FLiP-Pi-BreakoutGarden
FLiP-Py
Gear / Hardware
- Raspberry Pi 3 Model B Rev 1.2, Bullseye Raspian, armv71
- Pimoroni Breakout Garden Hat
- 1.12" Mono OLED Breakout 128x128 White/Black Screen
- BME680 Air Quality, Temperature, Pressure, Humidity Sensor
- LWM303D 6D0F Motion Sensor (X, Y, Z Axes)
- BH1745 Luminance and Color Sensor
- LTR-559 Light and Proximity Sensor 0.01 lux to 64,000 lux
- VL53L1X Time of Flight (TOF) Sensor
Software / Libraries
- Python 3.9
- Pulsar Python Client 2.10 (avro) pip3 install pulsar-client[avro]
- Python Breakout Garden
- Python PSUTIL https://pypi.org/project/psutil/
- Python LUMA OLED pip3 install --upgrade luma.oled
- Libraries sudo apt-get install python3 python3-pip python3-pil libjpeg-dev zlib1g-dev libfreetype6-dev liblcms2-dev libopenjp2-7 libtiff5 -y
StreamOps
bin/pulsar-admin topics create "persistent://public/default/pi-sensors"
Device Running
VL53L0X_GetDeviceInfo:
Device Name : VL53L1 cut1.1
Device Type : VL53L1
Device ID :
ProductRevisionMajor : 1
ProductRevisionMinor : 15
{'_required_default': False, '_default': None, '_required': False, 'uuid': 'snr_20220323200032', 'ipaddress': '192.168.1.229', 'cputempf': 99, 'runtime': 154, 'host': 'piups', 'hostname': 'piups', 'macaddress': 'b8:27:eb:4a:4b:61', 'endtime': '1648065632.645613', 'te': '154.00473523139954', 'cpu': 0.0, 'diskusage': '3895.3 MB', 'memory': 21.5, 'rowid': '20220323200032_6a66f9ea-1273-4e5d-b150-9300f6272482', 'systemtime': '03/23/2022 16:00:33', 'ts': 1648065633, 'starttime': '03/23/2022 15:57:58', 'BH1745_red': 112.2, 'BH1745_green': 82.0, 'BH1745_blue': 63.0, 'BH1745_clear': 110.0, 'VL53L1X_distance_in_mm': -1185.0, 'ltr559_lux': 6.65, 'ltr559_prox': 0.0, 'bme680_tempc': 23.6, 'bme680_tempf': 74.48, 'bme680_pressure': 1017.48, 'bme680_humidity': 33.931, 'lsm303d_accelerometer': '-00.08g : -01.00g : +00.01g', 'lsm303d_magnetometer': '+00.06 : +00.30 : +00.07'}
VL53L1X Start Ranging Address 0x29
Consumer
bin/pulsar-client consume "persistent://public/default/pi-sensors" -s "pisnsrgrdnrdr" -n 0
** SQL Consumers **
Pulsar SQL / Presto/Trino
desc pulsar."public/default"."pi-sensors";
Column | Type | Extra | Comment
------------------------+-----------+-------+-----------------------------------------------------------------------------
uuid | varchar | | ["null","string"]
ipaddress | varchar | | ["null","string"]
cputempf | integer | | ["null","int"]
runtime | integer | | ["null","int"]
host | varchar | | ["null","string"]
hostname | varchar | | ["null","string"]
macaddress | varchar | | ["null","string"]
endtime | varchar | | ["null","string"]
te | varchar | | ["null","string"]
cpu | real | | ["null","float"]
diskusage | varchar | | ["null","string"]
memory | real | | ["null","float"]
rowid | varchar | | ["null","string"]
systemtime | varchar | | ["null","string"]
ts | integer | | ["null","int"]
starttime | varchar | | ["null","string"]
bh1745_red | real | | ["null","float"]
bh1745_green | real | | ["null","float"]
bh1745_blue | real | | ["null","float"]
