verticapy.performance.vertica.qprof.QueryProfiler.get_qsteps#

QueryProfiler.get_qsteps(unit: Literal['s', 'm', 'h'] = 's', kind: Literal['bar', 'barh'] = 'bar', categoryorder: Literal['trace', 'category ascending', 'category descending', 'total ascending', 'total descending', 'min ascending', 'min descending', 'max ascending', 'max descending', 'sum ascending', 'sum descending', 'mean ascending', 'mean descending', 'median ascending', 'median descending'] = 'sum descending', show: bool = True, **style_kwargs) → PlottingBase | TableSample | Axes | mFigure | Highchart | Highstock | Figure | vDataFrame#

Returns the Query Execution Steps chart.

Parameters#

unit: str, optional

Unit used to draw the chart.

s:
second
m:
minute
h:
hour

kind: str, optional

Chart Type.

bar:
Bar Chart.
barh:
Horizontal Bar Chart.

categoryorder: str, optional

How to sort the bars. One of the following options:

trace (no transformation)
category ascending
category descending
total ascending
total descending
min ascending
min descending
max ascending
max descending
sum ascending
sum descending
mean ascending
mean descending
median ascending
median descending

show: bool, optional

If set to True, the Plotting object is returned.

**style_kwargs

Any optional parameter to pass to the plotting functions.

Returns#

obj: Plotting Object.

Examples#

First, let’s import the QueryProfiler object.

from verticapy.performance.vertica import QueryProfiler

Then we can create a query:

qprof = QueryProfiler(
    "select transaction_id, statement_id, request, request_duration"
    " from query_requests where start_timestamp > now() - interval'1 hour'"
    " order by request_duration desc limit 10;"
)

We can get the time breakdown of all the steps in a graphical output, we can call the get_qsteps attribute.

qprof.get_qsteps(kind="bar")

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Note

For more details, please look at QueryProfiler.