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Version: Python

time_window

The time_window method creates a new table by applying a time window to the source table and adding a new Boolean column.

  • The Boolean column's value will be false when the row's timestamp is older than the specified number of nanoseconds.
  • If the timestamp is within N nanoseconds (windowNanos) of the current time, the result column is true.
  • If the timestamp is null, the value is null. The resulting table adds a new row whenever the source table ticks, and modifies a row's value in the result column (from true to false) when it passes out of the window.

Syntax​

time_window(table: Table, ts_col: str, window: int, bool_col: str) -> Table

Parameters​

ParameterTypeDescription
tableTable

The source table.

ts_colstr

The timestamp column in the source table to monitor.

windowint

How much time, in nanoseconds, to include in the window. Rows with a "Timestamp" value greater than or equal to the current time minus windowNanos will be marked true in the new output column. Results are refreshed on each UpdateGraph cycle.

bool_colstr

The name of the new Boolean column.

Returns​

A new table that contains an in-window Boolean column.

Examples​

The following example creates a time table, and then applies time_window to show whether a given row is within the last 10 seconds.

from deephaven.experimental import time_window
from deephaven import time_table

source = time_table("PT00:00:01")

result = time_window(source, "Timestamp", 5000000000, "WithinLastFiveSeconds")

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