions = []
self.visible_activities = []
self.stacked_chart_visible_activities = []
self.task_exec_by_activity_chart = None
self.task_exec_by_prefix_chart = None
self.get_data_by_activity_chart = None
# Selectors
self.function_selector = MultiChoice(
title="Filter by function",
placeholder="Select specific functions",
value=[],
options=[],
)
self.span_tag_selector = MultiChoice(
title="Filter by span tag",
placeholder="Select specific span tags",
value=[],
options=[],
)
self.unit_selector = Select(title="Unit selection", options=["seconds"])
self.unit_selector.value = "seconds"
self.unit_selector.on_change("value", self._handle_change_unit)
selectors_row = row(
children=[
self.span_tag_selector,
self.function_selector,
self.unit_selector,
],
sizing_mode="stretch_width",
)
self.root = column(
selectors_row,
sizing_mode="scale_width",
)
def _handle_change_unit(self, attr: str, old: str, new: str) -> None:
self.substantial_change = True
assert self.task_exec_by_prefix_chart
fmt = self._bokeh_unit_format()
self.task_exec_by_prefix_chart.xaxis[0].formatter.format = fmt
@without_property_validation
@log_errors
def update(self):
self._update_selectors()
self._build_data_sources()
needs_figures_row = self.task_exec_by_activity_chart is None
if needs_figures_row:
self.substantial_change = True
if needs_figures_row:
# First call to update()
self.task_exec_by_prefix_chart = (
self._build_task_execution_by_prefix_chart()
)
self.task_exec_by_activity_chart = self._build_pie_chart(
source=self.task_exec_by_activity_src,
title="Task execution, by activity",
)
self.get_data_by_activity_chart = self._build_pie_chart(
source=self.get_data_by_activity_src,
# get_data is called via RPC for data pull; the metrics for it are
# recorded on the worker *donating* the data
title="Send data, by activity",
)
self.task_exec_by_prefix_chart.x_range.end = self.task_exec_by_prefix_xmax * 1.1
if self.substantial_change:
# Visible activities and/or functions changed
self.substantial_change = False
self._update_task_execution_by_prefix_chart()
figures_row = row(
children=[
self.task_exec_by_prefix_chart,
self.task_exec_by_activity_chart,
self.get_data_by_activity_chart,
],
sizing_mode="stretch_width",
)
if needs_figures_row:
# First iteration, initial assignment of figures row
self.root.children.append(figures_row)
else:
# Otherwise needs forced refresh by replacing the figures row
self.root.children[-1] = figures_row
def _update_selectors(self) -> None:
"""Update choices available in
- self.unit_selector
- self.function_selector
- self.span_tag_selector
"""
units = set()
functions = set()
for k in self.scheduler.cumulative_worker_metrics:
if not isinstance(k, tuple):
continue
context, *other, activity, unit = k
assert isinstance(unit, str)
units.add(unit)
if context == "execute":
(function,) = other
assert isinstance(function, str)
functions.add(function)
units.difference_update(self.unit_selector.options)
if units:
self.unit_selector.options.extend(units)
if functions:
# Added on the fly by Span.cumulative_worker_metrics
functions.add("N/A")
functions.difference_update(self.function_selector.options)
if functions:
self.function_selector.options.extend(functions)
self.function_selector.title = (
f"Filter by function ({len(self.function_selector.options)}):"
)
spans_ext: SpansSchedulerExtension | None = self.scheduler.extensions.get(
"spans"
)
if spans_ext:
tags = set(spans_ext.spans_search_by_tag)
tags.difference_update(self.span_tag_selector.options)
if tags:
self.span_tag_selector.options.extend(tags)
self.span_tag_selector.title = (
f"Filter by span tag ({len(self.span_tag_selector.options)}):"
)
def _bokeh_unit_format(self) -> str:
unit = self.unit_selector.value
if unit == "seconds":
return "00:00:00"
elif unit == "bytes":
return "0.00b"
elif unit == "count":
return "0"
else:
return "0.000"
def _format(self, val: float) -> str:
unit = self.unit_selector.value
if unit == "seconds":
return format_time(val)
elif unit == "bytes":
return format_bytes(int(val))
# count or custom user-defined metric
elif (ival := int(val)) == val:
return str(ival)
else:
return str(val)
def _get_palette(self) -> list[str]:
n = len(self.visible_activities)
try:
from bokeh.palettes import interp_palette
return list(interp_palette(Viridis11, n))
except ImportError:
# Bokeh 2.4
return [Viridis11[i % len(Viridis11)] for i in range(n)]
def _build_data_sources(self) -> None:
"""Pre-process and filter fine performance metrics; build data tables in
Bokeh format
Updates:
- self.substantial_change
- self.visible_activities
- self.visible_functions
- self.task_exec_by_prefix_src.data
- self.task_exec_by_activity_src.data
- self.get_data_by_activity_src.data
"""
visible_functions = set()
visible_activities = set()
execute_by_func: defaultdict[tuple[str, str], float] = defaultdict(float)
execute: defaultdict[str, float] = defaultdict(float)
get_data: defaultdict[str, float] = defaultdict(float)
function_sel = set(self.function_selector.value)
spans_ext: SpansSchedulerExtension | None = self.scheduler.extensions.get(
"spans"
)
if spans_ext and self.span_tag_selector.value:
span = spans_ext.merge_by_tags(*self.span_tag_selector.value)
metrics = span.cumulative_worker_metrics
elif spans_ext and spans_ext.spans:
# Calculate idle time
span = spans_ext.merge_all()
metrics = span.cumulative_worker_metrics
else:
# Spans extension is not loaded
metrics = {
k: v
for k, v in self.scheduler.cumulative_worker_metrics.items()
if isinstance(k, tuple)
and len(k) == 4 # Skip get-data, gather-deps, and memory-monitor
}
for (context, function, activity, unit), v in metrics.items():
if context != "execute":
continue # TODO visualize 'shuffle' metrics
assert isinstance(function, str)
assert isinstance(unit, str)
assert self.unit_selector.value
if unit != self.unit_selector.value:
continue
if function_sel and function not in function_sel:
continue
# Custom metrics won't necessarily contain a string as the label
activity = str(activity)