bh1745_clear | real | | ["null","float"]
vl53l1x_distance_in_mm | real | | ["null","float"]
ltr559_lux | real | | ["null","float"]
ltr559_prox | real | | ["null","float"]
bme680_tempc | real | | ["null","float"]
bme680_tempf | real | | ["null","float"]
bme680_pressure | real | | ["null","float"]
bme680_humidity | real | | ["null","float"]
lsm303d_accelerometer | varchar | | ["null","string"]
lsm303d_magnetometer | varchar | | ["null","string"]
__partition__ | integer | | The partition number which the message belongs to
__event_time__ | timestamp | | Application defined timestamp in milliseconds of when the event occurred
__publish_time__ | timestamp | | The timestamp in milliseconds of when event as published
__message_id__ | varchar | | The message ID of the message used to generate this row
__sequence_id__ | bigint | | The sequence ID of the message used to generate this row
__producer_name__ | varchar | | The name of the producer that publish the message used to generate this row
__key__ | varchar | | The partition key for the topic
__properties__ | varchar | | User defined properties
(37 rows)
presto> select * from pulsar."public/default"."pi-sensors";
uuid | ipaddress | cputempf | runtime | host | hostname | macaddress | endtime | te | cpu | disk
--------------------+---------------+----------+---------+-------+----------+-------------------+--------------------+--------------------+-----+-----
snr_20220323180318 | 192.168.1.229 | 99 | 4 | piups | piups | b8:27:eb:4a:4b:61 | 1648058598.8543017 | 4.47935152053833 | 0.2 | 3895
snr_20220323180324 | 192.168.1.229 | 99 | 10 | piups | piups | b8:27:eb:4a:4b:61 | 1648058604.4054732 | 10.03052306175232 | 0.0 | 3895
snr_20220323180329 | 192.168.1.229 | 99 | 16 | piups | piups | b8:27:eb:4a:4b:61 | 1648058609.8929565 | 15.518006324768066 | 6.5 | 3895
snr_20220323180335 | 192.168.1.229 | 99 | 21 | piups | piups | b8:27:eb:4a:4b:61 | 1648058615.3783045 | 21.00335431098938 | 0.2 | 3895
snr_20220323180340 | 192.168.1.229 | 99 | 26 | piups | piups | b8:27:eb:4a:4b:61 | 1648058620.8675282 | 26.49257802963257 | 4.6 | 3895
snr_20220323180346 | 192.168.1.229 | 99 | 32 | piups | piups | b8:27:eb:4a:4b:61 | 1648058626.3639522 | 31.989001989364624 | 0.0 | 3895
snr_20220323180351 | 192.168.1.229 | 99 | 38 | piups | piups | b8:27:eb:4a:4b:61 | 1648058631.8793604 | 37.50441026687622 | 0.0 | 3895
snr_20220323180357 | 192.168.1.229 | 100 | 43 | piups | piups | b8:27:eb:4a:4b:61 | 1648058637.38347 | 43.008519887924194 | 0.0 | 3895
snr_20220323180402 | 192.168.1.229 | 99 | 49 | piups | piups | b8:27:eb:4a:4b:61 | 1648058642.8820572 | 48.50710701942444 | 0.0 | 3895
snr_20220323180408 | 192.168.1.229 | 99 | 54 | piups | piups | b8:27:eb:4a:4b:61 | 1648058648.3795574 | 54.00460720062256 | 6.2 | 3895
snr_20220323180413 | 192.168.1.229 | 99 | 59 | piups | piups | b8:27:eb:4a:4b:61 | 1648058653.8280468 | 59.45309662818909 | 0.0 | 3895
snr_20220323180419 | 192.168.1.229 | 99 | 65 | piups | piups | b8:27:eb:4a:4b:61 | 1648058659.3180714 | 64.94312119483948 | 4.9 | 3895
