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Version: Python


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.


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



The source table.


The timestamp column in the source table to monitor.


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.


The name of the new Boolean column.


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


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")