# TODO We could implement some fancy logic in spans.py to change the label
# if no other spans are running at the same time.
if not self.span_tag_selector.value and activity == "idle or other spans":
activity = "idle"
execute_by_func[function, activity] += v
execute[activity] += v
visible_functions.add(function)
visible_activities.add(activity)
if not self.function_selector.value and not self.span_tag_selector.value:
for k, v in self.scheduler.cumulative_worker_metrics.items():
if isinstance(k, tuple) and k[0] == "get-data":
_, activity, unit = k
assert isinstance(activity, str)
assert isinstance(unit, str)
assert self.unit_selector.value
if unit == self.unit_selector.value:
visible_activities.add(activity)
get_data[activity] += v
# Ignore memory-monitor and gather-dep metrics
if visible_functions != set(self.visible_functions):
self.substantial_change = True
self.visible_functions = sorted(visible_functions)
if visible_activities != set(self.visible_activities):
self.visible_activities = sorted(visible_activities)
(
self.task_exec_by_prefix_src.data,
self.task_exec_by_prefix_xmax,
) = self._build_task_execution_by_prefix_data(execute_by_func)
self.task_exec_by_activity_src.data = self._build_pie_data(execute)
self.get_data_by_activity_src.data = self._build_pie_data(get_data)
def _build_pie_data(self, data: defaultdict[str, float]) -> dict[str, list]:
"""Build the data source for a pie chart by activity
See also
--------
_build_pie_chart
"""
activities = self.visible_activities
# Generate palette based on all visible activities to make sure that
# colors match between the plots
palette = self._get_palette()
values = [data[activity] for activity in activities]
# Sort by values from largest to smallest
# Hide activities that are missing in the current plot from the legend
idx = [i for i, v in sorted(enumerate(values), key=lambda el: -el[1]) if v]
activities = [activities[i] for i in idx]
palette = [palette[i] for i in idx]
values = [values[i] for i in idx]
total_value = sum(values)
total_text = self._format(total_value)
percent_k = 100.0 / total_value if total_value else 0.0
angle_k = 2.0 * math.pi / total_value if total_value else 0.0
return {
"activity": activities,
"value": values,
"text": [self._format(v) + f" ({v * percent_k:.0f}%)" for v in values],
"angle": [v * angle_k for v in values],
"color": palette,
"total_text": [total_text] * len(values),
}
def _build_pie_chart(self, source: ColumnDataSource, title: str) -> figure:
"""Create pie chart by activity
See also
--------
_build_pie_data
"""
piechart = figure(
height=500,
sizing_mode="scale_both",
title=title,
tools="hover",
tooltips="@{activity}: @text
total: @{total_text}",
x_range=(-0.5, 1.0),
)
piechart.axis.axis_label = None
piechart.axis.visible = False
piechart.grid.grid_line_color = None
piechart.wedge(
x=0,
y=1,
radius=0.4,
start_angle=cumsum("angle", include_zero=True),
end_angle=cumsum("angle"),
line_color="white",
fill_color="color",
legend_field="activity",
source=source,
)
return piechart
def _build_task_execution_by_prefix_data(
self, data: defaultdict[tuple[str, str], float]
) -> tuple[dict[str, list], float]:
"""Build the data source for the execute by function stacked chart
See also
--------
_build_task_execution_by_prefix_chart
_update_task_execution_by_prefix_chart
"""
func_totals = [
sum(data[function, activity] for activity in self.visible_activities)
for function in self.visible_functions
]
perc_k = [100.0 / v if v else 0.0 for v in func_totals]
out: dict[str, list] = {
"__functions": self.visible_functions,
"____total_text": [self._format(v) for v in func_totals],
}
sc_visible_activities = []
for activity in self.visible_activities:
values = [data[function, activity] for function in self.visible_functions]
if not any(values):
continue
sc_visible_activities.append(activity)
out[activity] = values
out[f"__{activity}_text"] = [
self._format(v) + f" ({v * perc_ki:.0f}%)"
for v, perc_ki in zip(values, perc_k)
]
if sc_visible_activities != self.stacked_chart_visible_activities:
self.substantial_change = True
self.stacked_chart_visible_activities[:] = sc_visible_activities
return out, max(func_totals, default=0.0)
def _build_task_execution_by_prefix_chart(self) -> figure:
"""Create empty stacked bar chart for execute by function
See also
--------
_build_task_execution_by_prefix_data
_update_task_execution_by_prefix_chart
"""
barchart = figure(
y_range=[],
height=500,
sizing_mode="scale_both",
title="Task execution, by function",
tools=",".join(self.BASE_TOOLS),
)