snr_20220323180424 | 192.168.1.229 | 99 | 70 | piups | piups | b8:27:eb:4a:4b:61 | 1648058664.8023574 | 70.42740726470947 | 0.0 | 3895
snr_20220323180430 | 192.168.1.229 | 99 | 76 | piups | piups | b8:27:eb:4a:4b:61 | 1648058670.286937 | 75.91198682785034 | 0.0 | 3895
snr_20220323180435 | 192.168.1.229 | 97 | 81 | piups | piups | b8:27:eb:4a:4b:61 | 1648058675.7804654 | 81.40551519393921 | 0.0 | 3895
snr_20220323180441 | 192.168.1.229 | 99 | 87 | piups | piups | b8:27:eb:4a:4b:61 | 1648058681.2751634 | 86.90021324157715 | 0.0 | 3895
snr_20220323180446 | 192.168.1.229 | 99 | 92 | piups | piups | b8:27:eb:4a:4b:61 | 1648058686.7713509 | 92.39640069007874 | 5.9 | 3895
snr_20220323180452 | 192.168.1.229 | 99 | 98 | piups | piups | b8:27:eb:4a:4b:61 | 1648058692.2672575 | 97.89230728149414 | 0.3 | 3895
snr_20220323180457 | 192.168.1.229 | 99 | 103 | piups | piups | b8:27:eb:4a:4b:61 | 1648058697.7704427 | 103.39549255371094 | 5.4 | 3895
snr_20220323180503 | 192.168.1.229 | 99 | 109 | piups | piups | b8:27:eb:4a:4b:61 | 1648058703.21333 | 108.83837985992432 | 0.3 | 3895
snr_20220323180508 | 192.168.1.229 | 99 | 114 | piups | piups | b8:27:eb:4a:4b:61 | 1648058708.6879904 | 114.31304025650024 | 0.0 | 3895
snr_20220323180514 | 192.168.1.229 | 99 | 120 | piups | piups | b8:27:eb:4a:4b:61 | 1648058714.1396198 | 119.76466965675354 | 0.3 | 3895
snr_20220323180519 | 192.168.1.229 | 99 | 125 | piups | piups | b8:27:eb:4a:4b:61 | 1648058719.6158638 | 125.24091362953186 | 0.0 | 3895
snr_20220323180525 | 192.168.1.229 | 100 | 131 | piups | piups | b8:27:eb:4a:4b:61 | 1648058725.0950723 | 130.72012209892273 | 6.5 | 3895
snr_20220323180530 | 192.168.1.229 | 99 | 136 | piups | piups | b8:27:eb:4a:4b:61 | 1648058730.57256 | 136.19760990142822 | 0.0 | 3895
(25 rows)
Query 20220323_184946_00003_p66fs, FINISHED, 1 node
Spark SQL
val dfPulsar = spark.readStream.format("pulsar").option("service.url", "pulsar://pulsar1:6650").option("admin.url", "http://pulsar1:8080").option("topic", "persistent://public/default/pi-sensors").load()
scala> dfPulsar.printSchema()
root
|-- uuid: string (nullable = true)
|-- ipaddress: string (nullable = true)
|-- cputempf: integer (nullable = true)
|-- runtime: integer (nullable = true)
|-- host: string (nullable = true)
|-- hostname: string (nullable = true)
|-- macaddress: string (nullable = true)
|-- endtime: string (nullable = true)
|-- te: string (nullable = true)
|-- cpu: float (nullable = true)
|-- diskusage: string (nullable = true)
|-- memory: float (nullable = true)
|-- rowid: string (nullable = true)
|-- systemtime: string (nullable = true)
|-- ts: integer (nullable = true)
|-- starttime: string (nullable = true)
|-- BH1745_red: float (nullable = true)
|-- BH1745_green: float (nullable = true)
|-- BH1745_blue: float (nullable = true)
|-- BH1745_clear: float (nullable = true)
|-- VL53L1X_distance_in_mm: float (nullable = true)
|-- ltr559_lux: float (nullable = true)
