timeshift Adjusts timestamps relative to a given start time, with an optional speedup.
timeshift field, [start = time, speed = double]
Description The timeshift
operator adjusts a series of time values by anchoring them
around a given start
time.
With speed
, you can adjust the relative speed of the time series induced by
field
with a multiplicative factor. This has the effect of making the time
series "faster" for values great than 1 and "slower" for values less than 1.
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t 0 t 2 t 3 t 1 t 4 Time Time Event Timestamps Timestamp Rewriting a c d b e Time Timestamp Scaling t 0 t 2 t 3 t 1 t 4 a c d b e u 0 u 2 u 3 u 1 u 4 u 0 u 2 u 3 u 1 u 4 a c d b e t 0 t 2 t 3 t 1 t 4
<field>
The field containing the timestamp values.
start = time (optional)
The timestamp to anchor the time values around.
Defaults to the first non-null timestamp in field
.
speed = double (optional)
A constant factor to be divided by the inter-arrival time. For example, 2.0
decreases the event gaps by a factor of two, resulting a twice as fast dataflow.
A value of 0.1 creates dataflow that spans ten times the original time frame.
Defaults to 1.0
.
Examples Reset events to begin at Jan 1, 1984 load_http "https://storage.googleapis.com/tenzir-datasets/M57/zeek-all.log.zst"
decompress "zstd"
read_zeek_tsv
timeshift ts, start = 1984 - 01 - 01
Scale inter-arrival times by 100x As above, but also make the time span of the trace 100 times longer:
load_http "https://storage.googleapis.com/tenzir-datasets/M57/zeek-all.log.zst"
decompress "zstd"
read_zeek_tsv
timeshift ts, start = 1984 - 01 - 01 , speed = 0.01