Using NiFi CLI to Restore NiFi Flows From Backups

Using NiFi CLI to Restore NiFi Flows From Backups

Please note, Apache NiFi 1.11.4 is now available for download


#> registry list-buckets -u

#   Name   Id                                     Description 
-   ----   ------------------------------------   ----------- 
1   IOT    45834964-d022-4f4c-891f-695898e1e5f0   (empty)     
2   IoT    250a5ae5-ced8-4f4e-8b3b-01eb9d47a0d9   (empty)     
3   dev    46b7bab7-400f-44ae-a0e6-7340ff19c96f   (empty)     
4   iot    c594d6bc-7413-4f6a-ba9a-50b8020eec37   (empty)     
5   prod   0bf59d2e-1dd5-4d24-8aa0-0614bf991dc9   (empty)     

#> registry create-flow -verbose -u -b 250a5ae5-ced8-4f4e-8b3b-01eb9d47a0d9 --flowName iotFlow


#> registry import-flow-version -verbose -u -f a5a4ac59-9aeb-416e-937f-e601ca8beba9 -i iot-1.json

#> registry list-flows  -u -b 250a5ae5-ced8-4f4e-8b3b-01eb9d47a0d9

#   Name      Id                                     Description 
-   -------   ------------------------------------   ----------- 
1   iotFlow   a5a4ac59-9aeb-416e-937f-e601ca8beba9   (empty)     

Fixing Linux Webcams

  v4l2-ctl --list-devices
  v4l2-ctl -d /dev/video0 --list-ctrls
  v4l2-ctl --get-ctrl=white_balance_temperature
  v4l2-ctl --set-ctrl=white_balance_temperature=4000
  v4l2-ctl --set-ctrl=white_balance_temperature=4000 -d /dev/video0
  v4l2-ctl --set-ctrl=white_balance_temperature_auto=1
  v4l2-ctl --set-ctrl=white_balance_temperature_auto=0
  v4l2-ctl --set-ctrl=white_balance_temperature_auto=4000
  v4l2-ctl --set-ctrl=exposure_auto=3
  v4l2-ctl --set-ctrl=exposure_auto_priority=0
  v4l2-ctl --set-ctrl=exposure_absolute=250
  v4l2-ctl --set-ctrl=exposure_absolute=0
  v4l2-ctl --set-ctrl=exposure_absolute=250
  v4l2-ctl --set-ctrl=gain=0
  v4l2-ctl -d /dev/video0 --list-ctrls
  v4l2-ctl --set-ctrl=white_balance_temperature_auto=4000
  v4l2-ctl --set-ctrl=white_balance_temperature_auto=0
  v4l2-ctl --set-ctrl=white_balance_temperature=4000
 v4l2-ctl -d /dev/video0 --list-ctrls

This article is great:

v4l2-ctl -d /dev/video0 --list-ctrls
                     brightness 0x00980900 (int)    : min=0 max=255 step=1 default=128 value=128
                       contrast 0x00980901 (int)    : min=0 max=255 step=1 default=128 value=128
                     saturation 0x00980902 (int)    : min=0 max=255 step=1 default=128 value=128
 white_balance_temperature_auto 0x0098090c (bool)   : default=1 value=0
                           gain 0x00980913 (int)    : min=0 max=255 step=1 default=0 value=0
           power_line_frequency 0x00980918 (menu)   : min=0 max=2 default=2 value=2
      white_balance_temperature 0x0098091a (int)    : min=2000 max=6500 step=1 default=4000 value=4000
                      sharpness 0x0098091b (int)    : min=0 max=255 step=1 default=128 value=128
         backlight_compensation 0x0098091c (int)    : min=0 max=1 step=1 default=0 value=0
                  exposure_auto 0x009a0901 (menu)   : min=0 max=3 default=3 value=3
              exposure_absolute 0x009a0902 (int)    : min=3 max=2047 step=1 default=250 value=83 flags=inactive
         exposure_auto_priority 0x009a0903 (bool)   : default=0 value=0
                   pan_absolute 0x009a0908 (int)    : min=-36000 max=36000 step=3600 default=0 value=0
                  tilt_absolute 0x009a0909 (int)    : min=-36000 max=36000 step=3600 default=0 value=0
                 focus_absolute 0x009a090a (int)    : min=0 max=250 step=5 default=0 value=0 flags=inactive
                     focus_auto 0x009a090c (bool)   : default=1 value=1
                  zoom_absolute 0x009a090d (int)    : min=100 max=500 step=1 default=100 value=100

v4l2-ctl --list-devices
HD Pro Webcam C920 (usb-70090000.xusb-2.2):

ODPI's OpenDS4All - Open Source Data Science Content To Teach the World


Start learning now:

ODPI has officially announced this recently and it looks great.

There is a ton of amazing materials including slides, notes, documentation, homework, exercises and Jupyter notebooks covering Data Wrangling, Data Science, the Basics and Apache Spark.   


This“starter set” of training materials can help you build a Data Science program for yourself, your company, your university or your non-profit.    I am going to bring some of these to my meetups and hopefully can help give back with new materials, updates and suggestions.

These are college level materials developed by the University of Pennsylvania and open source via the ODPI with IBM leading.   The code and slides look great.   I can see these helping to enable the world adding another million desperately needed Data Scientists, Data Engineers and Data Science Enabled professionals.

I have been running some of this via Cloudera Machine Learning in my CDP cluster in AWS and it works great.   This is really well made.   I am hoping to create a module on Streaming Data Science to contribute.