barchart.yaxis.visible = True
# As of Bokeh 3.1, DataRange1D (the default) does not work when switching back
# from bytes (GiBs) to seconds (hundreds). So we need to manually update it.
barchart.x_range = Range1d(0, 1)
barchart.xaxis[0].formatter = NumeralTickFormatter(format="00:00:00")
barchart.xaxis.major_label_orientation = 0.4
barchart.grid.grid_line_color = None
return barchart
def _update_task_execution_by_prefix_chart(self) -> None:
"""Rebuild X axis and tooltips of execution by prefix stacked chart
See also
--------
_build_task_execution_by_prefix_data
_build_task_execution_by_prefix_chart
"""
barchart = self.task_exec_by_prefix_chart
assert barchart is not None
barchart.y_range = FactorRange(*self.visible_functions)
palette = [
p
for p, a in zip(self._get_palette(), self.visible_activities)
if a in self.stacked_chart_visible_activities
]
assert len(palette) == len(self.stacked_chart_visible_activities)
renderers = barchart.hbar_stack(
self.stacked_chart_visible_activities,
y="__functions",
width=0.9,
source=self.task_exec_by_prefix_src,
color=palette,
legend_label=self.stacked_chart_visible_activities,
)
# Create or refresh hovertools on top of base tools
barchart.tools = barchart.tools[: len(self.BASE_TOOLS)]
for vbar in renderers:
tooltips = [
("function", "@__functions"),
(vbar.name, f"@{{__{vbar.name}_text}}"),
("total", "@____total_text"),
]
barchart.add_tools(HoverTool(tooltips=tooltips, renderers=[vbar]))
barchart.renderers = renderers
class Contention(DashboardComponent):
"""
Event Loop Health (and GIL Contention, if configured)
"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.data = dict(
names=[
("Scheduler", "Event Loop"),
("Scheduler", "GIL"),
("Workers", "Event Loop"),
("Workers", "GIL"),
],
values=[0, 0, 0, 0],
text=["0s", "0%", "0s", "0%"],
)
title = "Event Loop & GIL Contention"
# Remove GIL related names/values if not monitoring GIL
if not self.scheduler.monitor.monitor_gil_contention:
title = "Event Loop"
for key in self.data:
self.data[key] = self.data[key][::2]
self.source = ColumnDataSource(data=self.data)
self.root = figure(
title=title,
x_range=FactorRange(*self.data["names"]),
y_range=(0, 1),
tools="",
toolbar_location="above",
**kwargs,
)
self.root.vbar(
x="names",
top="values",
width=0.9,
line_color="white",
source=self.source,
fill_color=factor_cmap(
field_name="names",
palette=["#b8e0ce", "#81aae4"],
factors=["Event Loop", "GIL"],
start=1,
end=2,
),
)
self.root.x_range.group_padding = 0.25
self.root.xaxis.minor_tick_line_alpha = 0
self.root.ygrid.visible = True
self.root.xgrid.visible = False
hover = HoverTool(
tooltips=[("Name", "@names"), ("Value", "@text")], mode="vline"
)
self.root.add_tools(hover)
@without_property_validation
@log_errors
def update(self):
s = self.scheduler
self.data["values"] = [
s._tick_interval_observed,
self.gil_contention_scheduler,
sum(w.metrics["event_loop_interval"] for w in s.workers.values())
/ (len(s.workers) or 1),
self.gil_contention_workers,
][:: 1 if s.monitor.monitor_gil_contention else 2]
# Format event loop as time and GIL (if configured) as %
self.data["text"] = [
(
f"{x * 100:.1f}%"
if i % 2 and s.monitor.monitor_gil_contention
else format_time(x)
)
for i, x in enumerate(self.data["values"])
]
update(self.source, self.data)
@property
def gil_contention_workers(self) -> float:
workers = self.scheduler.workers
if workers:
return sum(
w.metrics.get("gil_contention", 0) for w in workers.values()
) / len(workers)
return float("NaN")
@property
def gil_contention_scheduler(self) -> float:
return self.scheduler.monitor.recent().get("gil_contention", float("NaN"))
class ExceptionsTable(DashboardComponent):
"""
Exceptions logged in tasks.
