Assigns timestamps to all the elements of a collection.
In the following examples, we create a pipeline with a PCollection
and attach a timestamp value to each of its elements. When windowing and late data play an important role in streaming pipelines, timestamps are especially useful.
The elements themselves often already contain a timestamp field. beam.window.TimestampedValue
takes a value and a Unix timestamp in the form of seconds.
{% github_sample /apache/beam/blob/master/sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps.py tag:withtimestamps_event_time %}``` {:.notebook-skip} Output `PCollection` after getting the timestamps: {:.notebook-skip}
{% github_sample /apache/beam/blob/master/sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps_test.py tag:plant_timestamps %}```
{% include buttons-code-snippet.md py=“sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps.py” notebook=“examples/notebooks/documentation/transforms/python/elementwise/withtimestamps” %}
To convert from a time.struct_time
to unix_time
you can use time.mktime
. For more information on time formatting options, see time.strftime
.
{% github_sample /apache/beam/blob/master/sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps.py tag:time_tuple2unix_time %}``` To convert from a [`datetime.datetime`](https://docs.python.org/3/library/datetime.html#datetime.datetime) to `unix_time` you can use convert it to a `time.struct_time` first with [`datetime.timetuple`](https://docs.python.org/3/library/datetime.html#datetime.datetime.timetuple).
{% github_sample /apache/beam/blob/master/sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps.py tag:datetime2unix_time %}```
If each element has a chronological number, these numbers can be used as a logical clock. These numbers have to be converted to a “seconds” equivalent, which can be especially important depending on your windowing and late data rules.
{% github_sample /apache/beam/blob/master/sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps.py tag:withtimestamps_logical_clock %}``` {:.notebook-skip} Output `PCollection` after getting the timestamps: {:.notebook-skip}
{% github_sample /apache/beam/blob/master/sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps_test.py tag:plant_events %}```
{% include buttons-code-snippet.md py=“sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps.py” notebook=“examples/notebooks/documentation/transforms/python/elementwise/withtimestamps” %}
If the elements do not have any time data available, you can also use the current processing time for each element. Note that this grabs the local time of the worker that is processing each element. Workers might have time deltas, so using this method is not a reliable way to do precise ordering.
By using processing time, there is no way of knowing if data is arriving late because the timestamp is attached when the element enters into the pipeline.
{% github_sample /apache/beam/blob/master/sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps.py tag:withtimestamps_processing_time %}``` {:.notebook-skip} Output `PCollection` after getting the timestamps: {:.notebook-skip}
{% github_sample /apache/beam/blob/master/sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps_test.py tag:plant_processing_times %}```
{% include buttons-code-snippet.md py=“sdks/python/apache_beam/examples/snippets/transforms/elementwise/withtimestamps.py” notebook=“examples/notebooks/documentation/transforms/python/elementwise/withtimestamps” %}