plc4j/examples/hello-storage-elasticsearch/README.adoc - plc4x - Git at Google

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 == IoT Factory example

 In this example we will be running the full stack of tools for a rudimentary factory dashboard.

 This example however is everything but production ready.
 First of all we use create an Elasticsearch single node cluster embedded within the applications VM.
 Secondly we communicate with the `cluster` using the NodeClient, which is super-easy to use, but shouldn't be used in production type environments.

 We decided to go this path because this way it's super-easy to setup everything and running the example is nothing but starting a Java application.

 === What else do I need?

 In General:
 - A PLC
 - A Factory

 Even if you might be able to get your hands on a PLC I doubt you have a spare factory available.

 This example is built to visualize a virtual factory simulated with https://factoryio.com/[Factory I/O].

 We have decided to stick with one of the on-board examples, to make it as easy as possible for you to reproduce.
 The example we used is: "Sorting by Height".

 Here's a video demonstrating this:
 https://www.youtube.com/watch?v=B0n8gT1vto4

 You can run this with a real PLC or use a PLC simulator.
 In our IoT lab we are currently running this with the real S7-1200.

 === What happens in detail?

 When the application is started it first starts up an Elasticsearch node.

 After that is up and running, it checks if the indexes we are going to write to exist.

 If they don't and we would just have ES create them on the fly, we wouldn't be able to use the time-data in the time fields as they would be treated as numbers.

 Any non-existent indexes are created.

 After that an `Apache Edgent` instance is created and one stream is created to fetch the state of all 8 outputs of the PLC every 100ms.

 This stream is then split up.

 One branch simply dumps the data into the `factory-data` index.

 The second branch is a little more complex as it monitors the state of the left and right conveyors to extrapolate if a new `big` or `small box is being transported.

 Only when a new box is detected an entry is written into the `product-data` index.
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	== IoT Factory example

	In this example we will be running the full stack of tools for a rudimentary factory dashboard.

	This example however is everything but production ready.
	First of all we use create an Elasticsearch single node cluster embedded within the applications VM.
	Secondly we communicate with the `cluster` using the NodeClient, which is super-easy to use, but shouldn't be used in production type environments.

	We decided to go this path because this way it's super-easy to setup everything and running the example is nothing but starting a Java application.

	=== What else do I need?

	In General:
	- A PLC
	- A Factory

	Even if you might be able to get your hands on a PLC I doubt you have a spare factory available.

	This example is built to visualize a virtual factory simulated with https://factoryio.com/[Factory I/O].

	We have decided to stick with one of the on-board examples, to make it as easy as possible for you to reproduce.
	The example we used is: "Sorting by Height".

	Here's a video demonstrating this:
	https://www.youtube.com/watch?v=B0n8gT1vto4

	You can run this with a real PLC or use a PLC simulator.
	In our IoT lab we are currently running this with the real S7-1200.

	=== What happens in detail?

	When the application is started it first starts up an Elasticsearch node.

	After that is up and running, it checks if the indexes we are going to write to exist.

	If they don't and we would just have ES create them on the fly, we wouldn't be able to use the time-data in the time fields as they would be treated as numbers.

	Any non-existent indexes are created.

	After that an `Apache Edgent` instance is created and one stream is created to fetch the state of all 8 outputs of the PLC every 100ms.

	This stream is then split up.

	One branch simply dumps the data into the `factory-data` index.

	The second branch is a little more complex as it monitors the state of the left and right conveyors to extrapolate if a new `big` or `small box is being transported.

	Only when a new box is detected an entry is written into the `product-data` index.