Since there might be many related exceptions (e.g., all tasks in a given
task group fail for the same reason), we make a best-effort attempt to
(1) aggregate to the task group, and (2) deduplicate similar looking tasks.
"""
scheduler: Scheduler
def __init__(self, scheduler: Scheduler, width: int = 1000, **kwargs: Any):
self.scheduler = scheduler
self.names = [
"Task",
"Exception",
"Traceback",
"Worker(s)",
"Count",
]
self.source = ColumnDataSource({k: [] for k in self.names})
code_formatter = HTMLTemplateFormatter(
template='<%= value %>'
)
columns = [
TableColumn(
field="Task",
title="Task",
formatter=code_formatter,
width=150,
),
TableColumn(
field="Exception",
title="Exception",
formatter=code_formatter,
width=300,
),
TableColumn(
field="Traceback",
title="Traceback",
formatter=code_formatter,
width=300,
),
TableColumn(
field="Worker(s)",
title="Worker(s)",
formatter=code_formatter,
width=200,
),
TableColumn(
field="Count",
title="Count",
formatter=NumberFormatter(format="0,0"),
width=50,
),
]
if "sizing_mode" in kwargs:
sizing_mode = {"sizing_mode": kwargs["sizing_mode"]}
else:
sizing_mode = {}
self.root = DataTable(
source=self.source,
columns=columns,
reorderable=True,
sortable=True,
width=width,
index_position=None,
**_DATATABLE_STYLESHEETS_KWARGS,
**sizing_mode,
)
@without_property_validation
def update(self):
new_data = {name: [] for name in self.names}
erred_tasks = self.scheduler.erred_tasks
for ts in erred_tasks:
new_data["Task"].append(ts.key)
new_data["Exception"].append(ts.exception_text)
new_data["Traceback"].append(ts.traceback_text)
new_data["Worker(s)"].append(",\n".join(ts.erred_on))
new_data["Count"].append(len(ts.erred_on))
update(self.source, new_data)
class WorkerTable(DashboardComponent):
"""Status of the current workers
This is two plots, a text-based table for each host and a thin horizontal
plot laying out hosts by their current memory use.
"""
excluded_names = {
"executing",
"in_flight",
"in_memory",
"ready",
"time",
# Use scheduler.WorkerState.memory.managed instead of
# scheduler.WorkerState.metrics["managed_bytes"]; the two measures are slightly
# different. See explanation in scheduler.WorkerState.memory().
"managed_bytes",
"spilled_bytes",
}
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.names = [
"name",
"address",
"nthreads",
"cpu",
"memory",
"memory_limit",
"memory_percent",
"memory_managed",
"memory_unmanaged_old",
"memory_unmanaged_recent",
"memory_spilled",
"num_fds",
"host_net_io.read_bps",
"host_net_io.write_bps",
"host_disk_io.read_bps",
"host_disk_io.write_bps",
"cpu_fraction",
]
workers = self.scheduler.workers.values()
self.extra_names = sorted(
{
m
for ws in workers
for m, v in ws.metrics.items()
if m not in self.names and isinstance(v, (str, int, float))
}
- self.excluded_names
)
table_names = [
"name",
"address",
"nthreads",
"cpu",
"memory",
"memory_limit",
"memory_percent",
"memory_managed",
"memory_unmanaged_old",
"memory_unmanaged_recent",
"memory_spilled",
"num_fds",
"host_net_io.read_bps",
"host_net_io.write_bps",
"host_disk_io.read_bps",
"host_disk_io.write_bps",
]
column_title_renames = {
"memory_limit": "limit",
"memory_percent": "memory %",
"memory_managed": "managed",
"memory_unmanaged_old": "unmanaged old",
"memory_unmanaged_recent": "unmanaged recent",
"memory_spilled": "spilled",
"num_fds": "# fds",
"host_net_io.read_bps": "net read",
"host_net_io.write_bps": "net write",