|-- ltr559_prox: float (nullable = true)
|-- bme680_tempc: float (nullable = true)
|-- bme680_tempf: float (nullable = true)
|-- bme680_pressure: float (nullable = true)
|-- bme680_humidity: float (nullable = true)
|-- lsm303d_accelerometer: string (nullable = true)
|-- lsm303d_magnetometer: string (nullable = true)
|-- __key: binary (nullable = true)
|-- __topic: string (nullable = true)
|-- __messageId: binary (nullable = true)
|-- __publishTime: timestamp (nullable = true)
|-- __eventTime: timestamp (nullable = true)
|-- __messageProperties: map (nullable = true)
| |-- key: string
| |-- value: string (valueContainsNull = true)
## Example Queries
val pQuery = dfPulsar.selectExpr("*").writeStream.format("console").option("truncate", false).start()
val pQuery = dfPulsar.selectExpr("CAST(__key AS STRING)",
"CAST(uuid AS STRING)",
"CAST(ipaddress AS STRING)",
"CAST(cputempf AS STRING)",
"CAST(host AS STRING)",
"CAST(cpu AS STRING)",
"CAST(diskusage AS STRING)",
"CAST(memory AS STRING)",
"CAST(systemtime AS STRING)",
"CAST(BH1745_red AS STRING)",
"CAST(BH1745_green AS STRING)",
"CAST(BH1745_blue AS STRING)",
"CAST(BH1745_clear AS STRING)",
"CAST(VL53L1X_distance_in_mm AS STRING)",
"CAST(ltr559_lux AS STRING)",
"CAST(bme680_tempf AS STRING)",
"CAST(bme680_pressure AS STRING)",
"CAST(bme680_humidity AS STRING)")
.as[(String, String, String, String, String, String, String, String,
String, String, String, String, String, String, String, String, String, String)]
.writeStream.format("csv")
.option("truncate", "false")
.option("header", true)
.option("path", "/opt/demo/pisensordata")
.option("checkpointLocation", "/tmp/checkpoint")
.start()
## You could do csv, parquet, json, orc
pQuery.explain()
pQuery.awaitTermination()
pQuery.stop()
// can be "orc", "json", "csv", etc.
Example Spark ETL CSV Output
/opt/demo/pisensordata# cat part-00000-0425bfc8-5d25-4143-818c-bc7af5e1d82c-c000.csv
__key,uuid,ipaddress,cputempf,host,cpu,diskusage,memory,systemtime,BH1745_red,BH1745_green,BH1745_blue,BH1745_clear,VL53L1X_distance_in_mm,ltr559_lux,bme680_tempf,bme680_pressure,bme680_humidity
snr_20220324215723,snr_20220324215723,192.168.1.229,95,piups,0.0,3887.5 MB,20.6,03/24/2022 17:57:24,134.2,99.0,75.6,130.0,15.0,6.09,70.66,1006.11,44.737
Flink SQL
CREATE CATALOG pulsar WITH (
'type' = 'pulsar',
'service-url' = 'pulsar://pulsar1:6650',
'admin-url' = 'http://pulsar1:8080',
'format' = 'json'
);
USE CATALOG pulsar;
SHOW TABLES;
describe `pi-sensors`;
>
+------------------------+--------+------+-----+--------+-----------+
| name | type | null | key | extras | watermark |
+------------------------+--------+------+-----+--------+-----------+
| uuid | STRING | true | | | |
| ipaddress | STRING | true | | | |
| cputempf | INT | true | | | |
| runtime | INT | true | | | |
| host | STRING | true | | | |
| hostname | STRING | true | | | |
| macaddress | STRING | true | | | |
| endtime | STRING | true | | | |
| te | STRING | true | | | |
| cpu | FLOAT | true | | | |
| diskusage | STRING | true | | | |
