[BUG] Hover tool takes long time to render

[sistemicorp]

Possible regression from bokeh ver 2.3.0 to 2.4.0.
Python 3.8. Chrome Version 93.0.4577.82 (Official Build) (64-bit). Ubuntu 20.

The hover tool is lightening fast to render in v2.3.0, but is very slow in 2.4.0 for the same minimal example.

from bokeh.layouts import layout
from bokeh.io import show
from bokeh.plotting import figure
from bokeh.models import ColumnDataSource, Range1d, LinearScale, LinearAxis, HoverTool

NUM_DATA_POINTS = 48000

source = ColumnDataSource(data={
    "t": [i for i in range(1, NUM_DATA_POINTS)],
    "i": [i for i in range(1, NUM_DATA_POINTS)],
    "y": [i * 2 for i in range(1, NUM_DATA_POINTS)],
})

plot = figure(toolbar_location="above",
              y_range=(0.1, NUM_DATA_POINTS*4),
              x_range=(0, NUM_DATA_POINTS),
              y_axis_type="linear")

line = plot.line(x="t", y="i", line_width=2, source=source, color="green", legend_label="i")
plot.line(x="t", y="y", line_width=4, alpha=0.4, source=source, color="red", legend_label="y")

ht = HoverTool(
    tooltips=[("i", "@i{0.00}"), ("y", "@y{0}"), ("t", "@t{0.000} ms")],
    # >>> Uncomment to make hover tool really slow
    #mode='vline',
    #show_arrow=True,
    #renderers=[line],
)
plot.tools = [ht]
doc_layout = layout()
doc_layout.children.append(plot)
show(doc_layout)

Chrome Inspect console:

bokeh-2.4.0.min.js:520 [Violation] 'requestAnimationFrame' handler took 6005ms
bokeh-2.4.0.min.js:520 [Violation] 'requestAnimationFrame' handler took 5998ms
bokeh-2.4.0.min.js:520 [Violation] 'requestAnimationFrame' handler took 6091ms

[Material-Scientist]

Unfortunately, the issue still persists:

Bokeh 2.3.3 (left) vs Bokeh 2.4.1 (right):

2021-10-18-17-29-20.mp4

Minimal reproducible example:

import xarray as xr
import numpy as np
import pandas as pd
import hvplot.xarray, hvplot.pandas
import holoviews

ds = xr.Dataset(
    data_vars=dict(
        frate=(["time","symbol"], np.random.rand(2307,138))
    ),
    coords=dict(
        symbol=(["symbol"], 
               np.array(['1000SHIBUSDT', '1000XECUSDT', '1INCHUSDT', 'AAVEUSDT', 'ADABUSD',
       'ADAUSDT', 'AKROUSDT', 'ALGOUSDT', 'ALICEUSDT', 'ALPHAUSDT',
       'ANKRUSDT', 'ARUSDT', 'ATAUSDT', 'ATOMUSDT', 'AUDIOUSDT',
       'AVAXUSDT', 'AXSUSDT', 'BAKEUSDT', 'BALUSDT', 'BANDUSDT',
       'BATUSDT', 'BCHUSDT', 'BELUSDT', 'BLZUSDT', 'BNBBUSD', 'BNBUSDT',
       'BTCBUSD', 'BTCDOMUSDT', 'BTCSTUSDT', 'BTCUSDT', 'BTSUSDT',
       'BTTUSDT', 'BZRXUSDT', 'C98USDT', 'CELOUSDT', 'CELRUSDT',
       'CHRUSDT', 'CHZUSDT', 'COMPUSDT', 'COTIUSDT', 'CRVUSDT', 'CTKUSDT',
       'CVCUSDT', 'DASHUSDT', 'DEFIUSDT', 'DENTUSDT', 'DGBUSDT',
       'DODOUSDT', 'DOGEBUSD', 'DOGEUSDT', 'DOTUSDT', 'DYDXUSDT',
       'EGLDUSDT', 'ENJUSDT', 'EOSUSDT', 'ETCUSDT', 'ETHBUSD', 'ETHUSDT',
       'FILUSDT', 'FLMUSDT', 'FTMUSDT', 'FTTBUSD', 'GALAUSDT', 'GRTUSDT',
       'GTCUSDT', 'HBARUSDT', 'HNTUSDT', 'HOTUSDT', 'ICPUSDT', 'ICXUSDT',
       'IOSTUSDT', 'IOTAUSDT', 'IOTXUSDT', 'KAVAUSDT', 'KEEPUSDT',
       'KLAYUSDT', 'KNCUSDT', 'KSMUSDT', 'LINAUSDT', 'LINKUSDT',
       'LITUSDT', 'LRCUSDT', 'LTCUSDT', 'LUNAUSDT', 'MANAUSDT',
       'MASKUSDT', 'MATICUSDT', 'MKRUSDT', 'MTLUSDT', 'NEARUSDT',
       'NEOUSDT', 'NKNUSDT', 'OCEANUSDT', 'OGNUSDT', 'OMGUSDT', 'ONEUSDT',
       'ONTUSDT', 'QTUMUSDT', 'RAYUSDT', 'REEFUSDT', 'RENUSDT', 'RLCUSDT',
       'RSRUSDT', 'RUNEUSDT', 'RVNUSDT', 'SANDUSDT', 'SCUSDT', 'SFPUSDT',
       'SKLUSDT', 'SNXUSDT', 'SOLBUSD', 'SOLUSDT', 'SRMUSDT', 'STMXUSDT',
       'STORJUSDT', 'SUSHIUSDT', 'SXPUSDT', 'THETAUSDT', 'TLMUSDT',
       'TOMOUSDT', 'TRBUSDT', 'TRXUSDT', 'UNFIUSDT', 'UNIUSDT', 'VETUSDT',
       'WAVESUSDT', 'XEMUSDT', 'XLMUSDT', 'XMRUSDT', 'XRPBUSD', 'XRPUSDT',
       'XTZUSDT', 'YFIIUSDT', 'YFIUSDT', 'ZECUSDT', 'ZENUSDT', 'ZILUSDT',
       'ZRXUSDT'])),
        time=(["time"],pd.date_range(start='2019-09-10 08:00:00', end='2021-10-18 00:00:00', periods=2307)),)
)

plot = ds.hvplot.heatmap(
    'time','symbol','frate',cmap='coolwarm',
)
plot

2021-10-18-18-01-53.mp4