"host_disk_io.read_bps": "disk read",
"host_disk_io.write_bps": "disk write",
}
self.source = ColumnDataSource({k: [] for k in self.names})
columns = {
name: TableColumn(field=name, title=column_title_renames.get(name, name))
for name in table_names
}
formatters = {
"cpu": NumberFormatter(format="0 %"),
"memory_percent": NumberFormatter(format="0.0 %"),
"memory": NumberFormatter(format="0.0 b"),
"memory_limit": NumberFormatter(format="0.0 b"),
"memory_managed": NumberFormatter(format="0.0 b"),
"memory_unmanaged_old": NumberFormatter(format="0.0 b"),
"memory_unmanaged_recent": NumberFormatter(format="0.0 b"),
"memory_spilled": NumberFormatter(format="0.0 b"),
"host_net_io.read_bps": NumberFormatter(format="0 b"),
"host_net_io.write_bps": NumberFormatter(format="0 b"),
"num_fds": NumberFormatter(format="0"),
"nthreads": NumberFormatter(format="0"),
"host_disk_io.read_bps": NumberFormatter(format="0 b"),
"host_disk_io.write_bps": NumberFormatter(format="0 b"),
}
table = DataTable(
source=self.source,
columns=[columns[n] for n in table_names],
reorderable=True,
sortable=True,
width_policy="max",
index_position=None,
**_DATATABLE_STYLESHEETS_KWARGS,
)
for name in table_names:
if name in formatters:
table.columns[table_names.index(name)].formatter = formatters[name]
extra_names = ["name", "address"] + self.extra_names
extra_columns = {
name: TableColumn(field=name, title=column_title_renames.get(name, name))
for name in extra_names
}
extra_table = DataTable(
source=self.source,
columns=[extra_columns[n] for n in extra_names],
reorderable=True,
sortable=True,
width_policy="max",
index_position=None,
**_DATATABLE_STYLESHEETS_KWARGS,
)
for name in extra_names:
if name in formatters:
extra_table.columns[extra_names.index(name)].formatter = formatters[
name
]
hover = HoverTool(
point_policy="follow_mouse",
tooltips="""
Worker (@name):
@memory_percent{0.0 %}
""",
)
mem_plot = figure(
title="Memory Use (%)",
toolbar_location=None,
x_range=(0, 1),
y_range=(-0.1, 0.1),
height=60,
tools="",
min_border_right=0,
**kwargs,
)
mem_plot.scatter(
source=self.source, x="memory_percent", y=0, size=10, fill_alpha=0.5
)
mem_plot.ygrid.visible = False
mem_plot.yaxis.minor_tick_line_alpha = 0
mem_plot.xaxis.visible = False
mem_plot.yaxis.visible = False
mem_plot.add_tools(hover, BoxSelectTool())
hover = HoverTool(
point_policy="follow_mouse",
tooltips="""
Worker (@name):
@cpu_fraction{0 %}
""",
)
cpu_plot = figure(
title="CPU Use (%)",
toolbar_location=None,
x_range=(0, 1),
y_range=(-0.1, 0.1),
height=60,
tools="",
min_border_right=0,
**kwargs,
)
cpu_plot.scatter(
source=self.source, x="cpu_fraction", y=0, size=10, fill_alpha=0.5
)
cpu_plot.ygrid.visible = False
cpu_plot.yaxis.minor_tick_line_alpha = 0
cpu_plot.xaxis.visible = False
cpu_plot.yaxis.visible = False
cpu_plot.add_tools(hover, BoxSelectTool())
self.cpu_plot = cpu_plot
if "sizing_mode" in kwargs:
sizing_mode = {"sizing_mode": kwargs["sizing_mode"]}
else:
sizing_mode = {}
components = [cpu_plot, mem_plot, table]
if self.extra_names:
components.append(extra_table)
self.root = column(*components, **sizing_mode)
@without_property_validation
def update(self):
data = {name: [] for name in self.names + self.extra_names}
for i, ws in enumerate(
sorted(self.scheduler.workers.values(), key=lambda ws: str(ws.name))
):
minfo = ws.memory
for name in self.names + self.extra_names:
if "." in name:
n0, _, n1 = name.partition(".")