| memory | FLOAT | true | | | |
| rowid | STRING | true | | | |
| systemtime | STRING | true | | | |
| ts | INT | true | | | |
| starttime | STRING | true | | | |
| BH1745_red | FLOAT | true | | | |
| BH1745_green | FLOAT | true | | | |
| BH1745_blue | FLOAT | true | | | |
| BH1745_clear | FLOAT | true | | | |
| VL53L1X_distance_in_mm | FLOAT | true | | | |
| ltr559_lux | FLOAT | true | | | |
| ltr559_prox | FLOAT | true | | | |
| bme680_tempc | FLOAT | true | | | |
| bme680_tempf | FLOAT | true | | | |
| bme680_pressure | FLOAT | true | | | |
| bme680_humidity | FLOAT | true | | | |
| lsm303d_accelerometer | STRING | true | | | |
| lsm303d_magnetometer | STRING | true | | | |
+------------------------+--------+------+-----+--------+-----------+
select max(bme680_pressure) as maxpressure, max(bme680_tempf) as maxtemp, max(ltr559_lux) as maxlux, avg(BH1745_red) as avgred,
max(VL53L1X_distance_in_mm) as maxdistance
from `pi-sensors`
select * from `pi-sensors`;
Apache NiFi - Pulsar Consumer. MongoDB Writer.
Data Store - MongoDB
mongo -u debezium -p dbz --authenticationDatabase admin pulsar1:27017/inventory
show databases
db.createCollection("pisensors")
show collections
db.pisensors.find().pretty()
db.pisensors.find().pretty()
{
"_id" : ObjectId("623b812e5dae8913d42a93ee"),
"uuid" : "snr_20220323194514",
"ipaddress" : "192.168.1.229",
"cputempf" : 100,
"runtime" : 9,
"host" : "piups",
"hostname" : "piups",
"macaddress" : "b8:27:eb:4a:4b:61",
"endtime" : "1648064714.7820184",
"te" : "9.371636629104614",
"cpu" : 6.5,
"diskusage" : "3895.4 MB",
"memory" : 21.4,
"rowid" : "20220323194514_c9ec900f-05c2-49c4-985f-ddd83e8b15c0",
"systemtime" : "03/23/2022 15:45:15",
"ts" : 1648064715,
"starttime" : "03/23/2022 15:45:05",
"BH1745_red" : 112.2,
"BH1745_green" : 83,
"BH1745_blue" : 64.8,
"BH1745_clear" : 110,
"VL53L1X_distance_in_mm" : 31,
"ltr559_lux" : 6.65,
"ltr559_prox" : 0,
"bme680_tempc" : 23.47,
"bme680_tempf" : 74.25,
"bme680_pressure" : 1017.71,
"bme680_humidity" : 34.432,
"lsm303d_accelerometer" : "-00.08g : -01.01g : +00.01g",
"lsm303d_magnetometer" : "+00.06 : +00.30 : +00.07"
}
Monitor Everything! Let me see what's going on!?!??!
References
- https://www.academy.streamnative.io/
- https://github.com/tspannhw/PulsarOnRaspberryPi
- https://community.cloudera.com/t5/Community-Articles/IoT-Series-Sensors-Utilizing-Breakout-Garden-Hat-Part-1/ta-p/249262
- https://shop.pimoroni.com/products/breakout-garden-hat?variant=12767628787795
- https://github.com/pimoroni/breakout-garden
- https://github.com/pimoroni/bme680-python
- https://github.com/pimoroni/bh1745-python
- https://github.com/pimoroni/vl53l1x-python
- https://github.com/pimoroni/ltr559-python
- https://github.com/pimoroni/lsm303d-python
- https://github.com/rm-hull/luma.oled
- https://luma-oled.readthedocs.io/en/latest/install.html
- https://github.com/streamnative/examples/blob/master/cloud/python/OAuth2Consumer.py
- https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html#output-sinks