39
edits
Telemetry/Custom analysis with spark: Difference between revisions
Telemetry/Custom analysis with spark (view source)
Revision as of 12:37, 17 October 2016
, 17 October 2016→Setting Up a Dashboard
(Sharing Notebooks) |
|||
| Line 35: | Line 35: | ||
The notebook is setup to work with Spark. See the "Using Spark" section for more information. | The notebook is setup to work with Spark. See the "Using Spark" section for more information. | ||
=== | === Schedule a period job === | ||
Scheduled Spark jobs allow a Jupyter notebook to be updated consistently, making a nice and easy-to-use dashboard. | Scheduled Spark jobs allow a Jupyter notebook to be updated consistently, making a nice and easy-to-use dashboard. | ||
| Line 49: | Line 49: | ||
## Set a schedule frequency using the remaining fields. | ## Set a schedule frequency using the remaining fields. | ||
Now, the notebook will be updated automatically | Now, the notebook will be updated automatically and the results can be easily shared. Furthermore, all files stored in the notebook's local working directory will be automatically uploaded to S3, which comes in handy for simple ETL jobs for example. | ||
For reference, see [https://robertovitillo.com/2015/03/13/simple-dashboards-with-scheduled-spark-jobs-and-plotly Simple Dashboard with Scheduled Spark Jobs and Plotly]. | For reference, see [https://robertovitillo.com/2015/03/13/simple-dashboards-with-scheduled-spark-jobs-and-plotly Simple Dashboard with Scheduled Spark Jobs and Plotly]. | ||