v = ws.metrics.get(n0, {}).get(n1, None)
else:
v = ws.metrics.get(name, None)
data[name].append(v)
data["name"][-1] = ws.name if ws.name is not None else i
data["address"][-1] = ws.address
if ws.memory_limit:
data["memory_percent"][-1] = ws.metrics["memory"] / ws.memory_limit
else:
data["memory_percent"][-1] = ""
data["memory_limit"][-1] = ws.memory_limit
data["memory_managed"][-1] = minfo.managed
data["memory_unmanaged_old"][-1] = minfo.unmanaged_old
data["memory_unmanaged_recent"][-1] = minfo.unmanaged_recent
data["memory_unmanaged_recent"][-1] = minfo.unmanaged_recent
data["memory_spilled"][-1] = minfo.spilled
data["cpu"][-1] = ws.metrics["cpu"] / 100.0
data["cpu_fraction"][-1] = ws.metrics["cpu"] / 100.0 / ws.nthreads
data["nthreads"][-1] = ws.nthreads
for name in self.names + self.extra_names:
if name == "name":
data[name].insert(0, f"Total ({len(data[name])})")
continue
try:
if len(self.scheduler.workers) == 0:
total_data = None
elif name == "memory_percent":
total_mem = sum(
ws.memory_limit for ws in self.scheduler.workers.values()
)
total_data = (
(
sum(
ws.metrics["memory"]
for ws in self.scheduler.workers.values()
)
/ total_mem
)
if total_mem
else ""
)
elif name == "cpu":
total_data = (
sum(ws.metrics["cpu"] for ws in self.scheduler.workers.values())
/ 100
/ len(self.scheduler.workers.values())
)
elif name == "cpu_fraction":
total_data = (
sum(ws.metrics["cpu"] for ws in self.scheduler.workers.values())
/ 100
/ sum(ws.nthreads for ws in self.scheduler.workers.values())
)
else:
total_data = sum(data[name])
data[name].insert(0, total_data)
except TypeError:
data[name].insert(0, None)
self.source.data.update(data)
class Shuffling(DashboardComponent):
"""Occupancy (in time) per worker"""
@log_errors
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
self.source = ColumnDataSource(
{
"worker": [],
"y": [],
"comm_memory": [],
"comm_memory_limit": [],
"comm_buckets": [],
"comm_avg_duration": [],
"comm_avg_size": [],
"comm_read": [],
"comm_written": [],
"comm_color": [],
"disk_memory": [],
"disk_memory_limit": [],
"disk_buckets": [],
"disk_avg_duration": [],
"disk_avg_size": [],
"disk_read": [],
"disk_written": [],
"disk_color": [],
}
)
self.totals_source = ColumnDataSource(
{
"x": ["Network Send", "Network Receive", "Disk Write", "Disk Read"],
"values": [0, 0, 0, 0],
}
)
self.comm_memory = figure(
title="Comms Buffer",
tools="",
toolbar_location="above",
x_range=Range1d(0, 100_000_000),
**kwargs,
)
self.comm_memory.hbar(
source=self.source,
right="comm_memory",
y="y",
height=0.9,
color="comm_color",
)
hover = HoverTool(
tooltips=[
("Memory Used", "@comm_memory{0.00 b}"),
("Average Write", "@comm_avg_size{0.00 b}"),
("# Buckets", "@comm_buckets"),
("Average Duration", "@comm_avg_duration"),
],
formatters={"@comm_avg_duration": "datetime"},
mode="hline",
)
self.comm_memory.add_tools(hover)
self.comm_memory.x_range.start = 0
self.comm_memory.x_range.end = 1
self.comm_memory.xaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.disk_memory = figure(
title="Disk Buffer",
tools="",
toolbar_location="above",
x_range=Range1d(0, 100_000_000),
**kwargs,
)
self.disk_memory.yaxis.visible = False
self.disk_memory.hbar(
source=self.source,
right="disk_memory",
y="y",
height=0.9,
color="disk_color",
)
hover = HoverTool(
tooltips=[
("Memory Used", "@disk_memory{0.00 b}"),
("Average Write", "@disk_avg_size{0.00 b}"),
("# Buckets", "@disk_buckets"),
("Average Duration", "@disk_avg_duration"),
],
formatters={"@disk_avg_duration": "datetime"},
mode="hline",
)
self.disk_memory.add_tools(hover)
self.disk_memory.xaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
self.totals = figure(
title="Total movement",
tools="",
toolbar_location="above",
**kwargs,
)
titles = ["Network Send", "Network Receive", "Disk Write", "Disk Read"]
self.totals = figure(
x_range=titles,
title="Totals",
toolbar_location=None,
tools="",
**kwargs,
)
self.totals.vbar(
x="x",
top="values",
width=0.9,
source=self.totals_source,
)
self.totals.xgrid.grid_line_color = None
self.totals.y_range.start = 0
self.totals.yaxis[0].formatter = NumeralTickFormatter(format="0.0 b")
hover = HoverTool(
tooltips=[("Total", "@values{0.00b}")],
mode="vline",
)
self.totals.add_tools(hover)
self.root = row(self.comm_memory, self.disk_memory)
@without_property_validation
@log_errors
def update(self):
input = self.scheduler.extensions["shuffle"].heartbeats
if not input:
return
input = list(input.values())[-1] # TODO: multiple concurrent shuffles
data = defaultdict(list)
now = time()
for i, (worker, d) in enumerate(input.items()):
data["y"].append(i)
data["worker"].append(worker)
for prefix in ["comm", "disk"]:
memory_limit = d[prefix]["memory_limit"] or 0
data[f"{prefix}_total"].append(d[prefix]["total"])
data[f"{prefix}_memory"].append(d[prefix]["memory"])
data[f"{prefix}_memory_limit"].append(memory_limit)
data[f"{prefix}_buckets"].append(d[prefix]["buckets"])
data[f"{prefix}_avg_duration"].append(d[prefix]["avg_duration"])
data[f"{prefix}_avg_size"].append(d[prefix]["avg_size"])
data[f"{prefix}_read"].append(d[prefix]["read"])
data[f"{prefix}_written"].append(d[prefix]["written"])
if self.scheduler.workers[worker].last_seen < now - 5:
data[f"{prefix}_color"].append("gray")
elif d[prefix]["memory"] > memory_limit:
data[f"{prefix}_color"].append("red")
else:
data[f"{prefix}_color"].append("blue")
totals = {
"x": ["Network Send", "Network Receive", "Disk Write", "Disk Read"],
"values": [
sum(data["comm_written"]),
sum(data["comm_read"]),
sum(data["disk_written"]),
sum(data["disk_read"]),
],
}
update(self.totals_source, totals)
update(self.source, dict(data))
limit = max(data["comm_memory_limit"] + data["disk_memory_limit"]) * 1.2
self.comm_memory.x_range.end = limit
self.disk_memory.x_range.end = limit
_STYLES = {
"width": "100%",
"height": "100%",
"max-width": "1920px",
"max-height": "1080px",
"padding": "12px",
"border": "1px solid lightgray",
"box-shadow": "inset 1px 0 8px 0 lightgray",
"overflow": "auto",
}
class SchedulerLogs:
def __init__(self, scheduler, start=None):
logs = scheduler.get_logs(start=start, timestamps=True)
if not logs:
logs_html = (
'No logs to report
'
)
else:
logs_html = Log(
"\n".join(
"%s - %s"
% (datetime.fromtimestamp(time).strftime("%H:%M:%S.%f"), line)
for time, level, line in logs
)
)._repr_html_()
self.root = Div(text=logs_html, styles=_STYLES)
@log_errors
def systemmonitor_doc(scheduler, extra, doc):
sysmon = SystemMonitor(scheduler, sizing_mode="stretch_both")
doc.title = "Dask: Scheduler System Monitor"
add_periodic_callback(doc, sysmon, 500)
doc.add_root(sysmon.root)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
@log_errors
def shuffling_doc(scheduler, extra, doc):
doc.title = "Dask: Shuffling"
shuffling = Shuffling(scheduler, width=400, height=400)
workers_memory = WorkersMemory(scheduler, width=400, height=400)
timeseries = SystemTimeseries(
scheduler, width=1600, height=200, follow_interval=10000
)
event_loop = Contention(scheduler, width=200, height=400)
add_periodic_callback(doc, shuffling, 200)
add_periodic_callback(doc, workers_memory, 200)
add_periodic_callback(doc, timeseries, 500)
add_periodic_callback(doc, event_loop, 500)
timeseries.bandwidth.y_range = timeseries.disk.y_range
doc.add_root(
column(
row(
workers_memory.root,
shuffling.comm_memory,
shuffling.disk_memory,
shuffling.totals,
event_loop.root,
),
row(column(timeseries.bandwidth, timeseries.disk)),
)
)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
@log_errors
def stealing_doc(scheduler, extra, doc):
occupancy = Occupancy(scheduler)
stealing_ts = StealingTimeSeries(scheduler)
stealing_events = StealingEvents(scheduler)
stealing_events.root.x_range = stealing_ts.root.x_range
doc.title = "Dask: Work Stealing"
add_periodic_callback(doc, occupancy, 500)
add_periodic_callback(doc, stealing_ts, 500)
add_periodic_callback(doc, stealing_events, 500)
doc.add_root(
row(
occupancy.root,
column(
stealing_ts.root,
stealing_events.root,
sizing_mode="stretch_both",
),
)
)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
@log_errors
def events_doc(scheduler, extra, doc):
events = Events(scheduler, "all", height=250)
events.update()
add_periodic_callback(doc, events, 500)
doc.title = "Dask: Scheduler Events"
doc.add_root(column(events.root, sizing_mode="scale_width"))
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
@log_errors
def exceptions_doc(scheduler, extra, doc):
table = ExceptionsTable(scheduler)
table.update()
add_periodic_callback(doc, table, 1000)
doc.title = "Dask: Exceptions"
doc.add_root(table.root)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
@log_errors
def workers_doc(scheduler, extra, doc):
table = WorkerTable(scheduler, sizing_mode="stretch_width")
table.update()
add_periodic_callback(doc, table, 500)
doc.title = "Dask: Workers"
doc.add_root(table.root)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
@log_errors
def hardware_doc(scheduler, extra, doc):
hw = Hardware(scheduler)
hw.update()
doc.title = "Dask: Cluster Hardware Bandwidth"
doc.add_root(hw.root)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
add_periodic_callback(doc, hw, 500)
@log_errors
def tasks_doc(scheduler, extra, doc):
ts = TaskStream(
scheduler,
n_rectangles=dask.config.get(
"distributed.scheduler.dashboard.tasks.task-stream-length"
),
clear_interval="60s",
sizing_mode="stretch_both",
)
ts.update()
add_periodic_callback(doc, ts, 5000)
doc.title = "Dask: Task Stream"
doc.add_root(ts.root)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
@log_errors
def graph_doc(scheduler, extra, doc):
graph = TaskGraph(scheduler, sizing_mode="stretch_both")
doc.title = "Dask: Task Graph"
graph.update()
add_periodic_callback(doc, graph, 200)
doc.add_root(graph.root)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
@log_errors
def tg_graph_doc(scheduler, extra, doc):
tg_graph = TaskGroupGraph(scheduler, sizing_mode="stretch_both")
doc.title = "Dask: Task Groups Graph"
tg_graph.update()
add_periodic_callback(doc, tg_graph, 200)
doc.add_root(tg_graph.root)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
@log_errors
def status_doc(scheduler, extra, doc):
cluster_memory = ClusterMemory(scheduler, sizing_mode="stretch_both")
cluster_memory.update()
add_periodic_callback(doc, cluster_memory, 100)
doc.add_root(cluster_memory.root)
if len(scheduler.workers) <= 100:
workers_memory = WorkersMemory(scheduler, sizing_mode="stretch_both")
processing = CurrentLoad(scheduler, sizing_mode="stretch_both")
processing_root = processing.processing_figure
else:
workers_memory = WorkersMemoryHistogram(scheduler, sizing_mode="stretch_both")
processing = ProcessingHistogram(scheduler, sizing_mode="stretch_both")
processing_root = processing.root
current_load = CurrentLoad(scheduler, sizing_mode="stretch_both")
occupancy = Occupancy(scheduler, sizing_mode="stretch_both")
workers_transfer_bytes = WorkersTransferBytes(scheduler, sizing_mode="stretch_both")
cpu_root = current_load.cpu_figure
occupancy_root = occupancy.root
workers_memory.update()
workers_transfer_bytes.update()
processing.update()
current_load.update()
occupancy.update()
add_periodic_callback(doc, workers_memory, 100)
add_periodic_callback(doc, workers_transfer_bytes, 100)
add_periodic_callback(doc, processing, 100)
add_periodic_callback(doc, current_load, 100)
add_periodic_callback(doc, occupancy, 100)
doc.add_root(workers_memory.root)
tabs = [
TabPanel(child=processing_root, title="Processing"),
TabPanel(child=cpu_root, title="CPU"),
TabPanel(child=occupancy_root, title="Occupancy"),
TabPanel(child=workers_transfer_bytes.root, title="Data Transfer"),
]
help_ = HelpTool(
redirect="https://docs.dask.org/en/stable/dashboard.html#task-processing-cpu-utilization-occupancy-data-transfer",
description="A description of Task Processing/CPU Utilization/Occupancy",
)
for tab in tabs:
tab.child.toolbar_location = "above"
tab.child.add_tools(help_)
proc_tabs = Tabs(tabs=tabs, name="processing_tabs", sizing_mode="stretch_both")
doc.add_root(proc_tabs)
task_stream = TaskStream(
scheduler,
n_rectangles=dask.config.get(
"distributed.scheduler.dashboard.status.task-stream-length"
),
clear_interval="5s",
sizing_mode="stretch_both",
)
task_stream.update()
add_periodic_callback(doc, task_stream, 100)
doc.add_root(task_stream.root)
task_progress = TaskProgress(scheduler, sizing_mode="stretch_both")
task_progress.update()
add_periodic_callback(doc, task_progress, 100)
doc.add_root(task_progress.root)
doc.title = "Dask: Status"
doc.theme = BOKEH_THEME
doc.template = env.get_template("status.html")
doc.template_variables.update(extra)
@log_errors
@curry
def individual_doc(cls, interval, scheduler, extra, doc, fig_attr="root", **kwargs):
# Note: @log_errors and @curry are not compatible
fig = cls(scheduler, sizing_mode="stretch_both", **kwargs)
fig.update()
add_periodic_callback(doc, fig, interval)
doc.add_root(getattr(fig, fig_attr))
doc.theme = BOKEH_THEME
doc.title = "Dask: " + funcname(cls)
@log_errors
def individual_profile_doc(scheduler, extra, doc):
prof = ProfileTimePlot(scheduler, sizing_mode="stretch_both", doc=doc)
doc.add_root(prof.root)
prof.trigger_update()
doc.theme = BOKEH_THEME
@log_errors
def individual_profile_server_doc(scheduler, extra, doc):
prof = ProfileServer(scheduler, sizing_mode="stretch_both", doc=doc)
doc.add_root(prof.root)
prof.trigger_update()
doc.theme = BOKEH_THEME
@log_errors
def profile_doc(scheduler, extra, doc):
doc.title = "Dask: Profile"
prof = ProfileTimePlot(scheduler, sizing_mode="stretch_both", doc=doc)
doc.add_root(prof.root)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
prof.trigger_update()
@log_errors
def profile_server_doc(scheduler, extra, doc):
doc.title = "Dask: Profile of Event Loop"
prof = ProfileServer(scheduler, sizing_mode="stretch_both", doc=doc)
doc.add_root(prof.root)
doc.template = env.get_template("simple.html")
doc.template_variables.update(extra)
doc.theme = BOKEH_THEME
prof.trigger_update()